Compare commits

...

283 Commits

Author SHA1 Message Date
Blake Mizerany
a2cf25caf7 WIP: gross fix 2024-04-07 22:20:41 -07:00
Blake Mizerany
aca112a308 x/model: update doc showing option name parts 2024-04-07 22:11:06 -07:00
Blake Mizerany
1389e6926a x/registry: mc -> s3 2024-04-07 21:40:51 -07:00
Blake Mizerany
a292cde2f3 x/model: test UnmarshalText safe copy 2024-04-07 21:30:24 -07:00
Blake Mizerany
ab9e476551 x/model: add MustParseName 2024-04-07 20:44:38 -07:00
Blake Mizerany
d721228a2b x/registry: remove unused code 2024-04-07 20:32:36 -07:00
Blake Mizerany
d3c6400487 x/model: more Digest docs 2024-04-07 20:24:06 -07:00
Blake Mizerany
06c21f00eb x/model: make Digest just hold a string
This is so much easier to reason about and allows Name to contain only
parts, instead of a special field for the digest.

It also removes the allocs in Digest.String().
2024-04-07 18:40:24 -07:00
Blake Mizerany
8b62eaf059 x/model: {Valid,Complete,Resolved} -> {IsValid,IsComplete,IsResolved} 2024-04-07 18:17:51 -07:00
Blake Mizerany
6c1c0f9f1a x/model: NamePart -> PartKind 2024-04-07 18:07:18 -07:00
Blake Mizerany
6a4b3c3823 x/mode: complete and resolved example 2024-04-07 16:58:07 -07:00
Blake Mizerany
38e7ddb39d x/api: fix broken build 2024-04-07 16:42:26 -07:00
Blake Mizerany
f595dea189 x/build: fix broken build 2024-04-07 16:42:24 -07:00
Blake Mizerany
be7fe0d6d8 x/mode: more tests and a quick note 2024-04-07 16:38:50 -07:00
Blake Mizerany
98dbc1202a x/mode: add WithDigest 2024-04-07 16:35:48 -07:00
Blake Mizerany
bdff89bc4c x/model: add roundtrip for String test 2024-04-07 16:33:55 -07:00
Blake Mizerany
2100129e83 x/model: add Digest type 2024-04-07 15:38:11 -07:00
Blake Mizerany
4eb7acf84b x/model: prefix NamePart constants with Part 2024-04-07 15:17:02 -07:00
Blake Mizerany
ff68227ca1 x/model: add support for @digest 2024-04-07 15:12:36 -07:00
Blake Mizerany
d2aef85dda x/model: keep TextMarshal tests together 2024-04-07 10:28:49 -07:00
Blake Mizerany
1407fd3d4a x/model: Name: implement sql.Scanner and driver.Valuer 2024-04-07 10:25:44 -07:00
Blake Mizerany
07f27312fa x/model: copy text in UnmarshalText 2024-04-07 10:16:55 -07:00
Blake Mizerany
6ba495d4a3 NameParts -> Parts 2024-04-06 23:46:01 -07:00
Blake Mizerany
bd446a72cc x/model: introduce Digest 2024-04-06 22:26:00 -07:00
Blake Mizerany
5615f60bb0 x/model: more comments on UnmarshalText and immutability 2024-04-06 21:56:28 -07:00
Blake Mizerany
348378ef56 x/model: make UnmarshalText illegal for an already valid Name 2024-04-06 18:00:03 -07:00
Blake Mizerany
81e8c49ac2 x/model: some doc fixes 2024-04-06 16:58:10 -07:00
Blake Mizerany
0172726a58 x/model: update docs; make File private for now 2024-04-06 16:51:31 -07:00
Blake Mizerany
c84f9b07b0 x/model: simplify Name.CompareFold 2024-04-06 16:10:21 -07:00
Blake Mizerany
712eaa4b09 x/model: add note about future changes to Name for memory efficiency 2024-04-06 15:56:20 -07:00
Blake Mizerany
2f241692bd x/model: be more clear slice bound for CompleteNoBuild
Also, update TODO.
2024-04-06 14:07:26 -07:00
Blake Mizerany
d35a6a577f x/model: update TODOs 2024-04-06 14:00:35 -07:00
Blake Mizerany
14a6f85e9e x/model: replace part fields with array of parts
This makes building strings and reasoning about parts easier.
2024-04-06 13:59:38 -07:00
Blake Mizerany
45d8d22785 x/model: add MarshalText and UnmarshalText to Name 2024-04-06 00:10:12 -07:00
Blake Mizerany
e201627c63 x/model: mention Name.String in Name.DisplayFullest comment 2024-04-05 23:41:09 -07:00
Blake Mizerany
5e76860c47 x/model: more doc updates 2024-04-05 23:37:57 -07:00
Blake Mizerany
fb0782b7a9 x/model: NamePartKind -> NamePart 2024-04-05 23:13:22 -07:00
Blake Mizerany
0bee38f6b5 x/model: update docs 2024-04-05 23:09:48 -07:00
Blake Mizerany
b24f1ad587 x/model: add DisplayFullest example 2024-04-05 22:50:42 -07:00
Blake Mizerany
0bea2b8916 x/model: make DisplayComplete DisplayFullest. 2024-04-05 22:47:39 -07:00
Blake Mizerany
e4d65d5aef x/model: remove vestigial DisplayFullest 2024-04-05 22:44:16 -07:00
Blake Mizerany
6e464ebef8 x/model: add CompleteNoBuild 2024-04-05 22:41:22 -07:00
Blake Mizerany
f2c17682b0 x/model: add BenchmarkNameDisplay
Also, use range over int in other benchmarks.
2024-04-05 22:37:39 -07:00
Blake Mizerany
f0e6c563e2 x/model: use isValidByte instead of passing string to isValidPart 2024-04-05 22:37:27 -07:00
Blake Mizerany
a187851900 x/model: fast-path CompareFold for unequal lengths 2024-04-05 22:17:56 -07:00
Blake Mizerany
2e600aa398 x/model: update TODOs 2024-04-05 22:14:41 -07:00
Blake Mizerany
0c78e6c23d x/mode: add Name.DisplayFullest and update docs 2024-04-05 22:14:09 -07:00
Blake Mizerany
c0d4f55f3e x/model: add LogValue
Also, fix GoString and test
2024-04-05 22:00:29 -07:00
Blake Mizerany
d67ff60643 x/model: remove old comment 2024-04-05 21:34:10 -07:00
Blake Mizerany
3cb07b3ac9 x/model: preserve build casing 2024-04-05 21:33:56 -07:00
Blake Mizerany
fc595d89bf x/model: add some clarity to Fill example about what is showing 2024-04-05 21:31:47 -07:00
Blake Mizerany
e1de015fbc x/model: introduce Name.CompareFold with example 2024-04-05 21:31:33 -07:00
Blake Mizerany
1c04951cac x/model: remove superfluous r.Valid() check 2024-04-05 21:05:30 -07:00
Blake Mizerany
95559adee3 x/model: test allocs for complete 2024-04-05 21:04:18 -07:00
Blake Mizerany
9821ca28e8 x/model: remove part getters; these should rarely be needed if ever 2024-04-05 20:55:31 -07:00
Blake Mizerany
c5768ceffe x/model: test Display funcs and add GoString 2024-04-05 20:53:40 -07:00
Blake Mizerany
0b65220936 x/model: remove Has until needed 2024-04-05 19:10:46 -07:00
Blake Mizerany
a5f05236f7 x/model: add test for NamePartKind.String 2024-04-05 18:58:32 -07:00
Blake Mizerany
3cf109ec59 x/model: make Name.String() less annoying when kind is Unknown 2024-04-05 18:54:57 -07:00
Blake Mizerany
7c7f56a7fb x/model: limit part len, not entire len
Limiting the whole name length comes naturally with part name length
restrictions. This aligns with Docker's registry behavior.
2024-04-05 18:49:11 -07:00
Blake Mizerany
bf8e0c09c9 x/model: rename func for display with Display prefix 2024-04-05 16:44:14 -07:00
Blake Mizerany
a6b8bdf938 x/model: disallow . in namespace 2024-04-05 16:23:56 -07:00
Blake Mizerany
f51197a814 failing tests 2024-04-05 16:10:43 -07:00
Blake Mizerany
713e2feacf x/model: add MapHash example 2024-04-04 16:54:46 -07:00
Blake Mizerany
7f1faf6c12 x/model: update package level docs 2024-04-04 16:48:46 -07:00
Blake Mizerany
ad6f020bd8 x/model: doc rule of thumb about valid vs. invalid Names 2024-04-04 16:36:33 -07:00
Blake Mizerany
e052bd8c0f x/mode: more docs 2024-04-04 16:29:35 -07:00
Blake Mizerany
aef832b298 x/mode: doc EqualFold 2024-04-04 16:19:50 -07:00
Blake Mizerany
805a92e6f2 x/model: fix typo 2024-04-04 16:18:14 -07:00
Blake Mizerany
0c46151700 x/model: add docs to Name 2024-04-04 16:16:39 -07:00
Blake Mizerany
bfe89d6fa0 x/model: make equality checks case-insensitive 2024-04-04 16:08:54 -07:00
Blake Mizerany
92b7e40fde x/model: more docs about ParseName 2024-04-04 15:38:21 -07:00
Blake Mizerany
d510a90214 x/model: Registry -> Host, Nick -> Model 2024-04-04 15:26:08 -07:00
Blake Mizerany
a4fd06d603 x/model: doc Merge semantics when dst is not valid 2024-04-04 15:10:06 -07:00
Blake Mizerany
cfe0bb6bb6 x/model: clarify Merge semantics 2024-04-04 15:03:54 -07:00
Blake Mizerany
6aa9795c4f x: replace all import paths for bllamo.com with github.com/ollama/ollama 2024-04-04 14:54:36 -07:00
Blake Mizerany
5041000a28 x/model: Name.Short -> Name.Nick 2024-04-04 14:45:15 -07:00
Blake Mizerany
7cd939690a x/mode: Path -> Name 2024-04-04 14:40:01 -07:00
Blake Mizerany
42cda9dd46 x/build: fix some build errors 2024-04-04 14:29:03 -07:00
Blake Mizerany
6917865bf3 x/model: ParameterPragma -> ParamPragma 2024-04-04 14:28:22 -07:00
Blake Mizerany
2633fcb149 x/model: disambiguate type names
There are now more than just File to the model package.  This change
disambiguates types like Error to FileError, etc. It also helps line
things up with GoDoc.
2024-04-04 14:12:23 -07:00
Blake Mizerany
58de2b8d4a x/model: move x/build.Ref -> x/model.Path
Also, update names and comments accordingly.
2024-04-04 14:02:31 -07:00
Blake Mizerany
de72688b35 x/build/blob: replace confusing WithX method forms with Merge 2024-04-04 13:51:24 -07:00
Blake Mizerany
cbb367b1df x/build/blob: check name + valid invariant 2024-04-04 13:39:15 -07:00
Blake Mizerany
18160475c4 x/build/blob: more tests 2024-04-04 12:11:07 -07:00
Blake Mizerany
31e9b3dd15 x/build/blob: cover Complete 2024-04-04 11:54:13 -07:00
Blake Mizerany
e28cfdf813 x/build/blob: cover the case of an empty build 2024-04-04 11:46:46 -07:00
Blake Mizerany
2751c26da7 x/build/blob: more tests 2024-04-04 11:43:07 -07:00
Blake Mizerany
45ca3c80e8 x/build/blob: more tests for ParseRef
Also, remove superfluous checks in Valid for invalid parts that are
present, which is impossible to have since Parts ensures all parts are
valid, and ParseRef ensures the ref is valid.
2024-04-04 11:36:10 -07:00
Blake Mizerany
d85fbd0e99 another fuzzing find 2024-04-04 11:19:03 -07:00
Blake Mizerany
acf1cb1dc4 x/build/blob: fix handling of slash prefixes 2024-04-04 00:41:13 -07:00
Blake Mizerany
c787b8b2dd ... 2024-04-04 00:27:06 -07:00
Blake Mizerany
9f2d8d2117 ... 2024-04-04 00:11:31 -07:00
Blake Mizerany
d42c3f6be1 x/build/blob: add fuzz test for ParseRef 2024-04-03 23:50:43 -07:00
Blake Mizerany
4ea3e9efa6 x/build/blob: lock in zero allocs for ParseRef 2024-04-03 23:03:36 -07:00
Blake Mizerany
2e1ea6ecaa x/build/blob: move most commit value checks to emit func 2024-04-03 22:55:53 -07:00
Blake Mizerany
6d2da77ce2 x/build/blob: add Parts for streaming ref parts
Also, make ParseRef use the new Parts method to parse the ref parts.
2024-04-03 22:27:55 -07:00
Blake Mizerany
def4d902bf ... wip still broke 2024-04-03 22:15:58 -07:00
Blake Mizerany
76a202c04e ... 2024-04-03 20:52:27 -07:00
Blake Mizerany
f7cfe946dc x/registry: fixing tests wip 2024-04-03 16:37:27 -07:00
Blake Mizerany
005b6373e2 x/registry: fix startMinio 2024-04-03 16:19:50 -07:00
Blake Mizerany
d54e0fb3b2 ... 2024-04-03 16:14:22 -07:00
Blake Mizerany
bdd05e0ae0 x/registry: skip ref test 2024-04-03 15:59:23 -07:00
Blake Mizerany
1a346640db x/registry: work on getting basic test passing 2024-04-03 15:58:04 -07:00
Blake Mizerany
f5883070f8 x/registry: upload smoke test passing 2024-04-03 14:30:58 -07:00
Blake Mizerany
adc23d5f96 Add 'x/' from commit 'a10a11b9d371f36b7c3510da32a1d70b74e27bd1'
git-subtree-dir: x
git-subtree-mainline: 7d05a6ee8f
git-subtree-split: a10a11b9d3
2024-04-03 10:40:23 -07:00
Blake Mizerany
a10a11b9d3 registry: initial work on multipart pushes 2024-04-03 10:39:30 -07:00
Blake Mizerany
7d05a6ee8f cmd: provide feedback if OLLAMA_MODELS is set on non-serve command (#3470)
This also moves the checkServerHeartbeat call out of the "RunE" Cobra
stuff (that's the only word I have for that) to on-site where it's after
the check for OLLAMA_MODELS, which allows the helpful error message to
be printed before the server heartbeat check. This also arguably makes
the code more readable without the magic/superfluous "pre" function
caller.
2024-04-02 22:11:13 -07:00
Daniel Hiltgen
464d817824 Merge pull request #3464 from dhiltgen/subprocess
Fix numgpu opt miscomparison
2024-04-02 20:10:17 -07:00
Pier Francesco Contino
531324a9be feat: add OLLAMA_DEBUG in ollama server help message (#3461)
Co-authored-by: Pier Francesco Contino <pfcontino@gmail.com>
2024-04-02 18:20:03 -07:00
Daniel Hiltgen
6589eb8a8c Revert options as a ref in the server 2024-04-02 16:44:10 -07:00
Michael Yang
a039e383cd Merge pull request #3465 from ollama/mxyng/fix-metal
fix metal gpu
2024-04-02 16:29:58 -07:00
Michael Yang
80163ebcb5 fix metal gpu 2024-04-02 16:06:45 -07:00
Daniel Hiltgen
a57818d93e Merge pull request #3343 from dhiltgen/bump_more2
Bump llama.cpp to b2581
2024-04-02 15:08:26 -07:00
Blake Mizerany
94befe366a ... 2024-04-02 14:28:06 -07:00
Blake Mizerany
c95f97689b utils/upload: init 2024-04-02 14:15:21 -07:00
Blake Mizerany
618eb5b909 registry: multipart push 2024-04-02 13:40:23 -07:00
Daniel Hiltgen
841adda157 Fix windows lint CI flakiness 2024-04-02 12:22:16 -07:00
Daniel Hiltgen
0035e31af8 Bump to b2581 2024-04-02 11:53:07 -07:00
Blake Mizerany
eb75418be9 build/blob: test ParseRef round-trip 2024-04-02 11:45:01 -07:00
Blake Mizerany
9959da05de build/blob: break out test refs for other tests/fuzzing 2024-04-02 11:38:10 -07:00
Daniel Hiltgen
c863c6a96d Merge pull request #3218 from dhiltgen/subprocess
Switch back to subprocessing for llama.cpp
2024-04-02 10:49:44 -07:00
Blake Mizerany
aff7970628 build: remove superfluous parseCompleteRef 2024-04-01 23:41:42 -07:00
Blake Mizerany
628f1feb36 build: back to taking manifests as []byte
Its nicer to have the manifests be an opaque []byte, rather than a
struct. This way users of the build package don't need to know about the
internal structure of the manifests. The registry can interpret the
manifests as it sees fit, while letting build keep its own Go type of
manifest which is easier to work with in the build package.
2024-04-01 23:18:58 -07:00
Blake Mizerany
ce3125afd5 registry: add New and take a minio client as argument 2024-04-01 22:53:49 -07:00
Blake Mizerany
f488652ba7 build: make Build accept only refs without builds 2024-04-01 22:12:43 -07:00
Blake Mizerany
2318ed2919 build: remove unused manifest() 2024-04-01 21:59:38 -07:00
Blake Mizerany
b1b8be33d9 build: cleanup error names and other things 2024-04-01 21:57:34 -07:00
Blake Mizerany
876f7eab81 build: move Manifest from internal/blobstore to build
It was getting confusing to have the arbirary handling of manifests in
the blobstore. It also prevented us from using model.Ref in the
blobstore because of cyclic dependencies.

This is much easier to grok now.
2024-04-01 21:43:30 -07:00
Blake Mizerany
7cfc8a0838 build/blob: fix awkward Ref type 2024-04-01 21:25:18 -07:00
Daniel Hiltgen
1f11b52511 Refined min memory from testing 2024-04-01 16:48:33 -07:00
Daniel Hiltgen
526d4eb204 Release gpu discovery library after use
Leaving the cudart library loaded kept ~30m of memory
pinned in the GPU in the main process.  This change ensures
we don't hold GPU resources when idle.
2024-04-01 16:48:33 -07:00
Daniel Hiltgen
0a74cb31d5 Safeguard for noexec
We may have users that run into problems with our current
payload model, so this gives us an escape valve.
2024-04-01 16:48:33 -07:00
Daniel Hiltgen
10ed1b6292 Detect too-old cuda driver
"cudart init failure: 35" isn't particularly helpful in the logs.
2024-04-01 16:48:33 -07:00
Daniel Hiltgen
4fec5816d6 Integration test improvements
Cleaner shutdown logic, a bit of response hardening
2024-04-01 16:48:18 -07:00
Daniel Hiltgen
0a0e9f3e0f Apply 01-cache.diff 2024-04-01 16:48:18 -07:00
Daniel Hiltgen
58d95cc9bd Switch back to subprocessing for llama.cpp
This should resolve a number of memory leak and stability defects by allowing
us to isolate llama.cpp in a separate process and shutdown when idle, and
gracefully restart if it has problems.  This also serves as a first step to be
able to run multiple copies to support multiple models concurrently.
2024-04-01 16:48:18 -07:00
Patrick Devine
3b6a9154dd Simplify model conversion (#3422) 2024-04-01 16:14:53 -07:00
Michael Yang
d6dd2ff839 Merge pull request #3241 from ollama/mxyng/mem
update memory estimations for gpu offloading
2024-04-01 13:59:14 -07:00
Michael Yang
e57a6ba89f Merge pull request #2926 from ollama/mxyng/decode-ggml-v2
refactor model parsing
2024-04-01 13:58:13 -07:00
Michael Yang
12ec2346ef Merge pull request #3442 from ollama/mxyng/generate-output
fix generate output
2024-04-01 13:56:09 -07:00
Michael Yang
1ec0df1069 fix generate output 2024-04-01 13:47:34 -07:00
Michael Yang
91b3e4d282 update memory calcualtions
count each layer independently when deciding gpu offloading
2024-04-01 13:16:32 -07:00
Michael Yang
d338d70492 refactor model parsing 2024-04-01 13:16:15 -07:00
Philipp Gillé
011bb67351 Add chromem-go to community integrations (#3437) 2024-04-01 11:17:37 -04:00
Saifeddine ALOUI
d124627202 Update README.md (#3436) 2024-04-01 11:16:31 -04:00
Jesse Zhang
b0a8246a69 Community Integration: CRAG Ollama Chat (#3423)
Corrective Retrieval Augmented Generation Demo, powered by Langgraph and Streamlit 🤗

Support: 
- Ollama
- OpenAI APIs
2024-04-01 11:16:14 -04:00
Blake Mizerany
fd411b3cf6 registry: commit Manifest 2024-03-31 18:20:19 -07:00
Blake Mizerany
04f38cf3f4 registry: commit manifest on successful /v1/push 2024-03-31 15:09:24 -07:00
Blake Mizerany
c0eddb10fd registry: use exact match on path 2024-03-31 15:01:26 -07:00
Blake Mizerany
60ef0e6b4a oweb: remove Fault
Also, fix typo in the comment.
2024-03-31 15:00:25 -07:00
Blake Mizerany
48c60c01e2 registry: move req/resp types to registry/apitype 2024-03-31 12:23:10 -07:00
Blake Mizerany
eb2c442a01 oweb: make DecodeUserJSON take a field name
This allows for better error messages when decoding fails. For example,
instead of:

    {"code":"invalid_json","message":"unexpected end of JSON input"}

We now get:

    {"code":"invalid_json","field":"manifest","message":"unexpected end of JSON input"}
2024-03-31 11:36:51 -07:00
Blake Mizerany
c87fe7df48 client/ollama: make Error.Message optional 2024-03-31 11:12:50 -07:00
Blake Mizerany
5182a1dfb1 client/ollama: document Do 2024-03-31 11:04:20 -07:00
Blake Mizerany
a32e7857b2 client/ollama: docs for Error type 2024-03-31 11:00:07 -07:00
Blake Mizerany
6acc205de0 client/ollama: install and use (*Client).HTTPClient 2024-03-31 10:54:17 -07:00
Blake Mizerany
f6e02d4bc7 client/ollama: Do take a *Client 2024-03-31 10:52:56 -07:00
Yaroslav
e6fb39c182 Update README.md (#3378)
Plugins list updated
2024-03-31 13:10:05 -04:00
Blake Mizerany
e1d457c73e client/ollama: report invalid server error response with raw bytes 2024-03-31 09:43:03 -07:00
Blake Mizerany
cd5df121a5 client: include Status in json Error response for symmetry.
Also, remove RawBody from error, which was previously used for
debugging.
2024-03-31 09:30:01 -07:00
Blake Mizerany
112ffed189 oweb: move Error and Do to client/ollama
This allows users of the ollama client library to need only import the
client/ollama package, rather than the oweb package as well when
inspecting errors.
2024-03-31 09:25:07 -07:00
Blake Mizerany
c49947dcf5 init 2024-03-31 09:24:53 -07:00
sugarforever
e1f1c374ea Community Integration: ChatOllama (#3400)
* Community Integration: ChatOllama

* fixed typo
2024-03-30 22:46:50 -04:00
Jeffrey Morgan
06a1508bfe Update 90_bug_report.yml 2024-03-29 10:11:17 -04:00
Patrick Devine
5a5efee46b Add gemma safetensors conversion (#3250)
Co-authored-by: Michael Yang <mxyng@pm.me>
2024-03-28 18:54:01 -07:00
Daniel Hiltgen
97ae517fbf Merge pull request #3398 from dhiltgen/release_latest
CI automation for tagging latest images
2024-03-28 16:25:54 -07:00
Daniel Hiltgen
44b813e459 Merge pull request #3377 from dhiltgen/rocm_v6_bump
Bump ROCm to 6.0.2 patch release
2024-03-28 16:07:54 -07:00
Daniel Hiltgen
539043f5e0 CI automation for tagging latest images 2024-03-28 16:07:37 -07:00
Daniel Hiltgen
dbcace6847 Merge pull request #3392 from dhiltgen/ci_build_win_cuda
CI windows gpu builds
2024-03-28 16:03:52 -07:00
Daniel Hiltgen
c91a4ebcff Bump ROCm to 6.0.2 patch release 2024-03-28 15:58:57 -07:00
Daniel Hiltgen
b79c7e4528 CI windows gpu builds
If we're doing generate, test windows cuda and rocm as well
2024-03-28 14:39:10 -07:00
Michael Yang
035b274b70 Merge pull request #3379 from ollama/mxyng/origins
fix: trim quotes on OLLAMA_ORIGINS
2024-03-28 14:14:18 -07:00
Michael Yang
9c6a254945 Merge pull request #3391 from ollama/mxyng-patch-1 2024-03-28 13:15:56 -07:00
Michael Yang
f31f2bedf4 Update troubleshooting link 2024-03-28 12:05:26 -07:00
Michael Yang
756c257553 Merge pull request #3380 from ollama/mxyng/conditional-generate
fix: workflows
2024-03-28 00:35:27 +01:00
Michael Yang
5255d0af8a fix: workflows 2024-03-27 16:30:01 -07:00
Michael Yang
af8a8a6b59 fix: trim quotes on OLLAMA_ORIGINS 2024-03-27 15:24:29 -07:00
Michael Yang
461ad25015 Merge pull request #3376 from ollama/mxyng/conditional-generate
only generate on changes to llm subdirectory
2024-03-27 22:12:53 +01:00
Michael Yang
8838ae787d stub stub 2024-03-27 13:59:12 -07:00
Michael Yang
db75402ade mangle arch 2024-03-27 13:44:50 -07:00
Michael Yang
1e85a140a3 only generate on changes to llm subdirectory 2024-03-27 12:45:35 -07:00
Michael Yang
c363282fdc Merge pull request #3375 from ollama/mxyng/conditional-generate
only generate cuda/rocm when changes to llm detected
2024-03-27 20:40:55 +01:00
Michael Yang
5b0c48d29e only generate cuda/rocm when changes to llm detected 2024-03-27 12:23:09 -07:00
Jeffrey Morgan
913306f4fd Detect arrow keys on windows (#3363)
* detect arrow keys on windows
* add some helpful comments
2024-03-26 18:21:56 -04:00
Jeffrey Morgan
f5ca7f8c8e add license in file header for vendored llama.cpp code (#3351) 2024-03-26 16:23:23 -04:00
Jeffrey Morgan
856b8ec131 remove need for $VSINSTALLDIR since build will fail if ninja cannot be found (#3350) 2024-03-26 16:23:16 -04:00
Patrick Devine
1b272d5bcd change github.com/jmorganca/ollama to github.com/ollama/ollama (#3347) 2024-03-26 13:04:17 -07:00
Christophe Dervieux
29715dbca7 malformed markdown link (#3358) 2024-03-26 10:46:36 -04:00
Daniel Hiltgen
54a028d07f Merge pull request #3356 from dhiltgen/fix_arm_linux
Switch runner for final release job
2024-03-25 20:54:46 -07:00
Daniel Hiltgen
f83e4db365 Switch runner for final release job
The manifest and tagging step use a lot of disk space
2024-03-25 20:51:40 -07:00
Daniel Hiltgen
3b5866a233 Merge pull request #3353 from dhiltgen/fix_arm_linux
Use Rocky Linux Vault to get GCC 10.2 installed
2024-03-25 19:38:56 -07:00
Daniel Hiltgen
b8c2be6142 Use Rocky Linux Vault to get GCC 10.2 installed
This should hopefully only be a temporary workaround until Rocky 8
picks up GCC 10.4 which fixes the NVCC bug
2024-03-25 19:18:50 -07:00
Daniel Hiltgen
e0319bd78d Revert "Switch arm cuda base image to centos 7"
This reverts commit 5dacc1ebe8.
2024-03-25 19:01:11 -07:00
Daniel Hiltgen
b31ed7f031 Merge pull request #3352 from dhiltgen/fix_arm_linux
Switch arm cuda base image to centos 7
2024-03-25 16:13:10 -07:00
Daniel Hiltgen
5dacc1ebe8 Switch arm cuda base image to centos 7
We had started using rocky linux 8, but they've updated to GCC 10.3,
which breaks NVCC.  10.2 is compatible (or 10.4, but that's not
available from rocky linux 8 repos yet)
2024-03-25 15:57:08 -07:00
Daniel Hiltgen
c2712b5566 Merge pull request #3348 from dhiltgen/bump_llamacpp
Bump llama.cpp to b2527
2024-03-25 14:15:53 -07:00
Daniel Hiltgen
8091ef2eeb Bump llama.cpp to b2527 2024-03-25 13:47:44 -07:00
Jeffrey Morgan
f38b705dc7 Fix ROCm link in development.md 2024-03-25 16:32:44 -04:00
Daniel Hiltgen
560be5e0b6 Merge pull request #3308 from dhiltgen/bump_more
Bump llama.cpp to b2510
2024-03-25 12:56:12 -07:00
Daniel Hiltgen
4a1c76b3aa Merge pull request #3331 from dhiltgen/integration_testing
Integration tests conditionally pull
2024-03-25 12:48:51 -07:00
Daniel Hiltgen
28a64e23ca Merge pull request #2279 from remy415/main
Add support for libcudart.so for CUDA devices (Adds Jetson support)
2024-03-25 12:46:28 -07:00
Niclas Pahlfer
92d74e2f59 adds ooo to community integrations (#1623)
Co-authored-by: Bruce MacDonald <brucewmacdonald@gmail.com>
2024-03-25 15:08:33 -04:00
Herval Freire
6f8f57dd1d Add cliobot to ollama supported list (#1873)
* Update README.md

* Update README.md

---------

Co-authored-by: Bruce MacDonald <brucewmacdonald@gmail.com>
2024-03-25 15:07:19 -04:00
Chenhe Gu
b2fa68b0ea Add Dify.AI to community integrations (#1944)
Dify.AI is a model-agnostic LLMOps platform for building and managing LLM applications.

Co-authored-by: Bruce MacDonald <brucewmacdonald@gmail.com>
2024-03-25 15:06:39 -04:00
Marco Antônio
3767d5ef0d enh: add ollero.nvim to community applications (#1905)
Co-authored-by: Bruce MacDonald <brucewmacdonald@gmail.com>
2024-03-25 15:06:08 -04:00
Ani Betts
9fed85bc8b Add typechat-cli to Terminal apps (#2428)
Co-authored-by: Bruce MacDonald <brucewmacdonald@gmail.com>
2024-03-25 15:05:04 -04:00
Miguel
4501bc0913 add new Web & Desktop link in readme for alpaca webui (#2881)
Co-authored-by: Bruce MacDonald <brucewmacdonald@gmail.com>
2024-03-25 15:00:18 -04:00
Danny Avila
57ba519e63 Add LibreChat to Web & Desktop Apps (#2918) 2024-03-25 14:59:18 -04:00
enoch1118
d98d322d24 Add Community Integration: OllamaGUI (#2927)
Co-authored-by: Bruce MacDonald <brucewmacdonald@gmail.com>
2024-03-25 14:58:28 -04:00
fly2tomato
0c3ec74cf1 Add Community Integration: OpenAOE (#2946)
* Update README.md

* Update README.md

---------

Co-authored-by: Bruce MacDonald <brucewmacdonald@gmail.com>
2024-03-25 14:57:40 -04:00
tusharhero
42ae8359fa docs: Add AI telegram to Community Integrations. (#3033) 2024-03-25 14:56:42 -04:00
Timothy Carambat
e4b76dfb76 docs: Add AnythingLLM to README as integration option (#3145)
Co-authored-by: Bruce MacDonald <brucewmacdonald@gmail.com>
2024-03-25 14:54:48 -04:00
Jikku Jose
2c56517494 Add Saddle (#3178) 2024-03-25 14:54:09 -04:00
Yusuf Can Bayrak
cfbc1b152b tlm added to README.md terminal section. (#3274) 2024-03-25 14:53:26 -04:00
RAPID ARCHITECT
9305ac1b2e Update README.md (#3288)
Added Ollama Basic chat based on hyperdiv

Co-authored-by: Bruce MacDonald <brucewmacdonald@gmail.com>
2024-03-25 14:52:25 -04:00
drazdra
45d6292959 Update README.md (#3338)
adding drazdra/ollama-chats to the list of UI :)
2024-03-25 14:50:51 -04:00
Blake Mizerany
22921a3969 doc: specify ADAPTER is optional (#3333) 2024-03-25 09:43:19 -07:00
Daniel Hiltgen
7b6cbc10ec Integration tests conditionally pull
If images aren't present, pull them.
Also fixes the expected responses
2024-03-25 08:57:45 -07:00
Jeremy
dfc6721b20 add support for libcudart.so for CUDA devices (adds Jetson support) 2024-03-25 11:07:44 -04:00
Blake Mizerany
acfa2b9422 llm: prevent race appending to slice (#3320) 2024-03-24 11:35:54 -07:00
Daniel Hiltgen
2c390a73ac Merge pull request #3282 from dhiltgen/gpu_docs
Add docs for GPU selection and nvidia uvm workaround
2024-03-24 19:15:03 +01:00
Daniel Hiltgen
3e30c75f3e Bump llama.cpp to b2510 2024-03-23 19:55:56 +01:00
Eddú Meléndez Gonzales
7e430ff352 Add Testcontainers into Libraries section (#3291)
Testcontainers provides a module for Ollama.
2024-03-23 19:55:25 +01:00
Daniel Hiltgen
1784113ef5 Merge pull request #3309 from dhiltgen/integration_testing
Revamp go based integration tests
2024-03-23 19:08:49 +01:00
Daniel Hiltgen
949b6c01e0 Revamp go based integration tests
This uplevels the integration tests to run the server which can allow
testing an existing server, or a remote server.
2024-03-23 14:24:18 +01:00
jmorganca
38daf0a252 rename .gitattributes 2024-03-23 12:40:31 +01:00
Daniel Hiltgen
43799532c1 Bump llama.cpp to b2474
The release just before ggml-cuda.cu refactoring
2024-03-23 09:54:56 +01:00
Daniel Hiltgen
d8fdbfd8da Add docs for GPU selection and nvidia uvm workaround 2024-03-21 11:52:54 +01:00
Bruce MacDonald
a5ba0fcf78 doc: faq gpu compatibility (#3142) 2024-03-21 05:21:34 -04:00
Jeffrey Morgan
3a30bf56dc Update faq.md 2024-03-20 17:48:39 +01:00
Daniel Hiltgen
a1c0a48524 Merge pull request #3122 from dhiltgen/better_tmp_cleanup
Better tmpdir cleanup
2024-03-20 16:28:03 +01:00
Daniel Hiltgen
74788b487c Better tmpdir cleanup
If expanding the runners fails, don't leave a corrupt/incomplete payloads dir
We now write a pid file out to the tmpdir, which allows us to scan for stale tmpdirs
and remove this as long as there isn't still a process running.
2024-03-20 16:03:19 +01:00
Jeffrey Morgan
7ed3e94105 Update faq.md 2024-03-18 10:24:39 +01:00
jmorganca
2297ad39da update faq.md 2024-03-18 10:17:59 +01:00
Michael Yang
01cff6136d Merge pull request #3217 from ollama/mxyng/cleanup
remove global
2024-03-18 02:13:30 -07:00
Michael Yang
3c4ad0ecab dyn global 2024-03-18 09:45:45 +01:00
Michael Yang
22f326464e Merge pull request #3083 from ollama/mxyng/refactor-readseeker
refactor readseeker
2024-03-16 12:08:56 -07:00
Jeffrey Morgan
e95ffc7448 llama: remove server static assets (#3174) 2024-03-15 19:24:12 -07:00
Jeffrey Morgan
2dce1ab40b add llm/ext_server directory to linguist-vendored (#3173) 2024-03-15 17:46:46 -07:00
Daniel Hiltgen
f4b31c2d53 Merge pull request #3111 from alitrack/main
Update ollama.iss
2024-03-15 16:46:59 -07:00
Daniel Hiltgen
ab3456207b Merge pull request #3028 from ollama/ci_release
CI release process
2024-03-15 16:40:54 -07:00
Daniel Hiltgen
6ad414f31e Merge pull request #3086 from dhiltgen/import_server
Import server.cpp to retain llava support
2024-03-15 16:10:35 -07:00
Daniel Hiltgen
052b5a3b77 Merge pull request #3171 from dhiltgen/rocm_94x
Add Radeon gfx940-942 GPU support
2024-03-15 15:58:33 -07:00
Daniel Hiltgen
d4c10df2b0 Add Radeon gfx940-942 GPU support 2024-03-15 15:34:58 -07:00
Daniel Hiltgen
540f4af45f Wire up more complete CI for releases
Flesh out our github actions CI so we can build official releaes.
2024-03-15 12:37:36 -07:00
Blake Mizerany
6ce37e4d96 llm,readline: use errors.Is instead of simple == check (#3161)
This fixes some brittle, simple equality checks to use errors.Is. Since
go1.13, errors.Is is the idiomatic way to check for errors.

Co-authored-by: Jeffrey Morgan <jmorganca@gmail.com>
2024-03-15 07:14:12 -07:00
Blake Mizerany
703684a82a server: replace blob prefix separator from ':' to '-' (#3146)
This fixes issues with blob file names that contain ':' characters to be rejected by file systems that do not support them.
2024-03-14 20:18:06 -07:00
Daniel Hiltgen
6459377ae0 Add ROCm support to linux install script (#2966) 2024-03-14 18:00:16 -07:00
Blake Mizerany
8546dd3d72 .github: fix model and feature request yml (#3155) 2024-03-14 15:26:06 -07:00
Blake Mizerany
87100be5e0 .github: add issue templates (#3143) 2024-03-14 15:19:10 -07:00
Michael Yang
e87c780ff9 Merge pull request #3149 from ollama/mxyng/fix-memory-leak
fix: clip memory leak
2024-03-14 13:34:15 -07:00
Michael Yang
291c663865 fix: clip memory leak 2024-03-14 13:12:42 -07:00
Daniel Hiltgen
da20786e3e Merge pull request #3068 from dhiltgen/win_pipe
Use stdin for term discovery on windows
2024-03-14 11:55:19 -07:00
Jeffrey Morgan
5ce997a7b9 Update README.md 2024-03-13 21:12:17 -07:00
Jeffrey Morgan
672ffe9b7d add OLLAMA_KEEP_ALIVE to environment variable docs for ollama serve (#3127) 2024-03-13 14:35:33 -07:00
Patrick Devine
47cfe58af5 Default Keep Alive environment variable (#3094)
---------

Co-authored-by: Chris-AS1 <8493773+Chris-AS1@users.noreply.github.com>
2024-03-13 13:29:40 -07:00
Daniel Hiltgen
c1a81c6fe3 Use stdin for term discovery on windows
When you feed input to the cmd via a pipe it no longer reports a warning
2024-03-13 10:37:31 -07:00
Steven Lee
152ab524c2 Update ollama.iss
add arm64 support
2024-03-13 20:15:45 +08:00
Jeffrey Morgan
e72c567cfd restore locale patch (#3091) 2024-03-12 22:08:13 -07:00
Bruce MacDonald
3e22611200 token repeat limit for prediction requests (#3080) 2024-03-12 22:08:25 -04:00
Daniel Hiltgen
a54d4a28dc Merge pull request #3088 from dhiltgen/rocm_igpu_linux
Fix iGPU detection for linux
2024-03-12 17:20:27 -07:00
Daniel Hiltgen
82b0c7c27e Fix iGPU detection for linux
This fixes a few bugs in the new sysfs discovery logic.  iGPUs are now
correctly identified by their <1G VRAM reported.  the sysfs IDs are off
by one compared to what HIP wants due to the CPU being reported
in amdgpu, but HIP only cares about GPUs.
2024-03-12 16:57:19 -07:00
Patrick Devine
ba7cf7fb66 add more docs on for the modelfile message command (#3087) 2024-03-12 16:41:41 -07:00
Bruce MacDonald
2f804068bd warn when json format is expected but not mentioned in prompt (#3081) 2024-03-12 19:07:11 -04:00
Daniel Hiltgen
85129d3a32 Adapt our build for imported server.cpp 2024-03-12 14:57:15 -07:00
Daniel Hiltgen
9ac6440da3 Import server.cpp as of b2356 2024-03-12 13:58:06 -07:00
Michael Yang
0085297928 refactor readseeker 2024-03-12 12:54:18 -07:00
Daniel Hiltgen
34d00f90b1 Merge pull request #3070 from dhiltgen/visible_devices
Add docs explaining GPU selection env vars
2024-03-12 11:36:46 -07:00
Daniel Hiltgen
b53229a2ed Add docs explaining GPU selection env vars 2024-03-12 11:33:06 -07:00
racerole
53c107e20e chore: fix typo (#3073)
Signed-off-by: racerole <jiangyifeng@outlook.com>
2024-03-12 14:09:22 -04:00
mofanke
51578d8573 fix gpu_info_cuda.c compile warning (#3077) 2024-03-12 14:08:40 -04:00
Jeffrey Morgan
b5fcd9d3aa use -trimpath when building releases (#3069) 2024-03-11 15:58:46 -07:00
Bruce MacDonald
b80661e8c7 relay load model errors to the client (#3065) 2024-03-11 16:48:27 -04:00
Jeffrey Morgan
6d3adfbea2 Update troubleshooting.md 2024-03-11 13:22:28 -07:00
Jeffrey Morgan
369eda65f5 update llama.cpp submodule to ceca1ae (#3064) 2024-03-11 12:57:48 -07:00
Michael Yang
f878e91070 Merge pull request #3044 from ollama/mxyng/fix-convert-shape
convert: fix shape
2024-03-11 09:56:57 -07:00
Daniel Hiltgen
0d651478e4 Merge pull request #3056 from dhiltgen/rocm_link_clash
Avoid rocm runner and dependency clash
2024-03-11 09:48:48 -07:00
Michael Yang
9ea492f1ce convert: fix shape 2024-03-11 09:41:01 -07:00
Daniel Hiltgen
bc13da2bfe Avoid rocm runner and dependency clash
Putting the rocm symlink next to the runners is risky.  This moves
the payloads into a subdir to avoid potential clashes.
2024-03-11 09:33:22 -07:00
Jeffrey Morgan
41b00b9856 fix 03-locale.diff 2024-03-10 16:21:05 -07:00
Daniel Hiltgen
c2a8ed48e7 Merge pull request #3048 from dhiltgen/harden_rocm_deps
Harden for deps file being empty (or short)
2024-03-10 15:17:22 -07:00
Daniel Hiltgen
3dc1bb6a35 Harden for deps file being empty (or short) 2024-03-10 14:45:38 -07:00
176 changed files with 47818 additions and 3768 deletions

1
.gitattributes vendored Normal file
View File

@@ -0,0 +1 @@
llm/ext_server/* linguist-vendored

View File

@@ -0,0 +1,18 @@
name: Model request
description: Request a new model for the library
labels: [mr]
body:
- type: markdown
attributes:
value: |
Please check if your Model request is [already available](https://ollama.com/search) or that you cannot [import it](https://github.com/ollama/ollama/blob/main/docs/import.md#import-a-model) yourself.
Tell us about which Model you'd like to see in the library!
- type: textarea
id: problem
attributes:
label: What model would you like?
description: Please provide a link to the model.
- type: markdown
attributes:
value: |
Thanks for filing a model request!

View File

@@ -0,0 +1,41 @@
name: Feature request
description: Propose a new feature
labels: [needs-triage, fr]
body:
- type: markdown
attributes:
value: |
Please check if your feature request is [already filed](https://github.com/ollama/ollama/issues).
Tell us about your idea!
- type: textarea
id: problem
attributes:
label: What are you trying to do?
description: Tell us about the problem you're trying to solve.
validations:
required: false
- type: textarea
id: solution
attributes:
label: How should we solve this?
description: If you have an idea of how you'd like to see this feature work, let us know.
validations:
required: false
- type: textarea
id: alternative
attributes:
label: What is the impact of not solving this?
description: (How) Are you currently working around the issue?
validations:
required: false
- type: textarea
id: context
attributes:
label: Anything else?
description: Any additional context to share, e.g., links
validations:
required: false
- type: markdown
attributes:
value: |
Thanks for filing a feature request!

125
.github/ISSUE_TEMPLATE/90_bug_report.yml vendored Normal file
View File

@@ -0,0 +1,125 @@
name: Bug report
description: File a bug report. If you need help, please join our Discord server.
labels: [needs-triage, bug]
body:
- type: markdown
attributes:
value: |
Please check if your bug is [already filed](https://github.com/ollama/ollama/issues) before filing a new one.
- type: textarea
id: what-happened
attributes:
label: What is the issue?
description: What happened? What did you expect to happen?
validations:
required: true
- type: textarea
id: what-was-expected
attributes:
label: What did you expect to see?
description: What did you expect to see/happen instead?
validations:
required: false
- type: textarea
id: steps
attributes:
label: Steps to reproduce
description: What are the steps you took that hit this issue?
validations:
required: false
- type: textarea
id: changes
attributes:
label: Are there any recent changes that introduced the issue?
description: If so, what are those changes?
validations:
required: false
- type: dropdown
id: os
attributes:
label: OS
description: What OS are you using? You may select more than one.
multiple: true
options:
- Linux
- macOS
- Windows
- Other
validations:
required: false
- type: dropdown
id: architecture
attributes:
label: Architecture
description: What architecture are you using? You may select more than one.
multiple: true
options:
- arm64
- amd64
- x86
- Other
- type: dropdown
id: platform
attributes:
label: Platform
description: What platform are you using? You may select more than one.
multiple: true
options:
- Docker
- WSL
- WSL2
validations:
required: false
- type: input
id: ollama-version
attributes:
label: Ollama version
description: What Ollama version are you using? (`ollama --version`)
placeholder: e.g., 1.14.4
validations:
required: false
- type: dropdown
id: gpu
attributes:
label: GPU
description: What GPU, if any, are you using? You may select more than one.
multiple: true
options:
- Nvidia
- AMD
- Intel
- Apple
- Other
validations:
required: false
- type: textarea
id: gpu-info
attributes:
label: GPU info
description: What GPU info do you have? (`nvidia-smi`, `rocminfo`, `system_profiler SPDisplaysDataType`, etc.)
validations:
required: false
- type: dropdown
id: cpu
attributes:
label: CPU
description: What CPU are you using? You may select more than one.
multiple: true
options:
- Intel
- AMD
- Apple
- Other
validations:
required: false
- type: textarea
id: other-software
attributes:
label: Other software
description: What other software are you using that might be related to this issue?
validations:
required: false
- type: markdown
attributes:
value: |
Thanks for filing a bug report!

8
.github/ISSUE_TEMPLATE/config.yml vendored Normal file
View File

@@ -0,0 +1,8 @@
blank_issues_enabled: true
contact_links:
- name: Help
url: https://discord.com/invite/ollama
about: Please join our Discord server for help using Ollama
- name: Troubleshooting
url: https://github.com/ollama/ollama/blob/main/docs/faq.md#faq
about: See the FAQ for common issues and solutions

24
.github/workflows/latest.yaml vendored Normal file
View File

@@ -0,0 +1,24 @@
name: latest
on:
release:
types: [released]
jobs:
update-latest:
environment: release
runs-on: linux
steps:
- uses: actions/checkout@v4
- name: Login to Docker Hub
uses: docker/login-action@v3
with:
username: ${{ vars.DOCKER_USER }}
password: ${{ secrets.DOCKER_ACCESS_TOKEN }}
- name: Tag images as latest
env:
PUSH: "1"
shell: bash
run: |
export "VERSION=${GITHUB_REF_NAME#v}"
./scripts/tag_latest.sh

470
.github/workflows/release.yaml vendored Normal file
View File

@@ -0,0 +1,470 @@
name: release
on:
push:
tags:
- 'v*'
jobs:
# Full build of the Mac assets
build-darwin:
runs-on: macos-latest
environment: release
steps:
- uses: actions/checkout@v4
- name: Set Version
shell: bash
run: |
echo "VERSION=${GITHUB_REF_NAME#v}" >> $GITHUB_ENV
echo "RELEASE_VERSION=$(echo ${GITHUB_REF_NAME} | cut -f1 -d-)" >> $GITHUB_ENV
- name: key
env:
MACOS_SIGNING_KEY: ${{ secrets.MACOS_SIGNING_KEY }}
MACOS_SIGNING_KEY_PASSWORD: ${{ secrets.MACOS_SIGNING_KEY_PASSWORD }}
run: |
echo $MACOS_SIGNING_KEY | base64 --decode > certificate.p12
security create-keychain -p password build.keychain
security default-keychain -s build.keychain
security unlock-keychain -p password build.keychain
security import certificate.p12 -k build.keychain -P $MACOS_SIGNING_KEY_PASSWORD -T /usr/bin/codesign
security set-key-partition-list -S apple-tool:,apple:,codesign: -s -k password build.keychain
- uses: actions/setup-go@v5
with:
go-version: '1.22'
cache: true
- name: Build Darwin
env:
APPLE_IDENTITY: ${{ secrets.APPLE_IDENTITY }}
APPLE_PASSWORD: ${{ secrets.APPLE_PASSWORD }}
APPLE_TEAM_ID: ${{ vars.APPLE_TEAM_ID }}
APPLE_ID: ${{ vars.APPLE_ID }}
run: |
./scripts/build_darwin.sh
- uses: actions/upload-artifact@v4
with:
name: dist-darwin
path: |
dist/*arwin*
!dist/*-cov
# Windows builds take a long time to both install the dependencies and build, so parallelize
# CPU generation step
generate-windows-cpu:
environment: release
runs-on: windows
env:
KEY_CONTAINER: ${{ vars.KEY_CONTAINER }}
steps:
- uses: actions/checkout@v4
- name: Set Version
shell: bash
run: echo "VERSION=${GITHUB_REF_NAME#v}" >> $GITHUB_ENV
- uses: 'google-github-actions/auth@v2'
with:
project_id: 'ollama'
credentials_json: '${{ secrets.GOOGLE_SIGNING_CREDENTIALS }}'
- run: echo "${{ vars.OLLAMA_CERT }}" > ollama_inc.crt
- name: install Windows SDK 8.1 to get signtool
run: |
$ErrorActionPreference = "Stop"
write-host "downloading SDK"
Invoke-WebRequest -Uri "https://go.microsoft.com/fwlink/p/?LinkId=323507" -OutFile "${env:RUNNER_TEMP}\sdksetup.exe"
Start-Process "${env:RUNNER_TEMP}\sdksetup.exe" -ArgumentList @("/q") -NoNewWindow -Wait
write-host "Win SDK 8.1 installed"
gci -path 'C:\Program Files (x86)\Windows Kits\' -r -fi 'signtool.exe'
- name: install signing plugin
run: |
$ErrorActionPreference = "Stop"
write-host "downloading plugin"
Invoke-WebRequest -Uri "https://github.com/GoogleCloudPlatform/kms-integrations/releases/download/cng-v1.0/kmscng-1.0-windows-amd64.zip" -OutFile "${env:RUNNER_TEMP}\plugin.zip"
Expand-Archive -Path "${env:RUNNER_TEMP}\plugin.zip" -DestinationPath ${env:RUNNER_TEMP}\plugin\
write-host "Installing plugin"
& "${env:RUNNER_TEMP}\plugin\*\kmscng.msi" /quiet
write-host "plugin installed"
- uses: actions/setup-go@v5
with:
go-version: '1.22'
cache: true
- run: go get ./...
- run: |
$gopath=(get-command go).source | split-path -parent
& "C:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\Common7\Tools\Launch-VsDevShell.ps1"
cd $env:GITHUB_WORKSPACE
$env:CMAKE_SYSTEM_VERSION="10.0.22621.0"
$env:PATH="$gopath;$env:PATH"
go generate -x ./...
name: go generate
- uses: actions/upload-artifact@v4
with:
name: generate-windows-cpu
path: llm/llama.cpp/build/**/lib/*
# ROCm generation step
generate-windows-rocm:
environment: release
runs-on: windows
env:
KEY_CONTAINER: ${{ vars.KEY_CONTAINER }}
steps:
- uses: actions/checkout@v4
- name: Set Version
shell: bash
run: echo "VERSION=${GITHUB_REF_NAME#v}" >> $GITHUB_ENV
- uses: 'google-github-actions/auth@v2'
with:
project_id: 'ollama'
credentials_json: '${{ secrets.GOOGLE_SIGNING_CREDENTIALS }}'
- run: echo "${{ vars.OLLAMA_CERT }}" > ollama_inc.crt
- name: install Windows SDK 8.1 to get signtool
run: |
$ErrorActionPreference = "Stop"
write-host "downloading SDK"
Invoke-WebRequest -Uri "https://go.microsoft.com/fwlink/p/?LinkId=323507" -OutFile "${env:RUNNER_TEMP}\sdksetup.exe"
Start-Process "${env:RUNNER_TEMP}\sdksetup.exe" -ArgumentList @("/q") -NoNewWindow -Wait
write-host "Win SDK 8.1 installed"
gci -path 'C:\Program Files (x86)\Windows Kits\' -r -fi 'signtool.exe'
- name: install signing plugin
run: |
$ErrorActionPreference = "Stop"
write-host "downloading plugin"
Invoke-WebRequest -Uri "https://github.com/GoogleCloudPlatform/kms-integrations/releases/download/cng-v1.0/kmscng-1.0-windows-amd64.zip" -OutFile "${env:RUNNER_TEMP}\plugin.zip"
Expand-Archive -Path "${env:RUNNER_TEMP}\plugin.zip" -DestinationPath ${env:RUNNER_TEMP}\plugin\
write-host "Installing plugin"
& "${env:RUNNER_TEMP}\plugin\*\kmscng.msi" /quiet
write-host "plugin installed"
- uses: actions/setup-go@v5
with:
go-version: '1.22'
cache: true
- name: "Install ROCm"
run: |
$ErrorActionPreference = "Stop"
write-host "downloading AMD HIP Installer"
Invoke-WebRequest -Uri "https://download.amd.com/developer/eula/rocm-hub/AMD-Software-PRO-Edition-23.Q4-WinSvr2022-For-HIP.exe" -OutFile "${env:RUNNER_TEMP}\rocm-install.exe"
write-host "Installing AMD HIP"
Start-Process "${env:RUNNER_TEMP}\rocm-install.exe" -ArgumentList '-install' -NoNewWindow -Wait
write-host "Completed AMD HIP"
- name: "Verify ROCm"
run: |
& 'C:\Program Files\AMD\ROCm\*\bin\clang.exe' --version
- run: go get ./...
- run: |
$gopath=(get-command go).source | split-path -parent
& "C:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\Common7\Tools\Launch-VsDevShell.ps1"
cd $env:GITHUB_WORKSPACE
$env:CMAKE_SYSTEM_VERSION="10.0.22621.0"
$env:PATH="$gopath;$env:PATH"
$env:OLLAMA_SKIP_CPU_GENERATE="1"
$env:HIP_PATH=$(Resolve-Path 'C:\Program Files\AMD\ROCm\*\bin\clang.exe' | split-path | split-path)
go generate -x ./...
name: go generate
- name: "gather rocm dependencies"
run: |
$HIP_PATH=$(Resolve-Path 'C:\Program Files\AMD\ROCm\*\bin\clang.exe' | split-path | split-path)
md "dist\deps\bin\rocblas\library"
cp "${HIP_PATH}\bin\hipblas.dll" "dist\deps\bin\"
cp "${HIP_PATH}\bin\rocblas.dll" "dist\deps\bin\"
cp "${HIP_PATH}\bin\rocblas\library\*" "dist\deps\bin\rocblas\library\"
- uses: actions/upload-artifact@v4
with:
name: generate-windows-rocm
path: llm/llama.cpp/build/**/lib/*
- uses: actions/upload-artifact@v4
with:
name: windows-rocm-deps
path: dist/deps/*
# CUDA generation step
generate-windows-cuda:
environment: release
runs-on: windows
env:
KEY_CONTAINER: ${{ vars.KEY_CONTAINER }}
steps:
- uses: actions/checkout@v4
- name: Set Version
shell: bash
run: echo "VERSION=${GITHUB_REF_NAME#v}" >> $GITHUB_ENV
- uses: 'google-github-actions/auth@v2'
with:
project_id: 'ollama'
credentials_json: '${{ secrets.GOOGLE_SIGNING_CREDENTIALS }}'
- run: echo "${{ vars.OLLAMA_CERT }}" > ollama_inc.crt
- name: install Windows SDK 8.1 to get signtool
run: |
$ErrorActionPreference = "Stop"
write-host "downloading SDK"
Invoke-WebRequest -Uri "https://go.microsoft.com/fwlink/p/?LinkId=323507" -OutFile "${env:RUNNER_TEMP}\sdksetup.exe"
Start-Process "${env:RUNNER_TEMP}\sdksetup.exe" -ArgumentList @("/q") -NoNewWindow -Wait
write-host "Win SDK 8.1 installed"
gci -path 'C:\Program Files (x86)\Windows Kits\' -r -fi 'signtool.exe'
- name: install signing plugin
run: |
$ErrorActionPreference = "Stop"
write-host "downloading plugin"
Invoke-WebRequest -Uri "https://github.com/GoogleCloudPlatform/kms-integrations/releases/download/cng-v1.0/kmscng-1.0-windows-amd64.zip" -OutFile "${env:RUNNER_TEMP}\plugin.zip"
Expand-Archive -Path "${env:RUNNER_TEMP}\plugin.zip" -DestinationPath ${env:RUNNER_TEMP}\plugin\
write-host "Installing plugin"
& "${env:RUNNER_TEMP}\plugin\*\kmscng.msi" /quiet
write-host "plugin installed"
- uses: actions/setup-go@v5
with:
go-version: '1.22'
cache: true
- name: "Install CUDA"
run: |
$ErrorActionPreference = "Stop"
write-host "downloading CUDA Installer"
Invoke-WebRequest -Uri "https://developer.download.nvidia.com/compute/cuda/11.3.1/local_installers/cuda_11.3.1_465.89_win10.exe" -OutFile "${env:RUNNER_TEMP}\cuda-install.exe"
write-host "Installing CUDA"
Start-Process "${env:RUNNER_TEMP}\cuda-install.exe" -ArgumentList '-s' -NoNewWindow -Wait
write-host "Completed CUDA"
$cudaPath=((resolve-path "c:\Program Files\NVIDIA*\CUDA\v*\bin\nvcc.exe")[0].path | split-path | split-path)
$cudaVer=($cudaPath | split-path -leaf ) -replace 'v(\d+).(\d+)', '$1_$2'
echo "$cudaPath\bin" >> $env:GITHUB_PATH
echo "CUDA_PATH=$cudaPath" >> $env:GITHUB_ENV
echo "CUDA_PATH_V${cudaVer}=$cudaPath" >> $env:GITHUB_ENV
echo "CUDA_PATH_VX_Y=CUDA_PATH_V${cudaVer}" >> $env:GITHUB_ENV
- name: "Verify CUDA"
run: nvcc -V
- run: go get ./...
- name: go generate
run: |
$gopath=(get-command go).source | split-path -parent
$cudabin=(get-command nvcc).source | split-path
& "C:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\Common7\Tools\Launch-VsDevShell.ps1"
cd $env:GITHUB_WORKSPACE
$env:CMAKE_SYSTEM_VERSION="10.0.22621.0"
$env:PATH="$gopath;$cudabin;$env:PATH"
$env:OLLAMA_SKIP_CPU_GENERATE="1"
go generate -x ./...
- name: "gather cuda dependencies"
run: |
$NVIDIA_DIR=(resolve-path 'C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\*\bin\')[0]
md "dist\deps"
cp "${NVIDIA_DIR}\cudart64_*.dll" "dist\deps\"
cp "${NVIDIA_DIR}\cublas64_*.dll" "dist\deps\"
cp "${NVIDIA_DIR}\cublasLt64_*.dll" "dist\deps\"
- uses: actions/upload-artifact@v4
with:
name: generate-windows-cuda
path: llm/llama.cpp/build/**/lib/*
- uses: actions/upload-artifact@v4
with:
name: windows-cuda-deps
path: dist/deps/*
# Import the prior generation steps and build the final windows assets
build-windows:
environment: release
runs-on: windows
needs:
- generate-windows-cuda
- generate-windows-rocm
- generate-windows-cpu
env:
KEY_CONTAINER: ${{ vars.KEY_CONTAINER }}
steps:
- uses: actions/checkout@v4
with:
submodules: recursive
- name: Set Version
shell: bash
run: echo "VERSION=${GITHUB_REF_NAME#v}" >> $GITHUB_ENV
- uses: 'google-github-actions/auth@v2'
with:
project_id: 'ollama'
credentials_json: '${{ secrets.GOOGLE_SIGNING_CREDENTIALS }}'
- run: echo "${{ vars.OLLAMA_CERT }}" > ollama_inc.crt
- name: install Windows SDK 8.1 to get signtool
run: |
$ErrorActionPreference = "Stop"
write-host "downloading SDK"
Invoke-WebRequest -Uri "https://go.microsoft.com/fwlink/p/?LinkId=323507" -OutFile "${env:RUNNER_TEMP}\sdksetup.exe"
Start-Process "${env:RUNNER_TEMP}\sdksetup.exe" -ArgumentList @("/q") -NoNewWindow -Wait
write-host "Win SDK 8.1 installed"
gci -path 'C:\Program Files (x86)\Windows Kits\' -r -fi 'signtool.exe'
- name: install signing plugin
run: |
$ErrorActionPreference = "Stop"
write-host "downloading plugin"
Invoke-WebRequest -Uri "https://github.com/GoogleCloudPlatform/kms-integrations/releases/download/cng-v1.0/kmscng-1.0-windows-amd64.zip" -OutFile "${env:RUNNER_TEMP}\plugin.zip"
Expand-Archive -Path "${env:RUNNER_TEMP}\plugin.zip" -DestinationPath ${env:RUNNER_TEMP}\plugin\
write-host "Installing plugin"
& "${env:RUNNER_TEMP}\plugin\*\kmscng.msi" /quiet
write-host "plugin installed"
- uses: actions/setup-go@v5
with:
go-version: '1.22'
cache: true
- run: go get
- uses: actions/download-artifact@v4
with:
name: generate-windows-cpu
path: llm/llama.cpp/build
- uses: actions/download-artifact@v4
with:
name: generate-windows-cuda
path: llm/llama.cpp/build
- uses: actions/download-artifact@v4
with:
name: windows-cuda-deps
path: dist/deps
- uses: actions/download-artifact@v4
with:
name: windows-rocm-deps
path: dist/deps
- uses: actions/download-artifact@v4
with:
name: generate-windows-rocm
path: llm/llama.cpp/build
- run: dir llm/llama.cpp/build
- run: |
$gopath=(get-command go).source | split-path -parent
& "C:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\Common7\Tools\Launch-VsDevShell.ps1"
cd $env:GITHUB_WORKSPACE
$env:CMAKE_SYSTEM_VERSION="10.0.22621.0"
$env:PATH="$gopath;$env:PATH"
$env:OLLAMA_SKIP_GENERATE="1"
$env:NVIDIA_DIR=$(resolve-path ".\dist\deps")
$env:HIP_PATH=$(resolve-path ".\dist\deps")
& .\scripts\build_windows.ps1
- uses: actions/upload-artifact@v4
with:
name: dist-windows
path: dist/*.exe
# Linux x86 assets built using the container based build
build-linux-amd64:
environment: release
runs-on: linux
env:
OLLAMA_SKIP_MANIFEST_CREATE: "1"
BUILD_ARCH: amd64
PUSH: "1"
steps:
- uses: actions/checkout@v4
with:
submodules: recursive
- name: Set Version
shell: bash
run: echo "VERSION=${GITHUB_REF_NAME#v}" >> $GITHUB_ENV
- name: Login to Docker Hub
uses: docker/login-action@v3
with:
username: ${{ vars.DOCKER_USER }}
password: ${{ secrets.DOCKER_ACCESS_TOKEN }}
- run: |
./scripts/build_linux.sh
./scripts/build_docker.sh
mv dist/deps/* dist/
- uses: actions/upload-artifact@v4
with:
name: dist-linux-amd64
path: |
dist/*linux*
!dist/*-cov
# Linux ARM assets built using the container based build
# (at present, docker isn't pre-installed on arm ubunutu images)
build-linux-arm64:
environment: release
runs-on: linux-arm64
env:
OLLAMA_SKIP_MANIFEST_CREATE: "1"
BUILD_ARCH: arm64
PUSH: "1"
steps:
- uses: actions/checkout@v4
with:
submodules: recursive
- name: Set Version
shell: bash
run: echo "VERSION=${GITHUB_REF_NAME#v}" >> $GITHUB_ENV
- name: "Install Docker"
run: |
# Add Docker's official GPG key:
env
uname -a
sudo apt-get update
sudo apt-get install -y ca-certificates curl
sudo install -m 0755 -d /etc/apt/keyrings
sudo curl -fsSL https://download.docker.com/linux/ubuntu/gpg -o /etc/apt/keyrings/docker.asc
sudo chmod a+r /etc/apt/keyrings/docker.asc
# Add the repository to Apt sources:
echo \
"deb [arch=$(dpkg --print-architecture) signed-by=/etc/apt/keyrings/docker.asc] https://download.docker.com/linux/ubuntu \
$(. /etc/os-release && echo "$VERSION_CODENAME") stable" | \
sudo tee /etc/apt/sources.list.d/docker.list > /dev/null
sudo apt-get update
sudo apt-get install -y docker-ce docker-ce-cli containerd.io
sudo usermod -aG docker $USER
sudo apt-get install acl
sudo setfacl --modify user:$USER:rw /var/run/docker.sock
- name: Login to Docker Hub
uses: docker/login-action@v3
with:
username: ${{ vars.DOCKER_USER }}
password: ${{ secrets.DOCKER_ACCESS_TOKEN }}
- run: |
./scripts/build_linux.sh
./scripts/build_docker.sh
- uses: actions/upload-artifact@v4
with:
name: dist-linux-arm64
path: |
dist/*linux*
!dist/*-cov
# Aggregate all the assets and ship a release
release:
needs:
- build-darwin
- build-windows
- build-linux-amd64
- build-linux-arm64
runs-on: linux
environment: release
permissions:
contents: write
env:
OLLAMA_SKIP_IMAGE_BUILD: "1"
PUSH: "1"
steps:
- uses: actions/checkout@v4
- name: Set Version
shell: bash
run: |
echo "VERSION=${GITHUB_REF_NAME#v}" >> $GITHUB_ENV
echo "RELEASE_VERSION=$(echo ${GITHUB_REF_NAME} | cut -f1 -d-)" >> $GITHUB_ENV
- name: Login to Docker Hub
uses: docker/login-action@v3
with:
username: ${{ vars.DOCKER_USER }}
password: ${{ secrets.DOCKER_ACCESS_TOKEN }}
- run: ./scripts/build_docker.sh
- name: Retrieve built artifact
uses: actions/download-artifact@v4
with:
path: dist
pattern: dist-*
merge-multiple: true
- run: |
ls -lh dist/
(cd dist; sha256sum * > sha256sum.txt)
cat dist/sha256sum.txt
- uses: ncipollo/release-action@v1
with:
name: ${{ env.RELEASE_VERSION }}
allowUpdates: true
artifacts: "dist/*"
draft: true
prerelease: true
omitBodyDuringUpdate: true
generateReleaseNotes: true
omitDraftDuringUpdate: true
omitPrereleaseDuringUpdate: true
replacesArtifacts: true

View File

@@ -9,7 +9,32 @@ on:
- '!README.md'
jobs:
changes:
runs-on: ubuntu-latest
outputs:
GENERATE: ${{ steps.changes.outputs.GENERATE }}
GENERATE_CUDA: ${{ steps.changes.outputs.GENERATE_CUDA }}
GENERATE_ROCM: ${{ steps.changes.outputs.GENERATE_ROCM }}
steps:
- uses: actions/checkout@v4
with:
fetch-depth: 0
- id: changes
run: |
changed() {
git diff-tree -r --no-commit-id --name-only ${{ github.event.pull_request.base.sha }} ${{ github.event.pull_request.head.sha }} \
| xargs python3 -c "import sys; print(any([x.startswith('$1') for x in sys.argv[1:]]))"
}
{
echo GENERATE=$(changed llm/)
echo GENERATE_CUDA=$(changed llm/)
echo GENERATE_ROCM=$(changed llm/)
} >>$GITHUB_OUTPUT
generate:
needs: [changes]
if: ${{ needs.changes.outputs.GENERATE == 'True' }}
strategy:
matrix:
os: [ubuntu-latest, macos-latest, windows-2019]
@@ -31,10 +56,12 @@ jobs:
- run: go get ./...
- run: |
$gopath=(get-command go).source | split-path -parent
$gccpath=(get-command gcc).source | split-path -parent
& "C:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\Common7\Tools\Launch-VsDevShell.ps1"
cd $env:GITHUB_WORKSPACE
$env:CMAKE_SYSTEM_VERSION="10.0.22621.0"
$env:PATH="$gopath;$env:PATH"
$env:PATH="$gopath;$gccpath;$env:PATH"
echo $env:PATH
go generate -x ./...
if: ${{ startsWith(matrix.os, 'windows-') }}
name: "Windows Go Generate"
@@ -44,8 +71,12 @@ jobs:
- uses: actions/upload-artifact@v4
with:
name: ${{ matrix.os }}-${{ matrix.arch }}-libraries
path: llm/llama.cpp/build/**/lib/*
path: |
llm/build/**/bin/*
llm/build/**/*.a
generate-cuda:
needs: [changes]
if: ${{ needs.changes.outputs.GENERATE_CUDA == 'True' }}
strategy:
matrix:
cuda-version:
@@ -73,12 +104,14 @@ jobs:
- uses: actions/upload-artifact@v4
with:
name: cuda-${{ matrix.cuda-version }}-libraries
path: llm/llama.cpp/build/**/lib/*
path: llm/build/**/bin/*
generate-rocm:
needs: [changes]
if: ${{ needs.changes.outputs.GENERATE_ROCM == 'True' }}
strategy:
matrix:
rocm-version:
- '6.0'
- '6.0.2'
runs-on: linux
container: rocm/dev-ubuntu-20.04:${{ matrix.rocm-version }}
steps:
@@ -102,7 +135,88 @@ jobs:
- uses: actions/upload-artifact@v4
with:
name: rocm-${{ matrix.rocm-version }}-libraries
path: llm/llama.cpp/build/**/lib/*
path: llm/build/**/lib/*
# ROCm generation step
generate-windows-rocm:
needs: [changes]
if: ${{ needs.changes.outputs.GENERATE_ROCM == 'True' }}
runs-on: windows
steps:
- uses: actions/checkout@v4
- uses: actions/setup-go@v5
with:
go-version: '1.22'
cache: true
- name: "Install ROCm"
run: |
$ErrorActionPreference = "Stop"
write-host "downloading AMD HIP Installer"
Invoke-WebRequest -Uri "https://download.amd.com/developer/eula/rocm-hub/AMD-Software-PRO-Edition-23.Q4-WinSvr2022-For-HIP.exe" -OutFile "${env:RUNNER_TEMP}\rocm-install.exe"
write-host "Installing AMD HIP"
Start-Process "${env:RUNNER_TEMP}\rocm-install.exe" -ArgumentList '-install' -NoNewWindow -Wait
write-host "Completed AMD HIP"
- name: "Verify ROCm"
run: |
& 'C:\Program Files\AMD\ROCm\*\bin\clang.exe' --version
- run: go get ./...
- run: |
$gopath=(get-command go).source | split-path -parent
& "C:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\Common7\Tools\Launch-VsDevShell.ps1"
cd $env:GITHUB_WORKSPACE
$env:CMAKE_SYSTEM_VERSION="10.0.22621.0"
$env:PATH="$gopath;$env:PATH"
$env:OLLAMA_SKIP_CPU_GENERATE="1"
$env:HIP_PATH=$(Resolve-Path 'C:\Program Files\AMD\ROCm\*\bin\clang.exe' | split-path | split-path)
go generate -x ./...
name: go generate
env:
OLLAMA_SKIP_CPU_GENERATE: '1'
# TODO - do we need any artifacts?
# CUDA generation step
generate-windows-cuda:
needs: [changes]
if: ${{ needs.changes.outputs.GENERATE_CUDA == 'True' }}
runs-on: windows
steps:
- uses: actions/checkout@v4
- uses: actions/setup-go@v5
with:
go-version: '1.22'
cache: true
- name: "Install CUDA"
run: |
$ErrorActionPreference = "Stop"
write-host "downloading CUDA Installer"
Invoke-WebRequest -Uri "https://developer.download.nvidia.com/compute/cuda/11.3.1/local_installers/cuda_11.3.1_465.89_win10.exe" -OutFile "${env:RUNNER_TEMP}\cuda-install.exe"
write-host "Installing CUDA"
Start-Process "${env:RUNNER_TEMP}\cuda-install.exe" -ArgumentList '-s' -NoNewWindow -Wait
write-host "Completed CUDA"
$cudaPath=((resolve-path "c:\Program Files\NVIDIA*\CUDA\v*\bin\nvcc.exe")[0].path | split-path | split-path)
$cudaVer=($cudaPath | split-path -leaf ) -replace 'v(\d+).(\d+)', '$1_$2'
echo "$cudaPath\bin" >> $env:GITHUB_PATH
echo "CUDA_PATH=$cudaPath" >> $env:GITHUB_ENV
echo "CUDA_PATH_V${cudaVer}=$cudaPath" >> $env:GITHUB_ENV
echo "CUDA_PATH_VX_Y=CUDA_PATH_V${cudaVer}" >> $env:GITHUB_ENV
- name: "Verify CUDA"
run: nvcc -V
- run: go get ./...
- name: go generate
run: |
$gopath=(get-command go).source | split-path -parent
$cudabin=(get-command nvcc).source | split-path
& "C:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\Common7\Tools\Launch-VsDevShell.ps1"
cd $env:GITHUB_WORKSPACE
$env:CMAKE_SYSTEM_VERSION="10.0.22621.0"
$env:PATH="$gopath;$cudabin;$env:PATH"
$env:OLLAMA_SKIP_CPU_GENERATE="1"
go generate -x ./...
env:
OLLAMA_SKIP_CPU_GENERATE: '1'
# TODO - do we need any artifacts?
lint:
strategy:
matrix:
@@ -128,21 +242,28 @@ jobs:
go-version: '1.22'
cache: false
- run: |
mkdir -p llm/llama.cpp/build/linux/${{ matrix.arch }}/stub/lib/
touch llm/llama.cpp/build/linux/${{ matrix.arch }}/stub/lib/stub.so
case ${{ matrix.arch }} in
amd64) echo ARCH=x86_64 ;;
arm64) echo ARCH=arm64 ;;
esac >>$GITHUB_ENV
shell: bash
- run: |
mkdir -p llm/build/linux/$ARCH/stub/bin/
touch llm/build/linux/$ARCH/stub/bin/stub.so
if: ${{ startsWith(matrix.os, 'ubuntu-') }}
- run: |
mkdir -p llm/llama.cpp/build/darwin/${{ matrix.arch }}/stub/lib/
touch llm/llama.cpp/build/darwin/${{ matrix.arch }}/stub/lib/stub.dylib
touch llm/llama.cpp/ggml-metal.metal
mkdir -p llm/build/darwin/$ARCH/stub/bin/
touch llm/build/darwin/$ARCH/stub/bin/stub.dylib
touch llm/ggml-metal.metal
if: ${{ startsWith(matrix.os, 'macos-') }}
- run: |
mkdir -p llm/llama.cpp/build/windows/${{ matrix.arch }}/stub/lib/
touch llm/llama.cpp/build/windows/${{ matrix.arch }}/stub/lib/stub.dll
mkdir -p llm/build/windows/$ARCH/stub/stub/bin/
touch llm/build/windows/$ARCH/stub/stub/bin/stub.dll
if: ${{ startsWith(matrix.os, 'windows-') }}
- uses: golangci/golangci-lint-action@v3
- uses: golangci/golangci-lint-action@v4
with:
args: --timeout 8m0s
test:
needs: generate
strategy:
matrix:
os: [ubuntu-latest, macos-latest, windows-2019]
@@ -156,6 +277,7 @@ jobs:
env:
GOARCH: ${{ matrix.arch }}
CGO_ENABLED: '1'
OLLAMA_CPU_TARGET: "static"
steps:
- uses: actions/checkout@v4
with:
@@ -165,10 +287,26 @@ jobs:
go-version: '1.22'
cache: true
- run: go get
- uses: actions/download-artifact@v4
with:
name: ${{ matrix.os }}-${{ matrix.arch }}-libraries
path: llm/llama.cpp/build
- run: |
case ${{ matrix.arch }} in
amd64) echo ARCH=x86_64 ;;
arm64) echo ARCH=arm64 ;;
esac >>$GITHUB_ENV
shell: bash
- run: |
mkdir -p llm/build/linux/$ARCH/stub/bin/
touch llm//build/linux/$ARCH/stub/bin/stub.so
if: ${{ startsWith(matrix.os, 'ubuntu-') }}
- run: |
mkdir -p llm/build/darwin/$ARCH/stub/bin/
touch llm/build/darwin/$ARCH/stub/bin/stub.dylib
touch llm/ggml-metal.metal
if: ${{ startsWith(matrix.os, 'macos-') }}
- run: |
mkdir -p llm/build/windows/$ARCH/stub/stub/bin/
touch llm/build/windows/$ARCH/stub/stub/bin/stub.dll
if: ${{ startsWith(matrix.os, 'windows-') }}
- run: go generate ./...
- run: go build
- run: go test -v ./...
- uses: actions/upload-artifact@v4

3
.gitignore vendored
View File

@@ -10,4 +10,5 @@ ggml-metal.metal
*.exe
.idea
test_data
*.crt
*.crt
llm/build

View File

@@ -15,13 +15,3 @@ linters:
- misspell
- nilerr
- unused
linters-settings:
errcheck:
# exclude the following functions since we don't generally
# need to be concerned with the returned errors
exclude-functions:
- encoding/binary.Read
- (*os.File).Seek
- (*bufio.Writer).WriteString
- (*github.com/spf13/pflag.FlagSet).Set
- (*github.com/jmorganca/ollama/llm.readSeekOffset).Seek

View File

@@ -1,7 +1,8 @@
ARG GOLANG_VERSION=1.22.1
ARG CMAKE_VERSION=3.22.1
# this CUDA_VERSION corresponds with the one specified in docs/gpu.md
ARG CUDA_VERSION=11.3.1
ARG ROCM_VERSION=6.0
ARG ROCM_VERSION=6.0.2
# Copy the minimal context we need to run the generate scripts
FROM scratch AS llm-code
@@ -14,8 +15,8 @@ ARG CMAKE_VERSION
COPY ./scripts/rh_linux_deps.sh /
RUN CMAKE_VERSION=${CMAKE_VERSION} sh /rh_linux_deps.sh
ENV PATH /opt/rh/devtoolset-10/root/usr/bin:$PATH
COPY --from=llm-code / /go/src/github.com/jmorganca/ollama/
WORKDIR /go/src/github.com/jmorganca/ollama/llm/generate
COPY --from=llm-code / /go/src/github.com/ollama/ollama/
WORKDIR /go/src/github.com/ollama/ollama/llm/generate
ARG CGO_CFLAGS
RUN OLLAMA_SKIP_CPU_GENERATE=1 sh gen_linux.sh
@@ -24,8 +25,8 @@ ARG CMAKE_VERSION
COPY ./scripts/rh_linux_deps.sh /
RUN CMAKE_VERSION=${CMAKE_VERSION} sh /rh_linux_deps.sh
ENV PATH /opt/rh/gcc-toolset-10/root/usr/bin:$PATH
COPY --from=llm-code / /go/src/github.com/jmorganca/ollama/
WORKDIR /go/src/github.com/jmorganca/ollama/llm/generate
COPY --from=llm-code / /go/src/github.com/ollama/ollama/
WORKDIR /go/src/github.com/ollama/ollama/llm/generate
ARG CGO_CFLAGS
RUN OLLAMA_SKIP_CPU_GENERATE=1 sh gen_linux.sh
@@ -35,18 +36,18 @@ COPY ./scripts/rh_linux_deps.sh /
RUN CMAKE_VERSION=${CMAKE_VERSION} sh /rh_linux_deps.sh
ENV PATH /opt/rh/devtoolset-10/root/usr/bin:$PATH
ENV LIBRARY_PATH /opt/amdgpu/lib64
COPY --from=llm-code / /go/src/github.com/jmorganca/ollama/
WORKDIR /go/src/github.com/jmorganca/ollama/llm/generate
COPY --from=llm-code / /go/src/github.com/ollama/ollama/
WORKDIR /go/src/github.com/ollama/ollama/llm/generate
ARG CGO_CFLAGS
ARG AMDGPU_TARGETS
RUN OLLAMA_SKIP_CPU_GENERATE=1 sh gen_linux.sh
RUN mkdir /tmp/scratch && \
for dep in $(cat /go/src/github.com/jmorganca/ollama/llm/llama.cpp/build/linux/x86_64/rocm*/lib/deps.txt) ; do \
for dep in $(cat /go/src/github.com/ollama/ollama/llm/llama.cpp/build/linux/x86_64/rocm*/lib/deps.txt) ; do \
cp ${dep} /tmp/scratch/ || exit 1 ; \
done && \
(cd /opt/rocm/lib && tar cf - rocblas/library) | (cd /tmp/scratch/ && tar xf - ) && \
mkdir -p /go/src/github.com/jmorganca/ollama/dist/deps/ && \
(cd /tmp/scratch/ && tar czvf /go/src/github.com/jmorganca/ollama/dist/deps/ollama-linux-amd64-rocm.tgz . )
mkdir -p /go/src/github.com/ollama/ollama/dist/deps/ && \
(cd /tmp/scratch/ && tar czvf /go/src/github.com/ollama/ollama/dist/deps/ollama-linux-amd64-rocm.tgz . )
FROM --platform=linux/amd64 centos:7 AS cpu-builder-amd64
@@ -55,11 +56,13 @@ ARG GOLANG_VERSION
COPY ./scripts/rh_linux_deps.sh /
RUN CMAKE_VERSION=${CMAKE_VERSION} GOLANG_VERSION=${GOLANG_VERSION} sh /rh_linux_deps.sh
ENV PATH /opt/rh/devtoolset-10/root/usr/bin:$PATH
COPY --from=llm-code / /go/src/github.com/jmorganca/ollama/
COPY --from=llm-code / /go/src/github.com/ollama/ollama/
ARG OLLAMA_CUSTOM_CPU_DEFS
ARG CGO_CFLAGS
WORKDIR /go/src/github.com/jmorganca/ollama/llm/generate
WORKDIR /go/src/github.com/ollama/ollama/llm/generate
FROM --platform=linux/amd64 cpu-builder-amd64 AS static-build-amd64
RUN OLLAMA_CPU_TARGET="static" sh gen_linux.sh
FROM --platform=linux/amd64 cpu-builder-amd64 AS cpu-build-amd64
RUN OLLAMA_CPU_TARGET="cpu" sh gen_linux.sh
FROM --platform=linux/amd64 cpu-builder-amd64 AS cpu_avx-build-amd64
@@ -67,56 +70,62 @@ RUN OLLAMA_CPU_TARGET="cpu_avx" sh gen_linux.sh
FROM --platform=linux/amd64 cpu-builder-amd64 AS cpu_avx2-build-amd64
RUN OLLAMA_CPU_TARGET="cpu_avx2" sh gen_linux.sh
FROM --platform=linux/arm64 centos:7 AS cpu-build-arm64
FROM --platform=linux/arm64 centos:7 AS cpu-builder-arm64
ARG CMAKE_VERSION
ARG GOLANG_VERSION
COPY ./scripts/rh_linux_deps.sh /
RUN CMAKE_VERSION=${CMAKE_VERSION} GOLANG_VERSION=${GOLANG_VERSION} sh /rh_linux_deps.sh
ENV PATH /opt/rh/devtoolset-10/root/usr/bin:$PATH
COPY --from=llm-code / /go/src/github.com/jmorganca/ollama/
WORKDIR /go/src/github.com/jmorganca/ollama/llm/generate
# Note, we only build the "base" CPU variant on arm since avx/avx2 are x86 features
COPY --from=llm-code / /go/src/github.com/ollama/ollama/
ARG OLLAMA_CUSTOM_CPU_DEFS
ARG CGO_CFLAGS
WORKDIR /go/src/github.com/ollama/ollama/llm/generate
FROM --platform=linux/arm64 cpu-builder-arm64 AS static-build-arm64
RUN OLLAMA_CPU_TARGET="static" sh gen_linux.sh
FROM --platform=linux/arm64 cpu-builder-arm64 AS cpu-build-arm64
RUN OLLAMA_CPU_TARGET="cpu" sh gen_linux.sh
# Intermediate stage used for ./scripts/build_linux.sh
FROM --platform=linux/amd64 cpu-build-amd64 AS build-amd64
ENV CGO_ENABLED 1
WORKDIR /go/src/github.com/jmorganca/ollama
WORKDIR /go/src/github.com/ollama/ollama
COPY . .
COPY --from=cpu_avx-build-amd64 /go/src/github.com/jmorganca/ollama/llm/llama.cpp/build/linux/ llm/llama.cpp/build/linux/
COPY --from=cpu_avx2-build-amd64 /go/src/github.com/jmorganca/ollama/llm/llama.cpp/build/linux/ llm/llama.cpp/build/linux/
COPY --from=cuda-build-amd64 /go/src/github.com/jmorganca/ollama/llm/llama.cpp/build/linux/ llm/llama.cpp/build/linux/
COPY --from=rocm-build-amd64 /go/src/github.com/jmorganca/ollama/llm/llama.cpp/build/linux/ llm/llama.cpp/build/linux/
COPY --from=rocm-build-amd64 /go/src/github.com/jmorganca/ollama/dist/deps/ ./dist/deps/
COPY --from=static-build-amd64 /go/src/github.com/ollama/ollama/llm/build/linux/ llm/build/linux/
COPY --from=cpu_avx-build-amd64 /go/src/github.com/ollama/ollama/llm/build/linux/ llm/build/linux/
COPY --from=cpu_avx2-build-amd64 /go/src/github.com/ollama/ollama/llm/build/linux/ llm/build/linux/
COPY --from=cuda-build-amd64 /go/src/github.com/ollama/ollama/llm/build/linux/ llm/build/linux/
COPY --from=rocm-build-amd64 /go/src/github.com/ollama/ollama/llm/build/linux/ llm/build/linux/
COPY --from=rocm-build-amd64 /go/src/github.com/ollama/ollama/dist/deps/ ./dist/deps/
ARG GOFLAGS
ARG CGO_CFLAGS
RUN go build .
RUN go build -trimpath .
# Intermediate stage used for ./scripts/build_linux.sh
FROM --platform=linux/arm64 cpu-build-arm64 AS build-arm64
ENV CGO_ENABLED 1
ARG GOLANG_VERSION
WORKDIR /go/src/github.com/jmorganca/ollama
WORKDIR /go/src/github.com/ollama/ollama
COPY . .
COPY --from=cuda-build-arm64 /go/src/github.com/jmorganca/ollama/llm/llama.cpp/build/linux/ llm/llama.cpp/build/linux/
COPY --from=static-build-arm64 /go/src/github.com/ollama/ollama/llm/build/linux/ llm/build/linux/
COPY --from=cuda-build-arm64 /go/src/github.com/ollama/ollama/llm/build/linux/ llm/build/linux/
ARG GOFLAGS
ARG CGO_CFLAGS
RUN go build .
RUN go build -trimpath .
# Runtime stages
FROM --platform=linux/amd64 ubuntu:22.04 as runtime-amd64
RUN apt-get update && apt-get install -y ca-certificates
COPY --from=build-amd64 /go/src/github.com/jmorganca/ollama/ollama /bin/ollama
COPY --from=build-amd64 /go/src/github.com/ollama/ollama/ollama /bin/ollama
FROM --platform=linux/arm64 ubuntu:22.04 as runtime-arm64
RUN apt-get update && apt-get install -y ca-certificates
COPY --from=build-arm64 /go/src/github.com/jmorganca/ollama/ollama /bin/ollama
COPY --from=build-arm64 /go/src/github.com/ollama/ollama/ollama /bin/ollama
# Radeon images are much larger so we keep it distinct from the CPU/CUDA image
FROM --platform=linux/amd64 rocm/dev-centos-7:${ROCM_VERSION}-complete as runtime-rocm
RUN update-pciids
COPY --from=build-amd64 /go/src/github.com/jmorganca/ollama/ollama /bin/ollama
COPY --from=build-amd64 /go/src/github.com/ollama/ollama/ollama /bin/ollama
EXPOSE 11434
ENV OLLAMA_HOST 0.0.0.0

View File

@@ -1,5 +1,5 @@
<div align="center">
<img alt="ollama" height="200px" src="https://github.com/jmorganca/ollama/assets/3325447/0d0b44e2-8f4a-4e99-9b52-a5c1c741c8f7">
<img alt="ollama" height="200px" src="https://github.com/ollama/ollama/assets/3325447/0d0b44e2-8f4a-4e99-9b52-a5c1c741c8f7">
</div>
# Ollama
@@ -22,7 +22,7 @@ Get up and running with large language models locally.
curl -fsSL https://ollama.com/install.sh | sh
```
[Manual install instructions](https://github.com/jmorganca/ollama/blob/main/docs/linux.md)
[Manual install instructions](https://github.com/ollama/ollama/blob/main/docs/linux.md)
### Docker
@@ -213,7 +213,7 @@ Then build the binary:
go build .
```
More detailed instructions can be found in the [developer guide](https://github.com/jmorganca/ollama/blob/main/docs/development.md)
More detailed instructions can be found in the [developer guide](https://github.com/ollama/ollama/blob/main/docs/development.md)
### Running local builds
@@ -259,9 +259,12 @@ See the [API documentation](./docs/api.md) for all endpoints.
### Web & Desktop
- [Lollms-Webui](https://github.com/ParisNeo/lollms-webui)
- [LibreChat](https://github.com/danny-avila/LibreChat)
- [Bionic GPT](https://github.com/bionic-gpt/bionic-gpt)
- [Enchanted (macOS native)](https://github.com/AugustDev/enchanted)
- [HTML UI](https://github.com/rtcfirefly/ollama-ui)
- [Saddle](https://github.com/jikkuatwork/saddle)
- [Chatbot UI](https://github.com/ivanfioravanti/chatbot-ollama)
- [Typescript UI](https://github.com/ollama-interface/Ollama-Gui?tab=readme-ov-file)
- [Minimalistic React UI for Ollama Models](https://github.com/richawo/minimal-llm-ui)
@@ -272,14 +275,23 @@ See the [API documentation](./docs/api.md) for all endpoints.
- [Amica](https://github.com/semperai/amica)
- [chatd](https://github.com/BruceMacD/chatd)
- [Ollama-SwiftUI](https://github.com/kghandour/Ollama-SwiftUI)
- [Dify.AI](https://github.com/langgenius/dify)
- [MindMac](https://mindmac.app)
- [NextJS Web Interface for Ollama](https://github.com/jakobhoeg/nextjs-ollama-llm-ui)
- [Msty](https://msty.app)
- [Chatbox](https://github.com/Bin-Huang/Chatbox)
- [WinForm Ollama Copilot](https://github.com/tgraupmann/WinForm_Ollama_Copilot)
- [NextChat](https://github.com/ChatGPTNextWeb/ChatGPT-Next-Web) with [Get Started Doc](https://docs.nextchat.dev/models/ollama)
- [Alpaca WebUI](https://github.com/mmo80/alpaca-webui)
- [OllamaGUI](https://github.com/enoch1118/ollamaGUI)
- [OpenAOE](https://github.com/InternLM/OpenAOE)
- [Odin Runes](https://github.com/leonid20000/OdinRunes)
- [LLM-X: Progressive Web App](https://github.com/mrdjohnson/llm-x)
- [AnythingLLM (Docker + MacOs/Windows/Linux native app)](https://github.com/Mintplex-Labs/anything-llm)
- [Ollama Basic Chat: Uses HyperDiv Reactive UI](https://github.com/rapidarchitect/ollama_basic_chat)
- [Ollama-chats RPG](https://github.com/drazdra/ollama-chats)
- [ChatOllama: Open Source Chatbot based on Ollama with Knowledge Bases](https://github.com/sugarforever/chat-ollama)
- [CRAG Ollama Chat: Simple Web Search with Corrective RAG](https://github.com/Nagi-ovo/CRAG-Ollama-Chat)
### Terminal
@@ -288,18 +300,23 @@ See the [API documentation](./docs/api.md) for all endpoints.
- [Emacs client](https://github.com/zweifisch/ollama)
- [gen.nvim](https://github.com/David-Kunz/gen.nvim)
- [ollama.nvim](https://github.com/nomnivore/ollama.nvim)
- [ollero.nvim](https://github.com/marco-souza/ollero.nvim)
- [ollama-chat.nvim](https://github.com/gerazov/ollama-chat.nvim)
- [ogpt.nvim](https://github.com/huynle/ogpt.nvim)
- [gptel Emacs client](https://github.com/karthink/gptel)
- [Oatmeal](https://github.com/dustinblackman/oatmeal)
- [cmdh](https://github.com/pgibler/cmdh)
- [ooo](https://github.com/npahlfer/ooo)
- [tenere](https://github.com/pythops/tenere)
- [llm-ollama](https://github.com/taketwo/llm-ollama) for [Datasette's LLM CLI](https://llm.datasette.io/en/stable/).
- [typechat-cli](https://github.com/anaisbetts/typechat-cli)
- [ShellOracle](https://github.com/djcopley/ShellOracle)
- [tlm](https://github.com/yusufcanb/tlm)
### Database
- [MindsDB](https://github.com/mindsdb/mindsdb/blob/staging/mindsdb/integrations/handlers/ollama_handler/README.md)
- [chromem-go](https://github.com/philippgille/chromem-go/blob/v0.5.0/embed_ollama.go) with [example](https://github.com/philippgille/chromem-go/tree/v0.5.0/examples/rag-wikipedia-ollama)
### Package managers
@@ -312,7 +329,6 @@ See the [API documentation](./docs/api.md) for all endpoints.
- [LangChainGo](https://github.com/tmc/langchaingo/) with [example](https://github.com/tmc/langchaingo/tree/main/examples/ollama-completion-example)
- [LangChain4j](https://github.com/langchain4j/langchain4j) with [example](https://github.com/langchain4j/langchain4j-examples/tree/main/ollama-examples/src/main/java)
- [LlamaIndex](https://gpt-index.readthedocs.io/en/stable/examples/llm/ollama.html)
- [LangChain4j](https://github.com/langchain4j/langchain4j/tree/main/langchain4j-ollama)
- [LiteLLM](https://github.com/BerriAI/litellm)
- [OllamaSharp for .NET](https://github.com/awaescher/OllamaSharp)
- [Ollama for Ruby](https://github.com/gbaptista/ollama-ai)
@@ -329,6 +345,7 @@ See the [API documentation](./docs/api.md) for all endpoints.
- [Ollama for R - rollama](https://github.com/JBGruber/rollama)
- [Ollama-ex for Elixir](https://github.com/lebrunel/ollama-ex)
- [Ollama Connector for SAP ABAP](https://github.com/b-tocs/abap_btocs_ollama)
- [Testcontainers](https://testcontainers.com/modules/ollama/)
### Mobile
@@ -350,9 +367,12 @@ See the [API documentation](./docs/api.md) for all endpoints.
- [Rivet plugin](https://github.com/abrenneke/rivet-plugin-ollama)
- [Llama Coder](https://github.com/ex3ndr/llama-coder) (Copilot alternative using Ollama)
- [Obsidian BMO Chatbot plugin](https://github.com/longy2k/obsidian-bmo-chatbot)
- [Cliobot](https://github.com/herval/cliobot) (Telegram bot with Ollama support)
- [Copilot for Obsidian plugin](https://github.com/logancyang/obsidian-copilot)
- [Obsidian Local GPT plugin](https://github.com/pfrankov/obsidian-local-gpt)
- [Open Interpreter](https://docs.openinterpreter.com/language-model-setup/local-models/ollama)
- [twinny](https://github.com/rjmacarthy/twinny) (Copilot and Copilot chat alternative using Ollama)
- [Wingman-AI](https://github.com/RussellCanfield/wingman-ai) (Copilot code and chat alternative using Ollama and HuggingFace)
- [Page Assist](https://github.com/n4ze3m/page-assist) (Chrome Extension)
- [AI Telegram Bot](https://github.com/tusharhero/aitelegrambot) (Telegram bot using Ollama in backend)
- [AI ST Completion](https://github.com/yaroslavyaroslav/OpenAI-sublime-text) (Sublime Text 4 AI assistant plugin with Ollama support)

View File

@@ -15,8 +15,8 @@ import (
"runtime"
"strings"
"github.com/jmorganca/ollama/format"
"github.com/jmorganca/ollama/version"
"github.com/ollama/ollama/format"
"github.com/ollama/ollama/version"
)
type Client struct {

50
api/types_test.go Normal file
View File

@@ -0,0 +1,50 @@
package api
import (
"encoding/json"
"math"
"testing"
"time"
"github.com/stretchr/testify/assert"
"github.com/stretchr/testify/require"
)
func TestKeepAliveParsingFromJSON(t *testing.T) {
tests := []struct {
name string
req string
exp *Duration
}{
{
name: "Positive Integer",
req: `{ "keep_alive": 42 }`,
exp: &Duration{42 * time.Second},
},
{
name: "Positive Integer String",
req: `{ "keep_alive": "42m" }`,
exp: &Duration{42 * time.Minute},
},
{
name: "Negative Integer",
req: `{ "keep_alive": -1 }`,
exp: &Duration{math.MaxInt64},
},
{
name: "Negative Integer String",
req: `{ "keep_alive": "-1m" }`,
exp: &Duration{math.MaxInt64},
},
}
for _, test := range tests {
t.Run(test.name, func(t *testing.T) {
var dec ChatRequest
err := json.Unmarshal([]byte(test.req), &dec)
require.NoError(t, err)
assert.Equal(t, test.exp, dec.KeepAlive)
})
}
}

View File

@@ -9,8 +9,8 @@ import (
"os/signal"
"syscall"
"github.com/jmorganca/ollama/app/store"
"github.com/jmorganca/ollama/app/tray"
"github.com/ollama/ollama/app/store"
"github.com/ollama/ollama/app/tray"
)
func Run() {

View File

@@ -9,9 +9,10 @@ import (
"os"
"os/exec"
"path/filepath"
"syscall"
"time"
"github.com/jmorganca/ollama/api"
"github.com/ollama/ollama/api"
)
func getCLIFullPath(command string) string {
@@ -83,6 +84,28 @@ func SpawnServer(ctx context.Context, command string) (chan int, error) {
io.Copy(logFile, stderr) //nolint:errcheck
}()
// Re-wire context done behavior to attempt a graceful shutdown of the server
cmd.Cancel = func() error {
if cmd.Process != nil {
cmd.Process.Signal(os.Interrupt) //nolint:errcheck
tick := time.NewTicker(10 * time.Millisecond)
defer tick.Stop()
for {
select {
case <-tick.C:
// OS agnostic "is it still running"
if proc, err := os.FindProcess(int(cmd.Process.Pid)); err != nil || errors.Is(proc.Signal(syscall.Signal(0)), os.ErrProcessDone) {
return nil //nolint:nilerr
}
case <-time.After(5 * time.Second):
slog.Warn("graceful server shutdown timeout, killing", "pid", cmd.Process.Pid)
cmd.Process.Kill() //nolint:errcheck
}
}
}
return nil
}
// run the command and wait for it to finish
if err := cmd.Start(); err != nil {
return done, fmt.Errorf("failed to start server %w", err)
@@ -105,7 +128,7 @@ func SpawnServer(ctx context.Context, command string) (chan int, error) {
select {
case <-ctx.Done():
slog.Debug(fmt.Sprintf("server shutdown with exit code %d", code))
slog.Info(fmt.Sprintf("server shutdown with exit code %d", code))
done <- code
return
default:

View File

@@ -18,8 +18,8 @@ import (
"strings"
"time"
"github.com/jmorganca/ollama/auth"
"github.com/jmorganca/ollama/version"
"github.com/ollama/ollama/auth"
"github.com/ollama/ollama/version"
)
var (

View File

@@ -4,7 +4,7 @@ package main
// go build -ldflags="-H windowsgui" .
import (
"github.com/jmorganca/ollama/app/lifecycle"
"github.com/ollama/ollama/app/lifecycle"
)
func main() {

View File

@@ -28,8 +28,8 @@ AppPublisher={#MyAppPublisher}
AppPublisherURL={#MyAppURL}
AppSupportURL={#MyAppURL}
AppUpdatesURL={#MyAppURL}
ArchitecturesAllowed=x64
ArchitecturesInstallIn64BitMode=x64
ArchitecturesAllowed=x64 arm64
ArchitecturesInstallIn64BitMode=x64 arm64
DefaultDirName={localappdata}\Programs\{#MyAppName}
DefaultGroupName={#MyAppName}
DisableProgramGroupPage=yes

View File

@@ -4,8 +4,8 @@ import (
"fmt"
"runtime"
"github.com/jmorganca/ollama/app/assets"
"github.com/jmorganca/ollama/app/tray/commontray"
"github.com/ollama/ollama/app/assets"
"github.com/ollama/ollama/app/tray/commontray"
)
func NewTray() (commontray.OllamaTray, error) {

View File

@@ -5,7 +5,7 @@ package tray
import (
"fmt"
"github.com/jmorganca/ollama/app/tray/commontray"
"github.com/ollama/ollama/app/tray/commontray"
)
func InitPlatformTray(icon, updateIcon []byte) (commontray.OllamaTray, error) {

View File

@@ -1,8 +1,8 @@
package tray
import (
"github.com/jmorganca/ollama/app/tray/commontray"
"github.com/jmorganca/ollama/app/tray/wintray"
"github.com/ollama/ollama/app/tray/commontray"
"github.com/ollama/ollama/app/tray/wintray"
)
func InitPlatformTray(icon, updateIcon []byte) (commontray.OllamaTray, error) {

View File

@@ -13,7 +13,7 @@ import (
"sync"
"unsafe"
"github.com/jmorganca/ollama/app/tray/commontray"
"github.com/ollama/ollama/app/tray/commontray"
"golang.org/x/sys/windows"
)

View File

@@ -30,12 +30,12 @@ import (
"golang.org/x/exp/slices"
"golang.org/x/term"
"github.com/jmorganca/ollama/api"
"github.com/jmorganca/ollama/format"
"github.com/jmorganca/ollama/parser"
"github.com/jmorganca/ollama/progress"
"github.com/jmorganca/ollama/server"
"github.com/jmorganca/ollama/version"
"github.com/ollama/ollama/api"
"github.com/ollama/ollama/format"
"github.com/ollama/ollama/parser"
"github.com/ollama/ollama/progress"
"github.com/ollama/ollama/server"
"github.com/ollama/ollama/version"
)
func CreateHandler(cmd *cobra.Command, args []string) error {
@@ -213,7 +213,10 @@ func createBlob(cmd *cobra.Command, client *api.Client, path string) (string, er
if _, err := io.Copy(hash, bin); err != nil {
return "", err
}
bin.Seek(0, io.SeekStart)
if _, err := bin.Seek(0, io.SeekStart); err != nil {
return "", err
}
digest := fmt.Sprintf("sha256:%x", hash.Sum(nil))
if err = client.CreateBlob(cmd.Context(), digest, bin); err != nil {
@@ -223,6 +226,14 @@ func createBlob(cmd *cobra.Command, client *api.Client, path string) (string, er
}
func RunHandler(cmd *cobra.Command, args []string) error {
if os.Getenv("OLLAMA_MODELS") != "" {
return errors.New("OLLAMA_MODELS must only be set for 'ollama serve'")
}
if err := checkServerHeartbeat(cmd, args); err != nil {
return err
}
client, err := api.ClientFromEnvironment()
if err != nil {
return err
@@ -900,8 +911,7 @@ func NewCLI() *cobra.Command {
cobra.EnableCommandSorting = false
if runtime.GOOS == "windows" {
// Enable colorful ANSI escape code in Windows terminal (disabled by default)
console.ConsoleFromFile(os.Stdout) //nolint:errcheck
console.ConsoleFromFile(os.Stdin) //nolint:errcheck
}
rootCmd := &cobra.Command{
@@ -949,11 +959,10 @@ func NewCLI() *cobra.Command {
showCmd.Flags().Bool("system", false, "Show system message of a model")
runCmd := &cobra.Command{
Use: "run MODEL [PROMPT]",
Short: "Run a model",
Args: cobra.MinimumNArgs(1),
PreRunE: checkServerHeartbeat,
RunE: RunHandler,
Use: "run MODEL [PROMPT]",
Short: "Run a model",
Args: cobra.MinimumNArgs(1),
RunE: RunHandler,
}
runCmd.Flags().Bool("verbose", false, "Show timings for response")
@@ -970,9 +979,11 @@ func NewCLI() *cobra.Command {
serveCmd.SetUsageTemplate(serveCmd.UsageTemplate() + `
Environment Variables:
OLLAMA_HOST The host:port to bind to (default "127.0.0.1:11434")
OLLAMA_ORIGINS A comma separated list of allowed origins.
OLLAMA_MODELS The path to the models directory (default is "~/.ollama/models")
OLLAMA_HOST The host:port to bind to (default "127.0.0.1:11434")
OLLAMA_ORIGINS A comma separated list of allowed origins.
OLLAMA_MODELS The path to the models directory (default is "~/.ollama/models")
OLLAMA_KEEP_ALIVE The duration that models stay loaded in memory (default is "5m")
OLLAMA_DEBUG Set to 1 to enable additional debug logging
`)
pullCmd := &cobra.Command{

View File

@@ -14,9 +14,9 @@ import (
"github.com/spf13/cobra"
"golang.org/x/exp/slices"
"github.com/jmorganca/ollama/api"
"github.com/jmorganca/ollama/progress"
"github.com/jmorganca/ollama/readline"
"github.com/ollama/ollama/api"
"github.com/ollama/ollama/progress"
"github.com/ollama/ollama/readline"
)
type MultilineState int
@@ -295,10 +295,14 @@ func generateInteractive(cmd *cobra.Command, opts runOptions) error {
opts.WordWrap = false
fmt.Println("Set 'nowordwrap' mode.")
case "verbose":
cmd.Flags().Set("verbose", "true")
if err := cmd.Flags().Set("verbose", "true"); err != nil {
return err
}
fmt.Println("Set 'verbose' mode.")
case "quiet":
cmd.Flags().Set("verbose", "false")
if err := cmd.Flags().Set("verbose", "false"); err != nil {
return err
}
fmt.Println("Set 'quiet' mode.")
case "format":
if len(args) < 3 || args[2] != "json" {

View File

@@ -7,7 +7,7 @@ import (
"github.com/stretchr/testify/assert"
"github.com/jmorganca/ollama/api"
"github.com/ollama/ollama/api"
)
func TestExtractFilenames(t *testing.T) {

View File

@@ -7,7 +7,7 @@ import (
"os/exec"
"strings"
"github.com/jmorganca/ollama/api"
"github.com/ollama/ollama/api"
)
func startApp(ctx context.Context, client *api.Client) error {

View File

@@ -6,7 +6,7 @@ import (
"context"
"fmt"
"github.com/jmorganca/ollama/api"
"github.com/ollama/ollama/api"
)
func startApp(ctx context.Context, client *api.Client) error {

View File

@@ -10,7 +10,7 @@ import (
"strings"
"syscall"
"github.com/jmorganca/ollama/api"
"github.com/ollama/ollama/api"
)
func startApp(ctx context.Context, client *api.Client) error {

View File

@@ -13,11 +13,13 @@ import (
"regexp"
"slices"
"github.com/d4l3k/go-bfloat16"
"github.com/mitchellh/mapstructure"
"github.com/x448/float16"
"google.golang.org/protobuf/proto"
"github.com/jmorganca/ollama/convert/sentencepiece"
"github.com/jmorganca/ollama/llm"
"github.com/ollama/ollama/convert/sentencepiece"
"github.com/ollama/ollama/llm"
)
type Params struct {
@@ -33,6 +35,15 @@ type Params struct {
RopeFreqBase float64 `json:"rope_theta"`
BoSTokenID int `json:"bos_token_id"`
EoSTokenID int `json:"eos_token_id"`
HeadDimension int `json:"head_dim"`
PaddingTokenID int `json:"pad_token_id"`
ByteOrder
}
type ByteOrder interface {
binary.ByteOrder
binary.AppendByteOrder
}
type MetaData struct {
@@ -41,27 +52,43 @@ type MetaData struct {
Offsets []int `mapstructure:"data_offsets"`
}
func ReadSafeTensors(fn string, offset uint64) ([]llm.Tensor, uint64, error) {
type ModelArch interface {
GetTensors() error
LoadVocab() error
WriteGGUF() (string, error)
}
type ModelData struct {
Path string
Name string
Params *Params
Vocab *Vocab
Tensors []llm.Tensor
}
func ReadSafeTensors(fn string, offset uint64, params *Params) ([]llm.Tensor, uint64, error) {
f, err := os.Open(fn)
if err != nil {
return []llm.Tensor{}, 0, err
return nil, 0, err
}
defer f.Close()
var jsonSize uint64
binary.Read(f, binary.LittleEndian, &jsonSize)
if err := binary.Read(f, binary.LittleEndian, &jsonSize); err != nil {
return nil, 0, err
}
buf := make([]byte, jsonSize)
_, err = io.ReadFull(f, buf)
if err != nil {
return []llm.Tensor{}, 0, err
return nil, 0, err
}
d := json.NewDecoder(bytes.NewBuffer(buf))
d.UseNumber()
var parsed map[string]interface{}
if err = d.Decode(&parsed); err != nil {
return []llm.Tensor{}, 0, err
return nil, 0, err
}
var keys []string
@@ -78,7 +105,7 @@ func ReadSafeTensors(fn string, offset uint64) ([]llm.Tensor, uint64, error) {
vals := parsed[k].(map[string]interface{})
var data MetaData
if err = mapstructure.Decode(vals, &data); err != nil {
return []llm.Tensor{}, 0, err
return nil, 0, err
}
var size uint64
@@ -100,23 +127,31 @@ func ReadSafeTensors(fn string, offset uint64) ([]llm.Tensor, uint64, error) {
ggufName, err := GetTensorName(k)
if err != nil {
slog.Error("%v", err)
return []llm.Tensor{}, 0, err
return nil, 0, err
}
shape := [4]uint64{1, 1, 1, 1}
for cnt, s := range data.Shape {
shape[cnt] = uint64(s)
shape := []uint64{0, 0, 0, 0}
for i := range data.Shape {
shape[i] = uint64(data.Shape[i])
}
t := llm.Tensor{
Name: ggufName,
Kind: kind,
Offset: offset,
Shape: shape[:],
FileName: fn,
OffsetPadding: 8 + jsonSize,
FileOffsets: []uint64{uint64(data.Offsets[0]), uint64(data.Offsets[1])},
Name: ggufName,
Kind: kind,
Offset: offset,
Shape: shape[:],
}
t.WriterTo = safetensorWriterTo{
t: &t,
params: params,
bo: params.ByteOrder,
filename: fn,
start: uint64(data.Offsets[0]),
end: uint64(data.Offsets[1]),
padding: 8 + jsonSize,
}
slog.Debug(fmt.Sprintf("%v", t))
tensors = append(tensors, t)
offset += size
@@ -124,21 +159,21 @@ func ReadSafeTensors(fn string, offset uint64) ([]llm.Tensor, uint64, error) {
return tensors, offset, nil
}
func GetSafeTensors(dirpath string) ([]llm.Tensor, error) {
func GetSafeTensors(dirpath string, params *Params) ([]llm.Tensor, error) {
var tensors []llm.Tensor
files, err := filepath.Glob(filepath.Join(dirpath, "/model-*.safetensors"))
if err != nil {
return []llm.Tensor{}, err
return nil, err
}
var offset uint64
for _, f := range files {
var t []llm.Tensor
var err error
t, offset, err = ReadSafeTensors(f, offset)
t, offset, err = ReadSafeTensors(f, offset, params)
if err != nil {
slog.Error("%v", err)
return []llm.Tensor{}, err
return nil, err
}
tensors = append(tensors, t...)
}
@@ -160,6 +195,7 @@ func GetParams(dirpath string) (*Params, error) {
return nil, err
}
params.ByteOrder = binary.LittleEndian
return &params, nil
}
@@ -171,7 +207,7 @@ type Vocab struct {
Types []int32
}
func LoadTokens(dirpath string) (*Vocab, error) {
func LoadSentencePieceTokens(dirpath string, vocabSize int) (*Vocab, error) {
slog.Info(fmt.Sprintf("reading vocab from %s", filepath.Join(dirpath, "tokenizer.model")))
in, err := os.ReadFile(filepath.Join(dirpath, "tokenizer.model"))
if err != nil {
@@ -196,6 +232,14 @@ func LoadTokens(dirpath string) (*Vocab, error) {
v.Tokens = append(v.Tokens, p.GetPiece())
v.Scores = append(v.Scores, p.GetScore())
t := p.GetType()
switch t {
case sentencepiece.ModelProto_SentencePiece_UNKNOWN:
case sentencepiece.ModelProto_SentencePiece_CONTROL:
case sentencepiece.ModelProto_SentencePiece_UNUSED:
case sentencepiece.ModelProto_SentencePiece_BYTE:
default:
t = sentencepiece.ModelProto_SentencePiece_NORMAL
}
v.Types = append(v.Types, int32(t))
}
@@ -243,6 +287,16 @@ func LoadTokens(dirpath string) (*Vocab, error) {
}
slog.Info(fmt.Sprintf("vocab size w/ extra tokens: %d", len(v.Tokens)))
if vocabSize > len(v.Tokens) {
missingTokens := vocabSize - len(v.Tokens)
slog.Warn(fmt.Sprintf("vocab is missing %d tokens", missingTokens))
for cnt := 0; cnt < missingTokens; cnt++ {
v.Tokens = append(v.Tokens, fmt.Sprintf("<dummy%05d>", cnt+1))
v.Scores = append(v.Scores, -1)
v.Types = append(v.Types, int32(llm.GGUFTokenUserDefined))
}
}
return v, nil
}
@@ -279,53 +333,102 @@ func GetTensorName(n string) (string, error) {
return "", fmt.Errorf("couldn't find a layer name for '%s'", n)
}
func WriteGGUF(name string, tensors []llm.Tensor, params *Params, vocab *Vocab) (string, error) {
c := llm.ContainerGGUF{
ByteOrder: binary.LittleEndian,
}
type safetensorWriterTo struct {
t *llm.Tensor
m := llm.NewGGUFModel(&c)
m.Tensors = tensors
m.KV["general.architecture"] = "llama"
m.KV["general.name"] = name
m.KV["llama.context_length"] = uint32(params.ContextSize)
m.KV["llama.embedding_length"] = uint32(params.HiddenSize)
m.KV["llama.block_count"] = uint32(params.HiddenLayers)
m.KV["llama.feed_forward_length"] = uint32(params.IntermediateSize)
m.KV["llama.rope.dimension_count"] = uint32(128)
m.KV["llama.attention.head_count"] = uint32(params.AttentionHeads)
m.KV["llama.attention.head_count_kv"] = uint32(params.KeyValHeads)
m.KV["llama.attention.layer_norm_rms_epsilon"] = float32(params.NormEPS)
m.KV["llama.rope.freq_base"] = float32(params.RopeFreqBase)
m.KV["general.file_type"] = uint32(1)
m.KV["tokenizer.ggml.model"] = "llama"
params *Params
bo ByteOrder
m.KV["tokenizer.ggml.tokens"] = vocab.Tokens
m.KV["tokenizer.ggml.scores"] = vocab.Scores
m.KV["tokenizer.ggml.token_type"] = vocab.Types
filename string
m.KV["tokenizer.ggml.bos_token_id"] = uint32(params.BoSTokenID)
m.KV["tokenizer.ggml.eos_token_id"] = uint32(params.EoSTokenID)
m.KV["tokenizer.ggml.unknown_token_id"] = uint32(0)
m.KV["tokenizer.ggml.add_bos_token"] = true
m.KV["tokenizer.ggml.add_eos_token"] = false
start, end, padding uint64
handler func(w io.Writer, r safetensorWriterTo, f *os.File) error
}
// llamacpp sets the chat template, however we don't need to set it since we pass it in through a layer
// m.KV["tokenizer.chat_template"] = "{{ bos_token }}{% for message in messages %}{% if (message['role'] == 'user') != (loop.index0 % 2 == 0) %}{{ raise_exception('Conversation roles must alternate user/assistant/user/assistant/...') }}{% endif %}{% if message['role'] == 'user' %}{{ '[INST] ' + message['content'] + ' [/INST]' }}{% elif message['role'] == 'assistant' %}{{ message['content'] + eos_token}}{% else %}{{ raise_exception('Only user and assistant roles are supported!') }}{% endif %}{% endfor %}" // XXX removeme
c.V3.NumTensor = uint64(len(tensors))
c.V3.NumKV = uint64(len(m.KV))
f, err := os.CreateTemp("", "ollama-gguf")
func (r safetensorWriterTo) WriteTo(w io.Writer) (n int64, err error) {
f, err := os.Open(r.filename)
if err != nil {
return "", err
return 0, err
}
defer f.Close()
err = m.Encode(f)
if err != nil {
return "", err
if _, err = f.Seek(int64(r.padding+r.start), 0); err != nil {
return 0, err
}
return f.Name(), nil
// use the handler if one is present
if r.handler != nil {
return 0, r.handler(w, r, f)
}
remaining := r.end - r.start
bufSize := uint64(10240)
var finished bool
for {
data := make([]byte, min(bufSize, remaining))
b, err := io.ReadFull(f, data)
remaining -= uint64(b)
if err == io.EOF || remaining <= 0 {
finished = true
} else if err != nil {
return 0, err
}
// convert bfloat16 -> ieee float32
tDataF32 := bfloat16.DecodeFloat32(data)
switch r.t.Kind {
case 0:
if err := binary.Write(w, r.bo, tDataF32); err != nil {
return 0, err
}
case 1:
// convert float32 -> float16
tempBuf := make([]uint16, len(data)/2)
for cnt, v := range tDataF32 {
tDataF16 := float16.Fromfloat32(v)
tempBuf[cnt] = uint16(tDataF16)
}
if err := binary.Write(w, binary.LittleEndian, tempBuf); err != nil {
return 0, err
}
}
if finished {
break
}
}
return 0, nil
}
func GetModelArchFromParams(name, dirPath string, params *Params) (ModelArch, error) {
switch len(params.Architectures) {
case 0:
return nil, fmt.Errorf("No architecture specified to convert")
case 1:
switch params.Architectures[0] {
case "MistralForCausalLM":
return &MistralModel{
ModelData{
Name: name,
Path: dirPath,
Params: params,
},
}, nil
case "GemmaForCausalLM":
return &GemmaModel{
ModelData{
Name: name,
Path: dirPath,
Params: params,
},
}, nil
default:
return nil, fmt.Errorf("Models based on '%s' are not yet supported", params.Architectures[0])
}
}
return nil, fmt.Errorf("Unknown error")
}

136
convert/gemma.go Normal file
View File

@@ -0,0 +1,136 @@
package convert
import (
"encoding/binary"
"fmt"
"io"
"log/slog"
"os"
"strings"
"github.com/d4l3k/go-bfloat16"
"github.com/pdevine/tensor"
"github.com/pdevine/tensor/native"
"github.com/ollama/ollama/llm"
)
type GemmaModel struct {
ModelData
}
func gemmaLayerHandler(w io.Writer, r safetensorWriterTo, f *os.File) error {
slog.Debug(fmt.Sprintf("converting '%s'", r.t.Name))
data := make([]byte, r.end-r.start)
if err := binary.Read(f, r.bo, data); err != nil {
return err
}
tDataF32 := bfloat16.DecodeFloat32(data)
var err error
tDataF32, err = addOnes(tDataF32, int(r.t.Shape[0]))
if err != nil {
return err
}
if err := binary.Write(w, r.bo, tDataF32); err != nil {
return err
}
return nil
}
func addOnes(data []float32, vectorSize int) ([]float32, error) {
n := tensor.New(tensor.WithShape(vectorSize), tensor.WithBacking(data))
ones := tensor.Ones(tensor.Float32, vectorSize)
var err error
n, err = n.Add(ones)
if err != nil {
return []float32{}, err
}
newN, err := native.SelectF32(n, 0)
if err != nil {
return []float32{}, err
}
var fullTensor []float32
for _, v := range newN {
fullTensor = append(fullTensor, v...)
}
return fullTensor, nil
}
func (m *GemmaModel) GetTensors() error {
t, err := GetSafeTensors(m.Path, m.Params)
if err != nil {
return err
}
m.Tensors = []llm.Tensor{}
for _, l := range t {
if strings.HasSuffix(l.Name, "norm.weight") {
wt := l.WriterTo.(safetensorWriterTo)
wt.handler = gemmaLayerHandler
l.WriterTo = wt
}
m.Tensors = append(m.Tensors, l)
}
return nil
}
func (m *GemmaModel) LoadVocab() error {
v, err := LoadSentencePieceTokens(m.Path, m.Params.VocabSize)
if err != nil {
return err
}
m.Vocab = v
return nil
}
func (m *GemmaModel) WriteGGUF() (string, error) {
kv := llm.KV{
"general.architecture": "gemma",
"general.name": m.Name,
"gemma.context_length": uint32(m.Params.ContextSize),
"gemma.embedding_length": uint32(m.Params.HiddenSize),
"gemma.block_count": uint32(m.Params.HiddenLayers),
"gemma.feed_forward_length": uint32(m.Params.IntermediateSize),
"gemma.attention.head_count": uint32(m.Params.AttentionHeads),
"gemma.attention.head_count_kv": uint32(m.Params.KeyValHeads),
"gemma.attention.layer_norm_rms_epsilon": float32(m.Params.NormEPS),
"gemma.attention.key_length": uint32(m.Params.HeadDimension),
"gemma.attention.value_length": uint32(m.Params.HeadDimension),
"general.file_type": uint32(1),
"tokenizer.ggml.model": "llama",
"tokenizer.ggml.tokens": m.Vocab.Tokens,
"tokenizer.ggml.scores": m.Vocab.Scores,
"tokenizer.ggml.token_type": m.Vocab.Types,
"tokenizer.ggml.bos_token_id": uint32(m.Params.BoSTokenID),
"tokenizer.ggml.eos_token_id": uint32(m.Params.EoSTokenID),
"tokenizer.ggml.padding_token_id": uint32(m.Params.PaddingTokenID),
"tokenizer.ggml.unknown_token_id": uint32(3),
"tokenizer.ggml.add_bos_token": true,
"tokenizer.ggml.add_eos_token": false,
}
f, err := os.CreateTemp("", "ollama-gguf")
if err != nil {
return "", err
}
defer f.Close()
mod := llm.NewGGUFV3(m.Params.ByteOrder)
if err := mod.Encode(f, kv, m.Tensors); err != nil {
return "", err
}
return f.Name(), nil
}

174
convert/mistral.go Normal file
View File

@@ -0,0 +1,174 @@
package convert
import (
"encoding/binary"
"fmt"
"io"
"os"
"regexp"
"strings"
"github.com/d4l3k/go-bfloat16"
"github.com/pdevine/tensor"
"github.com/pdevine/tensor/native"
"github.com/x448/float16"
"github.com/ollama/ollama/llm"
)
type MistralModel struct {
ModelData
}
func mistralLayerHandler(w io.Writer, r safetensorWriterTo, f *os.File) error {
layerSize := r.end - r.start
var err error
tData := make([]uint16, layerSize/2)
if err = binary.Read(f, r.bo, tData); err != nil {
return err
}
var heads uint32
if strings.Contains(r.t.Name, "attn_q") {
heads = uint32(r.params.AttentionHeads)
} else if strings.Contains(r.t.Name, "attn_k") {
heads = uint32(r.params.KeyValHeads)
if heads == 0 {
heads = uint32(r.params.AttentionHeads)
}
} else {
return fmt.Errorf("unknown layer type")
}
tData, err = repack(tData, int(heads), r.t.Shape)
if err != nil {
return err
}
var buf []byte
for _, n := range tData {
buf = r.bo.AppendUint16(buf, n)
}
tempBuf := make([]uint16, len(tData))
tDataF32 := bfloat16.DecodeFloat32(buf)
for cnt, v := range tDataF32 {
tDataF16 := float16.Fromfloat32(v)
tempBuf[cnt] = uint16(tDataF16)
}
if err = binary.Write(w, r.bo, tempBuf); err != nil {
return err
}
return nil
}
func repack(data []uint16, heads int, shape []uint64) ([]uint16, error) {
n := tensor.New(tensor.WithShape(int(shape[0]), int(shape[1])), tensor.WithBacking(data))
origShape := n.Shape().Clone()
// reshape the tensor and swap axes 1 and 2 to unpack the layer for gguf
if err := n.Reshape(heads, 2, origShape[0]/heads/2, origShape[1]); err != nil {
return nil, err
}
if err := n.T(0, 2, 1, 3); err != nil {
return nil, err
}
if err := n.Reshape(origShape...); err != nil {
return nil, err
}
if err := n.Transpose(); err != nil {
return nil, err
}
newN, err := native.SelectU16(n, 1)
if err != nil {
return nil, err
}
var fullTensor []uint16
for _, v := range newN {
fullTensor = append(fullTensor, v...)
}
return fullTensor, nil
}
func (m *MistralModel) GetTensors() error {
t, err := GetSafeTensors(m.Path, m.Params)
if err != nil {
return err
}
m.Tensors = []llm.Tensor{}
pattern := `^blk\.[0-9]+\.attn_(?P<layer>q|k)\.weight$`
re, err := regexp.Compile(pattern)
if err != nil {
return err
}
for _, l := range t {
matches := re.FindAllStringSubmatch(l.Name, -1)
if len(matches) > 0 {
wt := l.WriterTo.(safetensorWriterTo)
wt.handler = mistralLayerHandler
l.WriterTo = wt
}
m.Tensors = append(m.Tensors, l)
}
return nil
}
func (m *MistralModel) LoadVocab() error {
v, err := LoadSentencePieceTokens(m.Path, m.Params.VocabSize)
if err != nil {
return err
}
m.Vocab = v
return nil
}
func (m *MistralModel) WriteGGUF() (string, error) {
kv := llm.KV{
"general.architecture": "llama",
"general.name": m.Name,
"llama.context_length": uint32(m.Params.ContextSize),
"llama.embedding_length": uint32(m.Params.HiddenSize),
"llama.block_count": uint32(m.Params.HiddenLayers),
"llama.feed_forward_length": uint32(m.Params.IntermediateSize),
"llama.rope.dimension_count": uint32(m.Params.HiddenSize / m.Params.AttentionHeads),
"llama.attention.head_count": uint32(m.Params.AttentionHeads),
"llama.attention.head_count_kv": uint32(m.Params.KeyValHeads),
"llama.attention.layer_norm_rms_epsilon": float32(m.Params.NormEPS),
"llama.rope.freq_base": float32(m.Params.RopeFreqBase),
"general.file_type": uint32(1),
"tokenizer.ggml.model": "llama",
"tokenizer.ggml.tokens": m.Vocab.Tokens,
"tokenizer.ggml.scores": m.Vocab.Scores,
"tokenizer.ggml.token_type": m.Vocab.Types,
"tokenizer.ggml.bos_token_id": uint32(m.Params.BoSTokenID),
"tokenizer.ggml.eos_token_id": uint32(m.Params.EoSTokenID),
"tokenizer.ggml.add_bos_token": true,
"tokenizer.ggml.add_eos_token": false,
"tokenizer.ggml.unknown_token_id": uint32(0),
}
f, err := os.CreateTemp("", "ollama-gguf")
if err != nil {
return "", err
}
defer f.Close()
mod := llm.NewGGUFV3(m.Params.ByteOrder)
if err := mod.Encode(f, kv, m.Tensors); err != nil {
return "", err
}
return f.Name(), nil
}

View File

@@ -3,7 +3,7 @@
### Getting Started
* [Quickstart](../README.md#quickstart)
* [Examples](../examples)
* [Importing models](./import.md) from GGUF, Pytorch and Safetensors
* [Importing models](./import.md)
* [Linux Documentation](./linux.md)
* [Windows Documentation](./windows.md)
* [Docker Documentation](https://hub.docker.com/r/ollama/ollama)

View File

@@ -69,7 +69,7 @@ go build .
_Your operating system distribution may already have packages for AMD ROCm and CLBlast. Distro packages are often preferable, but instructions are distro-specific. Please consult distro-specific docs for dependencies if available!_
Install [CLBlast](https://github.com/CNugteren/CLBlast/blob/master/doc/installation.md) and [ROCm](https://rocm.docs.amd.com/en/latest/deploy/linux/quick_start.html) development packages first, as well as `cmake` and `golang`.
Install [CLBlast](https://github.com/CNugteren/CLBlast/blob/master/doc/installation.md) and [ROCm](https://rocm.docs.amd.com/en/latest/) development packages first, as well as `cmake` and `golang`.
Typically the build scripts will auto-detect ROCm, however, if your Linux distro
or installation approach uses unusual paths, you can specify the location by
@@ -116,29 +116,30 @@ Note: The windows build for Ollama is still under development.
Install required tools:
- MSVC toolchain - C/C++ and cmake as minimal requirements - You must build from a "Developer Shell" with the environment variables set
- go version 1.22 or higher
- MSVC toolchain - C/C++ and cmake as minimal requirements
- Go version 1.22 or higher
- MinGW (pick one variant) with GCC.
- <https://www.mingw-w64.org/>
- <https://www.msys2.org/>
- [MinGW-w64](https://www.mingw-w64.org/)
- [MSYS2](https://www.msys2.org/)
```powershell
$env:CGO_ENABLED="1"
go generate ./...
go build .
```
#### Windows CUDA (NVIDIA)
In addition to the common Windows development tools described above, install CUDA **AFTER** you install MSVC.
In addition to the common Windows development tools described above, install CUDA after installing MSVC.
- [NVIDIA CUDA](https://docs.nvidia.com/cuda/cuda-installation-guide-microsoft-windows/index.html)
#### Windows ROCm (AMD Radeon)
In addition to the common Windows development tools described above, install AMDs HIP package **AFTER** you install MSVC
In addition to the common Windows development tools described above, install AMDs HIP package after installing MSVC.
- [AMD HIP](https://www.amd.com/en/developer/resources/rocm-hub/hip-sdk.html)
- [AMD HIP](https://www.amd.com/en/developer/resources/rocm-hub/hip-sdk.html)
- [Strawberry Perl](https://strawberryperl.com/)
Lastly, add `ninja.exe` included with MSVC to the system path (e.g. `C:\Program Files (x86)\Microsoft Visual Studio\2019\Community\Common7\IDE\CommonExtensions\Microsoft\CMake\Ninja`).

View File

@@ -14,6 +14,10 @@ curl -fsSL https://ollama.com/install.sh | sh
Review the [Troubleshooting](./troubleshooting.md) docs for more about using logs.
## Is my GPU compatible with Ollama?
Please refer to the [GPU docs](./gpu.md).
## How can I specify the context window size?
By default, Ollama uses a context window size of 2048 tokens.
@@ -95,6 +99,37 @@ Ollama binds 127.0.0.1 port 11434 by default. Change the bind address with the `
Refer to the section [above](#how-do-i-configure-ollama-server) for how to set environment variables on your platform.
## How can I use Ollama with a proxy server?
Ollama runs an HTTP server and can be exposed using a proxy server such as Nginx. To do so, configure the proxy to forward requests and optionally set required headers (if not exposing Ollama on the network). For example, with Nginx:
```
server {
listen 80;
server_name example.com; # Replace with your domain or IP
location / {
proxy_pass http://localhost:11434;
proxy_set_header Host localhost:11434;
}
}
```
## How can I use Ollama with ngrok?
Ollama can be accessed using a range of tools for tunneling tools. For example with Ngrok:
```
ngrok http 11434 --host-header="localhost:11434"
```
## How can I use Ollama with Cloudflare Tunnel?
To use Ollama with Cloudflare Tunnel, use the `--url` and `--http-host-header` flags:
```
cloudflared tunnel --url http://localhost:11434 --http-host-header="localhost:11434"
```
## How can I allow additional web origins to access Ollama?
Ollama allows cross-origin requests from `127.0.0.1` and `0.0.0.0` by default. Additional origins can be configured with `OLLAMA_ORIGINS`.
@@ -119,7 +154,7 @@ No. Ollama runs locally, and conversation data does not leave your machine.
## How can I use Ollama in Visual Studio Code?
There is already a large collection of plugins available for VSCode as well as other editors that leverage Ollama. See the list of [extensions & plugins](https://github.com/jmorganca/ollama#extensions--plugins) at the bottom of the main repository readme.
There is already a large collection of plugins available for VSCode as well as other editors that leverage Ollama. See the list of [extensions & plugins](https://github.com/ollama/ollama#extensions--plugins) at the bottom of the main repository readme.
## How do I use Ollama behind a proxy?

102
docs/gpu.md Normal file
View File

@@ -0,0 +1,102 @@
# GPU
## Nvidia
Ollama supports Nvidia GPUs with compute capability 5.0+.
Check your compute compatibility to see if your card is supported:
[https://developer.nvidia.com/cuda-gpus](https://developer.nvidia.com/cuda-gpus)
| Compute Capability | Family | Cards |
| ------------------ | ------------------- | ----------------------------------------------------------------------------------------------------------- |
| 9.0 | NVIDIA | `H100` |
| 8.9 | GeForce RTX 40xx | `RTX 4090` `RTX 4080` `RTX 4070 Ti` `RTX 4060 Ti` |
| | NVIDIA Professional | `L4` `L40` `RTX 6000` |
| 8.6 | GeForce RTX 30xx | `RTX 3090 Ti` `RTX 3090` `RTX 3080 Ti` `RTX 3080` `RTX 3070 Ti` `RTX 3070` `RTX 3060 Ti` `RTX 3060` |
| | NVIDIA Professional | `A40` `RTX A6000` `RTX A5000` `RTX A4000` `RTX A3000` `RTX A2000` `A10` `A16` `A2` |
| 8.0 | NVIDIA | `A100` `A30` |
| 7.5 | GeForce GTX/RTX | `GTX 1650 Ti` `TITAN RTX` `RTX 2080 Ti` `RTX 2080` `RTX 2070` `RTX 2060` |
| | NVIDIA Professional | `T4` `RTX 5000` `RTX 4000` `RTX 3000` `T2000` `T1200` `T1000` `T600` `T500` |
| | Quadro | `RTX 8000` `RTX 6000` `RTX 5000` `RTX 4000` |
| 7.0 | NVIDIA | `TITAN V` `V100` `Quadro GV100` |
| 6.1 | NVIDIA TITAN | `TITAN Xp` `TITAN X` |
| | GeForce GTX | `GTX 1080 Ti` `GTX 1080` `GTX 1070 Ti` `GTX 1070` `GTX 1060` `GTX 1050` |
| | Quadro | `P6000` `P5200` `P4200` `P3200` `P5000` `P4000` `P3000` `P2200` `P2000` `P1000` `P620` `P600` `P500` `P520` |
| | Tesla | `P40` `P4` |
| 6.0 | NVIDIA | `Tesla P100` `Quadro GP100` |
| 5.2 | GeForce GTX | `GTX TITAN X` `GTX 980 Ti` `GTX 980` `GTX 970` `GTX 960` `GTX 950` |
| | Quadro | `M6000 24GB` `M6000` `M5000` `M5500M` `M4000` `M2200` `M2000` `M620` |
| | Tesla | `M60` `M40` |
| 5.0 | GeForce GTX | `GTX 750 Ti` `GTX 750` `NVS 810` |
| | Quadro | `K2200` `K1200` `K620` `M1200` `M520` `M5000M` `M4000M` `M3000M` `M2000M` `M1000M` `K620M` `M600M` `M500M` |
### GPU Selection
If you have multiple NVIDIA GPUs in your system and want to limit Ollama to use
a subset, you can set `CUDA_VISIBLE_DEVICES` to a comma separated list of GPUs.
Numeric IDs may be used, however ordering may vary, so UUIDs are more reliable.
You can discover the UUID of your GPUs by running `nvidia-smi -L` If you want to
ignore the GPUs and force CPU usage, use an invalid GPU ID (e.g., "-1")
### Laptop Suspend Resume
On linux, after a suspend/resume cycle, sometimes Ollama will fail to discover
your NVIDIA GPU, and fallback to running on the CPU. You can workaround this
driver bug by reloading the NVIDIA UVM driver with `sudo rmmod nvidia_uvm &&
sudo modprobe nvidia_uvm`
## AMD Radeon
Ollama supports the following AMD GPUs:
| Family | Cards and accelerators |
| -------------- | ---------------------------------------------------------------------------------------------------------------------------------------------- |
| AMD Radeon RX | `7900 XTX` `7900 XT` `7900 GRE` `7800 XT` `7700 XT` `7600 XT` `7600` `6950 XT` `6900 XTX` `6900XT` `6800 XT` `6800` `Vega 64` `Vega 56` |
| AMD Radeon PRO | `W7900` `W7800` `W7700` `W7600` `W7500` `W6900X` `W6800X Duo` `W6800X` `W6800` `V620` `V420` `V340` `V320` `Vega II Duo` `Vega II` `VII` `SSG` |
| AMD Instinct | `MI300X` `MI300A` `MI300` `MI250X` `MI250` `MI210` `MI200` `MI100` `MI60` `MI50` |
### Overrides
Ollama leverages the AMD ROCm library, which does not support all AMD GPUs. In
some cases you can force the system to try to use a similar LLVM target that is
close. For example The Radeon RX 5400 is `gfx1034` (also known as 10.3.4)
however, ROCm does not currently support this target. The closest support is
`gfx1030`. You can use the environment variable `HSA_OVERRIDE_GFX_VERSION` with
`x.y.z` syntax. So for example, to force the system to run on the RX 5400, you
would set `HSA_OVERRIDE_GFX_VERSION="10.3.0"` as an environment variable for the
server. If you have an unsupported AMD GPU you can experiment using the list of
supported types below.
At this time, the known supported GPU types are the following LLVM Targets.
This table shows some example GPUs that map to these LLVM targets:
| **LLVM Target** | **An Example GPU** |
|-----------------|---------------------|
| gfx900 | Radeon RX Vega 56 |
| gfx906 | Radeon Instinct MI50 |
| gfx908 | Radeon Instinct MI100 |
| gfx90a | Radeon Instinct MI210 |
| gfx940 | Radeon Instinct MI300 |
| gfx941 | |
| gfx942 | |
| gfx1030 | Radeon PRO V620 |
| gfx1100 | Radeon PRO W7900 |
| gfx1101 | Radeon PRO W7700 |
| gfx1102 | Radeon RX 7600 |
AMD is working on enhancing ROCm v6 to broaden support for families of GPUs in a
future release which should increase support for more GPUs.
Reach out on [Discord](https://discord.gg/ollama) or file an
[issue](https://github.com/ollama/ollama/issues) for additional help.
### GPU Selection
If you have multiple AMD GPUs in your system and want to limit Ollama to use a
subset, you can set `HIP_VISIBLE_DEVICES` to a comma separated list of GPUs.
You can see the list of devices with `rocminfo`. If you want to ignore the GPUs
and force CPU usage, use an invalid GPU ID (e.g., "-1")
### Container Permission
In some Linux distributions, SELinux can prevent containers from
accessing the AMD GPU devices. On the host system you can run
`sudo setsebool container_use_devices=1` to allow containers to use devices.
### Metal (Apple GPUs)
Ollama supports GPU acceleration on Apple devices via the Metal API.

View File

@@ -113,7 +113,7 @@ FROM llama2
```
A list of available base models:
<https://github.com/jmorganca/ollama#model-library>
<https://github.com/ollama/ollama#model-library>
#### Build from a `bin` file
@@ -131,7 +131,7 @@ The `PARAMETER` instruction defines a parameter that can be set when the model i
PARAMETER <parameter> <parametervalue>
```
### Valid Parameters and Values
#### Valid Parameters and Values
| Parameter | Description | Value Type | Example Usage |
| -------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ---------- | -------------------- |
@@ -183,7 +183,7 @@ SYSTEM """<system message>"""
### ADAPTER
The `ADAPTER` instruction specifies the LoRA adapter to apply to the base model. The value of this instruction should be an absolute path or a path relative to the Modelfile and the file must be in a GGML file format. The adapter should be tuned from the base model otherwise the behaviour is undefined.
The `ADAPTER` instruction is an optional instruction that specifies any LoRA adapter that should apply to the base model. The value of this instruction should be an absolute path or a path relative to the Modelfile and the file must be in a GGML file format. The adapter should be tuned from the base model otherwise the behaviour is undefined.
```modelfile
ADAPTER ./ollama-lora.bin
@@ -201,7 +201,22 @@ LICENSE """
### MESSAGE
The `MESSAGE` instruction allows you to specify a message history for the model to use when responding:
The `MESSAGE` instruction allows you to specify a message history for the model to use when responding. Use multiple iterations of the MESSAGE command to build up a conversation which will guide the model to answer in a similar way.
```modelfile
MESSAGE <role> <message>
```
#### Valid roles
| Role | Description |
| --------- | ------------------------------------------------------------ |
| system | Alternate way of providing the SYSTEM message for the model. |
| user | An example message of what the user could have asked. |
| assistant | An example message of how the model should respond. |
#### Example conversation
```modelfile
MESSAGE user Is Toronto in Canada?
@@ -212,6 +227,7 @@ MESSAGE user Is Ontario in Canada?
MESSAGE assistant yes
```
## Notes
- the **`Modelfile` is not case sensitive**. In the examples, uppercase instructions are used to make it easier to distinguish it from arguments.

View File

@@ -1,6 +1,6 @@
# OpenAI compatibility
> **Note:** OpenAI compatibility is experimental and is subject to major adjustments including breaking changes. For fully-featured access to the Ollama API, see the Ollama [Python library](https://github.com/ollama/ollama-python), [JavaScript library](https://github.com/ollama/ollama-js) and [REST API](https://github.com/jmorganca/ollama/blob/main/docs/api.md).
> **Note:** OpenAI compatibility is experimental and is subject to major adjustments including breaking changes. For fully-featured access to the Ollama API, see the Ollama [Python library](https://github.com/ollama/ollama-python), [JavaScript library](https://github.com/ollama/ollama-js) and [REST API](https://github.com/ollama/ollama/blob/main/docs/api.md).
Ollama provides experimental compatibility with parts of the [OpenAI API](https://platform.openai.com/docs/api-reference) to help connect existing applications to Ollama.

View File

@@ -67,49 +67,19 @@ You can see what features your CPU has with the following.
cat /proc/cpuinfo| grep flags | head -1
```
## AMD Radeon GPU Support
## Installing older or pre-release versions on Linux
Ollama leverages the AMD ROCm library, which does not support all AMD GPUs. In
some cases you can force the system to try to use a similar LLVM target that is
close. For example The Radeon RX 5400 is `gfx1034` (also known as 10.3.4)
however, ROCm does not currently support this target. The closest support is
`gfx1030`. You can use the environment variable `HSA_OVERRIDE_GFX_VERSION` with
`x.y.z` syntax. So for example, to force the system to run on the RX 5400, you
would set `HSA_OVERRIDE_GFX_VERSION="10.3.0"` as an environment variable for the
server. If you have an unsupported AMD GPU you can experiment using the list of
supported types below.
At this time, the known supported GPU types are the following LLVM Targets.
This table shows some example GPUs that map to these LLVM targets:
| **LLVM Target** | **An Example GPU** |
|-----------------|---------------------|
| gfx900 | Radeon RX Vega 56 |
| gfx906 | Radeon Instinct MI50 |
| gfx908 | Radeon Instinct MI100 |
| gfx90a | Radeon Instinct MI210 |
| gfx940 | Radeon Instinct MI300 |
| gfx941 | |
| gfx942 | |
| gfx1030 | Radeon PRO V620 |
| gfx1100 | Radeon PRO W7900 |
| gfx1101 | Radeon PRO W7700 |
| gfx1102 | Radeon RX 7600 |
AMD is working on enhancing ROCm v6 to broaden support for families of GPUs in a
future release which should increase support for more GPUs.
Reach out on [Discord](https://discord.gg/ollama) or file an
[issue](https://github.com/ollama/ollama/issues) for additional help.
## Installing older versions on Linux
If you run into problems on Linux and want to install an older version you can tell the install script
which version to install.
If you run into problems on Linux and want to install an older version, or you'd
like to try out a pre-release before it's officially released, you can tell the
install script which version to install.
```sh
curl -fsSL https://ollama.com/install.sh | OLLAMA_VERSION="0.1.27" sh
curl -fsSL https://ollama.com/install.sh | OLLAMA_VERSION="0.1.29" sh
```
## Known issues
## Linux tmp noexec
* N/A
If your system is configured with the "noexec" flag where Ollama stores its
temporary executable files, you can specify an alternate location by setting
OLLAMA_TMPDIR to a location writable by the user ollama runs as. For example
OLLAMA_TMPDIR=/usr/share/ollama/

View File

@@ -1,6 +1,6 @@
# PrivateGPT with Llama 2 uncensored
https://github.com/jmorganca/ollama/assets/3325447/20cf8ec6-ff25-42c6-bdd8-9be594e3ce1b
https://github.com/ollama/ollama/assets/3325447/20cf8ec6-ff25-42c6-bdd8-9be594e3ce1b
> Note: this example is a slightly modified version of PrivateGPT using models such as Llama 2 Uncensored. All credit for PrivateGPT goes to Iván Martínez who is the creator of it, and you can find his GitHub repo [here](https://github.com/imartinez/privateGPT).

View File

@@ -28,7 +28,7 @@ You are Mario from Super Mario Bros, acting as an assistant.
What if you want to change its behaviour?
- Try changing the prompt
- Try changing the parameters [Docs](https://github.com/jmorganca/ollama/blob/main/docs/modelfile.md)
- Try changing the parameters [Docs](https://github.com/ollama/ollama/blob/main/docs/modelfile.md)
- Try changing the model (e.g. An uncensored model by `FROM wizard-vicuna` this is the wizard-vicuna uncensored model )
Once the changes are made,

View File

@@ -1,6 +1,6 @@
# JSON Output Example
![llmjson 2023-11-10 15_31_31](https://github.com/jmorganca/ollama/assets/633681/e599d986-9b4a-4118-81a4-4cfe7e22da25)
![llmjson 2023-11-10 15_31_31](https://github.com/ollama/ollama/assets/633681/e599d986-9b4a-4118-81a4-4cfe7e22da25)
There are two python scripts in this example. `randomaddresses.py` generates random addresses from different countries. `predefinedschema.py` sets a template for the model to fill in.

View File

@@ -1,6 +1,6 @@
# Log Analysis example
![loganalyzer 2023-11-10 08_53_29](https://github.com/jmorganca/ollama/assets/633681/ad30f1fc-321f-4953-8914-e30e24db9921)
![loganalyzer 2023-11-10 08_53_29](https://github.com/ollama/ollama/assets/633681/ad30f1fc-321f-4953-8914-e30e24db9921)
This example shows one possible way to create a log file analyzer. It uses the model **mattw/loganalyzer** which is based on **codebooga**, a 34b parameter model.

View File

@@ -1,6 +1,6 @@
# Function calling
![function calling 2023-11-16 16_12_58](https://github.com/jmorganca/ollama/assets/633681/a0acc247-9746-45ab-b325-b65dfbbee4fb)
![function calling 2023-11-16 16_12_58](https://github.com/ollama/ollama/assets/633681/a0acc247-9746-45ab-b325-b65dfbbee4fb)
One of the features added to some models is 'function calling'. It's a bit of a confusing name. It's understandable if you think that means the model can call functions, but that's not what it means. Function calling simply means that the output of the model is formatted in JSON, using a preconfigured schema, and uses the expected types. Then your code can use the output of the model and call functions with it. Using the JSON format in Ollama, you can use any model for function calling.

View File

@@ -6,11 +6,15 @@ import (
)
const (
Byte = 1
Byte = 1
KiloByte = Byte * 1000
MegaByte = KiloByte * 1000
GigaByte = MegaByte * 1000
TeraByte = GigaByte * 1000
KibiByte = Byte * 1024
MebiByte = KibiByte * 1024
)
func HumanBytes(b int64) string {
@@ -45,3 +49,14 @@ func HumanBytes(b int64) string {
return fmt.Sprintf("%d %s", int(value), unit)
}
}
func HumanBytes2(b int64) string {
switch {
case b >= MebiByte:
return fmt.Sprintf("%.1f MiB", float64(b)/MebiByte)
case b >= KibiByte:
return fmt.Sprintf("%.1f KiB", float64(b)/KibiByte)
default:
return fmt.Sprintf("%d B", b)
}
}

32
go.mod
View File

@@ -1,4 +1,4 @@
module github.com/jmorganca/ollama
module github.com/ollama/ollama
go 1.22
@@ -9,8 +9,8 @@ require (
github.com/d4l3k/go-bfloat16 v0.0.0-20211005043715-690c3bdd05f1
github.com/emirpasic/gods v1.18.1
github.com/gin-gonic/gin v1.9.1
github.com/golang/protobuf v1.5.0
github.com/google/uuid v1.0.0
github.com/golang/protobuf v1.5.0 // indirect
github.com/google/uuid v1.6.0
github.com/mitchellh/mapstructure v1.5.0
github.com/olekukonko/tablewriter v0.0.5
github.com/spf13/cobra v1.7.0
@@ -19,23 +19,35 @@ require (
golang.org/x/sync v0.3.0
)
require github.com/pdevine/tensor v0.0.0-20240228013915-64ccaa8d9ca9
require (
github.com/minio/minio-go/v7 v7.0.69
github.com/pdevine/tensor v0.0.0-20240228013915-64ccaa8d9ca9
kr.dev/diff v0.3.0
)
require (
github.com/apache/arrow/go/arrow v0.0.0-20201229220542-30ce2eb5d4dc // indirect
github.com/chewxy/hm v1.0.0 // indirect
github.com/chewxy/math32 v1.0.8 // indirect
github.com/davecgh/go-spew v1.1.1 // indirect
github.com/dustin/go-humanize v1.0.1 // indirect
github.com/gogo/protobuf v1.3.2 // indirect
github.com/google/flatbuffers v1.12.0 // indirect
github.com/klauspost/compress v1.17.6 // indirect
github.com/mattn/go-runewidth v0.0.14 // indirect
github.com/minio/md5-simd v1.1.2 // indirect
github.com/minio/sha256-simd v1.0.1 // indirect
github.com/pkg/diff v0.0.0-20210226163009-20ebb0f2a09e // indirect
github.com/pkg/errors v0.9.1 // indirect
github.com/pmezard/go-difflib v1.0.0 // indirect
github.com/rivo/uniseg v0.2.0 // indirect
github.com/rogpeppe/go-internal v1.8.1 // indirect
github.com/rs/xid v1.5.0 // indirect
github.com/xtgo/set v1.0.0 // indirect
go4.org/unsafe/assume-no-moving-gc v0.0.0-20231121144256-b99613f794b6 // indirect
golang.org/x/xerrors v0.0.0-20200804184101-5ec99f83aff1 // indirect
gonum.org/v1/gonum v0.8.2 // indirect
gopkg.in/ini.v1 v1.67.0 // indirect
gorgonia.org/vecf32 v0.9.0 // indirect
gorgonia.org/vecf64 v0.9.0 // indirect
)
@@ -53,7 +65,7 @@ require (
github.com/google/go-cmp v0.5.9 // indirect
github.com/inconshreveable/mousetrap v1.1.0 // indirect
github.com/json-iterator/go v1.1.12 // indirect
github.com/klauspost/cpuid/v2 v2.2.4 // indirect
github.com/klauspost/cpuid/v2 v2.2.6 // indirect
github.com/leodido/go-urn v1.2.4 // indirect
github.com/mattn/go-isatty v0.0.19 // indirect
github.com/modern-go/concurrent v0.0.0-20180306012644-bacd9c7ef1dd // indirect
@@ -63,12 +75,12 @@ require (
github.com/twitchyliquid64/golang-asm v0.15.1 // indirect
github.com/ugorji/go/codec v1.2.11 // indirect
golang.org/x/arch v0.3.0 // indirect
golang.org/x/crypto v0.14.0
golang.org/x/crypto v0.19.0
golang.org/x/exp v0.0.0-20230817173708-d852ddb80c63
golang.org/x/net v0.17.0 // indirect
golang.org/x/sys v0.13.0
golang.org/x/term v0.13.0
golang.org/x/text v0.13.0 // indirect
golang.org/x/net v0.21.0 // indirect
golang.org/x/sys v0.17.0
golang.org/x/term v0.17.0
golang.org/x/text v0.14.0 // indirect
google.golang.org/protobuf v1.30.0
gopkg.in/yaml.v3 v3.0.1 // indirect
)

51
go.sum
View File

@@ -26,6 +26,8 @@ github.com/d4l3k/go-bfloat16 v0.0.0-20211005043715-690c3bdd05f1/go.mod h1:uw2gLc
github.com/davecgh/go-spew v1.1.0/go.mod h1:J7Y8YcW2NihsgmVo/mv3lAwl/skON4iLHjSsI+c5H38=
github.com/davecgh/go-spew v1.1.1 h1:vj9j/u1bqnvCEfJOwUhtlOARqs3+rkHYY13jYWTU97c=
github.com/davecgh/go-spew v1.1.1/go.mod h1:J7Y8YcW2NihsgmVo/mv3lAwl/skON4iLHjSsI+c5H38=
github.com/dustin/go-humanize v1.0.1 h1:GzkhY7T5VNhEkwH0PVJgjz+fX1rhBrR7pRT3mDkpeCY=
github.com/dustin/go-humanize v1.0.1/go.mod h1:Mu1zIs6XwVuF/gI1OepvI0qD18qycQx+mFykh5fBlto=
github.com/emirpasic/gods v1.18.1 h1:FXtiHYKDGKCW2KzwZKx0iC0PQmdlorYgdFG9jPXJ1Bc=
github.com/emirpasic/gods v1.18.1/go.mod h1:8tpGGwCnJ5H4r6BWwaV6OrWmMoPhUl5jm/FMNAnJvWQ=
github.com/envoyproxy/go-control-plane v0.9.0/go.mod h1:YTl/9mNaCwkRvm6d1a2C3ymFceY/DCBVvsKhRF0iEA4=
@@ -86,8 +88,8 @@ github.com/google/go-cmp v0.5.5/go.mod h1:v8dTdLbMG2kIc/vJvl+f65V22dbkXbowE6jgT/
github.com/google/go-cmp v0.5.9 h1:O2Tfq5qg4qc4AmwVlvv0oLiVAGB7enBSJ2x2DqQFi38=
github.com/google/go-cmp v0.5.9/go.mod h1:17dUlkBOakJ0+DkrSSNjCkIjxS6bF9zb3elmeNGIjoY=
github.com/google/gofuzz v1.0.0/go.mod h1:dBl0BpW6vV/+mYPU4Po3pmUjxk6FQPldtuIdl/M65Eg=
github.com/google/uuid v1.0.0 h1:b4Gk+7WdP/d3HZH8EJsZpvV7EtDOgaZLtnaNGIu1adA=
github.com/google/uuid v1.0.0/go.mod h1:TIyPZe4MgqvfeYDBFedMoGGpEw/LqOeaOT+nhxU+yHo=
github.com/google/uuid v1.6.0 h1:NIvaJDMOsjHA8n1jAhLSgzrAzy1Hgr+hNrb57e+94F0=
github.com/google/uuid v1.6.0/go.mod h1:TIyPZe4MgqvfeYDBFedMoGGpEw/LqOeaOT+nhxU+yHo=
github.com/inconshreveable/mousetrap v1.1.0 h1:wN+x4NVGpMsO7ErUn/mUI3vEoE6Jt13X2s0bqwp9tc8=
github.com/inconshreveable/mousetrap v1.1.0/go.mod h1:vpF70FUmC8bwa3OWnCshd2FqLfsEA9PFc4w1p2J65bw=
github.com/json-iterator/go v1.1.12 h1:PV8peI4a0ysnczrg+LtxykD8LfKY9ML6u2jnxaEnrnM=
@@ -95,9 +97,12 @@ github.com/json-iterator/go v1.1.12/go.mod h1:e30LSqwooZae/UwlEbR2852Gd8hjQvJoHm
github.com/jung-kurt/gofpdf v1.0.3-0.20190309125859-24315acbbda5/go.mod h1:7Id9E/uU8ce6rXgefFLlgrJj/GYY22cpxn+r32jIOes=
github.com/kisielk/errcheck v1.5.0/go.mod h1:pFxgyoBC7bSaBwPgfKdkLd5X25qrDl4LWUI2bnpBCr8=
github.com/kisielk/gotool v1.0.0/go.mod h1:XhKaO+MFFWcvkIS/tQcRk01m1F5IRFswLeQ+oQHNcck=
github.com/klauspost/compress v1.17.6 h1:60eq2E/jlfwQXtvZEeBUYADs+BwKBWURIY+Gj2eRGjI=
github.com/klauspost/compress v1.17.6/go.mod h1:/dCuZOvVtNoHsyb+cuJD3itjs3NbnF6KH9zAO4BDxPM=
github.com/klauspost/cpuid/v2 v2.0.1/go.mod h1:FInQzS24/EEf25PyTYn52gqo7WaD8xa0213Md/qVLRg=
github.com/klauspost/cpuid/v2 v2.0.9/go.mod h1:FInQzS24/EEf25PyTYn52gqo7WaD8xa0213Md/qVLRg=
github.com/klauspost/cpuid/v2 v2.2.4 h1:acbojRNwl3o09bUq+yDCtZFc1aiwaAAxtcn8YkZXnvk=
github.com/klauspost/cpuid/v2 v2.2.4/go.mod h1:RVVoqg1df56z8g3pUjL/3lE5UfnlrJX8tyFgg4nqhuY=
github.com/klauspost/cpuid/v2 v2.2.6 h1:ndNyv040zDGIDh8thGkXYjnFtiN02M1PVVF+JE/48xc=
github.com/klauspost/cpuid/v2 v2.2.6/go.mod h1:Lcz8mBdAVJIBVzewtcLocK12l3Y+JytZYpaMropDUws=
github.com/kr/pretty v0.1.0/go.mod h1:dAy3ld7l9f0ibDNOQOHHMYYIIbhfbHSm3C4ZsoJORNo=
github.com/kr/pretty v0.2.1/go.mod h1:ipq/a2n7PKx3OHsz4KJII5eveXtPO4qwEXGdVfWzfnI=
github.com/kr/pretty v0.3.0 h1:WgNl7dwNpEZ6jJ9k1snq4pZsg7DOEN8hP9Xw0Tsjwk0=
@@ -115,6 +120,12 @@ github.com/mattn/go-isatty v0.0.19/go.mod h1:W+V8PltTTMOvKvAeJH7IuucS94S2C6jfK/D
github.com/mattn/go-runewidth v0.0.9/go.mod h1:H031xJmbD/WCDINGzjvQ9THkh0rPKHF+m2gUSrubnMI=
github.com/mattn/go-runewidth v0.0.14 h1:+xnbZSEeDbOIg5/mE6JF0w6n9duR1l3/WmbinWVwUuU=
github.com/mattn/go-runewidth v0.0.14/go.mod h1:Jdepj2loyihRzMpdS35Xk/zdY8IAYHsh153qUoGf23w=
github.com/minio/md5-simd v1.1.2 h1:Gdi1DZK69+ZVMoNHRXJyNcxrMA4dSxoYHZSQbirFg34=
github.com/minio/md5-simd v1.1.2/go.mod h1:MzdKDxYpY2BT9XQFocsiZf/NKVtR7nkE4RoEpN+20RM=
github.com/minio/minio-go/v7 v7.0.69 h1:l8AnsQFyY1xiwa/DaQskY4NXSLA2yrGsW5iD9nRPVS0=
github.com/minio/minio-go/v7 v7.0.69/go.mod h1:XAvOPJQ5Xlzk5o3o/ArO2NMbhSGkimC+bpW/ngRKDmQ=
github.com/minio/sha256-simd v1.0.1 h1:6kaan5IFmwTNynnKKpDHe6FWHohJOHhCPchzK49dzMM=
github.com/minio/sha256-simd v1.0.1/go.mod h1:Pz6AKMiUdngCLpeTL/RJY1M9rUuPMYujV5xJjtbRSN8=
github.com/mitchellh/mapstructure v1.5.0 h1:jeMsZIYE/09sWLaz43PL7Gy6RuMjD2eJVyuac5Z2hdY=
github.com/mitchellh/mapstructure v1.5.0/go.mod h1:bFUtVrKA4DC2yAKiSyO/QUcy7e+RRV2QTWOzhPopBRo=
github.com/modern-go/concurrent v0.0.0-20180228061459-e0a39a4cb421/go.mod h1:6dJC0mAP4ikYIbvyc7fijjWJddQyLn8Ig3JB5CqoB9Q=
@@ -129,6 +140,7 @@ github.com/pdevine/tensor v0.0.0-20240228013915-64ccaa8d9ca9/go.mod h1:nR7l3gM6u
github.com/pelletier/go-toml/v2 v2.0.1/go.mod h1:r9LEWfGN8R5k0VXJ+0BkIe7MYkRdwZOjgMj2KwnJFUo=
github.com/pelletier/go-toml/v2 v2.0.8 h1:0ctb6s9mE31h0/lhu+J6OPmVeDxJn+kYnJc2jZR9tGQ=
github.com/pelletier/go-toml/v2 v2.0.8/go.mod h1:vuYfssBdrU2XDZ9bYydBu6t+6a6PYNcZljzZR9VXg+4=
github.com/pkg/diff v0.0.0-20210226163009-20ebb0f2a09e h1:aoZm08cpOy4WuID//EZDgcC4zIxODThtZNPirFr42+A=
github.com/pkg/diff v0.0.0-20210226163009-20ebb0f2a09e/go.mod h1:pJLUxLENpZxwdsKMEsNbx1VGcRFpLqf3715MtcvvzbA=
github.com/pkg/errors v0.9.1 h1:FEBLx1zS214owpjy7qsBeixbURkuhQAwrK5UwLGTwt4=
github.com/pkg/errors v0.9.1/go.mod h1:bwawxfHBFNV+L2hUp1rHADufV3IMtnDRdf1r5NINEl0=
@@ -138,8 +150,11 @@ github.com/prometheus/client_model v0.0.0-20190812154241-14fe0d1b01d4/go.mod h1:
github.com/rivo/uniseg v0.2.0 h1:S1pD9weZBuJdFmowNwbpi7BJ8TNftyUImj/0WQi72jY=
github.com/rivo/uniseg v0.2.0/go.mod h1:J6wj4VEh+S6ZtnVlnTBMWIodfgj8LQOQFoIToxlJtxc=
github.com/rogpeppe/go-internal v1.6.1/go.mod h1:xXDCJY+GAPziupqXw64V24skbSoqbTEfhy4qGm1nDQc=
github.com/rogpeppe/go-internal v1.8.0 h1:FCbCCtXNOY3UtUuHUYaghJg4y7Fd14rXifAYUAtL9R8=
github.com/rogpeppe/go-internal v1.8.0/go.mod h1:WmiCO8CzOY8rg0OYDC4/i/2WRWAB6poM+XZ2dLUbcbE=
github.com/rogpeppe/go-internal v1.8.1 h1:geMPLpDpQOgVyCg5z5GoRwLHepNdb71NXb67XFkP+Eg=
github.com/rogpeppe/go-internal v1.8.1/go.mod h1:JeRgkft04UBgHMgCIwADu4Pn6Mtm5d4nPKWu0nJ5d+o=
github.com/rs/xid v1.5.0 h1:mKX4bl4iPYJtEIxp6CYiUuLQ/8DYMoz0PUdtGgMFRVc=
github.com/rs/xid v1.5.0/go.mod h1:trrq9SKmegXys3aeAKXMUTdJsYXVwGY3RLcfgqegfbg=
github.com/russross/blackfriday/v2 v2.1.0/go.mod h1:+Rmxgy9KzJVeS9/2gXHxylqXiyQDYRxCVz55jmeOWTM=
github.com/spf13/cobra v1.7.0 h1:hyqWnYt1ZQShIddO5kBpj3vu05/++x6tJ6dg8EC572I=
github.com/spf13/cobra v1.7.0/go.mod h1:uLxZILRyS/50WlhOIKD7W6V5bgeIt+4sICxh6uRMrb0=
@@ -181,8 +196,8 @@ golang.org/x/crypto v0.0.0-20190308221718-c2843e01d9a2/go.mod h1:djNgcEr1/C05ACk
golang.org/x/crypto v0.0.0-20191011191535-87dc89f01550/go.mod h1:yigFU9vqHzYiE8UmvKecakEJjdnWj3jj499lnFckfCI=
golang.org/x/crypto v0.0.0-20200622213623-75b288015ac9/go.mod h1:LzIPMQfyMNhhGPhUkYOs5KpL4U8rLKemX1yGLhDgUto=
golang.org/x/crypto v0.0.0-20210711020723-a769d52b0f97/go.mod h1:GvvjBRRGRdwPK5ydBHafDWAxML/pGHZbMvKqRZ5+Abc=
golang.org/x/crypto v0.14.0 h1:wBqGXzWJW6m1XrIKlAH0Hs1JJ7+9KBwnIO8v66Q9cHc=
golang.org/x/crypto v0.14.0/go.mod h1:MVFd36DqK4CsrnJYDkBA3VC4m2GkXAM0PvzMCn4JQf4=
golang.org/x/crypto v0.19.0 h1:ENy+Az/9Y1vSrlrvBSyna3PITt4tiZLf7sgCjZBX7Wo=
golang.org/x/crypto v0.19.0/go.mod h1:Iy9bg/ha4yyC70EfRS8jz+B6ybOBKMaSxLj6P6oBDfU=
golang.org/x/exp v0.0.0-20180321215751-8460e604b9de/go.mod h1:CJ0aWSM057203Lf6IL+f9T1iT9GByDxfZKAQTCR3kQA=
golang.org/x/exp v0.0.0-20180807140117-3d87b88a115f/go.mod h1:CJ0aWSM057203Lf6IL+f9T1iT9GByDxfZKAQTCR3kQA=
golang.org/x/exp v0.0.0-20190121172915-509febef88a4/go.mod h1:CJ0aWSM057203Lf6IL+f9T1iT9GByDxfZKAQTCR3kQA=
@@ -205,8 +220,8 @@ golang.org/x/net v0.0.0-20200226121028-0de0cce0169b/go.mod h1:z5CRVTTTmAJ677TzLL
golang.org/x/net v0.0.0-20200904194848-62affa334b73/go.mod h1:/O7V0waA8r7cgGh81Ro3o1hOxt32SMVPicZroKQ2sZA=
golang.org/x/net v0.0.0-20201021035429-f5854403a974/go.mod h1:sp8m0HH+o8qH0wwXwYZr8TS3Oi6o0r6Gce1SSxlDquU=
golang.org/x/net v0.0.0-20210226172049-e18ecbb05110/go.mod h1:m0MpNAwzfU5UDzcl9v0D8zg8gWTRqZa9RBIspLL5mdg=
golang.org/x/net v0.17.0 h1:pVaXccu2ozPjCXewfr1S7xza/zcXTity9cCdXQYSjIM=
golang.org/x/net v0.17.0/go.mod h1:NxSsAGuq816PNPmqtQdLE42eU2Fs7NoRIZrHJAlaCOE=
golang.org/x/net v0.21.0 h1:AQyQV4dYCvJ7vGmJyKki9+PBdyvhkSd8EIx/qb0AYv4=
golang.org/x/net v0.21.0/go.mod h1:bIjVDfnllIU7BJ2DNgfnXvpSvtn8VRwhlsaeUTyUS44=
golang.org/x/oauth2 v0.0.0-20180821212333-d2e6202438be/go.mod h1:N/0e6XlmueqKjAGxoOufVs8QHGRruUQn6yWY3a++T0U=
golang.org/x/sync v0.0.0-20180314180146-1d60e4601c6f/go.mod h1:RxMgew5VJxzue5/jJTE5uejpjVlOe/izrB70Jof72aM=
golang.org/x/sync v0.0.0-20181108010431-42b317875d0f/go.mod h1:RxMgew5VJxzue5/jJTE5uejpjVlOe/izrB70Jof72aM=
@@ -226,18 +241,18 @@ golang.org/x/sys v0.0.0-20210124154548-22da62e12c0c/go.mod h1:h1NjWce9XRLGQEsW7w
golang.org/x/sys v0.0.0-20210615035016-665e8c7367d1/go.mod h1:oPkhp1MJrh7nUepCBck5+mAzfO9JrbApNNgaTdGDITg=
golang.org/x/sys v0.0.0-20210630005230-0f9fa26af87c/go.mod h1:oPkhp1MJrh7nUepCBck5+mAzfO9JrbApNNgaTdGDITg=
golang.org/x/sys v0.0.0-20210806184541-e5e7981a1069/go.mod h1:oPkhp1MJrh7nUepCBck5+mAzfO9JrbApNNgaTdGDITg=
golang.org/x/sys v0.0.0-20220704084225-05e143d24a9e/go.mod h1:oPkhp1MJrh7nUepCBck5+mAzfO9JrbApNNgaTdGDITg=
golang.org/x/sys v0.5.0/go.mod h1:oPkhp1MJrh7nUepCBck5+mAzfO9JrbApNNgaTdGDITg=
golang.org/x/sys v0.6.0/go.mod h1:oPkhp1MJrh7nUepCBck5+mAzfO9JrbApNNgaTdGDITg=
golang.org/x/sys v0.13.0 h1:Af8nKPmuFypiUBjVoU9V20FiaFXOcuZI21p0ycVYYGE=
golang.org/x/sys v0.13.0/go.mod h1:oPkhp1MJrh7nUepCBck5+mAzfO9JrbApNNgaTdGDITg=
golang.org/x/sys v0.17.0 h1:25cE3gD+tdBA7lp7QfhuV+rJiE9YXTcS3VG1SqssI/Y=
golang.org/x/sys v0.17.0/go.mod h1:/VUhepiaJMQUp4+oa/7Zr1D23ma6VTLIYjOOTFZPUcA=
golang.org/x/term v0.0.0-20201126162022-7de9c90e9dd1/go.mod h1:bj7SfCRtBDWHUb9snDiAeCFNEtKQo2Wmx5Cou7ajbmo=
golang.org/x/term v0.13.0 h1:bb+I9cTfFazGW51MZqBVmZy7+JEJMouUHTUSKVQLBek=
golang.org/x/term v0.13.0/go.mod h1:LTmsnFJwVN6bCy1rVCoS+qHT1HhALEFxKncY3WNNh4U=
golang.org/x/term v0.17.0 h1:mkTF7LCd6WGJNL3K1Ad7kwxNfYAW6a8a8QqtMblp/4U=
golang.org/x/term v0.17.0/go.mod h1:lLRBjIVuehSbZlaOtGMbcMncT+aqLLLmKrsjNrUguwk=
golang.org/x/text v0.3.0/go.mod h1:NqM8EUOU14njkJ3fqMW+pc6Ldnwhi/IjpwHt7yyuwOQ=
golang.org/x/text v0.3.3/go.mod h1:5Zoc/QRtKVWzQhOtBMvqHzDpF6irO9z98xDceosuGiQ=
golang.org/x/text v0.3.6/go.mod h1:5Zoc/QRtKVWzQhOtBMvqHzDpF6irO9z98xDceosuGiQ=
golang.org/x/text v0.13.0 h1:ablQoSUd0tRdKxZewP80B+BaqeKJuVhuRxj/dkrun3k=
golang.org/x/text v0.13.0/go.mod h1:TvPlkZtksWOMsz7fbANvkp4WM8x/WCo/om8BMLbz+aE=
golang.org/x/text v0.14.0 h1:ScX5w1eTa3QqT8oi6+ziP7dTV1S2+ALU0bI+0zXKWiQ=
golang.org/x/text v0.14.0/go.mod h1:18ZOQIKpY8NJVqYksKHtTdi31H5itFRjB5/qKTNYzSU=
golang.org/x/tools v0.0.0-20180525024113-a5b4c53f6e8b/go.mod h1:n7NCudcB/nEzxVGmLbDWY5pfWTLqBcC2KZ6jyYvM4mQ=
golang.org/x/tools v0.0.0-20180917221912-90fa682c2a6e/go.mod h1:n7NCudcB/nEzxVGmLbDWY5pfWTLqBcC2KZ6jyYvM4mQ=
golang.org/x/tools v0.0.0-20190114222345-bf090417da8b/go.mod h1:n7NCudcB/nEzxVGmLbDWY5pfWTLqBcC2KZ6jyYvM4mQ=
@@ -292,6 +307,8 @@ gopkg.in/check.v1 v1.0.0-20180628173108-788fd7840127/go.mod h1:Co6ibVJAznAaIkqp8
gopkg.in/check.v1 v1.0.0-20201130134442-10cb98267c6c h1:Hei/4ADfdWqJk1ZMxUNpqntNwaWcugrBjAiHlqqRiVk=
gopkg.in/check.v1 v1.0.0-20201130134442-10cb98267c6c/go.mod h1:JHkPIbrfpd72SG/EVd6muEfDQjcINNoR0C8j2r3qZ4Q=
gopkg.in/errgo.v2 v2.1.0/go.mod h1:hNsd1EY+bozCKY1Ytp96fpM3vjJbqLJn88ws8XvfDNI=
gopkg.in/ini.v1 v1.67.0 h1:Dgnx+6+nfE+IfzjUEISNeydPJh9AXNNsWbGP9KzCsOA=
gopkg.in/ini.v1 v1.67.0/go.mod h1:pNLf8WUiyNEtQjuu5G5vTm06TEv9tsIgeAvK8hOrP4k=
gopkg.in/yaml.v2 v2.4.0/go.mod h1:RDklbk79AGWmwhnvt/jBztapEOGDOx6ZbXqjP6csGnQ=
gopkg.in/yaml.v3 v3.0.0-20200313102051-9f266ea9e77c/go.mod h1:K4uyk7z7BCEPqu6E+C64Yfv1cQ7kz7rIZviUmN+EgEM=
gopkg.in/yaml.v3 v3.0.0-20210107192922-496545a6307b/go.mod h1:K4uyk7z7BCEPqu6E+C64Yfv1cQ7kz7rIZviUmN+EgEM=
@@ -303,4 +320,6 @@ gorgonia.org/vecf64 v0.9.0 h1:bgZDP5x0OzBF64PjMGC3EvTdOoMEcmfAh1VCUnZFm1A=
gorgonia.org/vecf64 v0.9.0/go.mod h1:hp7IOWCnRiVQKON73kkC/AUMtEXyf9kGlVrtPQ9ccVA=
honnef.co/go/tools v0.0.0-20190102054323-c2f93a96b099/go.mod h1:rf3lG4BRIbNafJWhAfAdb/ePZxsR/4RtNHQocxwk9r4=
honnef.co/go/tools v0.0.0-20190523083050-ea95bdfd59fc/go.mod h1:rf3lG4BRIbNafJWhAfAdb/ePZxsR/4RtNHQocxwk9r4=
kr.dev/diff v0.3.0 h1:o/T8/tkAq9IuRIuFqCupyKPC5iSY3WXpVZ2p6ZK3Emw=
kr.dev/diff v0.3.0/go.mod h1:XiTaLOg2/PD0cmXY7WQXUR8RAF3RwWpqIQEj910J2NY=
rsc.io/pdf v0.1.1/go.mod h1:n8OzWcQ6Sp37PL01nO98y4iUCRdTGarVfzxY20ICaU4=

View File

@@ -40,19 +40,17 @@ func amdSetVisibleDevices(ids []int, skip map[int]interface{}) {
// TODO - does sort order matter?
devices := []string{}
for i := range ids {
slog.Debug(fmt.Sprintf("i=%d", i))
if _, skipped := skip[i]; skipped {
slog.Debug("skipped")
continue
}
devices = append(devices, strconv.Itoa(i))
}
slog.Debug(fmt.Sprintf("devices=%v", devices))
val := strings.Join(devices, ",")
err := os.Setenv("HIP_VISIBLE_DEVICES", val)
if err != nil {
slog.Warn(fmt.Sprintf("failed to set env: %s", err))
} else {
slog.Info("Setting HIP_VISIBLE_DEVICES=" + val)
}
slog.Debug("HIP_VISIBLE_DEVICES=" + val)
}

View File

@@ -24,6 +24,9 @@ const (
GPUTotalMemoryFileGlob = "mem_banks/*/properties" // size_in_bytes line
GPUUsedMemoryFileGlob = "mem_banks/*/used_memory"
RocmStandardLocation = "/opt/rocm/lib"
// TODO find a better way to detect iGPU instead of minimum memory
IGPUMemLimit = 1024 * 1024 * 1024 // 512G is what they typically report, so anything less than 1G must be iGPU
)
var (
@@ -97,6 +100,8 @@ func AMDGetGPUInfo(resp *GpuInfo) {
return
}
updateLibPath(libDir)
gfxOverride := os.Getenv("HSA_OVERRIDE_GFX_VERSION")
if gfxOverride == "" {
supported, err := GetSupportedGFX(libDir)
@@ -110,7 +115,7 @@ func AMDGetGPUInfo(resp *GpuInfo) {
if !slices.Contains[[]string, string](supported, v.ToGFXString()) {
slog.Warn(fmt.Sprintf("amdgpu [%d] %s is not supported by %s %v", i, v.ToGFXString(), libDir, supported))
// TODO - consider discrete markdown just for ROCM troubleshooting?
slog.Warn("See https://github.com/ollama/ollama/blob/main/docs/troubleshooting.md for HSA_OVERRIDE_GFX_VERSION usage")
slog.Warn("See https://github.com/ollama/ollama/blob/main/docs/gpu.md#overrides for HSA_OVERRIDE_GFX_VERSION usage")
skip[i] = struct{}{}
} else {
slog.Info(fmt.Sprintf("amdgpu [%d] %s is supported", i, v.ToGFXString()))
@@ -140,14 +145,29 @@ func AMDGetGPUInfo(resp *GpuInfo) {
}
}
func updateLibPath(libDir string) {
ldPaths := []string{}
if val, ok := os.LookupEnv("LD_LIBRARY_PATH"); ok {
ldPaths = strings.Split(val, ":")
}
for _, d := range ldPaths {
if d == libDir {
return
}
}
val := strings.Join(append(ldPaths, libDir), ":")
slog.Debug("updated lib path", "LD_LIBRARY_PATH", val)
os.Setenv("LD_LIBRARY_PATH", val)
}
// Walk the sysfs nodes for the available GPUs and gather information from them
// skipping over any devices in the skip map
func amdProcMemLookup(resp *GpuInfo, skip map[int]interface{}, ids []int) {
resp.memInfo.DeviceCount = 0
resp.memInfo.TotalMemory = 0
resp.memInfo.FreeMemory = 0
slog.Debug("discovering VRAM for amdgpu devices")
if len(ids) == 0 {
slog.Debug("discovering all amdgpu devices")
entries, err := os.ReadDir(AMDNodesSysfsDir)
if err != nil {
slog.Warn(fmt.Sprintf("failed to read amdgpu sysfs %s - %s", AMDNodesSysfsDir, err))
@@ -165,7 +185,7 @@ func amdProcMemLookup(resp *GpuInfo, skip map[int]interface{}, ids []int) {
ids = append(ids, id)
}
}
slog.Debug(fmt.Sprintf("discovering amdgpu devices %v", ids))
slog.Debug(fmt.Sprintf("amdgpu devices %v", ids))
for _, id := range ids {
if _, skipped := skip[id]; skipped {
@@ -173,7 +193,8 @@ func amdProcMemLookup(resp *GpuInfo, skip map[int]interface{}, ids []int) {
}
totalMemory := uint64(0)
usedMemory := uint64(0)
propGlob := filepath.Join(AMDNodesSysfsDir, strconv.Itoa(id), GPUTotalMemoryFileGlob)
// Adjust for sysfs vs HIP ids
propGlob := filepath.Join(AMDNodesSysfsDir, strconv.Itoa(id+1), GPUTotalMemoryFileGlob)
propFiles, err := filepath.Glob(propGlob)
if err != nil {
slog.Warn(fmt.Sprintf("error looking up total GPU memory: %s %s", propGlob, err))
@@ -205,6 +226,13 @@ func amdProcMemLookup(resp *GpuInfo, skip map[int]interface{}, ids []int) {
}
}
if totalMemory == 0 {
slog.Warn(fmt.Sprintf("amdgpu [%d] reports zero total memory, skipping", id))
skip[id] = struct{}{}
continue
}
if totalMemory < IGPUMemLimit {
slog.Info(fmt.Sprintf("amdgpu [%d] appears to be an iGPU with %dM reported total memory, skipping", id, totalMemory/1024/1024))
skip[id] = struct{}{}
continue
}
usedGlob := filepath.Join(AMDNodesSysfsDir, strconv.Itoa(id), GPUUsedMemoryFileGlob)
@@ -232,8 +260,8 @@ func amdProcMemLookup(resp *GpuInfo, skip map[int]interface{}, ids []int) {
}
usedMemory += used
}
slog.Info(fmt.Sprintf("[%d] amdgpu totalMemory %d", id, totalMemory))
slog.Info(fmt.Sprintf("[%d] amdgpu freeMemory %d", id, (totalMemory - usedMemory)))
slog.Info(fmt.Sprintf("[%d] amdgpu totalMemory %dM", id, totalMemory/1024/1024))
slog.Info(fmt.Sprintf("[%d] amdgpu freeMemory %dM", id, (totalMemory-usedMemory)/1024/1024))
resp.memInfo.DeviceCount++
resp.memInfo.TotalMemory += totalMemory
resp.memInfo.FreeMemory += (totalMemory - usedMemory)
@@ -282,7 +310,7 @@ func AMDValidateLibDir() (string, error) {
}
// If we already have a rocm dependency wired, nothing more to do
rocmTargetDir := filepath.Join(payloadsDir, "rocm")
rocmTargetDir := filepath.Clean(filepath.Join(payloadsDir, "..", "rocm"))
if rocmLibUsable(rocmTargetDir) {
return rocmTargetDir, nil
}
@@ -358,6 +386,8 @@ func AMDDriverVersion() (string, error) {
}
func AMDGFXVersions() map[int]Version {
// The amdgpu driver always exposes the host CPU as node 0, but we have to skip that and subtract one
// from the other IDs to get alignment with the HIP libraries expectations (zero is the first GPU, not the CPU)
res := map[int]Version{}
matches, _ := filepath.Glob(GPUPropertiesFileGlob)
for _, match := range matches {
@@ -373,17 +403,20 @@ func AMDGFXVersions() map[int]Version {
continue
}
if i == 0 {
// Skipping the CPU
continue
}
// Align with HIP IDs (zero is first GPU, not CPU)
i -= 1
scanner := bufio.NewScanner(fp)
for scanner.Scan() {
line := strings.TrimSpace(scanner.Text())
if strings.HasPrefix(line, "gfx_target_version") {
ver := strings.Fields(line)
if len(ver) != 2 || len(ver[1]) < 5 {
if ver[1] == "0" {
// Silently skip the CPU
continue
} else {
if ver[1] != "0" {
slog.Debug("malformed " + line)
}
res[i] = Version{

View File

@@ -1,13 +1,17 @@
package gpu
import (
"errors"
"fmt"
"log/slog"
"os"
"path/filepath"
"runtime"
"strconv"
"strings"
"sync"
"syscall"
"time"
)
var (
@@ -18,24 +22,84 @@ var (
func PayloadsDir() (string, error) {
lock.Lock()
defer lock.Unlock()
var err error
if payloadsDir == "" {
tmpDir, err := os.MkdirTemp("", "ollama")
if err != nil {
return "", fmt.Errorf("failed to generate tmp dir: %w", err)
cleanupTmpDirs()
tmpDir := os.Getenv("OLLAMA_TMPDIR")
if tmpDir == "" {
tmpDir, err = os.MkdirTemp("", "ollama")
if err != nil {
return "", fmt.Errorf("failed to generate tmp dir: %w", err)
}
} else {
err = os.MkdirAll(tmpDir, 0755)
if err != nil {
return "", fmt.Errorf("failed to generate tmp dir %s: %w", tmpDir, err)
}
}
payloadsDir = tmpDir
// Track our pid so we can clean up orphaned tmpdirs
pidFilePath := filepath.Join(tmpDir, "ollama.pid")
pidFile, err := os.OpenFile(pidFilePath, os.O_CREATE|os.O_TRUNC|os.O_WRONLY, os.ModePerm)
if err != nil {
return "", err
}
if _, err := pidFile.Write([]byte(fmt.Sprint(os.Getpid()))); err != nil {
return "", err
}
// We create a distinct subdirectory for payloads within the tmpdir
// This will typically look like /tmp/ollama3208993108/runners on linux
payloadsDir = filepath.Join(tmpDir, "runners")
}
return payloadsDir, nil
}
// Best effort to clean up prior tmpdirs
func cleanupTmpDirs() {
dirs, err := filepath.Glob(filepath.Join(os.TempDir(), "ollama*"))
if err != nil {
return
}
for _, d := range dirs {
info, err := os.Stat(d)
if err != nil || !info.IsDir() {
continue
}
raw, err := os.ReadFile(filepath.Join(d, "ollama.pid"))
if err == nil {
pid, err := strconv.Atoi(string(raw))
if err == nil {
if proc, err := os.FindProcess(int(pid)); err == nil && !errors.Is(proc.Signal(syscall.Signal(0)), os.ErrProcessDone) {
// Another running ollama, ignore this tmpdir
continue
}
}
} else {
slog.Debug("failed to open ollama.pid", "path", d, "error", err)
}
err = os.RemoveAll(d)
if err != nil {
slog.Debug(fmt.Sprintf("unable to cleanup stale tmpdir %s: %s", d, err))
}
}
}
func Cleanup() {
lock.Lock()
defer lock.Unlock()
if payloadsDir != "" {
slog.Debug("cleaning up", "dir", payloadsDir)
err := os.RemoveAll(payloadsDir)
// We want to fully clean up the tmpdir parent of the payloads dir
tmpDir := filepath.Clean(filepath.Join(payloadsDir, ".."))
slog.Debug("cleaning up", "dir", tmpDir)
err := os.RemoveAll(tmpDir)
if err != nil {
slog.Warn("failed to clean up", "dir", payloadsDir, "err", err)
// On windows, if we remove too quickly the llama.dll may still be in-use and fail to remove
time.Sleep(1000 * time.Millisecond)
err = os.RemoveAll(tmpDir)
if err != nil {
slog.Warn("failed to clean up", "dir", tmpDir, "err", err)
}
}
}
}

View File

@@ -20,20 +20,27 @@ import (
"strings"
"sync"
"unsafe"
"github.com/ollama/ollama/format"
)
type handles struct {
cuda *C.cuda_handle_t
nvml *C.nvml_handle_t
cudart *C.cudart_handle_t
}
const (
cudaMinimumMemory = 457 * format.MebiByte
rocmMinimumMemory = 457 * format.MebiByte
)
var gpuMutex sync.Mutex
var gpuHandles *handles = nil
// With our current CUDA compile flags, older than 5.0 will not work properly
var CudaComputeMin = [2]C.int{5, 0}
// Possible locations for the nvidia-ml library
var CudaLinuxGlobs = []string{
var NvmlLinuxGlobs = []string{
"/usr/local/cuda/lib64/libnvidia-ml.so*",
"/usr/lib/x86_64-linux-gnu/nvidia/current/libnvidia-ml.so*",
"/usr/lib/x86_64-linux-gnu/libnvidia-ml.so*",
@@ -41,49 +48,98 @@ var CudaLinuxGlobs = []string{
"/usr/lib/wsl/drivers/*/libnvidia-ml.so*",
"/opt/cuda/lib64/libnvidia-ml.so*",
"/usr/lib*/libnvidia-ml.so*",
"/usr/local/lib*/libnvidia-ml.so*",
"/usr/lib/aarch64-linux-gnu/nvidia/current/libnvidia-ml.so*",
"/usr/lib/aarch64-linux-gnu/libnvidia-ml.so*",
"/usr/local/lib*/libnvidia-ml.so*",
// TODO: are these stubs ever valid?
"/opt/cuda/targets/x86_64-linux/lib/stubs/libnvidia-ml.so*",
}
var CudaWindowsGlobs = []string{
var NvmlWindowsGlobs = []string{
"c:\\Windows\\System32\\nvml.dll",
}
var CudartLinuxGlobs = []string{
"/usr/local/cuda/lib64/libcudart.so*",
"/usr/lib/x86_64-linux-gnu/nvidia/current/libcudart.so*",
"/usr/lib/x86_64-linux-gnu/libcudart.so*",
"/usr/lib/wsl/lib/libcudart.so*",
"/usr/lib/wsl/drivers/*/libcudart.so*",
"/opt/cuda/lib64/libcudart.so*",
"/usr/local/cuda*/targets/aarch64-linux/lib/libcudart.so*",
"/usr/lib/aarch64-linux-gnu/nvidia/current/libcudart.so*",
"/usr/lib/aarch64-linux-gnu/libcudart.so*",
"/usr/local/cuda/lib*/libcudart.so*",
"/usr/lib*/libcudart.so*",
"/usr/local/lib*/libcudart.so*",
}
var CudartWindowsGlobs = []string{
"c:\\Program Files\\NVIDIA GPU Computing Toolkit\\CUDA\\v*\\bin\\cudart64_*.dll",
}
// Jetson devices have JETSON_JETPACK="x.y.z" factory set to the Jetpack version installed.
// Included to drive logic for reducing Ollama-allocated overhead on L4T/Jetson devices.
var CudaTegra string = os.Getenv("JETSON_JETPACK")
// Note: gpuMutex must already be held
func initGPUHandles() {
func initGPUHandles() *handles {
// TODO - if the ollama build is CPU only, don't do these checks as they're irrelevant and confusing
gpuHandles = &handles{nil}
var cudaMgmtName string
var cudaMgmtPatterns []string
gpuHandles := &handles{nil, nil}
var nvmlMgmtName string
var nvmlMgmtPatterns []string
var cudartMgmtName string
var cudartMgmtPatterns []string
tmpDir, _ := PayloadsDir()
switch runtime.GOOS {
case "windows":
cudaMgmtName = "nvml.dll"
cudaMgmtPatterns = make([]string, len(CudaWindowsGlobs))
copy(cudaMgmtPatterns, CudaWindowsGlobs)
nvmlMgmtName = "nvml.dll"
nvmlMgmtPatterns = make([]string, len(NvmlWindowsGlobs))
copy(nvmlMgmtPatterns, NvmlWindowsGlobs)
cudartMgmtName = "cudart64_*.dll"
localAppData := os.Getenv("LOCALAPPDATA")
cudartMgmtPatterns = []string{filepath.Join(localAppData, "Programs", "Ollama", cudartMgmtName)}
cudartMgmtPatterns = append(cudartMgmtPatterns, CudartWindowsGlobs...)
case "linux":
cudaMgmtName = "libnvidia-ml.so"
cudaMgmtPatterns = make([]string, len(CudaLinuxGlobs))
copy(cudaMgmtPatterns, CudaLinuxGlobs)
nvmlMgmtName = "libnvidia-ml.so"
nvmlMgmtPatterns = make([]string, len(NvmlLinuxGlobs))
copy(nvmlMgmtPatterns, NvmlLinuxGlobs)
cudartMgmtName = "libcudart.so*"
if tmpDir != "" {
// TODO - add "payloads" for subprocess
cudartMgmtPatterns = []string{filepath.Join(tmpDir, "cuda*", cudartMgmtName)}
}
cudartMgmtPatterns = append(cudartMgmtPatterns, CudartLinuxGlobs...)
default:
return
return gpuHandles
}
slog.Info("Detecting GPU type")
cudaLibPaths := FindGPULibs(cudaMgmtName, cudaMgmtPatterns)
if len(cudaLibPaths) > 0 {
cuda := LoadCUDAMgmt(cudaLibPaths)
if cuda != nil {
slog.Info("Nvidia GPU detected")
gpuHandles.cuda = cuda
return
cudartLibPaths := FindGPULibs(cudartMgmtName, cudartMgmtPatterns)
if len(cudartLibPaths) > 0 {
cudart := LoadCUDARTMgmt(cudartLibPaths)
if cudart != nil {
slog.Info("Nvidia GPU detected via cudart")
gpuHandles.cudart = cudart
return gpuHandles
}
}
// TODO once we build confidence, remove this and the gpu_info_nvml.[ch] files
nvmlLibPaths := FindGPULibs(nvmlMgmtName, nvmlMgmtPatterns)
if len(nvmlLibPaths) > 0 {
nvml := LoadNVMLMgmt(nvmlLibPaths)
if nvml != nil {
slog.Info("Nvidia GPU detected via nvidia-ml")
gpuHandles.nvml = nvml
return gpuHandles
}
}
return gpuHandles
}
func GetGPUInfo() GpuInfo {
@@ -91,9 +147,16 @@ func GetGPUInfo() GpuInfo {
// GPUs so we can report warnings if we see Nvidia/AMD but fail to load the libraries
gpuMutex.Lock()
defer gpuMutex.Unlock()
if gpuHandles == nil {
initGPUHandles()
}
gpuHandles := initGPUHandles()
defer func() {
if gpuHandles.nvml != nil {
C.nvml_release(*gpuHandles.nvml)
}
if gpuHandles.cudart != nil {
C.cudart_release(*gpuHandles.cudart)
}
}()
// All our GPU builds on x86 have AVX enabled, so fallback to CPU if we don't detect at least AVX
cpuVariant := GetCPUVariant()
@@ -103,28 +166,50 @@ func GetGPUInfo() GpuInfo {
var memInfo C.mem_info_t
resp := GpuInfo{}
if gpuHandles.cuda != nil && (cpuVariant != "" || runtime.GOARCH != "amd64") {
C.cuda_check_vram(*gpuHandles.cuda, &memInfo)
if gpuHandles.nvml != nil && (cpuVariant != "" || runtime.GOARCH != "amd64") {
C.nvml_check_vram(*gpuHandles.nvml, &memInfo)
if memInfo.err != nil {
slog.Info(fmt.Sprintf("error looking up CUDA GPU memory: %s", C.GoString(memInfo.err)))
slog.Info(fmt.Sprintf("[nvidia-ml] error looking up NVML GPU memory: %s", C.GoString(memInfo.err)))
C.free(unsafe.Pointer(memInfo.err))
} else if memInfo.count > 0 {
// Verify minimum compute capability
var cc C.cuda_compute_capability_t
C.cuda_compute_capability(*gpuHandles.cuda, &cc)
var cc C.nvml_compute_capability_t
C.nvml_compute_capability(*gpuHandles.nvml, &cc)
if cc.err != nil {
slog.Info(fmt.Sprintf("error looking up CUDA GPU compute capability: %s", C.GoString(cc.err)))
slog.Info(fmt.Sprintf("[nvidia-ml] error looking up NVML GPU compute capability: %s", C.GoString(cc.err)))
C.free(unsafe.Pointer(cc.err))
} else if cc.major > CudaComputeMin[0] || (cc.major == CudaComputeMin[0] && cc.minor >= CudaComputeMin[1]) {
slog.Info(fmt.Sprintf("CUDA Compute Capability detected: %d.%d", cc.major, cc.minor))
slog.Info(fmt.Sprintf("[nvidia-ml] NVML CUDA Compute Capability detected: %d.%d", cc.major, cc.minor))
resp.Library = "cuda"
resp.MinimumMemory = cudaMinimumMemory
} else {
slog.Info(fmt.Sprintf("CUDA GPU is too old. Falling back to CPU mode. Compute Capability detected: %d.%d", cc.major, cc.minor))
slog.Info(fmt.Sprintf("[nvidia-ml] CUDA GPU is too old. Falling back to CPU mode. Compute Capability detected: %d.%d", cc.major, cc.minor))
}
}
} else if gpuHandles.cudart != nil && (cpuVariant != "" || runtime.GOARCH != "amd64") {
C.cudart_check_vram(*gpuHandles.cudart, &memInfo)
if memInfo.err != nil {
slog.Info(fmt.Sprintf("[cudart] error looking up CUDART GPU memory: %s", C.GoString(memInfo.err)))
C.free(unsafe.Pointer(memInfo.err))
} else if memInfo.count > 0 {
// Verify minimum compute capability
var cc C.cudart_compute_capability_t
C.cudart_compute_capability(*gpuHandles.cudart, &cc)
if cc.err != nil {
slog.Info(fmt.Sprintf("[cudart] error looking up CUDA compute capability: %s", C.GoString(cc.err)))
C.free(unsafe.Pointer(cc.err))
} else if cc.major > CudaComputeMin[0] || (cc.major == CudaComputeMin[0] && cc.minor >= CudaComputeMin[1]) {
slog.Info(fmt.Sprintf("[cudart] CUDART CUDA Compute Capability detected: %d.%d", cc.major, cc.minor))
resp.Library = "cuda"
resp.MinimumMemory = cudaMinimumMemory
} else {
slog.Info(fmt.Sprintf("[cudart] CUDA GPU is too old. Falling back to CPU mode. Compute Capability detected: %d.%d", cc.major, cc.minor))
}
}
} else {
AMDGetGPUInfo(&resp)
if resp.Library != "" {
resp.MinimumMemory = rocmMinimumMemory
return resp
}
}
@@ -170,15 +255,7 @@ func CheckVRAM() (int64, error) {
}
gpuInfo := GetGPUInfo()
if gpuInfo.FreeMemory > 0 && (gpuInfo.Library == "cuda" || gpuInfo.Library == "rocm") {
// leave 10% or 1024MiB of VRAM free per GPU to handle unaccounted for overhead
overhead := gpuInfo.FreeMemory / 10
gpus := uint64(gpuInfo.DeviceCount)
if overhead < gpus*1024*1024*1024 {
overhead = gpus * 1024 * 1024 * 1024
}
avail := int64(gpuInfo.FreeMemory - overhead)
slog.Debug(fmt.Sprintf("%s detected %d devices with %dM available memory", gpuInfo.Library, gpuInfo.DeviceCount, avail/1024/1024))
return avail, nil
return int64(gpuInfo.FreeMemory), nil
}
return 0, fmt.Errorf("no GPU detected") // TODO - better handling of CPU based memory determiniation
@@ -238,15 +315,32 @@ func FindGPULibs(baseLibName string, patterns []string) []string {
return gpuLibPaths
}
func LoadCUDAMgmt(cudaLibPaths []string) *C.cuda_handle_t {
var resp C.cuda_init_resp_t
func LoadNVMLMgmt(nvmlLibPaths []string) *C.nvml_handle_t {
var resp C.nvml_init_resp_t
resp.ch.verbose = getVerboseState()
for _, libPath := range cudaLibPaths {
for _, libPath := range nvmlLibPaths {
lib := C.CString(libPath)
defer C.free(unsafe.Pointer(lib))
C.cuda_init(lib, &resp)
C.nvml_init(lib, &resp)
if resp.err != nil {
slog.Info(fmt.Sprintf("Unable to load CUDA management library %s: %s", libPath, C.GoString(resp.err)))
slog.Info(fmt.Sprintf("Unable to load NVML management library %s: %s", libPath, C.GoString(resp.err)))
C.free(unsafe.Pointer(resp.err))
} else {
return &resp.ch
}
}
return nil
}
func LoadCUDARTMgmt(cudartLibPaths []string) *C.cudart_handle_t {
var resp C.cudart_init_resp_t
resp.ch.verbose = getVerboseState()
for _, libPath := range cudartLibPaths {
lib := C.CString(libPath)
defer C.free(unsafe.Pointer(lib))
C.cudart_init(lib, &resp)
if resp.err != nil {
slog.Info(fmt.Sprintf("Unable to load cudart CUDA management library %s: %s", libPath, C.GoString(resp.err)))
C.free(unsafe.Pointer(resp.err))
} else {
return &resp.ch

View File

@@ -52,7 +52,8 @@ void cpu_check_ram(mem_info_t *resp);
}
#endif
#include "gpu_info_cuda.h"
#include "gpu_info_nvml.h"
#include "gpu_info_cudart.h"
#endif // __GPU_INFO_H__
#endif // __APPLE__

200
gpu/gpu_info_cudart.c Normal file
View File

@@ -0,0 +1,200 @@
#ifndef __APPLE__ // TODO - maybe consider nvidia support on intel macs?
#include <string.h>
#include "gpu_info_cudart.h"
void cudart_init(char *cudart_lib_path, cudart_init_resp_t *resp) {
cudartReturn_t ret;
resp->err = NULL;
const int buflen = 256;
char buf[buflen + 1];
int i;
struct lookup {
char *s;
void **p;
} l[] = {
{"cudaSetDevice", (void *)&resp->ch.cudaSetDevice},
{"cudaDeviceSynchronize", (void *)&resp->ch.cudaDeviceSynchronize},
{"cudaDeviceReset", (void *)&resp->ch.cudaDeviceReset},
{"cudaMemGetInfo", (void *)&resp->ch.cudaMemGetInfo},
{"cudaGetDeviceCount", (void *)&resp->ch.cudaGetDeviceCount},
{"cudaDeviceGetAttribute", (void *)&resp->ch.cudaDeviceGetAttribute},
{"cudaDriverGetVersion", (void *)&resp->ch.cudaDriverGetVersion},
{NULL, NULL},
};
resp->ch.handle = LOAD_LIBRARY(cudart_lib_path, RTLD_LAZY);
if (!resp->ch.handle) {
char *msg = LOAD_ERR();
LOG(resp->ch.verbose, "library %s load err: %s\n", cudart_lib_path, msg);
snprintf(buf, buflen,
"Unable to load %s library to query for Nvidia GPUs: %s",
cudart_lib_path, msg);
free(msg);
resp->err = strdup(buf);
return;
}
// TODO once we've squashed the remaining corner cases remove this log
LOG(resp->ch.verbose, "wiring cudart library functions in %s\n", cudart_lib_path);
for (i = 0; l[i].s != NULL; i++) {
// TODO once we've squashed the remaining corner cases remove this log
LOG(resp->ch.verbose, "dlsym: %s\n", l[i].s);
*l[i].p = LOAD_SYMBOL(resp->ch.handle, l[i].s);
if (!l[i].p) {
char *msg = LOAD_ERR();
LOG(resp->ch.verbose, "dlerr: %s\n", msg);
UNLOAD_LIBRARY(resp->ch.handle);
resp->ch.handle = NULL;
snprintf(buf, buflen, "symbol lookup for %s failed: %s", l[i].s,
msg);
free(msg);
resp->err = strdup(buf);
return;
}
}
ret = (*resp->ch.cudaSetDevice)(0);
if (ret != CUDART_SUCCESS) {
LOG(resp->ch.verbose, "cudaSetDevice err: %d\n", ret);
UNLOAD_LIBRARY(resp->ch.handle);
resp->ch.handle = NULL;
if (ret == CUDA_ERROR_INSUFFICIENT_DRIVER) {
resp->err = strdup("your nvidia driver is too old or missing, please upgrade to run ollama");
return;
}
snprintf(buf, buflen, "cudart init failure: %d", ret);
resp->err = strdup(buf);
return;
}
int version = 0;
cudartDriverVersion_t driverVersion;
driverVersion.major = 0;
driverVersion.minor = 0;
// Report driver version if we're in verbose mode, ignore errors
ret = (*resp->ch.cudaDriverGetVersion)(&version);
if (ret != CUDART_SUCCESS) {
LOG(resp->ch.verbose, "cudaDriverGetVersion failed: %d\n", ret);
} else {
driverVersion.major = version / 1000;
driverVersion.minor = (version - (driverVersion.major * 1000)) / 10;
LOG(resp->ch.verbose, "CUDA driver version: %d-%d\n", driverVersion.major, driverVersion.minor);
}
}
void cudart_check_vram(cudart_handle_t h, mem_info_t *resp) {
resp->err = NULL;
cudartMemory_t memInfo = {0,0,0};
cudartReturn_t ret;
const int buflen = 256;
char buf[buflen + 1];
int i;
if (h.handle == NULL) {
resp->err = strdup("cudart handle isn't initialized");
return;
}
// cudaGetDeviceCount takes int type, resp-> count is uint
int deviceCount;
ret = (*h.cudaGetDeviceCount)(&deviceCount);
if (ret != CUDART_SUCCESS) {
snprintf(buf, buflen, "unable to get device count: %d", ret);
resp->err = strdup(buf);
return;
} else {
resp->count = (unsigned int)deviceCount;
}
resp->total = 0;
resp->free = 0;
for (i = 0; i < resp-> count; i++) {
ret = (*h.cudaSetDevice)(i);
if (ret != CUDART_SUCCESS) {
snprintf(buf, buflen, "cudart device failed to initialize");
resp->err = strdup(buf);
return;
}
ret = (*h.cudaMemGetInfo)(&memInfo.free, &memInfo.total);
if (ret != CUDART_SUCCESS) {
snprintf(buf, buflen, "cudart device memory info lookup failure %d", ret);
resp->err = strdup(buf);
return;
}
LOG(h.verbose, "[%d] CUDA totalMem %lu\n", i, memInfo.total);
LOG(h.verbose, "[%d] CUDA freeMem %lu\n", i, memInfo.free);
resp->total += memInfo.total;
resp->free += memInfo.free;
}
}
void cudart_compute_capability(cudart_handle_t h, cudart_compute_capability_t *resp) {
resp->err = NULL;
resp->major = 0;
resp->minor = 0;
int major = 0;
int minor = 0;
cudartReturn_t ret;
const int buflen = 256;
char buf[buflen + 1];
int i;
if (h.handle == NULL) {
resp->err = strdup("cudart handle not initialized");
return;
}
int devices;
ret = (*h.cudaGetDeviceCount)(&devices);
if (ret != CUDART_SUCCESS) {
snprintf(buf, buflen, "unable to get cudart device count: %d", ret);
resp->err = strdup(buf);
return;
}
for (i = 0; i < devices; i++) {
ret = (*h.cudaSetDevice)(i);
if (ret != CUDART_SUCCESS) {
snprintf(buf, buflen, "cudart device failed to initialize");
resp->err = strdup(buf);
return;
}
ret = (*h.cudaDeviceGetAttribute)(&major, cudartDevAttrComputeCapabilityMajor, i);
if (ret != CUDART_SUCCESS) {
snprintf(buf, buflen, "device compute capability lookup failure %d: %d", i, ret);
resp->err = strdup(buf);
return;
}
ret = (*h.cudaDeviceGetAttribute)(&minor, cudartDevAttrComputeCapabilityMinor, i);
if (ret != CUDART_SUCCESS) {
snprintf(buf, buflen, "device compute capability lookup failure %d: %d", i, ret);
resp->err = strdup(buf);
return;
}
// Report the lowest major.minor we detect as that limits our compatibility
if (resp->major == 0 || resp->major > major ) {
resp->major = major;
resp->minor = minor;
} else if ( resp->major == major && resp->minor > minor ) {
resp->minor = minor;
}
}
}
void cudart_release(cudart_handle_t h) {
LOG(h.verbose, "releasing cudart library\n");
UNLOAD_LIBRARY(h.handle);
h.handle = NULL;
}
#endif // __APPLE__

61
gpu/gpu_info_cudart.h Normal file
View File

@@ -0,0 +1,61 @@
#ifndef __APPLE__
#ifndef __GPU_INFO_CUDART_H__
#define __GPU_INFO_CUDART_H__
#include "gpu_info.h"
// Just enough typedef's to dlopen/dlsym for memory information
typedef enum cudartReturn_enum {
CUDART_SUCCESS = 0,
CUDART_UNSUPPORTED = 1,
CUDA_ERROR_INSUFFICIENT_DRIVER = 35,
// Other values omitted for now...
} cudartReturn_t;
typedef enum cudartDeviceAttr_enum {
cudartDevAttrComputeCapabilityMajor = 75,
cudartDevAttrComputeCapabilityMinor = 76,
} cudartDeviceAttr_t;
typedef void *cudartDevice_t; // Opaque is sufficient
typedef struct cudartMemory_st {
size_t total;
size_t free;
size_t used;
} cudartMemory_t;
typedef struct cudartDriverVersion {
int major;
int minor;
} cudartDriverVersion_t;
typedef struct cudart_handle {
void *handle;
uint16_t verbose;
cudartReturn_t (*cudaSetDevice)(int device);
cudartReturn_t (*cudaDeviceSynchronize)(void);
cudartReturn_t (*cudaDeviceReset)(void);
cudartReturn_t (*cudaMemGetInfo)(size_t *, size_t *);
cudartReturn_t (*cudaGetDeviceCount)(int *);
cudartReturn_t (*cudaDeviceGetAttribute)(int* value, cudartDeviceAttr_t attr, int device);
cudartReturn_t (*cudaDriverGetVersion) (int *driverVersion);
} cudart_handle_t;
typedef struct cudart_init_resp {
char *err; // If err is non-null handle is invalid
cudart_handle_t ch;
} cudart_init_resp_t;
typedef struct cudart_compute_capability {
char *err;
int major;
int minor;
} cudart_compute_capability_t;
void cudart_init(char *cudart_lib_path, cudart_init_resp_t *resp);
void cudart_check_vram(cudart_handle_t ch, mem_info_t *resp);
void cudart_compute_capability(cudart_handle_t th, cudart_compute_capability_t *cc);
void cudart_release(cudart_handle_t ch);
#endif // __GPU_INFO_CUDART_H__
#endif // __APPLE__

View File

@@ -1,10 +1,10 @@
#ifndef __APPLE__ // TODO - maybe consider nvidia support on intel macs?
#include "gpu_info_cuda.h"
#include <string.h>
void cuda_init(char *cuda_lib_path, cuda_init_resp_t *resp) {
#include "gpu_info_nvml.h"
void nvml_init(char *nvml_lib_path, nvml_init_resp_t *resp) {
nvmlReturn_t ret;
resp->err = NULL;
const int buflen = 256;
@@ -30,20 +30,20 @@ void cuda_init(char *cuda_lib_path, cuda_init_resp_t *resp) {
{NULL, NULL},
};
resp->ch.handle = LOAD_LIBRARY(cuda_lib_path, RTLD_LAZY);
resp->ch.handle = LOAD_LIBRARY(nvml_lib_path, RTLD_LAZY);
if (!resp->ch.handle) {
char *msg = LOAD_ERR();
LOG(resp->ch.verbose, "library %s load err: %s\n", cuda_lib_path, msg);
LOG(resp->ch.verbose, "library %s load err: %s\n", nvml_lib_path, msg);
snprintf(buf, buflen,
"Unable to load %s library to query for Nvidia GPUs: %s",
cuda_lib_path, msg);
nvml_lib_path, msg);
free(msg);
resp->err = strdup(buf);
return;
}
// TODO once we've squashed the remaining corner cases remove this log
LOG(resp->ch.verbose, "wiring nvidia management library functions in %s\n", cuda_lib_path);
LOG(resp->ch.verbose, "wiring nvidia management library functions in %s\n", nvml_lib_path);
for (i = 0; l[i].s != NULL; i++) {
// TODO once we've squashed the remaining corner cases remove this log
@@ -82,7 +82,7 @@ void cuda_init(char *cuda_lib_path, cuda_init_resp_t *resp) {
}
}
void cuda_check_vram(cuda_handle_t h, mem_info_t *resp) {
void nvml_check_vram(nvml_handle_t h, mem_info_t *resp) {
resp->err = NULL;
nvmlDevice_t device;
nvmlMemory_t memInfo = {0};
@@ -92,7 +92,7 @@ void cuda_check_vram(cuda_handle_t h, mem_info_t *resp) {
int i;
if (h.handle == NULL) {
resp->err = strdup("nvml handle sn't initialized");
resp->err = strdup("nvml handle isn't initialized");
return;
}
@@ -156,14 +156,14 @@ void cuda_check_vram(cuda_handle_t h, mem_info_t *resp) {
}
LOG(h.verbose, "[%d] CUDA totalMem %ld\n", i, memInfo.total);
LOG(h.verbose, "[%d] CUDA usedMem %ld\n", i, memInfo.used);
LOG(h.verbose, "[%d] CUDA freeMem %ld\n", i, memInfo.free);
resp->total += memInfo.total;
resp->free += memInfo.free;
}
}
void cuda_compute_capability(cuda_handle_t h, cuda_compute_capability_t *resp) {
void nvml_compute_capability(nvml_handle_t h, nvml_compute_capability_t *resp) {
resp->err = NULL;
resp->major = 0;
resp->minor = 0;
@@ -211,4 +211,11 @@ void cuda_compute_capability(cuda_handle_t h, cuda_compute_capability_t *resp) {
}
}
}
void nvml_release(nvml_handle_t h) {
LOG(h.verbose, "releasing nvml library\n");
UNLOAD_LIBRARY(h.handle);
h.handle = NULL;
}
#endif // __APPLE__

View File

@@ -1,6 +1,6 @@
#ifndef __APPLE__
#ifndef __GPU_INFO_CUDA_H__
#define __GPU_INFO_CUDA_H__
#ifndef __GPU_INFO_NVML_H__
#define __GPU_INFO_NVML_H__
#include "gpu_info.h"
// Just enough typedef's to dlopen/dlsym for memory information
@@ -20,7 +20,7 @@ typedef enum nvmlBrandType_enum
NVML_BRAND_UNKNOWN = 0,
} nvmlBrandType_t;
typedef struct cuda_handle {
typedef struct nvml_handle {
void *handle;
uint16_t verbose;
nvmlReturn_t (*nvmlInit_v2)(void);
@@ -35,22 +35,23 @@ typedef struct cuda_handle {
nvmlReturn_t (*nvmlDeviceGetVbiosVersion) (nvmlDevice_t device, char* version, unsigned int length);
nvmlReturn_t (*nvmlDeviceGetBoardPartNumber) (nvmlDevice_t device, char* partNumber, unsigned int length);
nvmlReturn_t (*nvmlDeviceGetBrand) (nvmlDevice_t device, nvmlBrandType_t* type);
} cuda_handle_t;
} nvml_handle_t;
typedef struct cuda_init_resp {
typedef struct nvml_init_resp {
char *err; // If err is non-null handle is invalid
cuda_handle_t ch;
} cuda_init_resp_t;
nvml_handle_t ch;
} nvml_init_resp_t;
typedef struct cuda_compute_capability {
typedef struct nvml_compute_capability {
char *err;
int major;
int minor;
} cuda_compute_capability_t;
} nvml_compute_capability_t;
void cuda_init(char *cuda_lib_path, cuda_init_resp_t *resp);
void cuda_check_vram(cuda_handle_t ch, mem_info_t *resp);
void cuda_compute_capability(cuda_handle_t ch, cuda_compute_capability_t *cc);
void nvml_init(char *nvml_lib_path, nvml_init_resp_t *resp);
void nvml_check_vram(nvml_handle_t ch, mem_info_t *resp);
void nvml_compute_capability(nvml_handle_t ch, nvml_compute_capability_t *cc);
void nvml_release(nvml_handle_t ch);
#endif // __GPU_INFO_CUDA_H__
#endif // __GPU_INFO_NVML_H__
#endif // __APPLE__

View File

@@ -14,6 +14,9 @@ type GpuInfo struct {
// Optional variant to select (e.g. versions, cpu feature flags)
Variant string `json:"variant,omitempty"`
// MinimumMemory represents the minimum memory required to use the GPU
MinimumMemory int64 `json:"-"`
// TODO add other useful attributes about the card here for discovery information
}

11
integration/README.md Normal file
View File

@@ -0,0 +1,11 @@
# Integration Tests
This directory contains integration tests to exercise Ollama end-to-end to verify behavior
By default, these tests are disabled so `go test ./...` will exercise only unit tests. To run integration tests you must pass the integration tag. `go test -tags=integration ./...`
The integration tests have 2 modes of operating.
1. By default, they will start the server on a random port, run the tests, and then shutdown the server.
2. If `OLLAMA_TEST_EXISTING` is set to a non-empty string, the tests will run against an existing running server, which can be remote

28
integration/basic_test.go Normal file
View File

@@ -0,0 +1,28 @@
//go:build integration
package integration
import (
"context"
"net/http"
"testing"
"time"
"github.com/ollama/ollama/api"
)
func TestOrcaMiniBlueSky(t *testing.T) {
ctx, cancel := context.WithTimeout(context.Background(), 2*time.Minute)
defer cancel()
// Set up the test data
req := api.GenerateRequest{
Model: "orca-mini",
Prompt: "why is the sky blue?",
Stream: &stream,
Options: map[string]interface{}{
"temperature": 0,
"seed": 123,
},
}
GenerateTestHelper(ctx, t, &http.Client{}, req, []string{"rayleigh", "scattering"})
}

View File

@@ -1,49 +1,38 @@
//go:build integration
package server
package integration
import (
"context"
"encoding/base64"
"log"
"os"
"strings"
"net/http"
"testing"
"time"
"github.com/jmorganca/ollama/api"
"github.com/jmorganca/ollama/llm"
"github.com/stretchr/testify/assert"
"github.com/ollama/ollama/api"
"github.com/stretchr/testify/require"
)
func TestIntegrationMultimodal(t *testing.T) {
SkipIFNoTestData(t)
image, err := base64.StdEncoding.DecodeString(imageEncoding)
require.NoError(t, err)
req := api.GenerateRequest{
Model: "llava:7b",
Prompt: "what does the text in this image say?",
Options: map[string]interface{}{},
Model: "llava:7b",
Prompt: "what does the text in this image say?",
Stream: &stream,
Options: map[string]interface{}{
"seed": 42,
"temperature": 0.0,
},
Images: []api.ImageData{
image,
},
}
resp := "the ollamas"
workDir, err := os.MkdirTemp("", "ollama")
require.NoError(t, err)
defer os.RemoveAll(workDir)
require.NoError(t, llm.Init(workDir))
ctx, cancel := context.WithTimeout(context.Background(), time.Second*60)
ctx, cancel := context.WithTimeout(context.Background(), 3*time.Minute)
defer cancel()
opts := api.DefaultOptions()
opts.Seed = 42
opts.Temperature = 0.0
model, llmRunner := PrepareModelForPrompts(t, req.Model, opts)
defer llmRunner.Close()
response := OneShotPromptResponse(t, ctx, req, model, llmRunner)
log.Print(response)
assert.Contains(t, strings.ToLower(response), resp)
GenerateTestHelper(ctx, t, &http.Client{}, req, []string{resp})
}
const imageEncoding = `iVBORw0KGgoAAAANSUhEUgAAANIAAAB4CAYAAACHHqzKAAAAAXNSR0IArs4c6QAAAIRlWElmTU0AKgAAAAgABQESAAMAAAABAAEAAAEaAAUAAAABAAAASgEb

73
integration/llm_test.go Normal file
View File

@@ -0,0 +1,73 @@
//go:build integration
package integration
import (
"context"
"net/http"
"sync"
"testing"
"time"
"github.com/ollama/ollama/api"
)
// TODO - this would ideally be in the llm package, but that would require some refactoring of interfaces in the server
// package to avoid circular dependencies
// WARNING - these tests will fail on mac if you don't manually copy ggml-metal.metal to this dir (./server)
//
// TODO - Fix this ^^
var (
stream = false
req = [2]api.GenerateRequest{
{
Model: "orca-mini",
Prompt: "why is the ocean blue?",
Stream: &stream,
Options: map[string]interface{}{
"seed": 42,
"temperature": 0.0,
},
}, {
Model: "orca-mini",
Prompt: "what is the origin of the us thanksgiving holiday?",
Stream: &stream,
Options: map[string]interface{}{
"seed": 42,
"temperature": 0.0,
},
},
}
resp = [2][]string{
[]string{"sunlight"},
[]string{"england", "english", "massachusetts", "pilgrims"},
}
)
func TestIntegrationSimpleOrcaMini(t *testing.T) {
ctx, cancel := context.WithTimeout(context.Background(), time.Second*120)
defer cancel()
GenerateTestHelper(ctx, t, &http.Client{}, req[0], resp[0])
}
// TODO
// The server always loads a new runner and closes the old one, which forces serial execution
// At present this test case fails with concurrency problems. Eventually we should try to
// get true concurrency working with n_parallel support in the backend
func TestIntegrationConcurrentPredictOrcaMini(t *testing.T) {
var wg sync.WaitGroup
wg.Add(len(req))
ctx, cancel := context.WithTimeout(context.Background(), time.Second*120)
defer cancel()
for i := 0; i < len(req); i++ {
go func(i int) {
defer wg.Done()
GenerateTestHelper(ctx, t, &http.Client{}, req[i], resp[i])
}(i)
}
wg.Wait()
}
// TODO - create a parallel test with 2 different models once we support concurrency

265
integration/utils_test.go Normal file
View File

@@ -0,0 +1,265 @@
//go:build integration
package integration
import (
"bytes"
"context"
"encoding/json"
"fmt"
"io"
"log/slog"
"math/rand"
"net"
"net/http"
"os"
"path/filepath"
"runtime"
"strconv"
"strings"
"sync"
"testing"
"time"
"github.com/ollama/ollama/api"
"github.com/ollama/ollama/app/lifecycle"
"github.com/stretchr/testify/assert"
)
func FindPort() string {
port := 0
if a, err := net.ResolveTCPAddr("tcp", "localhost:0"); err == nil {
var l *net.TCPListener
if l, err = net.ListenTCP("tcp", a); err == nil {
port = l.Addr().(*net.TCPAddr).Port
l.Close()
}
}
if port == 0 {
port = rand.Intn(65535-49152) + 49152 // get a random port in the ephemeral range
}
return strconv.Itoa(port)
}
func GetTestEndpoint() (string, string) {
defaultPort := "11434"
ollamaHost := os.Getenv("OLLAMA_HOST")
scheme, hostport, ok := strings.Cut(ollamaHost, "://")
if !ok {
scheme, hostport = "http", ollamaHost
}
// trim trailing slashes
hostport = strings.TrimRight(hostport, "/")
host, port, err := net.SplitHostPort(hostport)
if err != nil {
host, port = "127.0.0.1", defaultPort
if ip := net.ParseIP(strings.Trim(hostport, "[]")); ip != nil {
host = ip.String()
} else if hostport != "" {
host = hostport
}
}
if os.Getenv("OLLAMA_TEST_EXISTING") == "" && port == defaultPort {
port = FindPort()
}
url := fmt.Sprintf("%s:%s", host, port)
slog.Info("server connection", "url", url)
return scheme, url
}
// TODO make fanicier, grab logs, etc.
var serverMutex sync.Mutex
var serverReady bool
func StartServer(ctx context.Context, ollamaHost string) error {
// Make sure the server has been built
CLIName, err := filepath.Abs("../ollama")
if err != nil {
return err
}
if runtime.GOOS == "windows" {
CLIName += ".exe"
}
_, err = os.Stat(CLIName)
if err != nil {
return fmt.Errorf("CLI missing, did you forget to build first? %w", err)
}
serverMutex.Lock()
defer serverMutex.Unlock()
if serverReady {
return nil
}
if tmp := os.Getenv("OLLAMA_HOST"); tmp != ollamaHost {
slog.Info("setting env", "OLLAMA_HOST", ollamaHost)
os.Setenv("OLLAMA_HOST", ollamaHost)
}
slog.Info("starting server", "url", ollamaHost)
done, err := lifecycle.SpawnServer(ctx, "../ollama")
if err != nil {
return fmt.Errorf("failed to start server: %w", err)
}
go func() {
<-ctx.Done()
serverMutex.Lock()
defer serverMutex.Unlock()
exitCode := <-done
if exitCode > 0 {
slog.Warn("server failure", "exit", exitCode)
}
serverReady = false
}()
// TODO wait only long enough for the server to be responsive...
time.Sleep(500 * time.Millisecond)
serverReady = true
return nil
}
func PullIfMissing(ctx context.Context, client *http.Client, scheme, testEndpoint, modelName string) error {
slog.Info("checking status of model", "model", modelName)
showReq := &api.ShowRequest{Name: modelName}
requestJSON, err := json.Marshal(showReq)
if err != nil {
return err
}
req, err := http.NewRequest("POST", scheme+"://"+testEndpoint+"/api/show", bytes.NewReader(requestJSON))
if err != nil {
return err
}
// Make the request with the HTTP client
response, err := client.Do(req.WithContext(ctx))
if err != nil {
return err
}
defer response.Body.Close()
if response.StatusCode == 200 {
slog.Info("model already present", "model", modelName)
return nil
}
slog.Info("model missing", "status", response.StatusCode)
pullReq := &api.PullRequest{Name: modelName, Stream: &stream}
requestJSON, err = json.Marshal(pullReq)
if err != nil {
return err
}
req, err = http.NewRequest("POST", scheme+"://"+testEndpoint+"/api/pull", bytes.NewReader(requestJSON))
if err != nil {
return err
}
slog.Info("pulling", "model", modelName)
response, err = client.Do(req.WithContext(ctx))
if err != nil {
return err
}
defer response.Body.Close()
if response.StatusCode != 200 {
return fmt.Errorf("failed to pull model") // TODO more details perhaps
}
slog.Info("model pulled", "model", modelName)
return nil
}
var serverProcMutex sync.Mutex
func GenerateTestHelper(ctx context.Context, t *testing.T, client *http.Client, genReq api.GenerateRequest, anyResp []string) {
// TODO maybe stuff in an init routine?
lifecycle.InitLogging()
requestJSON, err := json.Marshal(genReq)
if err != nil {
t.Fatalf("Error serializing request: %v", err)
}
defer func() {
if os.Getenv("OLLAMA_TEST_EXISTING") == "" {
defer serverProcMutex.Unlock()
if t.Failed() {
fp, err := os.Open(lifecycle.ServerLogFile)
if err != nil {
slog.Error("failed to open server log", "logfile", lifecycle.ServerLogFile, "error", err)
return
}
data, err := io.ReadAll(fp)
if err != nil {
slog.Error("failed to read server log", "logfile", lifecycle.ServerLogFile, "error", err)
return
}
slog.Warn("SERVER LOG FOLLOWS")
os.Stderr.Write(data)
slog.Warn("END OF SERVER")
}
err = os.Remove(lifecycle.ServerLogFile)
if err != nil && !os.IsNotExist(err) {
slog.Warn("failed to cleanup", "logfile", lifecycle.ServerLogFile, "error", err)
}
}
}()
scheme, testEndpoint := GetTestEndpoint()
if os.Getenv("OLLAMA_TEST_EXISTING") == "" {
serverProcMutex.Lock()
fp, err := os.CreateTemp("", "ollama-server-*.log")
if err != nil {
t.Fatalf("failed to generate log file: %s", err)
}
lifecycle.ServerLogFile = fp.Name()
fp.Close()
assert.NoError(t, StartServer(ctx, testEndpoint))
}
err = PullIfMissing(ctx, client, scheme, testEndpoint, genReq.Model)
if err != nil {
t.Fatalf("Error pulling model: %v", err)
}
// Make the request and get the response
req, err := http.NewRequest("POST", scheme+"://"+testEndpoint+"/api/generate", bytes.NewReader(requestJSON))
if err != nil {
t.Fatalf("Error creating request: %v", err)
}
// Set the content type for the request
req.Header.Set("Content-Type", "application/json")
// Make the request with the HTTP client
response, err := client.Do(req.WithContext(ctx))
if err != nil {
t.Fatalf("Error making request: %v", err)
}
defer response.Body.Close()
body, err := io.ReadAll(response.Body)
assert.NoError(t, err)
assert.Equal(t, response.StatusCode, 200, string(body))
// Verify the response is valid JSON
var payload api.GenerateResponse
err = json.Unmarshal(body, &payload)
if err != nil {
assert.NoError(t, err, body)
}
// Verify the response contains the expected data
atLeastOne := false
for _, resp := range anyResp {
if strings.Contains(strings.ToLower(payload.Response), resp) {
atLeastOne = true
break
}
}
assert.True(t, atLeastOne, "none of %v found in %s", anyResp, payload.Response)
}

View File

@@ -1,142 +0,0 @@
#include "dyn_ext_server.h"
#include <stdio.h>
#include <string.h>
#ifdef __linux__
#include <dlfcn.h>
#define LOAD_LIBRARY(lib, flags) dlopen(lib, flags)
#define LOAD_SYMBOL(handle, sym) dlsym(handle, sym)
#define LOAD_ERR() strdup(dlerror())
#define UNLOAD_LIBRARY(handle) dlclose(handle)
#elif _WIN32
#include <windows.h>
#define LOAD_LIBRARY(lib, flags) LoadLibrary(lib)
#define LOAD_SYMBOL(handle, sym) GetProcAddress(handle, sym)
#define UNLOAD_LIBRARY(handle) FreeLibrary(handle)
#define LOAD_ERR() ({\
LPSTR messageBuffer = NULL; \
size_t size = FormatMessageA(FORMAT_MESSAGE_ALLOCATE_BUFFER | FORMAT_MESSAGE_FROM_SYSTEM | FORMAT_MESSAGE_IGNORE_INSERTS, \
NULL, GetLastError(), MAKELANGID(LANG_NEUTRAL, SUBLANG_DEFAULT), (LPSTR)&messageBuffer, 0, NULL); \
char *resp = strdup(messageBuffer); \
LocalFree(messageBuffer); \
resp; \
})
#else
#include <dlfcn.h>
#define LOAD_LIBRARY(lib, flags) dlopen(lib, flags)
#define LOAD_SYMBOL(handle, sym) dlsym(handle, sym)
#define LOAD_ERR() strdup(dlerror())
#define UNLOAD_LIBRARY(handle) dlclose(handle)
#endif
void dyn_init(const char *libPath, struct dynamic_llama_server *s,
ext_server_resp_t *err) {
int i = 0;
struct lookup {
char *s;
void **p;
} l[] = {
{"llama_server_init", (void *)&s->llama_server_init},
{"llama_server_start", (void *)&s->llama_server_start},
{"llama_server_stop", (void *)&s->llama_server_stop},
{"llama_server_completion", (void *)&s->llama_server_completion},
{"llama_server_completion_next_result",
(void *)&s->llama_server_completion_next_result},
{"llama_server_completion_cancel",
(void *)&s->llama_server_completion_cancel},
{"llama_server_release_task_result",
(void *)&s->llama_server_release_task_result},
{"llama_server_tokenize", (void *)&s->llama_server_tokenize},
{"llama_server_detokenize", (void *)&s->llama_server_detokenize},
{"llama_server_embedding", (void *)&s->llama_server_embedding},
{"llama_server_release_json_resp",
(void *)&s->llama_server_release_json_resp},
{"", NULL},
};
printf("loading library %s\n", libPath);
s->handle = LOAD_LIBRARY(libPath, RTLD_LOCAL|RTLD_NOW);
if (!s->handle) {
err->id = -1;
char *msg = LOAD_ERR();
snprintf(err->msg, err->msg_len,
"Unable to load dynamic server library: %s", msg);
free(msg);
return;
}
for (i = 0; l[i].p != NULL; i++) {
*l[i].p = LOAD_SYMBOL(s->handle, l[i].s);
if (!l[i].p) {
UNLOAD_LIBRARY(s->handle);
err->id = -1;
char *msg = LOAD_ERR();
snprintf(err->msg, err->msg_len, "symbol lookup for %s failed: %s",
l[i].s, msg);
free(msg);
return;
}
}
}
inline void dyn_llama_server_init(struct dynamic_llama_server s,
ext_server_params_t *sparams,
ext_server_resp_t *err) {
s.llama_server_init(sparams, err);
}
inline void dyn_llama_server_start(struct dynamic_llama_server s) {
s.llama_server_start();
}
inline void dyn_llama_server_stop(struct dynamic_llama_server s) {
s.llama_server_stop();
}
inline void dyn_llama_server_completion(struct dynamic_llama_server s,
const char *json_req,
ext_server_resp_t *resp) {
s.llama_server_completion(json_req, resp);
}
inline void dyn_llama_server_completion_next_result(
struct dynamic_llama_server s, const int task_id,
ext_server_task_result_t *result) {
s.llama_server_completion_next_result(task_id, result);
}
inline void dyn_llama_server_completion_cancel(
struct dynamic_llama_server s, const int task_id, ext_server_resp_t *err) {
s.llama_server_completion_cancel(task_id, err);
}
inline void dyn_llama_server_release_task_result(
struct dynamic_llama_server s, ext_server_task_result_t *result) {
s.llama_server_release_task_result(result);
}
inline void dyn_llama_server_tokenize(struct dynamic_llama_server s,
const char *json_req,
char **json_resp,
ext_server_resp_t *err) {
s.llama_server_tokenize(json_req, json_resp, err);
}
inline void dyn_llama_server_detokenize(struct dynamic_llama_server s,
const char *json_req,
char **json_resp,
ext_server_resp_t *err) {
s.llama_server_detokenize(json_req, json_resp, err);
}
inline void dyn_llama_server_embedding(struct dynamic_llama_server s,
const char *json_req,
char **json_resp,
ext_server_resp_t *err) {
s.llama_server_embedding(json_req, json_resp, err);
}
inline void dyn_llama_server_release_json_resp(
struct dynamic_llama_server s, char **json_resp) {
s.llama_server_release_json_resp(json_resp);
}

View File

@@ -1,368 +0,0 @@
package llm
/*
#cgo CFLAGS: -I${SRCDIR}/ext_server -I${SRCDIR}/llama.cpp -I${SRCDIR}/llama.cpp/common -I${SRCDIR}/llama.cpp/examples/server
#cgo CFLAGS: -DNDEBUG -DLLAMA_SERVER_LIBRARY=1 -D_XOPEN_SOURCE=600 -DACCELERATE_NEW_LAPACK -DACCELERATE_LAPACK_ILP64
#cgo CFLAGS: -Wmissing-noreturn -Wextra -Wcast-qual -Wno-unused-function -Wno-array-bounds
#cgo CPPFLAGS: -Ofast -Wextra -Wno-unused-function -Wno-unused-variable -Wno-deprecated-declarations
#cgo darwin CFLAGS: -D_DARWIN_C_SOURCE
#cgo darwin CPPFLAGS: -DGGML_USE_ACCELERATE
#cgo darwin CPPFLAGS: -DGGML_USE_METAL -DGGML_METAL_NDEBUG
#cgo darwin LDFLAGS: -lc++ -framework Accelerate
#cgo darwin LDFLAGS: -framework Foundation -framework Metal -framework MetalKit -framework MetalPerformanceShaders
#cgo linux CFLAGS: -D_GNU_SOURCE
#cgo linux LDFLAGS: -lrt -ldl -lstdc++ -lm
#cgo linux windows LDFLAGS: -lpthread
#include <stdlib.h>
#include "dyn_ext_server.h"
*/
import "C"
import (
"bytes"
"context"
"encoding/json"
"fmt"
"log/slog"
"os"
"path/filepath"
"strings"
"sync"
"time"
"unsafe"
"github.com/jmorganca/ollama/api"
"github.com/jmorganca/ollama/gpu"
)
type dynExtServer struct {
s C.struct_dynamic_llama_server
options api.Options
}
// Note: current implementation does not support concurrent instantiations
var mutex sync.Mutex
func newExtServerResp(len C.size_t) C.ext_server_resp_t {
var resp C.ext_server_resp_t
resp.msg_len = len
bytes := make([]byte, len)
resp.msg = (*C.char)(C.CBytes(bytes))
return resp
}
func freeExtServerResp(resp C.ext_server_resp_t) {
if resp.msg_len == 0 {
return
}
C.free(unsafe.Pointer(resp.msg))
}
func extServerResponseToErr(resp C.ext_server_resp_t) error {
return fmt.Errorf(C.GoString(resp.msg))
}
// Note: current implementation does not support concurrent instantiations
var llm *dynExtServer
func newDynExtServer(library, model string, adapters, projectors []string, opts api.Options) (LLM, error) {
if !mutex.TryLock() {
slog.Info("concurrent llm servers not yet supported, waiting for prior server to complete")
mutex.Lock()
}
gpu.UpdatePath(filepath.Dir(library))
libPath := C.CString(library)
defer C.free(unsafe.Pointer(libPath))
resp := newExtServerResp(512)
defer freeExtServerResp(resp)
var srv C.struct_dynamic_llama_server
C.dyn_init(libPath, &srv, &resp)
if resp.id < 0 {
mutex.Unlock()
return nil, fmt.Errorf("Unable to load dynamic library: %s", C.GoString(resp.msg))
}
llm = &dynExtServer{
s: srv,
options: opts,
}
slog.Info(fmt.Sprintf("Loading Dynamic llm server: %s", library))
var sparams C.ext_server_params_t
sparams.model = C.CString(model)
defer C.free(unsafe.Pointer(sparams.model))
sparams.embedding = true
sparams.n_ctx = C.uint(opts.NumCtx)
sparams.n_batch = C.uint(opts.NumBatch)
sparams.n_gpu_layers = C.int(opts.NumGPU)
sparams.main_gpu = C.int(opts.MainGPU)
sparams.n_parallel = 1 // TODO - wire up concurrency
// Always use the value encoded in the model
sparams.rope_freq_base = 0.0
sparams.rope_freq_scale = 0.0
sparams.memory_f16 = C.bool(opts.F16KV)
sparams.use_mlock = C.bool(opts.UseMLock)
sparams.use_mmap = C.bool(opts.UseMMap)
if opts.UseNUMA {
sparams.numa = C.int(1)
} else {
sparams.numa = C.int(0)
}
sparams.lora_adapters = nil
for i := 0; i < len(adapters); i++ {
la := (*C.ext_server_lora_adapter_t)(C.malloc(C.sizeof_ext_server_lora_adapter_t))
defer C.free(unsafe.Pointer(la))
la.adapter = C.CString(adapters[i])
defer C.free(unsafe.Pointer(la.adapter))
la.scale = C.float(1.0) // TODO expose scale/weights up through ollama UX
la.next = nil
if i == 0 {
sparams.lora_adapters = la
} else {
tmp := sparams.lora_adapters
for ; tmp.next != nil; tmp = tmp.next {
}
tmp.next = la
}
}
if len(projectors) > 0 {
// TODO: applying multiple projectors is not supported by the llama.cpp server yet
sparams.mmproj = C.CString(projectors[0])
defer C.free(unsafe.Pointer(sparams.mmproj))
} else {
sparams.mmproj = nil
}
sparams.n_threads = C.uint(opts.NumThread)
if debug := os.Getenv("OLLAMA_DEBUG"); debug != "" {
sparams.verbose_logging = C.bool(true)
} else {
sparams.verbose_logging = C.bool(false)
}
slog.Info("Initializing llama server")
slog.Debug(fmt.Sprintf("server params: %+v", sparams))
initResp := newExtServerResp(128)
defer freeExtServerResp(initResp)
C.dyn_llama_server_init(llm.s, &sparams, &initResp)
if initResp.id < 0 {
mutex.Unlock()
err := extServerResponseToErr(initResp)
slog.Debug(fmt.Sprintf("failure during initialization: %s", err))
return nil, err
}
slog.Info("Starting llama main loop")
C.dyn_llama_server_start(llm.s)
return llm, nil
}
func (llm *dynExtServer) Predict(ctx context.Context, predict PredictOpts, fn func(PredictResult)) error {
resp := newExtServerResp(128)
defer freeExtServerResp(resp)
if len(predict.Images) > 0 {
slog.Info(fmt.Sprintf("loaded %d images", len(predict.Images)))
}
request := map[string]any{
"prompt": predict.Prompt,
"stream": true,
"n_predict": predict.Options.NumPredict,
"n_keep": predict.Options.NumKeep,
"temperature": predict.Options.Temperature,
"top_k": predict.Options.TopK,
"top_p": predict.Options.TopP,
"tfs_z": predict.Options.TFSZ,
"typical_p": predict.Options.TypicalP,
"repeat_last_n": predict.Options.RepeatLastN,
"repeat_penalty": predict.Options.RepeatPenalty,
"presence_penalty": predict.Options.PresencePenalty,
"frequency_penalty": predict.Options.FrequencyPenalty,
"mirostat": predict.Options.Mirostat,
"mirostat_tau": predict.Options.MirostatTau,
"mirostat_eta": predict.Options.MirostatEta,
"penalize_nl": predict.Options.PenalizeNewline,
"seed": predict.Options.Seed,
"stop": predict.Options.Stop,
"image_data": predict.Images,
"cache_prompt": true,
}
if predict.Format == "json" {
request["grammar"] = jsonGrammar
}
retryDelay := 100 * time.Microsecond
for retries := 0; retries < maxRetries; retries++ {
if retries > 0 {
time.Sleep(retryDelay) // wait before retrying
retryDelay *= 2 // exponential backoff
}
// Handling JSON marshaling with special characters unescaped.
buffer := &bytes.Buffer{}
enc := json.NewEncoder(buffer)
enc.SetEscapeHTML(false)
if err := enc.Encode(request); err != nil {
return fmt.Errorf("failed to marshal data: %w", err)
}
req := C.CString(buffer.String())
defer C.free(unsafe.Pointer(req))
C.dyn_llama_server_completion(llm.s, req, &resp)
if resp.id < 0 {
return extServerResponseToErr(resp)
}
retryNeeded := false
out:
for {
select {
case <-ctx.Done():
// This handles the request cancellation
C.dyn_llama_server_completion_cancel(llm.s, resp.id, &resp)
if resp.id < 0 {
return extServerResponseToErr(resp)
} else {
return nil
}
default:
var result C.ext_server_task_result_t
C.dyn_llama_server_completion_next_result(llm.s, resp.id, &result)
json_resp := C.GoString(result.json_resp)
C.dyn_llama_server_release_task_result(llm.s, &result)
var p prediction
if err := json.Unmarshal([]byte(json_resp), &p); err != nil {
C.dyn_llama_server_completion_cancel(llm.s, resp.id, &resp)
if resp.id < 0 {
return fmt.Errorf("error unmarshaling llm prediction response: %w and cancel %s", err, C.GoString(resp.msg))
} else {
return fmt.Errorf("error unmarshaling llm prediction response: %w", err)
}
}
if bool(result.error) && strings.Contains(json_resp, "slot unavailable") {
retryNeeded = true
// task will already be canceled
break out
}
if p.Content != "" {
fn(PredictResult{
Content: p.Content,
})
}
if p.Stop || bool(result.stop) {
fn(PredictResult{
Done: true,
PromptEvalCount: p.Timings.PromptN,
PromptEvalDuration: parseDurationMs(p.Timings.PromptMS),
EvalCount: p.Timings.PredictedN,
EvalDuration: parseDurationMs(p.Timings.PredictedMS),
})
return nil
}
}
}
if !retryNeeded {
return nil // success
}
}
// should never reach here ideally
return fmt.Errorf("max retries exceeded")
}
func (llm *dynExtServer) Encode(ctx context.Context, prompt string) ([]int, error) {
data, err := json.Marshal(TokenizeRequest{Content: prompt})
if err != nil {
return nil, fmt.Errorf("marshaling encode data: %w", err)
}
req := C.CString(string(data))
defer C.free(unsafe.Pointer(req))
var json_resp *C.char
resp := newExtServerResp(128)
defer freeExtServerResp(resp)
C.dyn_llama_server_tokenize(llm.s, req, &json_resp, &resp)
if resp.id < 0 {
return nil, extServerResponseToErr(resp)
}
defer C.dyn_llama_server_release_json_resp(llm.s, &json_resp)
var encoded TokenizeResponse
if err2 := json.Unmarshal([]byte(C.GoString(json_resp)), &encoded); err2 != nil {
return nil, fmt.Errorf("unmarshal encode response: %w", err2)
}
return encoded.Tokens, err
}
func (llm *dynExtServer) Decode(ctx context.Context, tokens []int) (string, error) {
if len(tokens) == 0 {
return "", nil
}
data, err := json.Marshal(DetokenizeRequest{Tokens: tokens})
if err != nil {
return "", fmt.Errorf("marshaling decode data: %w", err)
}
req := C.CString(string(data))
defer C.free(unsafe.Pointer(req))
var json_resp *C.char
resp := newExtServerResp(128)
defer freeExtServerResp(resp)
C.dyn_llama_server_detokenize(llm.s, req, &json_resp, &resp)
if resp.id < 0 {
return "", extServerResponseToErr(resp)
}
defer C.dyn_llama_server_release_json_resp(llm.s, &json_resp)
var decoded DetokenizeResponse
if err2 := json.Unmarshal([]byte(C.GoString(json_resp)), &decoded); err2 != nil {
return "", fmt.Errorf("unmarshal encode response: %w", err2)
}
return decoded.Content, err
}
func (llm *dynExtServer) Embedding(ctx context.Context, input string) ([]float64, error) {
data, err := json.Marshal(TokenizeRequest{Content: input})
if err != nil {
return nil, fmt.Errorf("error marshaling embed data: %w", err)
}
req := C.CString(string(data))
defer C.free(unsafe.Pointer(req))
var json_resp *C.char
resp := newExtServerResp(128)
defer freeExtServerResp(resp)
C.dyn_llama_server_embedding(llm.s, req, &json_resp, &resp)
if resp.id < 0 {
return nil, extServerResponseToErr(resp)
}
defer C.dyn_llama_server_release_json_resp(llm.s, &json_resp)
var embedding EmbeddingResponse
if err := json.Unmarshal([]byte(C.GoString(json_resp)), &embedding); err != nil {
return nil, fmt.Errorf("unmarshal tokenize response: %w", err)
}
return embedding.Embedding, nil
}
func (llm *dynExtServer) Close() {
C.dyn_llama_server_stop(llm.s)
mutex.Unlock()
}

View File

@@ -1,74 +0,0 @@
#include <stdlib.h>
#include "ext_server.h"
#ifdef __cplusplus
extern "C" {
#endif
struct dynamic_llama_server {
void *handle;
void (*llama_server_init)(ext_server_params_t *sparams,
ext_server_resp_t *err);
void (*llama_server_start)();
void (*llama_server_stop)();
void (*llama_server_completion)(const char *json_req,
ext_server_resp_t *resp);
void (*llama_server_completion_next_result)(const int task_id,
ext_server_task_result_t *result);
void (*llama_server_completion_cancel)(const int task_id,
ext_server_resp_t *err);
void (*llama_server_release_task_result)(ext_server_task_result_t *result);
void (*llama_server_tokenize)(const char *json_req, char **json_resp,
ext_server_resp_t *err);
void (*llama_server_detokenize)(const char *json_req, char **json_resp,
ext_server_resp_t *err);
void (*llama_server_embedding)(const char *json_req, char **json_resp,
ext_server_resp_t *err);
void (*llama_server_release_json_resp)(char **json_resp);
};
void dyn_init(const char *libPath, struct dynamic_llama_server *s,
ext_server_resp_t *err);
// No good way to call C function pointers from Go so inline the indirection
void dyn_llama_server_init(struct dynamic_llama_server s,
ext_server_params_t *sparams,
ext_server_resp_t *err);
void dyn_llama_server_start(struct dynamic_llama_server s);
void dyn_llama_server_stop(struct dynamic_llama_server s);
void dyn_llama_server_completion(struct dynamic_llama_server s,
const char *json_req,
ext_server_resp_t *resp);
void dyn_llama_server_completion_next_result(
struct dynamic_llama_server s, const int task_id,
ext_server_task_result_t *result);
void dyn_llama_server_completion_cancel(struct dynamic_llama_server s,
const int task_id,
ext_server_resp_t *err);
void dyn_llama_server_release_task_result(
struct dynamic_llama_server s, ext_server_task_result_t *result);
void dyn_llama_server_tokenize(struct dynamic_llama_server s,
const char *json_req, char **json_resp,
ext_server_resp_t *err);
void dyn_llama_server_detokenize(struct dynamic_llama_server s,
const char *json_req,
char **json_resp,
ext_server_resp_t *err);
void dyn_llama_server_embedding(struct dynamic_llama_server s,
const char *json_req, char **json_resp,
ext_server_resp_t *err);
void dyn_llama_server_release_json_resp(struct dynamic_llama_server s,
char **json_resp);
#ifdef __cplusplus
}
#endif

View File

@@ -1,25 +1,14 @@
# Ollama specific CMakefile to include in llama.cpp/examples/server
set(TARGET ext_server)
set(TARGET ollama_llama_server)
option(LLAMA_SERVER_VERBOSE "Build verbose logging option for Server" ON)
include_directories(${CMAKE_CURRENT_SOURCE_DIR})
add_executable(${TARGET} server.cpp utils.hpp json.hpp httplib.h)
install(TARGETS ${TARGET} RUNTIME)
target_compile_definitions(${TARGET} PRIVATE
SERVER_VERBOSE=$<BOOL:${LLAMA_SERVER_VERBOSE}>
)
target_link_libraries(${TARGET} PRIVATE common llava ${CMAKE_THREAD_LIBS_INIT})
if (WIN32)
add_library(${TARGET} SHARED ../../../ext_server/ext_server.cpp ../../llama.cpp)
else()
add_library(${TARGET} STATIC ../../../ext_server/ext_server.cpp ../../llama.cpp)
TARGET_LINK_LIBRARIES(${TARGET} PRIVATE ws2_32)
endif()
target_include_directories(${TARGET} PRIVATE ../../common)
target_include_directories(${TARGET} PRIVATE ../..)
target_include_directories(${TARGET} PRIVATE ../../..)
target_compile_features(${TARGET} PRIVATE cxx_std_11)
target_compile_definitions(${TARGET} PUBLIC LLAMA_SERVER_LIBRARY=1)
target_link_libraries(${TARGET} PRIVATE ggml llava common )
set_target_properties(${TARGET} PROPERTIES POSITION_INDEPENDENT_CODE ON)
target_compile_definitions(${TARGET} PRIVATE SERVER_VERBOSE=$<BOOL:${LLAMA_SERVER_VERBOSE}>)
install(TARGETS ext_server LIBRARY)
if (CUDAToolkit_FOUND)
target_include_directories(${TARGET} PRIVATE ${CMAKE_CUDA_TOOLKIT_INCLUDE_DIRECTORIES})
if (WIN32)
target_link_libraries(${TARGET} PRIVATE nvml)
endif()
endif()
target_compile_features(${TARGET} PRIVATE cxx_std_11)

View File

@@ -1,18 +0,0 @@
# Extern C Server
This directory contains a thin facade we layer on top of the Llama.cpp server to
expose `extern C` interfaces to access the functionality through direct API
calls in-process. The llama.cpp code uses compile time macros to configure GPU
type along with other settings. During the `go generate ./...` execution, the
build will generate one or more copies of the llama.cpp `extern C` server based
on what GPU libraries are detected to support multiple GPU types as well as CPU
only support. The Ollama go build then embeds these different servers to support
different GPUs and settings at runtime.
If you are making changes to the code in this directory, make sure to disable
caching during your go build to ensure you pick up your changes. A typical
iteration cycle from the top of the source tree looks like:
```
go generate ./... && go build -a .
```

View File

@@ -1,381 +0,0 @@
#include "ext_server.h"
#include <atomic>
// Necessary evil since the server types are not defined in a header
#include "server.cpp"
// Low level API access to verify GPU access
#if defined(GGML_USE_CUBLAS)
#if defined(GGML_USE_HIPBLAS)
#include <hip/hip_runtime.h>
#include <hipblas/hipblas.h>
#include <hip/hip_fp16.h>
#ifdef __HIP_PLATFORM_AMD__
// for rocblas_initialize()
#include "rocblas/rocblas.h"
#endif // __HIP_PLATFORM_AMD__
#define cudaGetDevice hipGetDevice
#define cudaError_t hipError_t
#define cudaSuccess hipSuccess
#define cudaGetErrorString hipGetErrorString
#else
#include <cuda_runtime.h>
#include <cublas_v2.h>
#include <cuda_fp16.h>
#endif // defined(GGML_USE_HIPBLAS)
#endif // GGML_USE_CUBLAS
// Expose the llama server as a callable extern "C" API
server_context *llama = NULL;
std::thread ext_server_thread;
bool shutting_down = false;
std::atomic_int recv_counter;
// RAII wrapper for tracking in-flight recv calls
class atomicRecv {
public:
atomicRecv(std::atomic<int> &atomic) : atomic(atomic) {
++this->atomic;
}
~atomicRecv() {
--this->atomic;
}
private:
std::atomic<int> &atomic;
};
void llama_server_init(ext_server_params *sparams, ext_server_resp_t *err) {
recv_counter = 0;
assert(err != NULL && sparams != NULL);
log_set_target(stderr);
if (!sparams->verbose_logging) {
server_verbose = true;
log_disable();
}
LOG_TEE("system info: %s\n", llama_print_system_info());
err->id = 0;
err->msg[0] = '\0';
try {
llama = new server_context;
gpt_params params;
params.n_ctx = sparams->n_ctx;
params.n_batch = sparams->n_batch;
if (sparams->n_threads > 0) {
params.n_threads = sparams->n_threads;
}
params.n_parallel = sparams->n_parallel;
params.rope_freq_base = sparams->rope_freq_base;
params.rope_freq_scale = sparams->rope_freq_scale;
if (sparams->memory_f16) {
params.cache_type_k = "f16";
params.cache_type_v = "f16";
} else {
params.cache_type_k = "f32";
params.cache_type_v = "f32";
}
params.n_gpu_layers = sparams->n_gpu_layers;
params.main_gpu = sparams->main_gpu;
params.use_mlock = sparams->use_mlock;
params.use_mmap = sparams->use_mmap;
params.numa = (ggml_numa_strategy)sparams->numa;
params.embedding = sparams->embedding;
if (sparams->model != NULL) {
params.model = sparams->model;
}
if (sparams->lora_adapters != NULL) {
for (ext_server_lora_adapter *la = sparams->lora_adapters; la != NULL;
la = la->next) {
params.lora_adapter.push_back(std::make_tuple(la->adapter, la->scale));
}
params.use_mmap = false;
}
if (sparams->mmproj != NULL) {
params.mmproj = std::string(sparams->mmproj);
}
#if defined(GGML_USE_CUBLAS)
// Before attempting to init the backend which will assert on error, verify the CUDA/ROCM GPU is accessible
LOG_TEE("Performing pre-initialization of GPU\n");
int id;
cudaError_t cudaErr = cudaGetDevice(&id);
if (cudaErr != cudaSuccess) {
err->id = -1;
snprintf(err->msg, err->msg_len, "Unable to init GPU: %s", cudaGetErrorString(cudaErr));
return;
}
#endif
llama_backend_init();
llama_numa_init(params.numa);
// load the model
if (!llama->load_model(params)) {
// TODO - consider modifying the logging logic or patching load_model so
// we can capture more detailed error messages and pass them back to the
// caller for better UX
err->id = -1;
snprintf(err->msg, err->msg_len, "error loading model %s",
params.model.c_str());
return;
}
llama->init();
} catch (std::exception &e) {
err->id = -1;
snprintf(err->msg, err->msg_len, "exception %s", e.what());
} catch (...) {
err->id = -1;
snprintf(err->msg, err->msg_len,
"Unknown exception initializing llama server");
}
}
void llama_server_start() {
assert(llama != NULL);
// TODO mutex to protect thread creation
ext_server_thread = std::thread([&]() {
try {
LOG_TEE("llama server main loop starting\n");
ggml_time_init();
llama->queue_tasks.on_new_task(std::bind(
&server_context::process_single_task, llama, std::placeholders::_1));
llama->queue_tasks.on_finish_multitask(std::bind(
&server_context::on_finish_multitask, llama, std::placeholders::_1));
llama->queue_tasks.on_run_slots(std::bind(
&server_context::update_slots, llama));
llama->queue_results.on_multitask_update(std::bind(
&server_queue::update_multitask,
&llama->queue_tasks,
std::placeholders::_1,
std::placeholders::_2,
std::placeholders::_3
));
llama->queue_tasks.start_loop();
} catch (std::exception &e) {
LOG_TEE("caught exception in llama server main loop: %s\n", e.what());
} catch (...) {
LOG_TEE("caught unknown exception in llama server main loop\n");
}
LOG_TEE("\nllama server shutting down\n");
llama_backend_free();
});
}
void llama_server_stop() {
assert(llama != NULL);
// Shutdown any in-flight requests and block incoming requests.
LOG_TEE("\ninitiating shutdown - draining remaining tasks...\n");
shutting_down = true;
while (recv_counter.load() > 0) {
std::this_thread::sleep_for(std::chrono::milliseconds(50));
}
// This may take a while for any pending tasks to drain
// TODO - consider a timeout to cancel tasks if it's taking too long
llama->queue_tasks.terminate();
ext_server_thread.join();
delete llama;
llama = NULL;
LOG_TEE("llama server shutdown complete\n");
shutting_down = false;
}
void llama_server_completion(const char *json_req, ext_server_resp_t *resp) {
assert(llama != NULL && json_req != NULL && resp != NULL);
resp->id = -1;
resp->msg[0] = '\0';
try {
if (shutting_down) {
throw std::runtime_error("server shutting down");
}
json data = json::parse(json_req);
resp->id = llama->queue_tasks.get_new_id();
llama->queue_results.add_waiting_task_id(resp->id);
llama->request_completion(resp->id, -1, data, false, false);
} catch (std::exception &e) {
snprintf(resp->msg, resp->msg_len, "exception %s", e.what());
} catch (...) {
snprintf(resp->msg, resp->msg_len, "Unknown exception during completion");
}
}
void llama_server_completion_next_result(const int task_id,
ext_server_task_result_t *resp) {
assert(llama != NULL && resp != NULL);
resp->id = -1;
resp->stop = false;
resp->error = false;
resp->json_resp = NULL;
std::string result_json;
try {
atomicRecv ar(recv_counter);
server_task_result result = llama->queue_results.recv(task_id);
result_json =
result.data.dump(-1, ' ', false, json::error_handler_t::replace);
resp->id = result.id;
resp->stop = result.stop;
resp->error = result.error;
if (result.error) {
LOG_TEE("next result cancel on error\n");
llama->request_cancel(task_id);
LOG_TEE("next result removing waiting tak ID: %d\n", task_id);
llama->queue_results.remove_waiting_task_id(task_id);
} else if (result.stop) {
LOG_TEE("next result cancel on stop\n");
llama->request_cancel(task_id);
LOG_TEE("next result removing waiting task ID: %d\n", task_id);
llama->queue_results.remove_waiting_task_id(task_id);
} else if (shutting_down) {
LOG_TEE("aborting completion due to shutdown %d\n", task_id);
llama->request_cancel(task_id);
llama->queue_results.remove_waiting_task_id(task_id);
resp->stop = true;
}
} catch (std::exception &e) {
resp->error = true;
resp->id = -1;
result_json = "{\"error\":\"exception " + std::string(e.what()) + "\"}";
LOG_TEE("llama server completion exception %s\n", e.what());
} catch (...) {
resp->error = true;
resp->id = -1;
result_json = "{\"error\":\"Unknown exception during completion\"}";
LOG_TEE("llama server completion unknown exception\n");
}
const std::string::size_type size = result_json.size() + 1;
resp->json_resp = new char[size];
snprintf(resp->json_resp, size, "%s", result_json.c_str());
}
void llama_server_release_task_result(ext_server_task_result_t *result) {
if (result == NULL || result->json_resp == NULL) {
return;
}
delete[] result->json_resp;
}
void llama_server_completion_cancel(const int task_id, ext_server_resp_t *err) {
assert(llama != NULL && err != NULL);
err->id = 0;
err->msg[0] = '\0';
try {
llama->request_cancel(task_id);
llama->queue_results.remove_waiting_task_id(task_id);
} catch (std::exception &e) {
err->id = -1;
snprintf(err->msg, err->msg_len, "exception %s", e.what());
} catch (...) {
err->id = -1;
snprintf(err->msg, err->msg_len,
"Unknown exception completion cancel in llama server");
}
}
void llama_server_tokenize(const char *json_req, char **json_resp,
ext_server_resp_t *err) {
assert(llama != NULL && json_req != NULL && json_resp != NULL && err != NULL);
*json_resp = NULL;
err->id = 0;
err->msg[0] = '\0';
try {
if (shutting_down) {
throw std::runtime_error("server shutting down");
}
const json body = json::parse(json_req);
std::vector<llama_token> tokens;
if (body.count("content") != 0) {
tokens = llama->tokenize(body["content"], false);
}
const json data = format_tokenizer_response(tokens);
std::string result_json = data.dump();
const std::string::size_type size = result_json.size() + 1;
*json_resp = new char[size];
snprintf(*json_resp, size, "%s", result_json.c_str());
} catch (std::exception &e) {
err->id = -1;
snprintf(err->msg, err->msg_len, "exception %s", e.what());
} catch (...) {
err->id = -1;
snprintf(err->msg, err->msg_len, "Unknown exception during tokenize");
}
}
void llama_server_release_json_resp(char **json_resp) {
if (json_resp == NULL || *json_resp == NULL) {
return;
}
delete[] *json_resp;
}
void llama_server_detokenize(const char *json_req, char **json_resp,
ext_server_resp_t *err) {
assert(llama != NULL && json_req != NULL && json_resp != NULL && err != NULL);
*json_resp = NULL;
err->id = 0;
err->msg[0] = '\0';
try {
if (shutting_down) {
throw std::runtime_error("server shutting down");
}
const json body = json::parse(json_req);
std::string content;
if (body.count("tokens") != 0) {
const std::vector<llama_token> tokens = body["tokens"];
content = tokens_to_str(llama->ctx, tokens.cbegin(), tokens.cend());
}
const json data = format_detokenized_response(content);
std::string result_json = data.dump();
const std::string::size_type size = result_json.size() + 1;
*json_resp = new char[size];
snprintf(*json_resp, size, "%s", result_json.c_str());
} catch (std::exception &e) {
err->id = -1;
snprintf(err->msg, err->msg_len, "exception %s", e.what());
} catch (...) {
err->id = -1;
snprintf(err->msg, err->msg_len, "Unknown exception during detokenize");
}
}
void llama_server_embedding(const char *json_req, char **json_resp,
ext_server_resp_t *err) {
assert(llama != NULL && json_req != NULL && json_resp != NULL && err != NULL);
*json_resp = NULL;
err->id = 0;
err->msg[0] = '\0';
try {
if (shutting_down) {
throw std::runtime_error("server shutting down");
}
const json body = json::parse(json_req);
json prompt;
if (body.count("content") != 0) {
prompt = body["content"];
} else {
prompt = "";
}
const int task_id = llama->queue_tasks.get_new_id();
llama->queue_results.add_waiting_task_id(task_id);
llama->request_completion(task_id, -1, {{"prompt", prompt}, {"n_predict", 0}}, false, true);
atomicRecv ar(recv_counter);
server_task_result result = llama->queue_results.recv(task_id);
std::string result_json = result.data.dump();
const std::string::size_type size = result_json.size() + 1;
*json_resp = new char[size];
snprintf(*json_resp, size, "%s", result_json.c_str());
llama->queue_results.remove_waiting_task_id(task_id);
} catch (std::exception &e) {
err->id = -1;
snprintf(err->msg, err->msg_len, "exception %s", e.what());
} catch (...) {
err->id = -1;
snprintf(err->msg, err->msg_len, "Unknown exception during embedding");
}
}

View File

@@ -1,95 +0,0 @@
#if defined(LLAMA_SERVER_LIBRARY)
#ifndef LLAMA_SERVER_H
#define LLAMA_SERVER_H
#include <stdbool.h>
#include <stddef.h>
#include <stdint.h>
#include <stdio.h>
int __main(int argc, char **argv);
// This exposes extern C entrypoints into the llama_server
// To enable the server compile with LLAMA_SERVER_LIBRARY
#ifdef __cplusplus
extern "C" {
#endif
typedef struct ext_server_resp {
int id; // < 0 on error
size_t msg_len; // caller must allocate msg and set msg_len
char *msg;
} ext_server_resp_t;
// Allocated and freed by caller
typedef struct ext_server_lora_adapter {
char *adapter;
float scale;
struct ext_server_lora_adapter *next;
} ext_server_lora_adapter_t;
// Allocated and freed by caller
typedef struct ext_server_params {
char *model;
uint32_t n_ctx; // token context window, 0 = from model
uint32_t n_batch; // prompt processing maximum batch size
uint32_t n_threads; // number of threads to use for generation
int32_t n_parallel; // number of parallel sequences to decodewra
float rope_freq_base; // RoPE base frequency, 0 = from model
float rope_freq_scale; // RoPE frequency scaling factor, 0 = from model
bool memory_f16; // use f16 instead of f32 for memory kv
int32_t n_gpu_layers; // number of layers to store in VRAM (-1 - use default)
int32_t main_gpu; // the GPU that is used for scratch and small tensors
bool use_mlock; // force system to keep model in RAM
bool use_mmap; // use mmap if possible
int numa; // attempt optimizations that help on some NUMA systems
bool embedding; // get only sentence embedding
ext_server_lora_adapter_t *lora_adapters;
char *mmproj;
bool verbose_logging; // Enable verbose logging of the server
} ext_server_params_t;
typedef struct ext_server_task_result {
int id;
bool stop;
bool error;
char *json_resp; // null terminated, memory managed by ext_server
} ext_server_task_result_t;
// Initialize the server once per process
// err->id = 0 for success and err->msg[0] = NULL
// err->id != 0 for failure, and err->msg contains error message
void llama_server_init(ext_server_params_t *sparams, ext_server_resp_t *err);
// Run the main loop, called once per init
void llama_server_start();
// Stop the main loop and free up resources allocated in init and start. Init
// must be called again to reuse
void llama_server_stop();
// json_req null terminated string, memory managed by caller
// resp->id >= 0 on success (task ID)
// resp->id < 0 on error, and resp->msg contains error message
void llama_server_completion(const char *json_req, ext_server_resp_t *resp);
// Caller must call llama_server_release_task_result to free resp->json_resp
void llama_server_completion_next_result(const int task_id,
ext_server_task_result_t *result);
void llama_server_completion_cancel(const int task_id, ext_server_resp_t *err);
void llama_server_release_task_result(ext_server_task_result_t *result);
// Caller must call llama_server_releaes_json_resp to free json_resp if err.id <
// 0
void llama_server_tokenize(const char *json_req, char **json_resp,
ext_server_resp_t *err);
void llama_server_detokenize(const char *json_req, char **json_resp,
ext_server_resp_t *err);
void llama_server_embedding(const char *json_req, char **json_resp,
ext_server_resp_t *err);
void llama_server_release_json_resp(char **json_resp);
#ifdef __cplusplus
}
#endif
#endif
#endif // LLAMA_SERVER_LIBRARY

8794
llm/ext_server/httplib.h vendored Normal file
View File

File diff suppressed because it is too large Load Diff

24596
llm/ext_server/json.hpp vendored Normal file
View File

File diff suppressed because it is too large Load Diff

3292
llm/ext_server/server.cpp vendored Normal file
View File

File diff suppressed because it is too large Load Diff

655
llm/ext_server/utils.hpp vendored Normal file
View File

@@ -0,0 +1,655 @@
// MIT License
// Copyright (c) 2023 Georgi Gerganov
// Permission is hereby granted, free of charge, to any person obtaining a copy
// of this software and associated documentation files (the "Software"), to deal
// in the Software without restriction, including without limitation the rights
// to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
// copies of the Software, and to permit persons to whom the Software is
// furnished to do so, subject to the following conditions:
// The above copyright notice and this permission notice shall be included in all
// copies or substantial portions of the Software.
// THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
// IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
// FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
// AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
// LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
// OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
// SOFTWARE.
#pragma once
#include <string>
#include <vector>
#include <set>
#include <mutex>
#include <condition_variable>
#include <unordered_map>
#include "json.hpp"
#include "../llava/clip.h"
using json = nlohmann::json;
extern bool server_verbose;
extern bool server_log_json;
#ifndef SERVER_VERBOSE
#define SERVER_VERBOSE 1
#endif
#if SERVER_VERBOSE != 1
#define LOG_VERBOSE(MSG, ...)
#else
#define LOG_VERBOSE(MSG, ...) \
do \
{ \
if (server_verbose) \
{ \
server_log("VERB", __func__, __LINE__, MSG, __VA_ARGS__); \
} \
} while (0)
#endif
#define LOG_ERROR( MSG, ...) server_log("ERR", __func__, __LINE__, MSG, __VA_ARGS__)
#define LOG_WARNING(MSG, ...) server_log("WARN", __func__, __LINE__, MSG, __VA_ARGS__)
#define LOG_INFO( MSG, ...) server_log("INFO", __func__, __LINE__, MSG, __VA_ARGS__)
enum server_state {
SERVER_STATE_LOADING_MODEL, // Server is starting up, model not fully loaded yet
SERVER_STATE_READY, // Server is ready and model is loaded
SERVER_STATE_ERROR // An error occurred, load_model failed
};
enum task_type {
TASK_TYPE_COMPLETION,
TASK_TYPE_CANCEL,
TASK_TYPE_NEXT_RESPONSE,
TASK_TYPE_METRICS
};
struct task_server {
int id = -1; // to be filled by llama_server_queue
int target_id;
task_type type;
json data;
bool infill_mode = false;
bool embedding_mode = false;
int multitask_id = -1;
};
struct task_result {
int id;
int multitask_id = -1;
bool stop;
bool error;
json result_json;
};
struct task_multi {
int id;
std::set<int> subtasks_remaining{};
std::vector<task_result> results{};
};
// completion token output with probabilities
struct completion_token_output {
struct token_prob
{
llama_token tok;
float prob;
};
std::vector<token_prob> probs;
llama_token tok;
std::string text_to_send;
};
struct token_translator {
llama_context * ctx;
std::string operator()(llama_token tok) const { return llama_token_to_piece(ctx, tok); }
std::string operator()(const completion_token_output &cto) const { return (*this)(cto.tok); }
};
static inline void server_log(const char *level, const char *function, int line, const char *message, const nlohmann::ordered_json &extra) {
std::stringstream ss_tid;
ss_tid << std::this_thread::get_id();
json log = nlohmann::ordered_json{
{"tid", ss_tid.str()},
{"timestamp", time(nullptr)},
};
if (server_log_json) {
log.merge_patch(
{
{"level", level},
{"function", function},
{"line", line},
{"msg", message},
});
if (!extra.empty()) {
log.merge_patch(extra);
}
std::cout << log.dump(-1, ' ', false, json::error_handler_t::replace) << "\n" << std::flush;
} else {
char buf[1024];
snprintf(buf, 1024, "%4s [%24s] %s", level, function, message);
if (!extra.empty()) {
log.merge_patch(extra);
}
std::stringstream ss;
ss << buf << " |";
for (const auto& el : log.items())
{
const std::string value = el.value().dump(-1, ' ', false, json::error_handler_t::replace);
ss << " " << el.key() << "=" << value;
}
const std::string str = ss.str();
printf("%.*s\n", (int)str.size(), str.data());
fflush(stdout);
}
}
//
// server utils
//
template <typename T>
static T json_value(const json &body, const std::string &key, const T &default_value) {
// Fallback null to default value
return body.contains(key) && !body.at(key).is_null()
? body.value(key, default_value)
: default_value;
}
// Check if the template supplied via "--chat-template" is supported or not. Returns true if it's valid
inline bool verify_custom_template(const std::string & tmpl) {
llama_chat_message chat[] = {{"user", "test"}};
std::vector<char> buf(1);
int res = llama_chat_apply_template(nullptr, tmpl.c_str(), chat, 1, true, buf.data(), buf.size());
return res >= 0;
}
// Format given chat. If tmpl is empty, we take the template from model metadata
inline std::string format_chat(const struct llama_model * model, const std::string & tmpl, const std::vector<json> & messages) {
size_t alloc_size = 0;
// vector holding all allocated string to be passed to llama_chat_apply_template
std::vector<std::string> str(messages.size() * 2);
std::vector<llama_chat_message> chat(messages.size());
for (size_t i = 0; i < messages.size(); ++i) {
auto &curr_msg = messages[i];
str[i*2 + 0] = json_value(curr_msg, "role", std::string(""));
str[i*2 + 1] = json_value(curr_msg, "content", std::string(""));
alloc_size += str[i*2 + 1].length();
chat[i].role = str[i*2 + 0].c_str();
chat[i].content = str[i*2 + 1].c_str();
}
const char * ptr_tmpl = tmpl.empty() ? nullptr : tmpl.c_str();
std::vector<char> buf(alloc_size * 2);
// run the first time to get the total output length
int32_t res = llama_chat_apply_template(model, ptr_tmpl, chat.data(), chat.size(), true, buf.data(), buf.size());
// if it turns out that our buffer is too small, we resize it
if ((size_t) res > buf.size()) {
buf.resize(res);
res = llama_chat_apply_template(model, ptr_tmpl, chat.data(), chat.size(), true, buf.data(), buf.size());
}
std::string formatted_chat(buf.data(), res);
LOG_VERBOSE("formatted_chat", {{"text", formatted_chat.c_str()}});
return formatted_chat;
}
//
// work queue utils
//
struct llama_server_queue {
int id = 0;
std::mutex mutex_tasks;
bool running;
// queues
std::vector<task_server> queue_tasks;
std::vector<task_server> queue_tasks_deferred;
std::vector<task_multi> queue_multitasks;
std::condition_variable condition_tasks;
// callback functions
std::function<void(task_server&)> callback_new_task;
std::function<void(task_multi&)> callback_finish_multitask;
std::function<void(void)> callback_run_slots;
// Add a new task to the end of the queue
int post(task_server task) {
std::unique_lock<std::mutex> lock(mutex_tasks);
if (task.id == -1) {
task.id = id++;
LOG_VERBOSE("new task id", {{"new_id", task.id}});
}
queue_tasks.push_back(std::move(task));
condition_tasks.notify_one();
return task.id;
}
// Add a new task, but defer until one slot is available
void defer(task_server task) {
std::unique_lock<std::mutex> lock(mutex_tasks);
queue_tasks_deferred.push_back(std::move(task));
}
// Get the next id for creating anew task
int get_new_id() {
std::unique_lock<std::mutex> lock(mutex_tasks);
int new_id = id++;
LOG_VERBOSE("new task id", {{"new_id", new_id}});
return new_id;
}
// Register function to process a new task
void on_new_task(std::function<void(task_server&)> callback) {
callback_new_task = callback;
}
// Register function to process a multitask when it is finished
void on_finish_multitask(std::function<void(task_multi&)> callback) {
callback_finish_multitask = callback;
}
// Register the function to be called when all slots data is ready to be processed
void on_run_slots(std::function<void(void)> callback) {
callback_run_slots = callback;
}
// Call when the state of one slot is changed
void notify_slot_changed() {
// move deferred tasks back to main loop
std::unique_lock<std::mutex> lock(mutex_tasks);
for (auto & task : queue_tasks_deferred) {
queue_tasks.push_back(std::move(task));
}
queue_tasks_deferred.clear();
}
// end the start_loop routine
void terminate() {
{
std::unique_lock<std::mutex> lock(mutex_tasks);
running = false;
}
condition_tasks.notify_all();
}
/**
* Main loop consists of these steps:
* - Wait until a new task arrives
* - Process the task (i.e. maybe copy data into slot)
* - Check if multitask is finished
* - Run all slots
*/
void start_loop() {
running = true;
while (true) {
LOG_VERBOSE("new task may arrive", {});
{
while (true)
{
std::unique_lock<std::mutex> lock(mutex_tasks);
if (queue_tasks.empty()) {
lock.unlock();
break;
}
task_server task = queue_tasks.front();
queue_tasks.erase(queue_tasks.begin());
lock.unlock();
LOG_VERBOSE("callback_new_task", {{"task_id", task.id}});
callback_new_task(task);
}
LOG_VERBOSE("update_multitasks", {});
// check if we have any finished multitasks
auto queue_iterator = queue_multitasks.begin();
while (queue_iterator != queue_multitasks.end())
{
if (queue_iterator->subtasks_remaining.empty())
{
// all subtasks done == multitask is done
task_multi current_multitask = *queue_iterator;
callback_finish_multitask(current_multitask);
// remove this multitask
queue_iterator = queue_multitasks.erase(queue_iterator);
}
else
{
++queue_iterator;
}
}
// all tasks in the current loop is processed, slots data is now ready
LOG_VERBOSE("callback_run_slots", {});
callback_run_slots();
}
LOG_VERBOSE("wait for new task", {});
// wait for new task
{
std::unique_lock<std::mutex> lock(mutex_tasks);
if (queue_tasks.empty()) {
if (!running) {
LOG_VERBOSE("ending start_loop", {});
return;
}
condition_tasks.wait(lock, [&]{
return (!queue_tasks.empty() || !running);
});
}
}
}
}
//
// functions to manage multitasks
//
// add a multitask by specifying the id of all subtask (subtask is a task_server)
void add_multitask(int multitask_id, std::vector<int>& sub_ids)
{
std::lock_guard<std::mutex> lock(mutex_tasks);
task_multi multi;
multi.id = multitask_id;
std::copy(sub_ids.begin(), sub_ids.end(), std::inserter(multi.subtasks_remaining, multi.subtasks_remaining.end()));
queue_multitasks.push_back(multi);
}
// updatethe remaining subtasks, while appending results to multitask
void update_multitask(int multitask_id, int subtask_id, task_result& result)
{
std::lock_guard<std::mutex> lock(mutex_tasks);
for (auto& multitask : queue_multitasks)
{
if (multitask.id == multitask_id)
{
multitask.subtasks_remaining.erase(subtask_id);
multitask.results.push_back(result);
}
}
}
};
struct llama_server_response {
typedef std::function<void(int, int, task_result&)> callback_multitask_t;
callback_multitask_t callback_update_multitask;
// for keeping track of all tasks waiting for the result
std::set<int> waiting_task_ids;
// the main result queue
std::vector<task_result> queue_results;
std::mutex mutex_results;
std::condition_variable condition_results;
// add the task_id to the list of tasks waiting for response
void add_waiting_task_id(int task_id) {
LOG_VERBOSE("waiting for task id", {{"task_id", task_id}});
std::unique_lock<std::mutex> lock(mutex_results);
waiting_task_ids.insert(task_id);
}
// when the request is finished, we can remove task associated with it
void remove_waiting_task_id(int task_id) {
LOG_VERBOSE("remove waiting for task id", {{"task_id", task_id}});
std::unique_lock<std::mutex> lock(mutex_results);
waiting_task_ids.erase(task_id);
}
// This function blocks the thread until there is a response for this task_id
task_result recv(int task_id) {
while (true)
{
std::unique_lock<std::mutex> lock(mutex_results);
condition_results.wait(lock, [&]{
return !queue_results.empty();
});
for (int i = 0; i < (int) queue_results.size(); i++)
{
if (queue_results[i].id == task_id)
{
assert(queue_results[i].multitask_id == -1);
task_result res = queue_results[i];
queue_results.erase(queue_results.begin() + i);
return res;
}
}
}
// should never reach here
}
// Register the function to update multitask
void on_multitask_update(callback_multitask_t callback) {
callback_update_multitask = callback;
}
// Send a new result to a waiting task_id
void send(task_result result) {
std::unique_lock<std::mutex> lock(mutex_results);
LOG_VERBOSE("send new result", {{"task_id", result.id}});
for (auto& task_id : waiting_task_ids) {
// LOG_TEE("waiting task id %i \n", task_id);
// for now, tasks that have associated parent multitasks just get erased once multitask picks up the result
if (result.multitask_id == task_id)
{
LOG_VERBOSE("callback_update_multitask", {{"task_id", task_id}});
callback_update_multitask(task_id, result.id, result);
continue;
}
if (result.id == task_id)
{
LOG_VERBOSE("queue_results.push_back", {{"task_id", task_id}});
queue_results.push_back(result);
condition_results.notify_all();
return;
}
}
}
};
//
// base64 utils (TODO: move to common in the future)
//
static const std::string base64_chars =
"ABCDEFGHIJKLMNOPQRSTUVWXYZ"
"abcdefghijklmnopqrstuvwxyz"
"0123456789+/";
static inline bool is_base64(uint8_t c)
{
return (isalnum(c) || (c == '+') || (c == '/'));
}
static inline std::vector<uint8_t> base64_decode(const std::string & encoded_string)
{
int i = 0;
int j = 0;
int in_ = 0;
int in_len = encoded_string.size();
uint8_t char_array_4[4];
uint8_t char_array_3[3];
std::vector<uint8_t> ret;
while (in_len-- && (encoded_string[in_] != '=') && is_base64(encoded_string[in_]))
{
char_array_4[i++] = encoded_string[in_]; in_++;
if (i == 4)
{
for (i = 0; i <4; i++)
{
char_array_4[i] = base64_chars.find(char_array_4[i]);
}
char_array_3[0] = ((char_array_4[0] ) << 2) + ((char_array_4[1] & 0x30) >> 4);
char_array_3[1] = ((char_array_4[1] & 0xf) << 4) + ((char_array_4[2] & 0x3c) >> 2);
char_array_3[2] = ((char_array_4[2] & 0x3) << 6) + char_array_4[3];
for (i = 0; (i < 3); i++)
{
ret.push_back(char_array_3[i]);
}
i = 0;
}
}
if (i)
{
for (j = i; j <4; j++)
{
char_array_4[j] = 0;
}
for (j = 0; j <4; j++)
{
char_array_4[j] = base64_chars.find(char_array_4[j]);
}
char_array_3[0] = ((char_array_4[0] ) << 2) + ((char_array_4[1] & 0x30) >> 4);
char_array_3[1] = ((char_array_4[1] & 0xf) << 4) + ((char_array_4[2] & 0x3c) >> 2);
char_array_3[2] = ((char_array_4[2] & 0x3) << 6) + char_array_4[3];
for (j = 0; (j < i - 1); j++)
{
ret.push_back(char_array_3[j]);
}
}
return ret;
}
//
// random string / id
//
static std::string random_string()
{
static const std::string str("0123456789ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz");
std::random_device rd;
std::mt19937 generator(rd());
std::string result(32, ' ');
for (int i = 0; i < 32; ++i) {
result[i] = str[generator() % str.size()];
}
return result;
}
static std::string gen_chatcmplid()
{
std::stringstream chatcmplid;
chatcmplid << "chatcmpl-" << random_string();
return chatcmplid.str();
}
//
// other common utils
//
static size_t common_part(const std::vector<llama_token> &a, const std::vector<llama_token> &b)
{
size_t i;
for (i = 0; i < a.size() && i < b.size() && a[i] == b[i]; i++)
{
}
return i;
}
static bool ends_with(const std::string &str, const std::string &suffix)
{
return str.size() >= suffix.size() &&
0 == str.compare(str.size() - suffix.size(), suffix.size(), suffix);
}
static size_t find_partial_stop_string(const std::string &stop,
const std::string &text)
{
if (!text.empty() && !stop.empty())
{
const char text_last_char = text.back();
for (int64_t char_index = stop.size() - 1; char_index >= 0; char_index--)
{
if (stop[char_index] == text_last_char)
{
const std::string current_partial = stop.substr(0, char_index + 1);
if (ends_with(text, current_partial))
{
return text.size() - char_index - 1;
}
}
}
}
return std::string::npos;
}
// TODO: reuse llama_detokenize
template <class Iter>
static std::string tokens_to_str(llama_context *ctx, Iter begin, Iter end)
{
std::string ret;
for (; begin != end; ++begin)
{
ret += llama_token_to_piece(ctx, *begin);
}
return ret;
}
// format incomplete utf-8 multibyte character for output
static std::string tokens_to_output_formatted_string(const llama_context *ctx, const llama_token token)
{
std::string out = token == -1 ? "" : llama_token_to_piece(ctx, token);
// if the size is 1 and first bit is 1, meaning it's a partial character
// (size > 1 meaning it's already a known token)
if (out.size() == 1 && (out[0] & 0x80) == 0x80)
{
std::stringstream ss;
ss << std::hex << (out[0] & 0xff);
std::string res(ss.str());
out = "byte: \\x" + res;
}
return out;
}
// convert a vector of completion_token_output to json
static json probs_vector_to_json(const llama_context *ctx, const std::vector<completion_token_output> &probs)
{
json out = json::array();
for (const auto &prob : probs)
{
json probs_for_token = json::array();
for (const auto &p : prob.probs)
{
std::string tok_str = tokens_to_output_formatted_string(ctx, p.tok);
probs_for_token.push_back(json
{
{"tok_str", tok_str},
{"prob", p.prob},
});
}
std::string tok_str = tokens_to_output_formatted_string(ctx, prob.tok);
out.push_back(json{
{"content", tok_str},
{"probs", probs_for_token},
});
}
return out;
}

View File

@@ -14,7 +14,7 @@ init_vars() {
LLAMACPP_DIR=../llama.cpp
CMAKE_DEFS=""
CMAKE_TARGETS="--target ext_server"
CMAKE_TARGETS="--target ollama_llama_server"
if echo "${CGO_CFLAGS}" | grep -- '-g' >/dev/null; then
CMAKE_DEFS="-DCMAKE_BUILD_TYPE=RelWithDebInfo -DCMAKE_VERBOSE_MAKEFILE=on -DLLAMA_GPROF=on -DLLAMA_SERVER_VERBOSE=on ${CMAKE_DEFS}"
else
@@ -39,7 +39,7 @@ init_vars() {
*)
;;
esac
if [ -z "${CMAKE_CUDA_ARCHITECTURES}" ] ; then
if [ -z "${CMAKE_CUDA_ARCHITECTURES}" ] ; then
CMAKE_CUDA_ARCHITECTURES="50;52;61;70;75;80"
fi
}
@@ -61,8 +61,8 @@ git_module_setup() {
apply_patches() {
# Wire up our CMakefile
if ! grep ollama ${LLAMACPP_DIR}/examples/server/CMakeLists.txt; then
echo 'include (../../../ext_server/CMakeLists.txt) # ollama' >>${LLAMACPP_DIR}/examples/server/CMakeLists.txt
if ! grep ollama ${LLAMACPP_DIR}/CMakeLists.txt; then
echo 'add_subdirectory(../ext_server ext_server) # ollama' >>${LLAMACPP_DIR}/CMakeLists.txt
fi
if [ -n "$(ls -A ../patches/*.diff)" ]; then
@@ -76,35 +76,29 @@ apply_patches() {
(cd ${LLAMACPP_DIR} && git apply ${patch})
done
fi
# Avoid duplicate main symbols when we link into the cgo binary
sed -e 's/int main(/int __main(/g' <${LLAMACPP_DIR}/examples/server/server.cpp >${LLAMACPP_DIR}/examples/server/server.cpp.tmp &&
mv ${LLAMACPP_DIR}/examples/server/server.cpp.tmp ${LLAMACPP_DIR}/examples/server/server.cpp
}
build() {
cmake -S ${LLAMACPP_DIR} -B ${BUILD_DIR} ${CMAKE_DEFS}
cmake --build ${BUILD_DIR} ${CMAKE_TARGETS} -j8
mkdir -p ${BUILD_DIR}/lib/
g++ -fPIC -g -shared -o ${BUILD_DIR}/lib/libext_server.${LIB_EXT} \
${GCC_ARCH} \
${WHOLE_ARCHIVE} ${BUILD_DIR}/examples/server/libext_server.a ${NO_WHOLE_ARCHIVE} \
${BUILD_DIR}/common/libcommon.a \
${BUILD_DIR}/libllama.a \
-Wl,-rpath,\$ORIGIN \
-lpthread -ldl -lm \
${EXTRA_LIBS}
}
compress_libs() {
compress() {
echo "Compressing payloads to reduce overall binary size..."
pids=""
rm -rf ${BUILD_DIR}/lib/*.${LIB_EXT}*.gz
for lib in ${BUILD_DIR}/lib/*.${LIB_EXT}* ; do
gzip -n --best -f ${lib} &
rm -rf ${BUILD_DIR}/bin/*.gz
for f in ${BUILD_DIR}/bin/* ; do
gzip -n --best -f ${f} &
pids+=" $!"
done
echo
# check for lib directory
if [ -d ${BUILD_DIR}/lib ]; then
for f in ${BUILD_DIR}/lib/* ; do
gzip -n --best -f ${f} &
pids+=" $!"
done
fi
echo
for pid in ${pids}; do
wait $pid
done
@@ -113,7 +107,7 @@ compress_libs() {
# Keep the local tree clean after we're done with the build
cleanup() {
(cd ${LLAMACPP_DIR}/examples/server/ && git checkout CMakeLists.txt server.cpp)
(cd ${LLAMACPP_DIR}/ && git checkout CMakeLists.txt)
if [ -n "$(ls -A ../patches/*.diff)" ]; then
for patch in ../patches/*.diff; do

View File

@@ -18,34 +18,31 @@ sign() {
fi
}
# bundle_metal bundles ggml-common.h and ggml-metal.metal into a single file
bundle_metal() {
grep -v '#include "ggml-common.h"' "${LLAMACPP_DIR}/ggml-metal.metal" | grep -v '#pragma once' > "${LLAMACPP_DIR}/ggml-metal.metal.temp"
echo '#define GGML_COMMON_IMPL_METAL' > "${LLAMACPP_DIR}/ggml-metal.metal"
cat "${LLAMACPP_DIR}/ggml-common.h" | grep -v '#pragma once' >> "${LLAMACPP_DIR}/ggml-metal.metal"
cat "${LLAMACPP_DIR}/ggml-metal.metal.temp" >> "${LLAMACPP_DIR}/ggml-metal.metal"
rm "${LLAMACPP_DIR}/ggml-metal.metal.temp"
}
cleanup_metal() {
(cd ${LLAMACPP_DIR} && git checkout ggml-metal.metal)
}
COMMON_DARWIN_DEFS="-DCMAKE_OSX_DEPLOYMENT_TARGET=11.0 -DCMAKE_SYSTEM_NAME=Darwin"
COMMON_DARWIN_DEFS="-DCMAKE_OSX_DEPLOYMENT_TARGET=11.0 -DCMAKE_SYSTEM_NAME=Darwin -DLLAMA_METAL_EMBED_LIBRARY=on"
case "${GOARCH}" in
"amd64")
COMMON_CPU_DEFS="${COMMON_DARWIN_DEFS} -DCMAKE_SYSTEM_PROCESSOR=${ARCH} -DCMAKE_OSX_ARCHITECTURES=${ARCH} -DLLAMA_METAL=off -DLLAMA_NATIVE=off"
# Static build for linking into the Go binary
init_vars
CMAKE_TARGETS="--target llama --target ggml"
CMAKE_DEFS="${COMMON_CPU_DEFS} -DBUILD_SHARED_LIBS=off -DLLAMA_ACCELERATE=off -DLLAMA_AVX=off -DLLAMA_AVX2=off -DLLAMA_AVX512=off -DLLAMA_FMA=off -DLLAMA_F16C=off ${CMAKE_DEFS}"
BUILD_DIR="../build/darwin/${ARCH}_static"
echo "Building static library"
build
#
# CPU first for the default library, set up as lowest common denominator for maximum compatibility (including Rosetta)
#
init_vars
CMAKE_DEFS="${COMMON_CPU_DEFS} -DLLAMA_ACCELERATE=off -DLLAMA_AVX=off -DLLAMA_AVX2=off -DLLAMA_AVX512=off -DLLAMA_FMA=off -DLLAMA_F16C=off ${CMAKE_DEFS}"
BUILD_DIR="${LLAMACPP_DIR}/build/darwin/${ARCH}/cpu"
BUILD_DIR="../build/darwin/${ARCH}/cpu"
echo "Building LCD CPU"
build
sign ${LLAMACPP_DIR}/build/darwin/${ARCH}/cpu/lib/libext_server.dylib
compress_libs
sign ${BUILD_DIR}/lib/libext_server.dylib
compress
#
# ~2011 CPU Dynamic library with more capabilities turned on to optimize performance
@@ -53,11 +50,11 @@ case "${GOARCH}" in
#
init_vars
CMAKE_DEFS="${COMMON_CPU_DEFS} -DLLAMA_ACCELERATE=off -DLLAMA_AVX=on -DLLAMA_AVX2=off -DLLAMA_AVX512=off -DLLAMA_FMA=off -DLLAMA_F16C=off ${CMAKE_DEFS}"
BUILD_DIR="${LLAMACPP_DIR}/build/darwin/${ARCH}/cpu_avx"
BUILD_DIR="../build/darwin/${ARCH}/cpu_avx"
echo "Building AVX CPU"
build
sign ${LLAMACPP_DIR}/build/darwin/${ARCH}/cpu_avx/lib/libext_server.dylib
compress_libs
sign ${BUILD_DIR}/lib/libext_server.dylib
compress
#
# ~2013 CPU Dynamic library
@@ -65,22 +62,30 @@ case "${GOARCH}" in
#
init_vars
CMAKE_DEFS="${COMMON_CPU_DEFS} -DLLAMA_ACCELERATE=on -DLLAMA_AVX=on -DLLAMA_AVX2=on -DLLAMA_AVX512=off -DLLAMA_FMA=on -DLLAMA_F16C=on ${CMAKE_DEFS}"
BUILD_DIR="${LLAMACPP_DIR}/build/darwin/${ARCH}/cpu_avx2"
BUILD_DIR="../build/darwin/${ARCH}/cpu_avx2"
echo "Building AVX2 CPU"
EXTRA_LIBS="${EXTRA_LIBS} -framework Accelerate -framework Foundation"
build
sign ${LLAMACPP_DIR}/build/darwin/${ARCH}/cpu_avx2/lib/libext_server.dylib
compress_libs
sign ${BUILD_DIR}/lib/libext_server.dylib
compress
;;
"arm64")
CMAKE_DEFS="${COMMON_DARWIN_DEFS} -DLLAMA_METAL_EMBED_LIBRARY=on -DLLAMA_ACCELERATE=on -DCMAKE_SYSTEM_PROCESSOR=${ARCH} -DCMAKE_OSX_ARCHITECTURES=${ARCH} -DLLAMA_METAL=on ${CMAKE_DEFS}"
BUILD_DIR="${LLAMACPP_DIR}/build/darwin/${ARCH}/metal"
EXTRA_LIBS="${EXTRA_LIBS} -framework Accelerate -framework Foundation -framework Metal -framework MetalKit -framework MetalPerformanceShaders"
bundle_metal
# Static build for linking into the Go binary
init_vars
CMAKE_TARGETS="--target llama --target ggml"
CMAKE_DEFS="${COMMON_CPU_DEFS} -DBUILD_SHARED_LIBS=off -DLLAMA_ACCELERATE=off -DLLAMA_AVX=off -DLLAMA_AVX2=off -DLLAMA_AVX512=off -DLLAMA_FMA=off -DLLAMA_F16C=off ${CMAKE_DEFS}"
BUILD_DIR="../build/darwin/${ARCH}_static"
echo "Building static library"
build
sign ${LLAMACPP_DIR}/build/darwin/${ARCH}/metal/lib/libext_server.dylib
compress_libs
cleanup_metal
init_vars
CMAKE_DEFS="${COMMON_DARWIN_DEFS} -DLLAMA_METAL_EMBED_LIBRARY=on -DLLAMA_ACCELERATE=on -DCMAKE_SYSTEM_PROCESSOR=${ARCH} -DCMAKE_OSX_ARCHITECTURES=${ARCH} -DLLAMA_METAL=on ${CMAKE_DEFS}"
BUILD_DIR="../build/darwin/${ARCH}/metal"
EXTRA_LIBS="${EXTRA_LIBS} -framework Accelerate -framework Foundation -framework Metal -framework MetalKit -framework MetalPerformanceShaders"
build
sign ${BUILD_DIR}/lib/libext_server.dylib
compress
;;
*)
echo "GOARCH must be set"
@@ -90,3 +95,4 @@ case "${GOARCH}" in
esac
cleanup
echo "go generate completed. LLM runners: $(cd ${BUILD_DIR}/..; echo *)"

View File

@@ -26,6 +26,9 @@ amdGPUs() {
"gfx908:xnack-"
"gfx90a:xnack+"
"gfx90a:xnack-"
"gfx940"
"gfx941"
"gfx942"
"gfx1010"
"gfx1012"
"gfx1030"
@@ -54,16 +57,31 @@ init_vars
git_module_setup
apply_patches
init_vars
if [ -z "${OLLAMA_SKIP_CPU_GENERATE}" ]; then
if [ -z "${OLLAMA_CPU_TARGET}" -o "${OLLAMA_CPU_TARGET}" = "static" ]; then
# Static build for linking into the Go binary
init_vars
CMAKE_TARGETS="--target llama --target ggml"
CMAKE_DEFS="-DBUILD_SHARED_LIBS=off -DLLAMA_NATIVE=off -DLLAMA_AVX=off -DLLAMA_AVX2=off -DLLAMA_AVX512=off -DLLAMA_FMA=off -DLLAMA_F16C=off ${CMAKE_DEFS}"
BUILD_DIR="../build/linux/${ARCH}_static"
echo "Building static library"
build
fi
# Users building from source can tune the exact flags we pass to cmake for configuring
# llama.cpp, and we'll build only 1 CPU variant in that case as the default.
if [ -n "${OLLAMA_CUSTOM_CPU_DEFS}" ]; then
init_vars
echo "OLLAMA_CUSTOM_CPU_DEFS=\"${OLLAMA_CUSTOM_CPU_DEFS}\""
CMAKE_DEFS="${OLLAMA_CUSTOM_CPU_DEFS} -DCMAKE_POSITION_INDEPENDENT_CODE=on ${CMAKE_DEFS}"
BUILD_DIR="${LLAMACPP_DIR}/build/linux/${ARCH}/cpu"
BUILD_DIR="../build/linux/${ARCH}/cpu"
echo "Building custom CPU"
build
compress_libs
compress
else
# Darwin Rosetta x86 emulation does NOT support AVX, AVX2, AVX512
# -DLLAMA_AVX -- 2011 Intel Sandy Bridge & AMD Bulldozer
@@ -80,37 +98,43 @@ if [ -z "${OLLAMA_SKIP_CPU_GENERATE}" ]; then
#
# CPU first for the default library, set up as lowest common denominator for maximum compatibility (including Rosetta)
#
init_vars
CMAKE_DEFS="${COMMON_CPU_DEFS} -DLLAMA_AVX=off -DLLAMA_AVX2=off -DLLAMA_AVX512=off -DLLAMA_FMA=off -DLLAMA_F16C=off ${CMAKE_DEFS}"
BUILD_DIR="${LLAMACPP_DIR}/build/linux/${ARCH}/cpu"
BUILD_DIR="../build/linux/${ARCH}/cpu"
echo "Building LCD CPU"
build
compress_libs
compress
fi
if [ -z "${OLLAMA_CPU_TARGET}" -o "${OLLAMA_CPU_TARGET}" = "cpu_avx" ]; then
if [ "${ARCH}" == "x86_64" ]; then
#
# ~2011 CPU Dynamic library with more capabilities turned on to optimize performance
# Approximately 400% faster than LCD on same CPU
# ARM chips in M1/M2/M3-based MACs and NVidia Tegra devices do not currently support avx extensions.
#
init_vars
CMAKE_DEFS="${COMMON_CPU_DEFS} -DLLAMA_AVX=on -DLLAMA_AVX2=off -DLLAMA_AVX512=off -DLLAMA_FMA=off -DLLAMA_F16C=off ${CMAKE_DEFS}"
BUILD_DIR="${LLAMACPP_DIR}/build/linux/${ARCH}/cpu_avx"
echo "Building AVX CPU"
build
compress_libs
fi
if [ -z "${OLLAMA_CPU_TARGET}" -o "${OLLAMA_CPU_TARGET}" = "cpu_avx" ]; then
#
# ~2011 CPU Dynamic library with more capabilities turned on to optimize performance
# Approximately 400% faster than LCD on same CPU
#
init_vars
CMAKE_DEFS="${COMMON_CPU_DEFS} -DLLAMA_AVX=on -DLLAMA_AVX2=off -DLLAMA_AVX512=off -DLLAMA_FMA=off -DLLAMA_F16C=off ${CMAKE_DEFS}"
BUILD_DIR="../build/linux/${ARCH}/cpu_avx"
echo "Building AVX CPU"
build
compress
fi
if [ -z "${OLLAMA_CPU_TARGET}" -o "${OLLAMA_CPU_TARGET}" = "cpu_avx2" ]; then
#
# ~2013 CPU Dynamic library
# Approximately 10% faster than AVX on same CPU
#
init_vars
CMAKE_DEFS="${COMMON_CPU_DEFS} -DLLAMA_AVX=on -DLLAMA_AVX2=on -DLLAMA_AVX512=off -DLLAMA_FMA=on -DLLAMA_F16C=on ${CMAKE_DEFS}"
BUILD_DIR="${LLAMACPP_DIR}/build/linux/${ARCH}/cpu_avx2"
echo "Building AVX2 CPU"
build
compress_libs
if [ -z "${OLLAMA_CPU_TARGET}" -o "${OLLAMA_CPU_TARGET}" = "cpu_avx2" ]; then
#
# ~2013 CPU Dynamic library
# Approximately 10% faster than AVX on same CPU
#
init_vars
CMAKE_DEFS="${COMMON_CPU_DEFS} -DLLAMA_AVX=on -DLLAMA_AVX2=on -DLLAMA_AVX512=off -DLLAMA_FMA=on -DLLAMA_F16C=on ${CMAKE_DEFS}"
BUILD_DIR="../build/linux/${ARCH}/cpu_avx2"
echo "Building AVX2 CPU"
build
compress
fi
fi
fi
else
@@ -139,29 +163,38 @@ if [ -d "${CUDA_LIB_DIR}" ]; then
if [ -n "${CUDA_MAJOR}" ]; then
CUDA_VARIANT=_v${CUDA_MAJOR}
fi
CMAKE_DEFS="-DLLAMA_CUBLAS=on -DLLAMA_CUDA_FORCE_MMQ=on -DCMAKE_CUDA_ARCHITECTURES=${CMAKE_CUDA_ARCHITECTURES} ${COMMON_CMAKE_DEFS} ${CMAKE_DEFS}"
BUILD_DIR="${LLAMACPP_DIR}/build/linux/${ARCH}/cuda${CUDA_VARIANT}"
if [ "${ARCH}" == "arm64" ]; then
echo "ARM CPU detected - disabling unsupported AVX instructions"
# ARM-based CPUs such as M1 and Tegra do not support AVX extensions.
#
# CUDA compute < 6.0 lacks proper FP16 support on ARM.
# Disabling has minimal performance effect while maintaining compatibility.
ARM64_DEFS="-DLLAMA_AVX=off -DLLAMA_AVX2=off -DLLAMA_AVX512=off -DLLAMA_CUDA_F16=off"
fi
CMAKE_DEFS="-DLLAMA_CUBLAS=on -DLLAMA_CUDA_FORCE_MMQ=on -DCMAKE_CUDA_ARCHITECTURES=${CMAKE_CUDA_ARCHITECTURES} ${COMMON_CMAKE_DEFS} ${CMAKE_DEFS} ${ARM64_DEFS}"
BUILD_DIR="../build/linux/${ARCH}/cuda${CUDA_VARIANT}"
EXTRA_LIBS="-L${CUDA_LIB_DIR} -lcudart -lcublas -lcublasLt -lcuda"
build
# Cary the CUDA libs as payloads to help reduce dependency burden on users
# Carry the CUDA libs as payloads to help reduce dependency burden on users
#
# TODO - in the future we may shift to packaging these separately and conditionally
# downloading them in the install script.
DEPS="$(ldd ${BUILD_DIR}/lib/libext_server.so )"
DEPS="$(ldd ${BUILD_DIR}/bin/ollama_llama_server )"
for lib in libcudart.so libcublas.so libcublasLt.so ; do
DEP=$(echo "${DEPS}" | grep ${lib} | cut -f1 -d' ' | xargs || true)
if [ -n "${DEP}" -a -e "${CUDA_LIB_DIR}/${DEP}" ]; then
cp "${CUDA_LIB_DIR}/${DEP}" "${BUILD_DIR}/lib/"
cp "${CUDA_LIB_DIR}/${DEP}" "${BUILD_DIR}/bin/"
elif [ -e "${CUDA_LIB_DIR}/${lib}.${CUDA_MAJOR}" ]; then
cp "${CUDA_LIB_DIR}/${lib}.${CUDA_MAJOR}" "${BUILD_DIR}/lib/"
cp "${CUDA_LIB_DIR}/${lib}.${CUDA_MAJOR}" "${BUILD_DIR}/bin/"
elif [ -e "${CUDART_LIB_DIR}/${lib}" ]; then
cp -d ${CUDART_LIB_DIR}/${lib}* "${BUILD_DIR}/lib/"
cp -d ${CUDART_LIB_DIR}/${lib}* "${BUILD_DIR}/bin/"
else
cp -d "${CUDA_LIB_DIR}/${lib}*" "${BUILD_DIR}/lib/"
cp -d "${CUDA_LIB_DIR}/${lib}*" "${BUILD_DIR}/bin/"
fi
done
compress_libs
compress
fi
@@ -184,17 +217,24 @@ if [ -d "${ROCM_PATH}" ]; then
fi
init_vars
CMAKE_DEFS="${COMMON_CMAKE_DEFS} ${CMAKE_DEFS} -DLLAMA_HIPBLAS=on -DCMAKE_C_COMPILER=$ROCM_PATH/llvm/bin/clang -DCMAKE_CXX_COMPILER=$ROCM_PATH/llvm/bin/clang++ -DAMDGPU_TARGETS=$(amdGPUs) -DGPU_TARGETS=$(amdGPUs)"
BUILD_DIR="${LLAMACPP_DIR}/build/linux/${ARCH}/rocm${ROCM_VARIANT}"
EXTRA_LIBS="-L${ROCM_PATH}/lib -L/opt/amdgpu/lib/x86_64-linux-gnu/ -Wl,-rpath,\$ORIGIN/../rocm/ -lhipblas -lrocblas -lamdhip64 -lrocsolver -lamd_comgr -lhsa-runtime64 -lrocsparse -ldrm -ldrm_amdgpu"
BUILD_DIR="../build/linux/${ARCH}/rocm${ROCM_VARIANT}"
EXTRA_LIBS="-L${ROCM_PATH}/lib -L/opt/amdgpu/lib/x86_64-linux-gnu/ -Wl,-rpath,\$ORIGIN/../../rocm/ -lhipblas -lrocblas -lamdhip64 -lrocsolver -lamd_comgr -lhsa-runtime64 -lrocsparse -ldrm -ldrm_amdgpu"
build
# Record the ROCM dependencies
rm -f "${BUILD_DIR}/lib/deps.txt"
touch "${BUILD_DIR}/lib/deps.txt"
for dep in $(ldd "${BUILD_DIR}/lib/libext_server.so" | grep "=>" | cut -f2 -d= | cut -f2 -d' ' | grep -e rocm -e amdgpu -e libtinfo ); do
echo "${dep}" >> "${BUILD_DIR}/lib/deps.txt"
rm -f "${BUILD_DIR}/bin/deps.txt"
touch "${BUILD_DIR}/bin/deps.txt"
for dep in $(ldd "${BUILD_DIR}/bin/ollama_llama_server" | grep "=>" | cut -f2 -d= | cut -f2 -d' ' | grep -e rocm -e amdgpu -e libtinfo ); do
echo "${dep}" >> "${BUILD_DIR}/bin/deps.txt"
done
compress_libs
# bomb out if for some reason we didn't get a few deps
if [ $(cat "${BUILD_DIR}/bin/deps.txt" | wc -l ) -lt 8 ] ; then
cat "${BUILD_DIR}/bin/deps.txt"
echo "ERROR: deps file short"
exit 1
fi
compress
fi
cleanup
echo "go generate completed. LLM runners: $(cd ${BUILD_DIR}/..; echo *)"

View File

@@ -13,6 +13,9 @@ function amdGPUs {
"gfx908:xnack-"
"gfx90a:xnack+"
"gfx90a:xnack-"
"gfx940"
"gfx941"
"gfx942"
"gfx1010"
"gfx1012"
"gfx1030"
@@ -24,19 +27,13 @@ function amdGPUs {
}
function init_vars {
# Verify the environment is a Developer Shell for MSVC 2019
write-host $env:VSINSTALLDIR
if (($env:VSINSTALLDIR -eq $null)) {
Write-Error "`r`nBUILD ERROR - YOUR DEVELOPMENT ENVIRONMENT IS NOT SET UP CORRECTLY`r`nTo build Ollama you must run from an MSVC Developer Shell`r`nSee .\docs\development.md for instructions to set up your dev environment"
exit 1
}
$script:SRC_DIR = $(resolve-path "..\..\")
$script:llamacppDir = "../llama.cpp"
$script:cmakeDefs = @(
"-DBUILD_SHARED_LIBS=on",
"-DLLAMA_NATIVE=off"
)
$script:cmakeTargets = @("ext_server")
$script:cmakeTargets = @("ollama_llama_server")
$script:ARCH = "amd64" # arm not yet supported.
if ($env:CGO_CFLAGS -contains "-g") {
$script:cmakeDefs += @("-DCMAKE_VERBOSE_MAKEFILE=on", "-DLLAMA_SERVER_VERBOSE=on", "-DCMAKE_BUILD_TYPE=RelWithDebInfo")
@@ -65,8 +62,12 @@ function init_vars {
} else {
$script:CMAKE_CUDA_ARCHITECTURES=$env:CMAKE_CUDA_ARCHITECTURES
}
# Note: 10 Windows Kit signtool crashes with GCP's plugin
${script:SignTool}="C:\Program Files (x86)\Windows Kits\8.1\bin\x64\signtool.exe"
# Note: Windows Kits 10 signtool crashes with GCP's plugin
if ($null -eq $env:SIGN_TOOL) {
${script:SignTool}="C:\Program Files (x86)\Windows Kits\8.1\bin\x64\signtool.exe"
} else {
${script:SignTool}=${env:SIGN_TOOL}
}
if ("${env:KEY_CONTAINER}") {
${script:OLLAMA_CERT}=$(resolve-path "${script:SRC_DIR}\ollama_inc.crt")
}
@@ -82,8 +83,8 @@ function git_module_setup {
function apply_patches {
# Wire up our CMakefile
if (!(Select-String -Path "${script:llamacppDir}/examples/server/CMakeLists.txt" -Pattern 'ollama')) {
Add-Content -Path "${script:llamacppDir}/examples/server/CMakeLists.txt" -Value 'include (../../../ext_server/CMakeLists.txt) # ollama'
if (!(Select-String -Path "${script:llamacppDir}/CMakeLists.txt" -Pattern 'ollama')) {
Add-Content -Path "${script:llamacppDir}/CMakeLists.txt" -Value 'add_subdirectory(../ext_server ext_server) # ollama'
}
# Apply temporary patches until fix is upstream
@@ -96,22 +97,15 @@ function apply_patches {
}
# Checkout each file
Set-Location -Path ${script:llamacppDir}
foreach ($file in $filePaths) {
git checkout $file
git -C "${script:llamacppDir}" checkout $file
}
}
# Apply each patch
foreach ($patch in $patches) {
Set-Location -Path ${script:llamacppDir}
git apply $patch.FullName
git -C "${script:llamacppDir}" apply $patch.FullName
}
# Avoid duplicate main symbols when we link into the cgo binary
$content = Get-Content -Path "${script:llamacppDir}/examples/server/server.cpp"
$content = $content -replace 'int main\(', 'int __main('
Set-Content -Path "${script:llamacppDir}/examples/server/server.cpp" -Value $content
}
function build {
@@ -119,26 +113,20 @@ function build {
& cmake --version
& cmake -S "${script:llamacppDir}" -B $script:buildDir $script:cmakeDefs
if ($LASTEXITCODE -ne 0) { exit($LASTEXITCODE)}
write-host "building with: cmake --build $script:buildDir --config $script:config ($script:cmakeTargets | ForEach-Object { "--target", $_ })"
write-host "building with: cmake --build $script:buildDir --config $script:config $($script:cmakeTargets | ForEach-Object { `"--target`", $_ })"
& cmake --build $script:buildDir --config $script:config ($script:cmakeTargets | ForEach-Object { "--target", $_ })
if ($LASTEXITCODE -ne 0) { exit($LASTEXITCODE)}
}
function install {
rm -ea 0 -recurse -force -path "${script:buildDir}/lib"
md "${script:buildDir}/lib" -ea 0 > $null
cp "${script:buildDir}/bin/${script:config}/ext_server.dll" "${script:buildDir}/lib"
cp "${script:buildDir}/bin/${script:config}/llama.dll" "${script:buildDir}/lib"
# Display the dll dependencies in the build log
if ($script:DUMPBIN -ne $null) {
& "$script:DUMPBIN" /dependents "${script:buildDir}/bin/${script:config}/ext_server.dll" | select-string ".dll"
# Rearrange output to be consistent between different generators
if ($null -ne ${script:config} -And (test-path -path "${script:buildDir}/bin/${script:config}" ) ) {
mv -force "${script:buildDir}/bin/${script:config}/*" "${script:buildDir}/bin/"
remove-item "${script:buildDir}/bin/${script:config}"
}
}
function sign {
if ("${env:KEY_CONTAINER}") {
write-host "Signing ${script:buildDir}/lib/*.dll"
foreach ($file in (get-childitem "${script:buildDir}/lib/*.dll")){
write-host "Signing ${script:buildDir}/bin/*.exe ${script:buildDir}/bin/*.dll"
foreach ($file in @(get-childitem "${script:buildDir}/bin/*.exe") + @(get-childitem "${script:buildDir}/bin/*.dll")){
& "${script:SignTool}" sign /v /fd sha256 /t http://timestamp.digicert.com /f "${script:OLLAMA_CERT}" `
/csp "Google Cloud KMS Provider" /kc "${env:KEY_CONTAINER}" $file
if ($LASTEXITCODE -ne 0) { exit($LASTEXITCODE)}
@@ -146,14 +134,20 @@ function sign {
}
}
function compress_libs {
function compress {
if ($script:GZIP -eq $null) {
write-host "gzip not installed, not compressing files"
return
}
write-host "Compressing binaries..."
$binaries = dir "${script:buildDir}/bin/*.exe"
foreach ($file in $binaries) {
& "$script:GZIP" --best -f $file
}
write-host "Compressing dlls..."
$libs = dir "${script:buildDir}/lib/*.dll"
foreach ($file in $libs) {
$binaries = dir "${script:buildDir}/bin/*.dll"
foreach ($file in $dlls) {
& "$script:GZIP" --best -f $file
}
}
@@ -168,14 +162,11 @@ function cleanup {
}
# Checkout each file
Set-Location -Path ${script:llamacppDir}
foreach ($file in $filePaths) {
git checkout $file
git -C "${script:llamacppDir}" checkout $file
}
git -C "${script:llamacppDir}" checkout CMakeLists.txt
}
Set-Location "${script:llamacppDir}/examples/server"
git checkout CMakeLists.txt server.cpp
}
init_vars
@@ -183,38 +174,56 @@ git_module_setup
apply_patches
# -DLLAMA_AVX -- 2011 Intel Sandy Bridge & AMD Bulldozer
# -DLLAMA_F16C -- 2012 Intel Ivy Bridge & AMD 2011 Bulldozer (No significant improvement over just AVX)
# -DLLAMA_AVX2 -- 2013 Intel Haswell & 2015 AMD Excavator / 2017 AMD Zen
# -DLLAMA_FMA (FMA3) -- 2013 Intel Haswell & 2012 AMD Piledriver
$script:commonCpuDefs = @("-DCMAKE_POSITION_INDEPENDENT_CODE=on")
init_vars
$script:cmakeDefs = $script:commonCpuDefs + @("-A", "x64", "-DLLAMA_AVX=off", "-DLLAMA_AVX2=off", "-DLLAMA_AVX512=off", "-DLLAMA_FMA=off", "-DLLAMA_F16C=off") + $script:cmakeDefs
$script:buildDir="${script:llamacppDir}/build/windows/${script:ARCH}/cpu"
write-host "Building LCD CPU"
build
install
sign
compress_libs
if ($null -eq ${env:OLLAMA_SKIP_CPU_GENERATE}) {
# GCC build for direct linking into the Go binary
init_vars
$script:cmakeDefs = $script:commonCpuDefs + @("-A", "x64", "-DLLAMA_AVX=on", "-DLLAMA_AVX2=off", "-DLLAMA_AVX512=off", "-DLLAMA_FMA=off", "-DLLAMA_F16C=off") + $script:cmakeDefs
$script:buildDir="${script:llamacppDir}/build/windows/${script:ARCH}/cpu_avx"
write-host "Building AVX CPU"
$script:cmakeTargets = @("llama", "ggml")
$script:cmakeDefs = @(
"-G", "MinGW Makefiles"
"-DBUILD_SHARED_LIBS=off",
"-DLLAMA_NATIVE=off",
"-DLLAMA_AVX=off",
"-DLLAMA_AVX2=off",
"-DLLAMA_AVX512=off",
"-DLLAMA_F16C=off",
"-DLLAMA_FMA=off")
$script:buildDir="../build/windows/${script:ARCH}_static"
write-host "Building static library"
build
install
sign
compress_libs
init_vars
$script:cmakeDefs = $script:commonCpuDefs + @("-A", "x64", "-DLLAMA_AVX=on", "-DLLAMA_AVX2=on", "-DLLAMA_AVX512=off", "-DLLAMA_FMA=on", "-DLLAMA_F16C=on") + $script:cmakeDefs
$script:buildDir="${script:llamacppDir}/build/windows/${script:ARCH}/cpu_avx2"
write-host "Building AVX2 CPU"
build
install
sign
compress_libs
# remaining llama.cpp builds use MSVC
init_vars
$script:cmakeDefs = $script:commonCpuDefs + @("-A", "x64", "-DLLAMA_AVX=off", "-DLLAMA_AVX2=off", "-DLLAMA_AVX512=off", "-DLLAMA_FMA=off", "-DLLAMA_F16C=off") + $script:cmakeDefs
$script:buildDir="../build/windows/${script:ARCH}/cpu"
write-host "Building LCD CPU"
build
sign
compress
init_vars
$script:cmakeDefs = $script:commonCpuDefs + @("-A", "x64", "-DLLAMA_AVX=on", "-DLLAMA_AVX2=off", "-DLLAMA_AVX512=off", "-DLLAMA_FMA=off", "-DLLAMA_F16C=off") + $script:cmakeDefs
$script:buildDir="../build/windows/${script:ARCH}/cpu_avx"
write-host "Building AVX CPU"
build
sign
compress
init_vars
$script:cmakeDefs = $script:commonCpuDefs + @("-A", "x64", "-DLLAMA_AVX=on", "-DLLAMA_AVX2=on", "-DLLAMA_AVX512=off", "-DLLAMA_FMA=on", "-DLLAMA_F16C=on") + $script:cmakeDefs
$script:buildDir="../build/windows/${script:ARCH}/cpu_avx2"
write-host "Building AVX2 CPU"
build
sign
compress
} else {
write-host "Skipping CPU generation step as requested"
}
if ($null -ne $script:CUDA_LIB_DIR) {
# Then build cuda as a dynamically loaded library
@@ -224,13 +233,11 @@ if ($null -ne $script:CUDA_LIB_DIR) {
$script:CUDA_VARIANT="_"+$script:CUDA_VERSION
}
init_vars
$script:buildDir="${script:llamacppDir}/build/windows/${script:ARCH}/cuda$script:CUDA_VARIANT"
$script:buildDir="../build/windows/${script:ARCH}/cuda$script:CUDA_VARIANT"
$script:cmakeDefs += @("-A", "x64", "-DLLAMA_CUBLAS=ON", "-DLLAMA_AVX=on", "-DLLAMA_AVX2=off", "-DCUDAToolkit_INCLUDE_DIR=$script:CUDA_INCLUDE_DIR", "-DCMAKE_CUDA_ARCHITECTURES=${script:CMAKE_CUDA_ARCHITECTURES}")
write-host "Building CUDA"
build
install
sign
compress_libs
compress
}
if ($null -ne $env:HIP_PATH) {
@@ -240,7 +247,7 @@ if ($null -ne $env:HIP_PATH) {
}
init_vars
$script:buildDir="${script:llamacppDir}/build/windows/${script:ARCH}/rocm$script:ROCM_VARIANT"
$script:buildDir="../build/windows/${script:ARCH}/rocm$script:ROCM_VARIANT"
$script:cmakeDefs += @(
"-G", "Ninja",
"-DCMAKE_C_COMPILER=clang.exe",
@@ -254,7 +261,7 @@ if ($null -ne $env:HIP_PATH) {
)
# Make sure the ROCm binary dir is first in the path
$env:PATH="$env:HIP_PATH\bin;$env:VSINSTALLDIR\Common7\IDE\CommonExtensions\Microsoft\CMake\Ninja;$env:PATH"
$env:PATH="$env:HIP_PATH\bin;$env:PATH"
# We have to clobber the LIB var from the developer shell for clang to work properly
$env:LIB=""
@@ -263,13 +270,13 @@ if ($null -ne $env:HIP_PATH) {
build
# Ninja doesn't prefix with config name
${script:config}=""
install
if ($null -ne $script:DUMPBIN) {
& "$script:DUMPBIN" /dependents "${script:buildDir}/bin/${script:config}/ext_server.dll" | select-string ".dll"
& "$script:DUMPBIN" /dependents "${script:buildDir}/bin/ollama_llama_server.exe" | select-string ".dll"
}
sign
compress_libs
compress
}
cleanup
write-host "`ngo generate completed"
write-host "`ngo generate completed. LLM runners: $(get-childitem -path ${script:SRC_DIR}\llm\build\windows\${script:ARCH})"

View File

@@ -1,3 +1,3 @@
package generate
//go:generate sh ./gen_darwin.sh
//go:generate bash ./gen_darwin.sh

View File

@@ -7,16 +7,18 @@ import (
"slices"
)
type ContainerGGLA struct {
type containerGGLA struct {
version uint32
}
func (c *ContainerGGLA) Name() string {
func (c *containerGGLA) Name() string {
return "ggla"
}
func (c *ContainerGGLA) Decode(rso *readSeekOffset) (model, error) {
binary.Read(rso, binary.LittleEndian, &c.version)
func (c *containerGGLA) Decode(rs io.ReadSeeker) (model, error) {
if err := binary.Read(rs, binary.LittleEndian, &c.version); err != nil {
return nil, err
}
switch c.version {
case 1:
@@ -24,58 +26,66 @@ func (c *ContainerGGLA) Decode(rso *readSeekOffset) (model, error) {
return nil, errors.New("invalid version")
}
model := newModelGGLA(c)
err := model.decode(rso)
model := newGGLA(c)
err := model.decode(rs)
return model, err
}
type ModelGGLA struct {
*ContainerGGLA
type ggla struct {
*containerGGLA
kv KV
tensors []Tensor
tensors []*Tensor
}
func newModelGGLA(container *ContainerGGLA) *ModelGGLA {
return &ModelGGLA{
ContainerGGLA: container,
func newGGLA(container *containerGGLA) *ggla {
return &ggla{
containerGGLA: container,
kv: make(KV),
}
}
func (m *ModelGGLA) decode(rso *readSeekOffset) error {
func (llm *ggla) KV() KV {
return llm.kv
}
func (llm *ggla) Tensors() []*Tensor {
return llm.tensors
}
func (llm *ggla) decode(rs io.ReadSeeker) error {
var r uint32
if err := binary.Read(rso, binary.LittleEndian, &r); err != nil {
if err := binary.Read(rs, binary.LittleEndian, &r); err != nil {
return err
}
m.kv["r"] = r
llm.kv["r"] = r
var alpha uint32
if err := binary.Read(rso, binary.LittleEndian, &alpha); err != nil {
if err := binary.Read(rs, binary.LittleEndian, &alpha); err != nil {
return err
}
m.kv["alpha"] = alpha
llm.kv["alpha"] = alpha
for {
var dims uint32
if err := binary.Read(rso, binary.LittleEndian, &dims); err != nil {
if err := binary.Read(rs, binary.LittleEndian, &dims); err != nil {
return err
}
var namesize uint32
if err := binary.Read(rso, binary.LittleEndian, &namesize); err != nil {
if err := binary.Read(rs, binary.LittleEndian, &namesize); err != nil {
return err
}
var t Tensor
if err := binary.Read(rso, binary.LittleEndian, &t.Kind); err != nil {
if err := binary.Read(rs, binary.LittleEndian, &t.Kind); err != nil {
return err
}
t.Shape = make([]uint64, dims)
for i := 0; uint32(i) < dims; i++ {
var shape32 uint32
if err := binary.Read(rso, binary.LittleEndian, &shape32); err != nil {
if err := binary.Read(rs, binary.LittleEndian, &shape32); err != nil {
return err
}
@@ -87,66 +97,32 @@ func (m *ModelGGLA) decode(rso *readSeekOffset) error {
slices.Reverse(t.Shape)
name := make([]byte, namesize)
if err := binary.Read(rso, binary.LittleEndian, &name); err != nil {
if err := binary.Read(rs, binary.LittleEndian, &name); err != nil {
return err
}
t.Name = string(name)
if _, err := rso.Seek((rso.offset+31)&-32, io.SeekStart); err != nil {
offset, err := rs.Seek(0, io.SeekCurrent)
if err != nil {
return err
}
t.Offset = uint64(rso.offset)
if _, err := rso.Seek(int64(t.Size()), io.SeekCurrent); err != nil {
if _, err := rs.Seek((offset+31)&-32, io.SeekStart); err != nil {
return err
}
m.tensors = append(m.tensors, t)
offset, err = rs.Seek(0, io.SeekCurrent)
if err != nil {
return err
}
t.Offset = uint64(offset)
if _, err := rs.Seek(int64(t.size()), io.SeekCurrent); err != nil {
return err
}
llm.tensors = append(llm.tensors, &t)
}
}
func (m *ModelGGLA) KV() KV {
return m.kv
}
func (m *ModelGGLA) Tensor() []Tensor {
return m.tensors
}
func (*ModelGGLA) ModelFamily() string {
return "ggla"
}
func (*ModelGGLA) ModelType() string {
panic("not implemented")
}
func (*ModelGGLA) FileType() string {
panic("not implemented")
}
func (*ModelGGLA) NumLayers() uint32 {
panic("not implemented")
}
func (*ModelGGLA) NumGQA() uint32 {
panic("not implemented")
}
func (*ModelGGLA) NumEmbed() uint32 {
panic("not implemented")
}
func (*ModelGGLA) NumHead() uint32 {
panic("not implemented")
}
func (*ModelGGLA) NumHeadKv() uint32 {
panic("not implemented")
}
func (*ModelGGLA) NumCtx() uint32 {
panic("not implemented")
}

View File

@@ -3,14 +3,24 @@ package llm
import (
"encoding/binary"
"errors"
"fmt"
"io"
"strings"
)
type GGML struct {
container
model
}
Size int64
func (ggml *GGML) LayerSize(prefix string) (n int64) {
for _, t := range ggml.Tensors() {
if strings.HasPrefix(t.Name, prefix) {
n += int64(t.size())
}
}
return
}
const (
@@ -90,20 +100,153 @@ func fileType(fileType uint32) string {
}
type model interface {
ModelFamily() string
ModelType() string
FileType() string
NumLayers() uint32
NumGQA() uint32
NumEmbed() uint32
NumHead() uint32
NumHeadKv() uint32
NumCtx() uint32
KV() KV
Tensors() []*Tensor
}
type KV map[string]any
func (kv KV) u64(key string) uint64 {
switch v := kv[key].(type) {
case uint64:
return v
case uint32:
return uint64(v)
case float64:
return uint64(v)
default:
return 0
}
}
func (kv KV) Architecture() string {
if s, ok := kv["general.architecture"].(string); ok {
return s
}
return "unknown"
}
func (kv KV) ParameterCount() uint64 {
return kv.u64("general.parameter_count")
}
func (kv KV) FileType() string {
if u64 := kv.u64("general.file_type"); u64 > 0 {
return fileType(uint32(u64))
}
return "unknown"
}
func (kv KV) BlockCount() uint64 {
return kv.u64(fmt.Sprintf("%s.block_count", kv.Architecture()))
}
func (kv KV) HeadCount() uint64 {
return kv.u64(fmt.Sprintf("%s.attention.head_count", kv.Architecture()))
}
func (kv KV) HeadCountKV() uint64 {
return kv.u64(fmt.Sprintf("%s.attention.head_count_kv", kv.Architecture()))
}
func (kv KV) GQA() uint64 {
if headCountKV := kv.HeadCountKV(); headCountKV > 0 {
return kv.HeadCount() / headCountKV
}
return 0
}
func (kv KV) EmbeddingLength() uint64 {
return kv.u64(fmt.Sprintf("%s.embedding_length", kv.Architecture()))
}
func (kv KV) ContextLength() uint64 {
return kv.u64(fmt.Sprintf("%s.context_length", kv.Architecture()))
}
type Tensor struct {
Name string `json:"name"`
Kind uint32 `json:"kind"`
Offset uint64 `json:"-"`
// Shape is the number of elements in each dimension
Shape []uint64 `json:"shape"`
io.WriterTo `json:"-"`
}
func (t Tensor) blockSize() uint64 {
switch {
case t.Kind < 2:
return 1
case t.Kind < 10:
return 32
default:
return 256
}
}
func (t Tensor) typeSize() uint64 {
blockSize := t.blockSize()
switch t.Kind {
case 0: // FP32
return 4
case 1: // FP16
return 2
case 2: // Q4_0
return 2 + blockSize/2
case 3: // Q4_1
return 2 + 2 + blockSize/2
case 6: // Q5_0
return 2 + 4 + blockSize/2
case 7: // Q5_1
return 2 + 2 + 4 + blockSize/2
case 8: // Q8_0
return 2 + blockSize
case 9: // Q8_1
return 4 + 4 + blockSize
case 10: // Q2_K
return blockSize/16 + blockSize/4 + 2 + 2
case 11: // Q3_K
return blockSize/8 + blockSize/4 + 12 + 2
case 12: // Q4_K
return 2 + 2 + 12 + blockSize/2
case 13: // Q5_K
return 2 + 2 + 12 + blockSize/8 + blockSize/2
case 14: // Q6_K
return blockSize/2 + blockSize/4 + blockSize/16 + 2
case 15: // Q8_K
return 2 + blockSize + 2*blockSize/16
case 16: // IQ2_XXS
return 2 + 2*blockSize/8
case 17: // IQ2_XS
return 2 + 2*blockSize/8 + blockSize/32
case 18: // IQ3_XXS
return 2 + 3*blockSize/8
default:
return 0
}
}
func (t Tensor) parameters() uint64 {
var count uint64 = 1
for _, n := range t.Shape {
count *= n
}
return count
}
func (t Tensor) size() uint64 {
return t.parameters() * t.typeSize() / t.blockSize()
}
type container interface {
Name() string
Decode(*readSeekOffset) (model, error)
Decode(io.ReadSeeker) (model, error)
}
const (
@@ -122,60 +265,41 @@ const (
var ErrUnsupportedFormat = errors.New("unsupported model format")
func DecodeGGML(r io.ReadSeeker) (*GGML, error) {
ro := readSeekOffset{ReadSeeker: r}
func DecodeGGML(rs io.ReadSeeker) (*GGML, int64, error) {
var magic uint32
if err := binary.Read(&ro, binary.LittleEndian, &magic); err != nil {
return nil, err
if err := binary.Read(rs, binary.LittleEndian, &magic); err != nil {
return nil, 0, err
}
var c container
switch magic {
case FILE_MAGIC_GGML, FILE_MAGIC_GGMF, FILE_MAGIC_GGJT:
return nil, ErrUnsupportedFormat
return nil, 0, ErrUnsupportedFormat
case FILE_MAGIC_GGLA:
c = &ContainerGGLA{}
c = &containerGGLA{}
case FILE_MAGIC_GGUF_LE:
c = &ContainerGGUF{ByteOrder: binary.LittleEndian}
c = &containerGGUF{ByteOrder: binary.LittleEndian}
case FILE_MAGIC_GGUF_BE:
c = &ContainerGGUF{ByteOrder: binary.BigEndian}
c = &containerGGUF{ByteOrder: binary.BigEndian}
default:
return nil, errors.New("invalid file magic")
return nil, 0, errors.New("invalid file magic")
}
model, err := c.Decode(&ro)
model, err := c.Decode(rs)
if errors.Is(err, io.EOF) {
// noop
} else if err != nil {
return nil, err
return nil, 0, err
}
offset, err := rs.Seek(0, io.SeekCurrent)
if err != nil {
return nil, 0, err
}
// final model type
return &GGML{
container: c,
model: model,
Size: ro.offset,
}, nil
}
type readSeekOffset struct {
io.ReadSeeker
offset int64
}
func (rso *readSeekOffset) Seek(offset int64, whence int) (int64, error) {
offset, err := rso.ReadSeeker.Seek(offset, whence)
if err != nil {
return 0, err
}
rso.offset = offset
return offset, nil
}
func (rso *readSeekOffset) Read(p []byte) (int, error) {
n, err := rso.ReadSeeker.Read(p)
rso.offset += int64(n)
return n, err
}, offset, nil
}

View File

File diff suppressed because it is too large Load Diff

View File

@@ -1,100 +0,0 @@
package llm
import (
_ "embed"
"fmt"
"time"
"github.com/jmorganca/ollama/api"
)
const jsonGrammar = `
root ::= object
value ::= object | array | string | number | ("true" | "false" | "null") ws
object ::=
"{" ws (
string ":" ws value
("," ws string ":" ws value)*
)? "}" ws
array ::=
"[" ws (
value
("," ws value)*
)? "]" ws
string ::=
"\"" (
[^"\\] |
"\\" (["\\/bfnrt] | "u" [0-9a-fA-F] [0-9a-fA-F] [0-9a-fA-F] [0-9a-fA-F]) # escapes
)* "\"" ws
number ::= ("-"? ([0-9] | [1-9] [0-9]*)) ("." [0-9]+)? ([eE] [-+]? [0-9]+)? ws
# Optional space: by convention, applied in this grammar after literal chars when allowed
ws ::= ([ \t\n] ws)?
`
type ImageData struct {
Data []byte `json:"data"`
ID int `json:"id"`
}
var payloadMissing = fmt.Errorf("expected dynamic library payloads not included in this build of ollama")
type prediction struct {
Content string `json:"content"`
Model string `json:"model"`
Prompt string `json:"prompt"`
Stop bool `json:"stop"`
Timings struct {
PredictedN int `json:"predicted_n"`
PredictedMS float64 `json:"predicted_ms"`
PromptN int `json:"prompt_n"`
PromptMS float64 `json:"prompt_ms"`
}
}
const maxRetries = 3
type PredictOpts struct {
Prompt string
Format string
Images []ImageData
Options api.Options
}
type PredictResult struct {
Content string
Done bool
PromptEvalCount int
PromptEvalDuration time.Duration
EvalCount int
EvalDuration time.Duration
}
type TokenizeRequest struct {
Content string `json:"content"`
}
type TokenizeResponse struct {
Tokens []int `json:"tokens"`
}
type DetokenizeRequest struct {
Tokens []int `json:"tokens"`
}
type DetokenizeResponse struct {
Content string `json:"content"`
}
type EmbeddingRequest struct {
Content string `json:"content"`
}
type EmbeddingResponse struct {
Embedding []float64 `json:"embedding"`
}

View File

@@ -1,175 +1,15 @@
package llm
import (
"context"
"fmt"
"log/slog"
"os"
"runtime"
"slices"
// #cgo CFLAGS: -Illama.cpp
// #cgo darwin,arm64 LDFLAGS: ${SRCDIR}/build/darwin/arm64_static/libllama.a -lstdc++
// #cgo darwin,amd64 LDFLAGS: ${SRCDIR}/build/darwin/x86_64_static/libllama.a -lstdc++
// #cgo windows,amd64 LDFLAGS: ${SRCDIR}/build/windows/amd64_static/libllama.a -static -lstdc++
// #cgo linux,amd64 LDFLAGS: ${SRCDIR}/build/linux/x86_64_static/libllama.a -lstdc++
// #cgo linux,arm64 LDFLAGS: ${SRCDIR}/build/linux/arm64_static/libllama.a -lstdc++
// #include "llama.h"
import "C"
"github.com/jmorganca/ollama/api"
"github.com/jmorganca/ollama/gpu"
)
type LLM interface {
Predict(context.Context, PredictOpts, func(PredictResult)) error
Embedding(context.Context, string) ([]float64, error)
Encode(context.Context, string) ([]int, error)
Decode(context.Context, []int) (string, error)
Close()
}
var cpuOnlyFamilies = []string{
"mamba",
}
func New(model string, adapters, projectors []string, opts api.Options) (LLM, error) {
if _, err := os.Stat(model); err != nil {
return nil, err
}
f, err := os.Open(model)
if err != nil {
return nil, err
}
defer f.Close()
ggml, err := DecodeGGML(f)
if err != nil {
return nil, err
}
if opts.NumCtx > int(ggml.NumCtx()) {
slog.Warn(fmt.Sprintf("requested context length is greater than model's max context length (%d > %d), using %d instead", opts.NumCtx, ggml.NumCtx(), ggml.NumCtx()))
opts.NumCtx = int(ggml.NumCtx())
}
if opts.NumCtx < 4 {
opts.NumCtx = 4
}
vram, _ := gpu.CheckVRAM()
size := ggml.Size
// fp16 k,v matrices require = n_ctx * n_layer * n_embd / n_head * n_head_kv * 2 bytes each * 2 key and value
kv := 2 * 2 * int64(opts.NumCtx) * int64(ggml.NumLayers()) * int64(ggml.NumEmbed()) * int64(ggml.NumHeadKv()) / int64(max(ggml.NumHead(), 1))
// this amount is the overhead + tensors in memory
// TODO: get this from the llama.cpp's graph calculations instead of
// estimating it's 1/6 * kv_cache_size * num_gqa
graph := int64(ggml.NumGQA()) * kv / 6
// certain model architectures don't support gpu inference yet
if slices.Contains(cpuOnlyFamilies, ggml.ModelFamily()) {
opts.NumGPU = 0
}
info := gpu.GetGPUInfo()
switch runtime.GOOS {
case "darwin":
if opts.NumGPU == 0 {
break
}
if size+kv+graph > vram {
slog.Info("not enough vram available, setting num_gpu=0")
opts.NumGPU = 0
break
}
// TODO: implement layer splitting on macOS
opts.NumGPU = 999
default:
if info.Library == "cpu" {
slog.Info("GPU not available, falling back to CPU")
opts.NumGPU = 0
break
}
// don't use GPU at all if no layers are loaded
if opts.NumGPU == 0 {
info.Library = "cpu"
info.Variant = gpu.GetCPUVariant()
break
}
// user-defined GPU count
if opts.NumGPU != -1 {
break
}
// the "main" GPU needs the most memory and determines the limit
// of how many layers can be loaded. It needs to fit:
// 1. the full compute graph allocation for all devices (graph)
// 2. the proportional kv cache for all devices (kv * % layers)
// 3. the proportional model (size * % layers / # devices)
// This estimates the number of layers
maxlayers := int64(ggml.NumLayers()) + 1
devices := int64(info.DeviceCount)
avg := vram / devices
layers := maxlayers * (avg - graph) / (kv + size/devices)
if layers > maxlayers {
layers = maxlayers
}
// 1 + 2 must fit on the main gpu
min := graph + kv*layers/maxlayers
if layers <= 0 || min > avg {
slog.Info("not enough vram available, falling back to CPU only")
info.Library = "cpu"
info.Variant = gpu.GetCPUVariant()
opts.NumGPU = 0
break
}
opts.NumGPU = int(layers)
}
opts.RopeFrequencyBase = 0.0
opts.RopeFrequencyScale = 0.0
return newLlmServer(info, model, adapters, projectors, opts)
}
// Give any native cgo implementations an opportunity to initialize
func Init() error {
return nativeInit()
}
func newLlmServer(gpuInfo gpu.GpuInfo, model string, adapters, projectors []string, opts api.Options) (LLM, error) {
dynLibs := getDynLibs(gpuInfo)
// Check to see if the user has requested a specific library instead of auto-detecting
demandLib := os.Getenv("OLLAMA_LLM_LIBRARY")
if demandLib != "" {
libPath := availableDynLibs[demandLib]
if libPath == "" {
slog.Info(fmt.Sprintf("Invalid OLLAMA_LLM_LIBRARY %s - not found", demandLib))
} else {
slog.Info(fmt.Sprintf("Loading OLLAMA_LLM_LIBRARY=%s", demandLib))
dynLibs = []string{libPath}
}
}
// We stage into a temp directory, and if we've been idle for a while, it may have been reaped
_, err := os.Stat(dynLibs[0])
if err != nil {
slog.Info(fmt.Sprintf("%s has disappeared, reloading libraries", dynLibs[0]))
err = nativeInit()
if err != nil {
return nil, err
}
}
err2 := fmt.Errorf("unable to locate suitable llm library")
for _, dynLib := range dynLibs {
srv, err := newDynExtServer(dynLib, model, adapters, projectors, opts)
if err == nil {
return srv, nil
}
slog.Warn(fmt.Sprintf("Failed to load dynamic library %s %s", dynLib, err))
err2 = err
}
return nil, err2
// SystemInfo is an unused example of calling llama.cpp functions using CGo
func SystemInfo() string {
return C.GoString(C.llama_print_system_info())
}

View File

@@ -4,5 +4,5 @@ import (
"embed"
)
//go:embed llama.cpp/build/linux/*/*/lib/*
//go:embed build/darwin/x86_64/*/bin/*
var libEmbed embed.FS

View File

@@ -4,5 +4,5 @@ import (
"embed"
)
//go:embed llama.cpp/build/windows/*/*/lib/*.dll*
//go:embed build/darwin/arm64/*/bin/*
var libEmbed embed.FS

6
llm/llm_linux.go Normal file
View File

@@ -0,0 +1,6 @@
package llm
import "embed"
//go:embed build/linux/*/*/bin/*
var libEmbed embed.FS

6
llm/llm_windows.go Normal file
View File

@@ -0,0 +1,6 @@
package llm
import "embed"
//go:embed build/windows/*/*/bin/*
var libEmbed embed.FS

View File

@@ -1,19 +0,0 @@
diff --git a/examples/server/server.cpp b/examples/server/server.cpp
index f255ad76..914ecfdd 100644
--- a/examples/server/server.cpp
+++ b/examples/server/server.cpp
@@ -1101,12 +1101,13 @@ struct server_context {
// add the token to slot queue and cache
}
- slot.add_token_string(result);
if (slot.params.stream) {
send_partial_response(slot, result);
}
}
+ slot.add_token_string(result);
+
if (incomplete) {
slot.has_next_token = true;
}

View File

@@ -1,116 +0,0 @@
diff --git a/examples/server/server.cpp b/examples/server/server.cpp
index b14cca61..02bfd4b1 100644
--- a/examples/server/server.cpp
+++ b/examples/server/server.cpp
@@ -29,6 +29,10 @@
#include <signal.h>
#include <memory>
+#ifdef GGML_USE_CUBLAS
+extern "C" GGML_CALL void ggml_free_cublas(void);
+#endif
+
using json = nlohmann::json;
bool server_verbose = false;
@@ -664,6 +668,10 @@ struct server_context {
llama_free_model(model);
model = nullptr;
}
+
+#ifdef GGML_USE_CUBLAS
+ ggml_free_cublas();
+#endif
}
bool load_model(const gpt_params & params_) {
@@ -3499,6 +3507,7 @@ int main(int argc, char ** argv) {
sigemptyset (&sigint_action.sa_mask);
sigint_action.sa_flags = 0;
sigaction(SIGINT, &sigint_action, NULL);
+ sigaction(SIGUSR1, &sigint_action, NULL);
#elif defined (_WIN32)
auto console_ctrl_handler = +[](DWORD ctrl_type) -> BOOL {
return (ctrl_type == CTRL_C_EVENT) ? (signal_handler(SIGINT), true) : false;
diff --git a/ggml-cuda.cu b/ggml-cuda.cu
index c207ff87..945708a4 100644
--- a/ggml-cuda.cu
+++ b/ggml-cuda.cu
@@ -46,6 +46,7 @@
#define __shfl_xor_sync(mask, var, laneMask, width) __shfl_xor(var, laneMask, width)
#define cublasComputeType_t hipblasDatatype_t //deprecated, new hipblasComputeType_t not in 5.6
#define cublasCreate hipblasCreate
+#define cublasDestroy hipblasDestroy
#define cublasGemmEx hipblasGemmEx
#define cublasGemmBatchedEx hipblasGemmBatchedEx
#define cublasGemmStridedBatchedEx hipblasGemmStridedBatchedEx
@@ -8014,10 +8015,10 @@ GGML_CALL bool ggml_cublas_loaded(void) {
return g_cublas_loaded;
}
-GGML_CALL void ggml_init_cublas() {
- static bool initialized = false;
+static bool g_cublas_initialized = false;
- if (!initialized) {
+GGML_CALL void ggml_init_cublas() {
+ if (!g_cublas_initialized) {
#ifdef __HIP_PLATFORM_AMD__
// Workaround for a rocBLAS bug when using multiple graphics cards:
@@ -8027,7 +8028,7 @@ GGML_CALL void ggml_init_cublas() {
#endif
if (cudaGetDeviceCount(&g_device_count) != cudaSuccess) {
- initialized = true;
+ g_cublas_initialized = true;
g_cublas_loaded = false;
fprintf(stderr, "%s: no " GGML_CUDA_NAME " devices found, " GGML_CUDA_NAME " will be disabled\n", __func__);
return;
@@ -8098,7 +8099,7 @@ GGML_CALL void ggml_init_cublas() {
// configure logging to stdout
// CUBLAS_CHECK(cublasLoggerConfigure(1, 1, 0, nullptr));
- initialized = true;
+ g_cublas_initialized = true;
g_cublas_loaded = true;
}
}
@@ -11753,3 +11754,23 @@ GGML_CALL int ggml_backend_cuda_reg_devices() {
}
return device_count;
}
+
+
+extern "C" GGML_CALL void ggml_free_cublas(void);
+GGML_CALL void ggml_free_cublas(void) {
+ for (int id = 0; id < g_device_count; ++id) {
+#if !(defined(GGML_USE_HIPBLAS) && defined(__HIP_PLATFORM_AMD__))
+ if (g_device_caps[id].vmm) {
+ CU_CHECK(cuMemUnmap(g_cuda_pool_addr[id], g_cuda_pool_size[id]));
+ g_cuda_pool_size[id] = 0;
+ g_cuda_pool_addr[id] = 0;
+ }
+#endif
+ // TODO: free legacy non-vmm memory
+ // destroy cublas handle
+ CUBLAS_CHECK(cublasDestroy(g_cublas_handles[id]));
+ g_cublas_handles[id] = nullptr;
+ }
+
+ g_cublas_initialized = false;
+}
diff --git a/ggml-cuda.h b/ggml-cuda.h
index b1ebd61d..6dd58ddf 100644
--- a/ggml-cuda.h
+++ b/ggml-cuda.h
@@ -23,6 +23,9 @@ GGML_API GGML_CALL void ggml_init_cublas(void);
// Returns `true` if there are available CUDA devices and cublas loads successfully; otherwise, it returns `false`.
GGML_API GGML_CALL bool ggml_cublas_loaded(void);
+// Release CUDA resources
+GGML_API GGML_CALL void ggml_free_cublas(void);
+
GGML_API GGML_CALL void * ggml_cuda_host_malloc(size_t size);
GGML_API GGML_CALL void ggml_cuda_host_free(void * ptr);

View File

@@ -0,0 +1,44 @@
diff --git a/llama.cpp b/llama.cpp
index 4225f955..7b762f86 100644
--- a/llama.cpp
+++ b/llama.cpp
@@ -4756,7 +4756,7 @@ static int llama_model_load(const std::string & fname, llama_model & model, llam
}
} catch (const std::exception & err) {
LLAMA_LOG_ERROR("%s: error loading model: %s\n", __func__, err.what());
- return -1;
+ throw;
}
return 0;
@@ -12102,16 +12102,22 @@ struct llama_model * llama_load_model_from_file(
};
}
- int status = llama_model_load(path_model, *model, params);
- GGML_ASSERT(status <= 0);
- if (status < 0) {
- if (status == -1) {
- LLAMA_LOG_ERROR("%s: failed to load model\n", __func__);
- } else if (status == -2) {
- LLAMA_LOG_INFO("%s: cancelled model load\n", __func__);
+ try {
+ int status = llama_model_load(path_model, *model, params);
+ GGML_ASSERT(status <= 0);
+ if (status < 0) {
+ if (status == -1) {
+ LLAMA_LOG_ERROR("%s: failed to load model\n", __func__);
+ } else if (status == -2) {
+ LLAMA_LOG_INFO("%s: cancelled model load\n", __func__);
+ }
+ delete model;
+ return nullptr;
}
+ } catch (...) {
+ LLAMA_LOG_ERROR("%s: exception loading model\n", __func__);
delete model;
- return nullptr;
+ throw;
}
return model;

View File

@@ -1,13 +0,0 @@
diff --git a/llama.cpp b/llama.cpp
index b19616e8..519b9602 100644
--- a/llama.cpp
+++ b/llama.cpp
@@ -9938,7 +9938,7 @@ struct llm_tokenizer_wpm {
}
uint32_t to_lower(uint32_t code) {
- static const std::locale locale("en_US.UTF-8");
+ static const std::locale locale("");
#if defined(_WIN32)
if (code > 0xFFFF) {
return code;

211
llm/payload.go Normal file
View File

@@ -0,0 +1,211 @@
package llm
import (
"compress/gzip"
"errors"
"fmt"
"io"
"io/fs"
"log/slog"
"os"
"path/filepath"
"strings"
"golang.org/x/exp/slices"
"golang.org/x/sync/errgroup"
"github.com/ollama/ollama/gpu"
)
var errPayloadMissing = fmt.Errorf("expected payloads not included in this build of ollama")
func Init() error {
payloadsDir, err := gpu.PayloadsDir()
if err != nil {
return err
}
slog.Info("extracting embedded files", "dir", payloadsDir)
binGlob := "build/*/*/*/bin/*"
// extract server libraries
err = extractFiles(payloadsDir, binGlob)
if err != nil {
return fmt.Errorf("extract binaries: %v", err)
}
var variants []string
for v := range availableServers() {
variants = append(variants, v)
}
slog.Info(fmt.Sprintf("Dynamic LLM libraries %v", variants))
slog.Debug("Override detection logic by setting OLLAMA_LLM_LIBRARY")
return nil
}
// binary names may contain an optional variant separated by '_'
// For example, "ollama_rocm_v6" and "ollama_rocm_v5" or "ollama_cpu" and "ollama_cpu_avx2"
// Any library without a variant is the lowest common denominator
func availableServers() map[string]string {
payloadsDir, err := gpu.PayloadsDir()
if err != nil {
slog.Error("payload lookup error", "error", err)
return nil
}
// glob payloadsDir for files that start with ollama_
pattern := filepath.Join(payloadsDir, "*")
files, err := filepath.Glob(pattern)
if err != nil {
slog.Debug("could not glob", "pattern", pattern, "error", err)
return nil
}
servers := make(map[string]string)
for _, file := range files {
slog.Debug("availableServers : found", "file", file)
servers[filepath.Base(file)] = file
}
return servers
}
// serversForGpu returns a list of compatible servers give the provided GPU
// info, ordered by performance. assumes Init() has been called
// TODO - switch to metadata based mapping
func serversForGpu(info gpu.GpuInfo) []string {
// glob workDir for files that start with ollama_
availableServers := availableServers()
requested := info.Library
if info.Variant != "" {
requested += "_" + info.Variant
}
servers := []string{}
// exact match first
for a := range availableServers {
if a == requested {
servers = []string{a}
if a == "metal" {
return servers
}
break
}
}
alt := []string{}
// Then for GPUs load alternates and sort the list for consistent load ordering
if info.Library != "cpu" {
for a := range availableServers {
if info.Library == strings.Split(a, "_")[0] && a != requested {
alt = append(alt, a)
}
}
slices.Sort(alt)
servers = append(servers, alt...)
}
// Load up the best CPU variant if not primary requested
if info.Library != "cpu" {
variant := gpu.GetCPUVariant()
// If no variant, then we fall back to default
// If we have a variant, try that if we find an exact match
// Attempting to run the wrong CPU instructions will panic the
// process
if variant != "" {
for cmp := range availableServers {
if cmp == "cpu_"+variant {
servers = append(servers, cmp)
break
}
}
} else {
servers = append(servers, "cpu")
}
}
if len(servers) == 0 {
servers = []string{"cpu"}
}
return servers
}
// extract extracts the embedded files to the target directory
func extractFiles(targetDir string, glob string) error {
files, err := fs.Glob(libEmbed, glob)
if err != nil || len(files) == 0 {
return errPayloadMissing
}
if err := os.MkdirAll(targetDir, 0o755); err != nil {
return fmt.Errorf("extractFiles could not mkdir %s: %v", targetDir, err)
}
g := new(errgroup.Group)
// build/$OS/$GOARCH/$VARIANT/{bin,lib}/$FILE
for _, file := range files {
filename := file
variant := filepath.Base(filepath.Dir(filepath.Dir(filename)))
slog.Debug("extracting", "variant", variant, "file", filename)
g.Go(func() error {
srcf, err := libEmbed.Open(filename)
if err != nil {
return err
}
defer srcf.Close()
src := io.Reader(srcf)
if strings.HasSuffix(filename, ".gz") {
src, err = gzip.NewReader(src)
if err != nil {
return fmt.Errorf("decompress payload %s: %v", filename, err)
}
filename = strings.TrimSuffix(filename, ".gz")
}
variantDir := filepath.Join(targetDir, variant)
if err := os.MkdirAll(variantDir, 0o755); err != nil {
return fmt.Errorf("extractFiles could not mkdir %s: %v", variantDir, err)
}
base := filepath.Base(filename)
destFilename := filepath.Join(variantDir, base)
_, err = os.Stat(destFilename)
switch {
case errors.Is(err, os.ErrNotExist):
destFile, err := os.OpenFile(destFilename, os.O_WRONLY|os.O_CREATE|os.O_TRUNC, 0o755)
if err != nil {
return fmt.Errorf("write payload %s: %v", filename, err)
}
defer destFile.Close()
if _, err := io.Copy(destFile, src); err != nil {
return fmt.Errorf("copy payload %s: %v", filename, err)
}
case err != nil:
return fmt.Errorf("stat payload %s: %v", filename, err)
}
return nil
})
}
err = g.Wait()
if err != nil {
// If we fail to extract, the payload dir is unusable, so cleanup whatever we extracted
gpu.Cleanup()
return err
}
return nil
}

View File

@@ -1,223 +0,0 @@
package llm
import (
"compress/gzip"
"errors"
"fmt"
"io"
"io/fs"
"log/slog"
"os"
"path/filepath"
"runtime"
"strings"
"golang.org/x/exp/slices"
"golang.org/x/sync/errgroup"
"github.com/jmorganca/ollama/gpu"
)
// Libraries names may contain an optional variant separated by '_'
// For example, "rocm_v6" and "rocm_v5" or "cpu" and "cpu_avx2"
// Any library without a variant is the lowest common denominator
var availableDynLibs = map[string]string{}
const pathComponentCount = 7
// getDynLibs returns an ordered list of LLM libraries to try, starting with the best
func getDynLibs(gpuInfo gpu.GpuInfo) []string {
// Short circuit if we know we're using the default built-in (darwin only)
if gpuInfo.Library == "default" {
return []string{"default"}
}
// TODO - temporary until we have multiple CPU variations for Darwin
// Short circuit on darwin with metal only
if len(availableDynLibs) == 1 {
if _, onlyMetal := availableDynLibs["metal"]; onlyMetal {
return []string{availableDynLibs["metal"]}
}
}
exactMatch := ""
dynLibs := []string{}
altDynLibs := []string{}
requested := gpuInfo.Library
if gpuInfo.Variant != "" {
requested += "_" + gpuInfo.Variant
}
// Try to find an exact match
for cmp := range availableDynLibs {
if requested == cmp {
exactMatch = cmp
dynLibs = []string{availableDynLibs[cmp]}
break
}
}
// Then for GPUs load alternates and sort the list for consistent load ordering
if gpuInfo.Library != "cpu" {
for cmp := range availableDynLibs {
if gpuInfo.Library == strings.Split(cmp, "_")[0] && cmp != exactMatch {
altDynLibs = append(altDynLibs, cmp)
}
}
slices.Sort(altDynLibs)
for _, altDynLib := range altDynLibs {
dynLibs = append(dynLibs, availableDynLibs[altDynLib])
}
}
// Load up the best CPU variant if not primary requested
if gpuInfo.Library != "cpu" {
variant := gpu.GetCPUVariant()
// If no variant, then we fall back to default
// If we have a variant, try that if we find an exact match
// Attempting to run the wrong CPU instructions will panic the
// process
if variant != "" {
for cmp := range availableDynLibs {
if cmp == "cpu_"+variant {
dynLibs = append(dynLibs, availableDynLibs[cmp])
break
}
}
} else {
dynLibs = append(dynLibs, availableDynLibs["cpu"])
}
}
// Finally, if we didn't find any matches, LCD CPU FTW
if len(dynLibs) == 0 {
dynLibs = []string{availableDynLibs["cpu"]}
}
slog.Debug(fmt.Sprintf("ordered list of LLM libraries to try %v", dynLibs))
return dynLibs
}
func rocmDynLibPresent() bool {
for dynLibName := range availableDynLibs {
if strings.HasPrefix(dynLibName, "rocm") {
return true
}
}
return false
}
func nativeInit() error {
payloadsDir, err := gpu.PayloadsDir()
if err != nil {
return err
}
slog.Info(fmt.Sprintf("Extracting dynamic libraries to %s ...", payloadsDir))
libs, err := extractDynamicLibs(payloadsDir, "llama.cpp/build/*/*/*/lib/*")
if err != nil {
if err == payloadMissing {
slog.Info(fmt.Sprintf("%s", payloadMissing))
return nil
}
return err
}
for _, lib := range libs {
// The last dir component is the variant name
variant := filepath.Base(filepath.Dir(lib))
availableDynLibs[variant] = lib
}
if err := verifyDriverAccess(); err != nil {
return err
}
// Report which dynamic libraries we have loaded to assist troubleshooting
variants := make([]string, len(availableDynLibs))
i := 0
for variant := range availableDynLibs {
variants[i] = variant
i++
}
slog.Info(fmt.Sprintf("Dynamic LLM libraries %v", variants))
slog.Debug("Override detection logic by setting OLLAMA_LLM_LIBRARY")
return nil
}
func extractDynamicLibs(payloadsDir, glob string) ([]string, error) {
files, err := fs.Glob(libEmbed, glob)
if err != nil || len(files) == 0 {
return nil, payloadMissing
}
libs := []string{}
g := new(errgroup.Group)
for _, file := range files {
pathComps := strings.Split(file, "/")
if len(pathComps) != pathComponentCount {
slog.Error(fmt.Sprintf("unexpected payload components: %v", pathComps))
continue
}
file := file
g.Go(func() error {
// llama.cpp/build/$OS/$GOARCH/$VARIANT/lib/$LIBRARY
// Include the variant in the path to avoid conflicts between multiple server libs
targetDir := filepath.Join(payloadsDir, pathComps[pathComponentCount-3])
srcFile, err := libEmbed.Open(file)
if err != nil {
return fmt.Errorf("read payload %s: %v", file, err)
}
defer srcFile.Close()
if err := os.MkdirAll(targetDir, 0o755); err != nil {
return fmt.Errorf("create payload lib dir %s: %v", payloadsDir, err)
}
src := io.Reader(srcFile)
filename := file
if strings.HasSuffix(file, ".gz") {
src, err = gzip.NewReader(src)
if err != nil {
return fmt.Errorf("decompress payload %s: %v", file, err)
}
filename = strings.TrimSuffix(filename, ".gz")
}
destFile := filepath.Join(targetDir, filepath.Base(filename))
if strings.Contains(destFile, "server") {
libs = append(libs, destFile)
}
destFp, err := os.OpenFile(destFile, os.O_WRONLY|os.O_CREATE|os.O_TRUNC, 0o755)
if err != nil {
return fmt.Errorf("write payload %s: %v", file, err)
}
defer destFp.Close()
if _, err := io.Copy(destFp, src); err != nil {
return fmt.Errorf("copy payload %s: %v", file, err)
}
return nil
})
}
return libs, g.Wait()
}
func verifyDriverAccess() error {
if runtime.GOOS != "linux" {
return nil
}
// Only check ROCm access if we have the dynamic lib loaded
if rocmDynLibPresent() {
// Verify we have permissions - either running as root, or we have group access to the driver
fd, err := os.OpenFile("/dev/kfd", os.O_RDWR, 0666)
if err != nil {
if errors.Is(err, fs.ErrPermission) {
return fmt.Errorf("Radeon card detected, but permissions not set up properly. Either run ollama as root, or add you user account to the render group.")
} else if errors.Is(err, fs.ErrNotExist) {
// expected behavior without a radeon card
return nil
}
return fmt.Errorf("failed to check permission on /dev/kfd: %w", err)
}
fd.Close()
}
return nil
}

View File

@@ -1,8 +0,0 @@
package llm
import (
"embed"
)
//go:embed llama.cpp/build/darwin/x86_64/*/lib/*.dylib*
var libEmbed embed.FS

View File

@@ -1,8 +0,0 @@
package llm
import (
"embed"
)
//go:embed llama.cpp/ggml-metal.metal llama.cpp/build/darwin/arm64/*/lib/*.dylib*
var libEmbed embed.FS

View File

@@ -1,58 +0,0 @@
package llm
import (
"testing"
"github.com/jmorganca/ollama/gpu"
"github.com/stretchr/testify/assert"
)
func TestGetDynLibs(t *testing.T) {
availableDynLibs = map[string]string{
"cpu": "X_cpu",
}
assert.Equal(t, false, rocmDynLibPresent())
res := getDynLibs(gpu.GpuInfo{Library: "cpu"})
assert.Len(t, res, 1)
assert.Equal(t, availableDynLibs["cpu"], res[0])
variant := gpu.GetCPUVariant()
if variant != "" {
variant = "_" + variant
}
availableDynLibs = map[string]string{
"rocm_v5": "X_rocm_v5",
"rocm_v6": "X_rocm_v6",
"cpu" + variant: "X_cpu",
}
assert.Equal(t, true, rocmDynLibPresent())
res = getDynLibs(gpu.GpuInfo{Library: "rocm"})
assert.Len(t, res, 3)
assert.Equal(t, availableDynLibs["rocm_v5"], res[0])
assert.Equal(t, availableDynLibs["rocm_v6"], res[1])
assert.Equal(t, availableDynLibs["cpu"+variant], res[2])
res = getDynLibs(gpu.GpuInfo{Library: "rocm", Variant: "v6"})
assert.Len(t, res, 3)
assert.Equal(t, availableDynLibs["rocm_v6"], res[0])
assert.Equal(t, availableDynLibs["rocm_v5"], res[1])
assert.Equal(t, availableDynLibs["cpu"+variant], res[2])
res = getDynLibs(gpu.GpuInfo{Library: "cuda"})
assert.Len(t, res, 1)
assert.Equal(t, availableDynLibs["cpu"+variant], res[0])
res = getDynLibs(gpu.GpuInfo{Library: "default"})
assert.Len(t, res, 1)
assert.Equal(t, "default", res[0])
availableDynLibs = map[string]string{
"rocm": "X_rocm_v5",
"cpu" + variant: "X_cpu",
}
assert.Equal(t, true, rocmDynLibPresent())
res = getDynLibs(gpu.GpuInfo{Library: "rocm", Variant: "v6"})
assert.Len(t, res, 2)
assert.Equal(t, availableDynLibs["rocm"], res[0])
assert.Equal(t, availableDynLibs["cpu"+variant], res[1])
}

854
llm/server.go Normal file
View File

@@ -0,0 +1,854 @@
package llm
import (
"bufio"
"bytes"
"context"
"encoding/json"
"errors"
"fmt"
"io"
"log"
"log/slog"
"math/rand"
"net"
"net/http"
"os"
"os/exec"
"path/filepath"
"runtime"
"slices"
"strconv"
"strings"
"time"
"github.com/ollama/ollama/api"
"github.com/ollama/ollama/format"
"github.com/ollama/ollama/gpu"
)
// LlamaServer is an instance of the llama.cpp server
type LlamaServer struct {
port int
cmd *exec.Cmd
done chan error // Channel to signal when the process exits
status *StatusWriter
options api.Options
}
var cpuOnlyFamilies = []string{
"mamba",
}
func NewLlamaServer(model string, adapters, projectors []string, opts api.Options) (*LlamaServer, error) {
if _, err := os.Stat(model); err != nil {
return nil, err
}
f, err := os.Open(model)
if err != nil {
return nil, err
}
defer f.Close()
ggml, _, err := DecodeGGML(f)
if err != nil {
return nil, err
}
if opts.NumCtx > int(ggml.KV().ContextLength()) {
slog.Warn("requested context length is greater than model max context length", "requested", opts.NumCtx, "model", ggml.KV().ContextLength())
opts.NumCtx = int(ggml.KV().ContextLength())
}
if opts.NumCtx < 4 {
opts.NumCtx = 4
}
availableMemory, _ := gpu.CheckVRAM()
info := gpu.GetGPUInfo()
usedMemory := info.MinimumMemory
for _, projector := range projectors {
usedMemory += projectorMemoryRequirements(projector)
// multimodal models require at least 2048 context
opts.NumCtx = max(opts.NumCtx, 2048)
}
// fp16 k,v = (1 (k) + 1 (v)) * sizeof(float16) * n_ctx * n_layer * n_embd / n_head * n_head_kv
kv := 2 * 2 * int64(opts.NumCtx) * int64(ggml.KV().BlockCount()) * int64(ggml.KV().EmbeddingLength()) / int64(ggml.KV().HeadCount()) * int64(ggml.KV().HeadCountKV())
// this amount is the overhead + tensors in memory
// TODO: get this from the llama.cpp's graph calculations instead of
// estimating it's 1/6 * kv_cache_size * num_gqa
graph := int64(ggml.KV().GQA()) * kv / 6
usedMemory += graph
if (usedMemory > availableMemory || slices.Contains(cpuOnlyFamilies, ggml.KV().Architecture())) && info.Library != "metal" {
info.Library = "cpu"
}
requiredMemory := usedMemory
var layers int
for i := 0; i < int(ggml.KV().BlockCount()); i++ {
layerMemory := ggml.LayerSize(fmt.Sprintf("blk.%d.", i)) + kv/int64(ggml.KV().BlockCount())
requiredMemory += layerMemory
if availableMemory > usedMemory+layerMemory && (opts.NumGPU < 0 || layers < opts.NumGPU) {
usedMemory += layerMemory
layers++
}
}
memOutputLayer := ggml.LayerSize("output.")
requiredMemory += memOutputLayer
// only offload output layer if all repeating layers are offloaded
if layers >= int(ggml.KV().BlockCount()) && availableMemory > usedMemory+memOutputLayer {
usedMemory += memOutputLayer
layers++
}
slog.Info(
"offload to gpu",
"layers", layers,
"required", format.HumanBytes2(requiredMemory),
"used", format.HumanBytes2(usedMemory),
"available", format.HumanBytes2(availableMemory),
"kv", format.HumanBytes2(kv),
"graph", format.HumanBytes2(graph),
)
if opts.NumGPU < 0 && info.Library != "cpu" {
opts.NumGPU = layers
}
if len(adapters) > 1 {
return nil, errors.New("ollama supports only one lora adapter, but multiple were provided")
}
availableServers := availableServers()
servers := serversForGpu(info)
demandLib := os.Getenv("OLLAMA_LLM_LIBRARY")
if demandLib != "" {
serverPath := availableServers[demandLib]
if serverPath == "" {
slog.Info(fmt.Sprintf("Invalid OLLAMA_LLM_LIBRARY %s - not found", demandLib))
} else {
slog.Info("user override", "OLLAMA_LLM_LIBRARY", demandLib, "path", serverPath)
servers = []string{demandLib}
}
}
if len(servers) == 0 {
return nil, fmt.Errorf("no servers found for %v", info)
}
params := []string{
"--model", model,
"--ctx-size", fmt.Sprintf("%d", opts.NumCtx),
"--batch-size", fmt.Sprintf("%d", opts.NumBatch),
"--embedding",
}
if debug := os.Getenv("OLLAMA_DEBUG"); debug != "" {
params = append(params, "--log-format", "json")
} else {
params = append(params, "--log-disable")
}
if opts.NumGPU >= 0 {
params = append(params, "--n-gpu-layers", fmt.Sprintf("%d", opts.NumGPU))
}
if debug := os.Getenv("OLLAMA_DEBUG"); debug != "" {
params = append(params, "--verbose")
}
if opts.MainGPU > 0 {
params = append(params, "--main-gpu", fmt.Sprintf("%d", opts.MainGPU))
}
if opts.RopeFrequencyBase > 0 {
params = append(params, "--rope-freq-base", fmt.Sprintf("%f", opts.RopeFrequencyBase))
}
if opts.RopeFrequencyScale > 0 {
params = append(params, "--rope-freq-scale", fmt.Sprintf("%f", opts.RopeFrequencyScale))
}
if len(adapters) > 0 {
// TODO: applying multiple adapters is not supported by the llama.cpp server yet
params = append(params, "--lora", adapters[0])
}
if len(projectors) > 0 {
// TODO: applying multiple projectors is not supported by the llama.cpp server yet
params = append(params, "--mmproj", projectors[0])
}
if opts.NumThread > 0 {
params = append(params, "--threads", fmt.Sprintf("%d", opts.NumThread))
}
if !opts.F16KV {
params = append(params, "--memory-f32")
}
if opts.UseMLock {
params = append(params, "--mlock")
}
if !opts.UseMMap {
params = append(params, "--no-mmap")
}
if opts.UseNUMA {
params = append(params, "--numa")
}
// Loop through potential servers
var finalErr error
for i := 0; i < len(servers); i++ {
dir := availableServers[servers[i]]
// Find an availableServers port, retry on each iterration in case the failure was a port conflict race
port := 0
if a, err := net.ResolveTCPAddr("tcp", "localhost:0"); err == nil {
var l *net.TCPListener
if l, err = net.ListenTCP("tcp", a); err == nil {
port = l.Addr().(*net.TCPAddr).Port
l.Close()
}
}
if port == 0 {
slog.Debug("ResolveTCPAddr failed ", "error", err)
port = rand.Intn(65535-49152) + 49152 // get a random port in the ephemeral range
}
finalParams := append(params, "--port", strconv.Itoa(port))
pathEnv := "LD_LIBRARY_PATH"
if runtime.GOOS == "windows" {
pathEnv = "PATH"
}
// append the server directory to LD_LIBRARY_PATH/PATH
libraryPaths := []string{dir}
if libraryPath, ok := os.LookupEnv(pathEnv); ok {
// Append our runner directory to the path
// This will favor system libraries over our bundled library dependencies
libraryPaths = append(filepath.SplitList(libraryPath), libraryPaths...)
}
server := filepath.Join(dir, "ollama_llama_server")
if runtime.GOOS == "windows" {
server = server + ".exe"
}
s := &LlamaServer{
port: port,
cmd: exec.Command(server, finalParams...),
status: NewStatusWriter(os.Stderr),
options: opts,
}
libEnv := fmt.Sprintf("%s=%s", pathEnv, strings.Join(libraryPaths, string(filepath.ListSeparator)))
slog.Debug(libEnv)
s.cmd.Env = append(os.Environ(), libEnv)
s.cmd.Stdout = os.Stdout
s.cmd.Stderr = s.status
slog.Info("starting llama server", "cmd", s.cmd.String())
if err = s.cmd.Start(); err != nil {
msg := ""
if s.status != nil && s.status.LastErrMsg != "" {
msg = s.status.LastErrMsg
}
err = fmt.Errorf("error starting the external llama server: %v %s", err, msg)
finalErr = err
continue
}
// reap subprocess when it exits
go func() {
// Exit status managed via getServerStatus
_ = s.cmd.Wait()
}()
if err = s.waitUntilRunning(); err != nil {
slog.Error("error starting llama server", "server", servers[i], "error", err)
s.Close()
finalErr = err
continue
}
return s, nil
}
slog.Error("unable to load any llama server", "error", finalErr)
return nil, finalErr
}
func projectorMemoryRequirements(filename string) int64 {
file, err := os.Open(filename)
if err != nil {
return 0
}
defer file.Close()
ggml, _, err := DecodeGGML(file)
if err != nil {
return 0
}
prefixes := make(map[string]struct{})
for _, layer := range ggml.Tensors() {
parts := strings.Split(layer.Name, ".")
prefixes[strings.Join(parts[:2], ".")] = struct{}{}
}
var ask int64
for prefix := range prefixes {
ask += ggml.LayerSize(prefix)
}
return ask
}
type ServerStatus int
const ( // iota is reset to 0
ServerStatusReady ServerStatus = iota
ServerStatusNoSlotsAvaialble
ServerStatusLoadingModel
ServerStatusNotResponding
ServerStatusError
)
type ServerStatusResp struct {
Status string `json:"status"`
SlotsIdle int `json:"slots_idle"`
SlotsProcessing int `json:"slots_processing"`
Error string `json:"error"`
}
func (s *LlamaServer) getServerStatus(ctx context.Context) (ServerStatus, error) {
// Fail fast if its exited
if s.cmd.ProcessState != nil {
msg := ""
if s.status != nil && s.status.LastErrMsg != "" {
msg = s.status.LastErrMsg
}
return ServerStatusError, fmt.Errorf("llama runner process no longer running: %d %s", s.cmd.ProcessState.ExitCode(), msg)
}
req, err := http.NewRequestWithContext(ctx, http.MethodGet, fmt.Sprintf("http://127.0.0.1:%d/health", s.port), nil)
if err != nil {
return ServerStatusError, fmt.Errorf("error creating GET request: %v", err)
}
req.Header.Set("Content-Type", "application/json")
resp, err := http.DefaultClient.Do(req)
if err != nil {
if errors.Is(err, context.DeadlineExceeded) {
return ServerStatusNotResponding, fmt.Errorf("server not responding")
}
return ServerStatusError, fmt.Errorf("health resp: %w", err)
}
defer resp.Body.Close()
body, err := io.ReadAll(resp.Body)
if err != nil {
return ServerStatusError, fmt.Errorf("read health request: %w", err)
}
var status ServerStatusResp
if err := json.Unmarshal(body, &status); err != nil {
return ServerStatusError, fmt.Errorf("health unmarshal encode response: %w", err)
}
switch status.Status {
case "ok":
return ServerStatusReady, nil
case "no slot available":
return ServerStatusNoSlotsAvaialble, nil
case "loading model":
return ServerStatusLoadingModel, nil
default:
return ServerStatusError, fmt.Errorf("server error: %+v", status)
}
}
func (s *LlamaServer) Ping(ctx context.Context) error {
_, err := s.getServerStatus(ctx)
if err != nil {
slog.Debug("server unhealthy", "error", err)
return err
}
return nil
}
func (s *LlamaServer) waitUntilRunning() error {
start := time.Now()
expiresAt := time.Now().Add(3 * time.Minute) // be generous with timeout, large models can take a while to load
ticker := time.NewTicker(50 * time.Millisecond)
defer ticker.Stop()
slog.Info("waiting for llama runner to start responding")
var lastStatus ServerStatus = -1
for {
select {
case err := <-s.done:
msg := ""
if s.status != nil && s.status.LastErrMsg != "" {
msg = s.status.LastErrMsg
}
return fmt.Errorf("llama runner process has terminated: %v %s", err, msg)
case <-ticker.C:
if time.Now().After(expiresAt) {
// timeout
msg := ""
if s.status != nil && s.status.LastErrMsg != "" {
msg = s.status.LastErrMsg
}
return fmt.Errorf("timed out waiting for llama runner to start: %s", msg)
}
if s.cmd.ProcessState != nil {
msg := ""
if s.status != nil && s.status.LastErrMsg != "" {
msg = s.status.LastErrMsg
}
return fmt.Errorf("llama runner process no longer running: %d %s", s.cmd.ProcessState.ExitCode(), msg)
}
ctx, cancel := context.WithTimeout(context.Background(), 200*time.Millisecond)
defer cancel()
status, err := s.getServerStatus(ctx)
if err != nil && lastStatus != status {
slog.Debug("server not yet available", "error", err)
lastStatus = status
continue
}
switch status {
case ServerStatusLoadingModel:
// TODO - this state never seems to happen with the current server.cpp code (bug?)
// it doesn't respond to the health endpoint until after the model is loaded
slog.Debug("loading model")
case ServerStatusReady:
slog.Debug(fmt.Sprintf("llama runner started in %f seconds", time.Since(start).Seconds()))
return nil
}
}
}
}
const jsonGrammar = `
root ::= object
value ::= object | array | string | number | ("true" | "false" | "null") ws
object ::=
"{" ws (
string ":" ws value
("," ws string ":" ws value)*
)? "}" ws
array ::=
"[" ws (
value
("," ws value)*
)? "]" ws
string ::=
"\"" (
[^"\\] |
"\\" (["\\/bfnrt] | "u" [0-9a-fA-F] [0-9a-fA-F] [0-9a-fA-F] [0-9a-fA-F]) # escapes
)* "\"" ws
number ::= ("-"? ([0-9] | [1-9] [0-9]*)) ("." [0-9]+)? ([eE] [-+]? [0-9]+)? ws
# Optional space: by convention, applied in this grammar after literal chars when allowed
ws ::= ([ \t\n] ws)?
`
const maxBufferSize = 512 * format.KiloByte
const maxRetries = 3
type ImageData struct {
Data []byte `json:"data"`
ID int `json:"id"`
}
type completion struct {
Content string `json:"content"`
Model string `json:"model"`
Prompt string `json:"prompt"`
Stop bool `json:"stop"`
Timings struct {
PredictedN int `json:"predicted_n"`
PredictedMS float64 `json:"predicted_ms"`
PromptN int `json:"prompt_n"`
PromptMS float64 `json:"prompt_ms"`
}
}
type CompletionRequest struct {
Prompt string
Format string
Images []ImageData
Options api.Options
}
type CompletionResponse struct {
Content string
Done bool
PromptEvalCount int
PromptEvalDuration time.Duration
EvalCount int
EvalDuration time.Duration
}
func (s *LlamaServer) Completion(ctx context.Context, req CompletionRequest, fn func(CompletionResponse)) error {
request := map[string]any{
"prompt": req.Prompt,
"stream": true,
"n_predict": req.Options.NumPredict,
"n_keep": req.Options.NumKeep,
"main_gpu": req.Options.MainGPU,
"temperature": req.Options.Temperature,
"top_k": req.Options.TopK,
"top_p": req.Options.TopP,
"tfs_z": req.Options.TFSZ,
"typical_p": req.Options.TypicalP,
"repeat_last_n": req.Options.RepeatLastN,
"repeat_penalty": req.Options.RepeatPenalty,
"presence_penalty": req.Options.PresencePenalty,
"frequency_penalty": req.Options.FrequencyPenalty,
"mirostat": req.Options.Mirostat,
"mirostat_tau": req.Options.MirostatTau,
"mirostat_eta": req.Options.MirostatEta,
"penalize_nl": req.Options.PenalizeNewline,
"seed": req.Options.Seed,
"stop": req.Options.Stop,
"image_data": req.Images,
"cache_prompt": true,
}
// Make sure the server is ready
status, err := s.getServerStatus(ctx)
if err != nil {
return err
} else if status != ServerStatusReady {
return fmt.Errorf("unexpected server status: %d", status)
}
if req.Format == "json" {
request["grammar"] = jsonGrammar
if !strings.Contains(strings.ToLower(req.Prompt), "json") {
slog.Warn("Prompt does not specify that the LLM should response in JSON, but JSON format is expected. For best results specify that JSON is expected in the system prompt.")
}
}
retryDelay := 100 * time.Microsecond
for retries := 0; retries < maxRetries; retries++ {
if retries > 0 {
time.Sleep(retryDelay) // wait before retrying
retryDelay *= 2 // exponential backoff
}
// Handling JSON marshaling with special characters unescaped.
buffer := &bytes.Buffer{}
enc := json.NewEncoder(buffer)
enc.SetEscapeHTML(false)
if err := enc.Encode(request); err != nil {
return fmt.Errorf("failed to marshal data: %v", err)
}
endpoint := fmt.Sprintf("http://127.0.0.1:%d/completion", s.port)
req, err := http.NewRequestWithContext(ctx, http.MethodPost, endpoint, buffer)
if err != nil {
return fmt.Errorf("error creating POST request: %v", err)
}
req.Header.Set("Content-Type", "application/json")
resp, err := http.DefaultClient.Do(req)
if err != nil {
return fmt.Errorf("POST predict: %v", err)
}
defer resp.Body.Close()
if resp.StatusCode >= 400 {
bodyBytes, err := io.ReadAll(resp.Body)
if err != nil {
return fmt.Errorf("failed reading llm error response: %w", err)
}
log.Printf("llm predict error: %s", bodyBytes)
return fmt.Errorf("%s", bodyBytes)
}
scanner := bufio.NewScanner(resp.Body)
buf := make([]byte, 0, maxBufferSize)
scanner.Buffer(buf, maxBufferSize)
retryNeeded := false
// keep track of the last token generated, this is used to abort if the model starts looping
var lastToken string
var tokenRepeat int
for scanner.Scan() {
select {
case <-ctx.Done():
// This handles the request cancellation
return ctx.Err()
default:
line := scanner.Bytes()
if len(line) == 0 {
continue
}
// try again on slot unavailable
if bytes.Contains(line, []byte("slot unavailable")) {
retryNeeded = true
break
}
evt, ok := bytes.CutPrefix(line, []byte("data: "))
if !ok {
return fmt.Errorf("error parsing llm response stream: %s", line)
}
var c completion
if err := json.Unmarshal(evt, &c); err != nil {
return fmt.Errorf("error unmarshaling llm prediction response: %v", err)
}
switch {
case strings.TrimSpace(c.Content) == lastToken:
tokenRepeat++
default:
lastToken = strings.TrimSpace(c.Content)
tokenRepeat = 0
}
// 30 picked as an arbitrary max token repeat limit, modify as needed
if tokenRepeat > 30 {
slog.Debug("prediction aborted, token repeat limit reached")
return ctx.Err()
}
if c.Content != "" {
fn(CompletionResponse{
Content: c.Content,
})
}
if c.Stop {
fn(CompletionResponse{
Done: true,
PromptEvalCount: c.Timings.PromptN,
PromptEvalDuration: parseDurationMs(c.Timings.PromptMS),
EvalCount: c.Timings.PredictedN,
EvalDuration: parseDurationMs(c.Timings.PredictedMS),
})
return nil
}
}
}
if err := scanner.Err(); err != nil {
if strings.Contains(err.Error(), "unexpected EOF") {
s.Close()
msg := ""
if s.status != nil && s.status.LastErrMsg != "" {
msg = s.status.LastErrMsg
}
return fmt.Errorf("an unknown error was encountered while running the model %s", msg)
}
return fmt.Errorf("error reading llm response: %v", err)
}
if !retryNeeded {
return nil // success
}
}
// should never reach here ideally
return fmt.Errorf("max retries exceeded")
}
type EmbeddingRequest struct {
Content string `json:"content"`
}
type EmbeddingResponse struct {
Embedding []float64 `json:"embedding"`
}
func (s *LlamaServer) Embedding(ctx context.Context, prompt string) ([]float64, error) {
// Make sure the server is ready
status, err := s.getServerStatus(ctx)
if err != nil {
return nil, err
} else if status != ServerStatusReady {
return nil, fmt.Errorf("unexpected server status: %d", status)
}
data, err := json.Marshal(TokenizeRequest{Content: prompt})
if err != nil {
return nil, fmt.Errorf("error marshaling embed data: %w", err)
}
req, err := http.NewRequestWithContext(ctx, http.MethodPost, fmt.Sprintf("http://127.0.0.1:%d/embedding", s.port), bytes.NewBuffer(data))
if err != nil {
return nil, fmt.Errorf("error creating embed request: %w", err)
}
req.Header.Set("Content-Type", "application/json")
resp, err := http.DefaultClient.Do(req)
if err != nil {
return nil, fmt.Errorf("do embedding request: %w", err)
}
defer resp.Body.Close()
body, err := io.ReadAll(resp.Body)
if err != nil {
return nil, fmt.Errorf("error reading embed response: %w", err)
}
if resp.StatusCode >= 400 {
log.Printf("llm encode error: %s", body)
return nil, fmt.Errorf("%s", body)
}
var embedding EmbeddingResponse
if err := json.Unmarshal(body, &embedding); err != nil {
return nil, fmt.Errorf("unmarshal tokenize response: %w", err)
}
return embedding.Embedding, nil
}
type TokenizeRequest struct {
Content string `json:"content"`
}
type TokenizeResponse struct {
Tokens []int `json:"tokens"`
}
func (s *LlamaServer) Tokenize(ctx context.Context, content string) ([]int, error) {
// Make sure the server is ready
status, err := s.getServerStatus(ctx)
if err != nil {
return nil, err
} else if status != ServerStatusReady {
return nil, fmt.Errorf("unexpected server status: %d", status)
}
data, err := json.Marshal(TokenizeRequest{Content: content})
if err != nil {
return nil, fmt.Errorf("marshaling encode data: %w", err)
}
req, err := http.NewRequestWithContext(ctx, http.MethodPost, fmt.Sprintf("http://127.0.0.1:%d/tokenize", s.port), bytes.NewBuffer(data))
if err != nil {
return nil, fmt.Errorf("encode request: %w", err)
}
req.Header.Set("Content-Type", "application/json")
resp, err := http.DefaultClient.Do(req)
if err != nil {
return nil, fmt.Errorf("do encode request: %w", err)
}
defer resp.Body.Close()
body, err := io.ReadAll(resp.Body)
if err != nil {
return nil, fmt.Errorf("read encode request: %w", err)
}
if resp.StatusCode >= 400 {
log.Printf("llm encode error: %s", body)
return nil, fmt.Errorf("%s", body)
}
var encoded TokenizeResponse
if err := json.Unmarshal(body, &encoded); err != nil {
return nil, fmt.Errorf("unmarshal encode response: %w", err)
}
return encoded.Tokens, nil
}
type DetokenizeRequest struct {
Tokens []int `json:"tokens"`
}
type DetokenizeResponse struct {
Content string `json:"content"`
}
func (s *LlamaServer) Detokenize(ctx context.Context, tokens []int) (string, error) {
// Make sure the server is ready
status, err := s.getServerStatus(ctx)
if err != nil {
return "", err
} else if status != ServerStatusReady {
return "", fmt.Errorf("unexpected server status: %d", status)
}
data, err := json.Marshal(DetokenizeRequest{Tokens: tokens})
if err != nil {
return "", fmt.Errorf("marshaling decode data: %w", err)
}
req, err := http.NewRequestWithContext(ctx, http.MethodPost, fmt.Sprintf("http://127.0.0.1:%d/detokenize", s.port), bytes.NewBuffer(data))
if err != nil {
return "", fmt.Errorf("decode request: %w", err)
}
req.Header.Set("Content-Type", "application/json")
resp, err := http.DefaultClient.Do(req)
if err != nil {
return "", fmt.Errorf("do decode request: %w", err)
}
defer resp.Body.Close()
body, err := io.ReadAll(resp.Body)
if err != nil {
return "", fmt.Errorf("read decode request: %w", err)
}
if resp.StatusCode >= 400 {
log.Printf("llm decode error: %s", body)
return "", fmt.Errorf("%s", body)
}
var decoded DetokenizeResponse
if err := json.Unmarshal(body, &decoded); err != nil {
return "", fmt.Errorf("unmarshal encode response: %w", err)
}
return decoded.Content, nil
}
func (s *LlamaServer) Close() error {
if s.cmd != nil {
slog.Debug("stopping llama server")
return s.cmd.Process.Kill()
}
return nil
}
func parseDurationMs(ms float64) time.Duration {
dur, err := time.ParseDuration(fmt.Sprintf("%fms", ms))
if err != nil {
panic(err)
}
return dur
}

42
llm/status.go Normal file
View File

@@ -0,0 +1,42 @@
package llm
import (
"bytes"
"os"
)
// StatusWriter is a writer that captures error messages from the llama runner process
type StatusWriter struct {
LastErrMsg string
out *os.File
}
func NewStatusWriter(out *os.File) *StatusWriter {
return &StatusWriter{
out: out,
}
}
// TODO - regex matching to detect errors like
// libcublasLt.so.11: cannot open shared object file: No such file or directory
var errorPrefixes = []string{
"error:",
"CUDA error",
"cudaMalloc failed",
"\"ERR\"",
}
func (w *StatusWriter) Write(b []byte) (int, error) {
var errMsg string
for _, prefix := range errorPrefixes {
if _, after, ok := bytes.Cut(b, []byte(prefix)); ok {
errMsg = prefix + string(bytes.TrimSpace(after))
}
}
if errMsg != "" {
w.LastErrMsg = errMsg
}
return w.out.Write(b)
}

View File

@@ -1,15 +0,0 @@
package llm
import (
"fmt"
"time"
)
func parseDurationMs(ms float64) time.Duration {
dur, err := time.ParseDuration(fmt.Sprintf("%fms", ms))
if err != nil {
panic(err)
}
return dur
}

Some files were not shown because too many files have changed in this diff Show More