## Motivation
Updated documentation for v1.0.68 release
## Changes
**docs/api.md:**
- Added documentation for new API endpoints: Claude Messages API
(`/v1/messages`), OpenAI Responses API (`/v1/responses`), and Ollama API
compatibility endpoints
- Documented custom model management endpoints (`POST /models/add`,
`DELETE /models/custom/{model_id}`)
- Added `enable_thinking` parameter documentation for thinking-capable
models (DeepSeek V3.1, Qwen3, GLM-4.7)
- Documented usage statistics in responses (prompt_tokens,
completion_tokens, total_tokens)
- Added streaming event format documentation for all API types
- Updated image generation section with FLUX.1-Kontext-dev support and
new dimensions (1024x1365, 1365x1024)
- Added request cancellation documentation
- Updated complete endpoint summary with all new endpoints
- Added security notes about trust_remote_code being opt-in
**README.md:**
- Updated Features section to highlight multiple API compatibility
options
- Added Environment Variables section documenting all configuration
options (EXO_MODELS_PATH, EXO_OFFLINE, EXO_ENABLE_IMAGE_MODELS,
EXO_LIBP2P_NAMESPACE, EXO_FAST_SYNCH, EXO_TRACING_ENABLED)
- Expanded "Using the API" section with examples for Claude Messages
API, OpenAI Responses API, and Ollama API
- Added custom model loading documentation with security notes
- Updated file locations to include log files and custom model cards
paths
**CONTRIBUTING.md:**
- Added documentation for TOML model cards format and the API adapter
pattern
**docs/architecture.md:**
- Documented the adapter architecture introduced in PR #1167Closes#1653
---------
Co-authored-by: askmanu[bot] <192355599+askmanu[bot]@users.noreply.github.com>
Co-authored-by: Evan Quiney <evanev7@gmail.com>
## Summary
- Adds explicit `POST /v1/cancel/{command_id}` REST endpoint to cancel
in-flight text and image generation commands by ID
- Previously, cancellation only worked via HTTP disconnect (client
closes SSE connection, triggering `anyio.get_cancelled_exc_class()`).
Non-streaming clients and external consumers had no way to cleanly
cancel active generation
- The endpoint looks up the command in active generation queues, sends
`TaskCancelled` to notify workers, and closes the sender stream. Returns
404 (OpenAI error format) if the command is not found or already
completed
## Changes
| File | Change |
|------|--------|
| `src/exo/shared/types/api.py` | Add `CancelCommandResponse` model |
| `src/exo/master/api.py` | Import, route registration, `cancel_command`
handler |
| `src/exo/master/tests/test_cancel_command.py` | 3 test cases (404,
text cancel, image cancel) |
| `docs/api.md` | Document new endpoint + update summary table |
## Design Decisions
- Uses `self._send()` (not raw `command_sender.send()`) — respects API
pause state during elections
- Uses `raise HTTPException` — feeds into exo's centralized OpenAI-style
error handler
- Returns typed `CancelCommandResponse` — consistent with
`CreateInstanceResponse` / `DeleteInstanceResponse` patterns
- `sender.close()` is idempotent so concurrent cancel requests for the
same command are harmless
## Test Plan
- [x] `test_cancel_nonexistent_command_returns_404` — verifies 404 with
OpenAI error format
- [x] `test_cancel_active_text_generation` — verifies 200,
`sender.close()` called, `TaskCancelled` sent with correct
`cancelled_command_id`
- [x] `test_cancel_active_image_generation` — same verification for
image queue
- [x] `basedpyright` — 0 new errors
- [x] `ruff check` — all checks passed
- [x] `pytest` — 3/3 new tests pass, no regressions
---------
Co-authored-by: Evan <evanev7@gmail.com>
## Motivation
Enable distributed image generation across exo clusters
## Changes
- Added OpenAI-compatible /v1/images/generations and /v1/images/edits
API endpoints - Added /bench/images/generations and /bench/images/edits
endpoints that return generation statistics (timing, throughput metrics)
- Implemented PipeFusion distributed inference for diffusion models,
enabling patch-based parallelism across nodes
- Added model adapters for Flux (schnell, dev) and Qwen image models
## Why It Works
https://arxiv.org/abs/2405.14430
## Test Plan
### Manual Testing
- Generate images using /v1/images/generations endpoint with single and
multi-node clusters
- Test image editing via /v1/images/edits with source images
- Verify streaming partial images appear progressively in the dashboard
- Use /bench/images/generations to measure generation performance
- Test both Flux and Qwen model families
---------
Co-authored-by: Sami Khan <smsak99@gmail.com>
