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2 Commits

Author SHA1 Message Date
ParthSareen
cb9427b6d7 anthropic: add unit and integration tests
- Unit tests for transformation functions (FromMessagesRequest, ToMessagesResponse)
- Unit tests for error handling and edge cases
- Middleware integration tests with httptest
- Fix lint issues (gofmt)
- Fix unused struct fields in StreamConverter
- Add fallback for crypto/rand errors
2026-01-02 01:55:04 -05:00
ParthSareen
331bee0b8f api: add Anthropic Messages API compatibility layer
Add middleware to support the Anthropic Messages API format at /v1/messages.
This enables tools like Claude Code to work with Ollama models through the
Anthropic API interface.

Features:
- Request/response transformation between Anthropic and internal formats
- Streaming support with SSE events (message_start, content_block_delta, etc.)
- Tool calling support (tool_use and tool_result content blocks)
- Thinking/extended thinking block support
- Image content block support (base64)
- System prompt handling
- Multi-turn conversation support
- Proper stop_reason mapping (end_turn, max_tokens, tool_use)
- Error responses in Anthropic format

New files:
- anthropic/anthropic.go: Types and transformation functions
- middleware/anthropic.go: Request/response middleware
2026-01-02 01:09:46 -05:00
8 changed files with 2430 additions and 1 deletions

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anthropic/anthropic.go Normal file
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// Package anthropic provides core transformation logic for compatibility with the Anthropic Messages API
package anthropic
import (
"crypto/rand"
"encoding/base64"
"encoding/json"
"errors"
"fmt"
"net/http"
"strings"
"time"
"github.com/ollama/ollama/api"
)
// Error types matching Anthropic API
type Error struct {
Type string `json:"type"`
Message string `json:"message"`
}
type ErrorResponse struct {
Type string `json:"type"` // always "error"
Error Error `json:"error"`
RequestID string `json:"request_id,omitempty"`
}
// NewError creates a new ErrorResponse with the appropriate error type based on HTTP status code
func NewError(code int, message string) ErrorResponse {
var etype string
switch code {
case http.StatusBadRequest:
etype = "invalid_request_error"
case http.StatusUnauthorized:
etype = "authentication_error"
case http.StatusForbidden:
etype = "permission_error"
case http.StatusNotFound:
etype = "not_found_error"
case http.StatusTooManyRequests:
etype = "rate_limit_error"
case http.StatusServiceUnavailable, 529:
etype = "overloaded_error"
default:
etype = "api_error"
}
return ErrorResponse{
Type: "error",
Error: Error{Type: etype, Message: message},
RequestID: generateID("req"),
}
}
// Request types
// MessagesRequest represents an Anthropic Messages API request
type MessagesRequest struct {
Model string `json:"model"`
MaxTokens int `json:"max_tokens"`
Messages []MessageParam `json:"messages"`
System any `json:"system,omitempty"` // string or []ContentBlock
Stream bool `json:"stream,omitempty"`
Temperature *float64 `json:"temperature,omitempty"`
TopP *float64 `json:"top_p,omitempty"`
TopK *int `json:"top_k,omitempty"`
StopSequences []string `json:"stop_sequences,omitempty"`
Tools []Tool `json:"tools,omitempty"`
ToolChoice *ToolChoice `json:"tool_choice,omitempty"`
Thinking *ThinkingConfig `json:"thinking,omitempty"`
Metadata *Metadata `json:"metadata,omitempty"`
}
// MessageParam represents a message in the request
type MessageParam struct {
Role string `json:"role"` // "user" or "assistant"
Content any `json:"content"` // string or []ContentBlock
}
// ContentBlock represents a content block in a message
type ContentBlock struct {
Type string `json:"type"` // text, image, tool_use, tool_result, thinking
// For text blocks
Text string `json:"text,omitempty"`
// For image blocks
Source *ImageSource `json:"source,omitempty"`
// For tool_use blocks
ID string `json:"id,omitempty"`
Name string `json:"name,omitempty"`
Input any `json:"input,omitempty"`
// For tool_result blocks
ToolUseID string `json:"tool_use_id,omitempty"`
Content any `json:"content,omitempty"` // string or []ContentBlock
IsError bool `json:"is_error,omitempty"`
// For thinking blocks
Thinking string `json:"thinking,omitempty"`
Signature string `json:"signature,omitempty"`
}
// ImageSource represents the source of an image
type ImageSource struct {
Type string `json:"type"` // "base64" or "url"
MediaType string `json:"media_type,omitempty"`
Data string `json:"data,omitempty"`
URL string `json:"url,omitempty"`
}
// Tool represents a tool definition
type Tool struct {
Type string `json:"type,omitempty"` // "custom" for user-defined tools
Name string `json:"name"`
Description string `json:"description,omitempty"`
InputSchema json.RawMessage `json:"input_schema,omitempty"`
}
// ToolChoice controls how the model uses tools
type ToolChoice struct {
Type string `json:"type"` // "auto", "any", "tool", "none"
Name string `json:"name,omitempty"`
DisableParallelToolUse bool `json:"disable_parallel_tool_use,omitempty"`
}
// ThinkingConfig controls extended thinking
type ThinkingConfig struct {
Type string `json:"type"` // "enabled" or "disabled"
BudgetTokens int `json:"budget_tokens,omitempty"`
}
// Metadata for the request
type Metadata struct {
UserID string `json:"user_id,omitempty"`
}
// Response types
// MessagesResponse represents an Anthropic Messages API response
type MessagesResponse struct {
ID string `json:"id"`
Type string `json:"type"` // "message"
Role string `json:"role"` // "assistant"
Model string `json:"model"`
Content []ContentBlock `json:"content"`
StopReason string `json:"stop_reason,omitempty"`
StopSequence string `json:"stop_sequence,omitempty"`
Usage Usage `json:"usage"`
}
// Usage contains token usage information
type Usage struct {
InputTokens int `json:"input_tokens"`
OutputTokens int `json:"output_tokens"`
}
// Streaming event types
// MessageStartEvent is sent at the start of streaming
type MessageStartEvent struct {
Type string `json:"type"` // "message_start"
Message MessagesResponse `json:"message"`
}
// ContentBlockStartEvent signals the start of a content block
type ContentBlockStartEvent struct {
Type string `json:"type"` // "content_block_start"
Index int `json:"index"`
ContentBlock ContentBlock `json:"content_block"`
}
// ContentBlockDeltaEvent contains incremental content updates
type ContentBlockDeltaEvent struct {
Type string `json:"type"` // "content_block_delta"
Index int `json:"index"`
Delta Delta `json:"delta"`
}
// Delta represents an incremental update
type Delta struct {
Type string `json:"type"` // "text_delta", "input_json_delta", "thinking_delta", "signature_delta"
Text string `json:"text,omitempty"`
PartialJSON string `json:"partial_json,omitempty"`
Thinking string `json:"thinking,omitempty"`
Signature string `json:"signature,omitempty"`
}
// ContentBlockStopEvent signals the end of a content block
type ContentBlockStopEvent struct {
Type string `json:"type"` // "content_block_stop"
Index int `json:"index"`
}
// MessageDeltaEvent contains updates to the message
type MessageDeltaEvent struct {
Type string `json:"type"` // "message_delta"
Delta MessageDelta `json:"delta"`
Usage DeltaUsage `json:"usage"`
}
// MessageDelta contains stop information
type MessageDelta struct {
StopReason string `json:"stop_reason,omitempty"`
StopSequence string `json:"stop_sequence,omitempty"`
}
// DeltaUsage contains cumulative token usage
type DeltaUsage struct {
OutputTokens int `json:"output_tokens"`
}
// MessageStopEvent signals the end of the message
type MessageStopEvent struct {
Type string `json:"type"` // "message_stop"
}
// PingEvent is a keepalive event
type PingEvent struct {
Type string `json:"type"` // "ping"
}
// StreamErrorEvent is an error during streaming
type StreamErrorEvent struct {
Type string `json:"type"` // "error"
Error Error `json:"error"`
}
// FromMessagesRequest converts an Anthropic MessagesRequest to an Ollama api.ChatRequest
func FromMessagesRequest(r MessagesRequest) (*api.ChatRequest, error) {
var messages []api.Message
// Handle system prompt
if r.System != nil {
switch sys := r.System.(type) {
case string:
if sys != "" {
messages = append(messages, api.Message{Role: "system", Content: sys})
}
case []any:
// System can be an array of content blocks
var content strings.Builder
for _, block := range sys {
if blockMap, ok := block.(map[string]any); ok {
if blockMap["type"] == "text" {
if text, ok := blockMap["text"].(string); ok {
content.WriteString(text)
}
}
}
}
if content.Len() > 0 {
messages = append(messages, api.Message{Role: "system", Content: content.String()})
}
}
}
// Convert messages
for _, msg := range r.Messages {
converted, err := convertMessage(msg)
if err != nil {
return nil, err
}
messages = append(messages, converted...)
}
// Build options
options := make(map[string]any)
options["num_predict"] = r.MaxTokens
if r.Temperature != nil {
options["temperature"] = *r.Temperature
}
if r.TopP != nil {
options["top_p"] = *r.TopP
}
if r.TopK != nil {
options["top_k"] = *r.TopK
}
if len(r.StopSequences) > 0 {
options["stop"] = r.StopSequences
}
// Convert tools
var tools api.Tools
for _, t := range r.Tools {
tool, err := convertTool(t)
if err != nil {
return nil, err
}
tools = append(tools, tool)
}
// Handle thinking
var think *api.ThinkValue
if r.Thinking != nil && r.Thinking.Type == "enabled" {
think = &api.ThinkValue{Value: true}
}
stream := r.Stream
return &api.ChatRequest{
Model: r.Model,
Messages: messages,
Options: options,
Stream: &stream,
Tools: tools,
Think: think,
}, nil
}
// convertMessage converts an Anthropic MessageParam to Ollama api.Message(s)
func convertMessage(msg MessageParam) ([]api.Message, error) {
var messages []api.Message
role := strings.ToLower(msg.Role)
switch content := msg.Content.(type) {
case string:
messages = append(messages, api.Message{Role: role, Content: content})
case []any:
// Handle array of content blocks
var textContent strings.Builder
var images []api.ImageData
var toolCalls []api.ToolCall
var thinking string
var toolResults []api.Message
for _, block := range content {
blockMap, ok := block.(map[string]any)
if !ok {
return nil, errors.New("invalid content block format")
}
blockType, _ := blockMap["type"].(string)
switch blockType {
case "text":
if text, ok := blockMap["text"].(string); ok {
textContent.WriteString(text)
}
case "image":
source, ok := blockMap["source"].(map[string]any)
if !ok {
return nil, errors.New("invalid image source")
}
sourceType, _ := source["type"].(string)
if sourceType == "base64" {
data, _ := source["data"].(string)
decoded, err := base64.StdEncoding.DecodeString(data)
if err != nil {
return nil, fmt.Errorf("invalid base64 image data: %w", err)
}
images = append(images, decoded)
}
// URL images would need to be fetched - skip for now
case "tool_use":
id, ok := blockMap["id"].(string)
if !ok {
return nil, errors.New("tool_use block missing required 'id' field")
}
name, ok := blockMap["name"].(string)
if !ok {
return nil, errors.New("tool_use block missing required 'name' field")
}
tc := api.ToolCall{
ID: id,
Function: api.ToolCallFunction{
Name: name,
},
}
if input, ok := blockMap["input"].(map[string]any); ok {
tc.Function.Arguments = api.ToolCallFunctionArguments(input)
}
toolCalls = append(toolCalls, tc)
case "tool_result":
toolUseID, _ := blockMap["tool_use_id"].(string)
var resultContent string
switch c := blockMap["content"].(type) {
case string:
resultContent = c
case []any:
// Extract text from content blocks
for _, cb := range c {
if cbMap, ok := cb.(map[string]any); ok {
if cbMap["type"] == "text" {
if text, ok := cbMap["text"].(string); ok {
resultContent += text
}
}
}
}
}
toolResults = append(toolResults, api.Message{
Role: "tool",
Content: resultContent,
ToolCallID: toolUseID,
})
case "thinking":
if t, ok := blockMap["thinking"].(string); ok {
thinking = t
}
}
}
// Build the main message
if textContent.Len() > 0 || len(images) > 0 || len(toolCalls) > 0 {
m := api.Message{
Role: role,
Content: textContent.String(),
Images: images,
ToolCalls: toolCalls,
Thinking: thinking,
}
messages = append(messages, m)
}
// Add tool results as separate messages
messages = append(messages, toolResults...)
default:
return nil, fmt.Errorf("invalid message content type: %T", content)
}
return messages, nil
}
// convertTool converts an Anthropic Tool to an Ollama api.Tool
func convertTool(t Tool) (api.Tool, error) {
var params api.ToolFunctionParameters
if len(t.InputSchema) > 0 {
if err := json.Unmarshal(t.InputSchema, &params); err != nil {
return api.Tool{}, fmt.Errorf("invalid input_schema for tool %q: %w", t.Name, err)
}
}
return api.Tool{
Type: "function",
Function: api.ToolFunction{
Name: t.Name,
Description: t.Description,
Parameters: params,
},
}, nil
}
// ToMessagesResponse converts an Ollama api.ChatResponse to an Anthropic MessagesResponse
func ToMessagesResponse(id string, r api.ChatResponse) MessagesResponse {
var content []ContentBlock
// Add thinking block if present
if r.Message.Thinking != "" {
content = append(content, ContentBlock{
Type: "thinking",
Thinking: r.Message.Thinking,
})
}
// Add text content if present
if r.Message.Content != "" {
content = append(content, ContentBlock{
Type: "text",
Text: r.Message.Content,
})
}
// Add tool use blocks
for _, tc := range r.Message.ToolCalls {
content = append(content, ContentBlock{
Type: "tool_use",
ID: tc.ID,
Name: tc.Function.Name,
Input: tc.Function.Arguments,
})
}
// Map stop reason
stopReason := mapStopReason(r.DoneReason, len(r.Message.ToolCalls) > 0)
return MessagesResponse{
ID: id,
Type: "message",
Role: "assistant",
Model: r.Model,
Content: content,
StopReason: stopReason,
Usage: Usage{
InputTokens: r.Metrics.PromptEvalCount,
OutputTokens: r.Metrics.EvalCount,
},
}
}
// mapStopReason converts Ollama done_reason to Anthropic stop_reason
func mapStopReason(reason string, hasToolCalls bool) string {
if hasToolCalls {
return "tool_use"
}
switch reason {
case "stop":
return "end_turn"
case "length":
return "max_tokens"
default:
if reason != "" {
return "stop_sequence"
}
return ""
}
}
// StreamConverter manages state for converting Ollama streaming responses to Anthropic format
type StreamConverter struct {
ID string
Model string
firstWrite bool
contentIndex int
inputTokens int
outputTokens int
thinkingStarted bool
thinkingDone bool
textStarted bool
toolCallsSent map[string]bool
}
// NewStreamConverter creates a new StreamConverter
func NewStreamConverter(id, model string) *StreamConverter {
return &StreamConverter{
ID: id,
Model: model,
firstWrite: true,
toolCallsSent: make(map[string]bool),
}
}
// StreamEvent represents a streaming event to be sent to the client
type StreamEvent struct {
Event string
Data any
}
// Process converts an Ollama ChatResponse to Anthropic streaming events
func (c *StreamConverter) Process(r api.ChatResponse) []StreamEvent {
var events []StreamEvent
// First write: emit message_start
if c.firstWrite {
c.firstWrite = false
c.inputTokens = r.Metrics.PromptEvalCount
events = append(events, StreamEvent{
Event: "message_start",
Data: MessageStartEvent{
Type: "message_start",
Message: MessagesResponse{
ID: c.ID,
Type: "message",
Role: "assistant",
Model: c.Model,
Content: []ContentBlock{},
Usage: Usage{
InputTokens: c.inputTokens,
OutputTokens: 0,
},
},
},
})
}
// Handle thinking content
if r.Message.Thinking != "" && !c.thinkingDone {
if !c.thinkingStarted {
c.thinkingStarted = true
events = append(events, StreamEvent{
Event: "content_block_start",
Data: ContentBlockStartEvent{
Type: "content_block_start",
Index: c.contentIndex,
ContentBlock: ContentBlock{
Type: "thinking",
Thinking: "",
},
},
})
}
events = append(events, StreamEvent{
Event: "content_block_delta",
Data: ContentBlockDeltaEvent{
Type: "content_block_delta",
Index: c.contentIndex,
Delta: Delta{
Type: "thinking_delta",
Thinking: r.Message.Thinking,
},
},
})
}
// Handle text content
if r.Message.Content != "" {
// Close thinking block if it was open
if c.thinkingStarted && !c.thinkingDone {
c.thinkingDone = true
events = append(events, StreamEvent{
Event: "content_block_stop",
Data: ContentBlockStopEvent{
Type: "content_block_stop",
Index: c.contentIndex,
},
})
c.contentIndex++
}
if !c.textStarted {
c.textStarted = true
events = append(events, StreamEvent{
Event: "content_block_start",
Data: ContentBlockStartEvent{
Type: "content_block_start",
Index: c.contentIndex,
ContentBlock: ContentBlock{
Type: "text",
Text: "",
},
},
})
}
events = append(events, StreamEvent{
Event: "content_block_delta",
Data: ContentBlockDeltaEvent{
Type: "content_block_delta",
Index: c.contentIndex,
Delta: Delta{
Type: "text_delta",
Text: r.Message.Content,
},
},
})
}
// Handle tool calls
for _, tc := range r.Message.ToolCalls {
if c.toolCallsSent[tc.ID] {
continue
}
// Close any previous block
if c.textStarted {
events = append(events, StreamEvent{
Event: "content_block_stop",
Data: ContentBlockStopEvent{
Type: "content_block_stop",
Index: c.contentIndex,
},
})
c.contentIndex++
c.textStarted = false
}
// Start tool use block
events = append(events, StreamEvent{
Event: "content_block_start",
Data: ContentBlockStartEvent{
Type: "content_block_start",
Index: c.contentIndex,
ContentBlock: ContentBlock{
Type: "tool_use",
ID: tc.ID,
Name: tc.Function.Name,
Input: map[string]any{},
},
},
})
// Send input as JSON delta
argsJSON, _ := json.Marshal(tc.Function.Arguments)
events = append(events, StreamEvent{
Event: "content_block_delta",
Data: ContentBlockDeltaEvent{
Type: "content_block_delta",
Index: c.contentIndex,
Delta: Delta{
Type: "input_json_delta",
PartialJSON: string(argsJSON),
},
},
})
// Close tool use block
events = append(events, StreamEvent{
Event: "content_block_stop",
Data: ContentBlockStopEvent{
Type: "content_block_stop",
Index: c.contentIndex,
},
})
c.toolCallsSent[tc.ID] = true
c.contentIndex++
}
// Handle done
if r.Done {
// Close any open block
if c.textStarted {
events = append(events, StreamEvent{
Event: "content_block_stop",
Data: ContentBlockStopEvent{
Type: "content_block_stop",
Index: c.contentIndex,
},
})
} else if c.thinkingStarted && !c.thinkingDone {
events = append(events, StreamEvent{
Event: "content_block_stop",
Data: ContentBlockStopEvent{
Type: "content_block_stop",
Index: c.contentIndex,
},
})
}
c.outputTokens = r.Metrics.EvalCount
stopReason := mapStopReason(r.DoneReason, len(c.toolCallsSent) > 0)
events = append(events, StreamEvent{
Event: "message_delta",
Data: MessageDeltaEvent{
Type: "message_delta",
Delta: MessageDelta{
StopReason: stopReason,
},
Usage: DeltaUsage{
OutputTokens: c.outputTokens,
},
},
})
events = append(events, StreamEvent{
Event: "message_stop",
Data: MessageStopEvent{
Type: "message_stop",
},
})
}
return events
}
// generateID generates a unique ID with the given prefix using crypto/rand
func generateID(prefix string) string {
b := make([]byte, 12)
if _, err := rand.Read(b); err != nil {
// Fallback to time-based ID if crypto/rand fails
return fmt.Sprintf("%s_%d", prefix, time.Now().UnixNano())
}
return fmt.Sprintf("%s_%x", prefix, b)
}
// GenerateMessageID generates a unique message ID
func GenerateMessageID() string {
return generateID("msg")
}

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package anthropic
import (
"encoding/base64"
"encoding/json"
"testing"
"github.com/google/go-cmp/cmp"
"github.com/ollama/ollama/api"
)
const (
testImage = `iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAQAAAC1HAwCAAAAC0lEQVR42mNk+A8AAQUBAScY42YAAAAASUVORK5CYII=`
)
func TestFromMessagesRequest_Basic(t *testing.T) {
req := MessagesRequest{
Model: "test-model",
MaxTokens: 1024,
Messages: []MessageParam{
{Role: "user", Content: "Hello"},
},
}
result, err := FromMessagesRequest(req)
if err != nil {
t.Fatalf("unexpected error: %v", err)
}
if result.Model != "test-model" {
t.Errorf("expected model 'test-model', got %q", result.Model)
}
if len(result.Messages) != 1 {
t.Fatalf("expected 1 message, got %d", len(result.Messages))
}
if result.Messages[0].Role != "user" || result.Messages[0].Content != "Hello" {
t.Errorf("unexpected message: %+v", result.Messages[0])
}
if numPredict, ok := result.Options["num_predict"].(int); !ok || numPredict != 1024 {
t.Errorf("expected num_predict 1024, got %v", result.Options["num_predict"])
}
}
func TestFromMessagesRequest_WithSystemPrompt(t *testing.T) {
req := MessagesRequest{
Model: "test-model",
MaxTokens: 1024,
System: "You are a helpful assistant.",
Messages: []MessageParam{
{Role: "user", Content: "Hello"},
},
}
result, err := FromMessagesRequest(req)
if err != nil {
t.Fatalf("unexpected error: %v", err)
}
if len(result.Messages) != 2 {
t.Fatalf("expected 2 messages, got %d", len(result.Messages))
}
if result.Messages[0].Role != "system" || result.Messages[0].Content != "You are a helpful assistant." {
t.Errorf("unexpected system message: %+v", result.Messages[0])
}
}
func TestFromMessagesRequest_WithSystemPromptArray(t *testing.T) {
req := MessagesRequest{
Model: "test-model",
MaxTokens: 1024,
System: []any{
map[string]any{"type": "text", "text": "You are helpful."},
map[string]any{"type": "text", "text": " Be concise."},
},
Messages: []MessageParam{
{Role: "user", Content: "Hello"},
},
}
result, err := FromMessagesRequest(req)
if err != nil {
t.Fatalf("unexpected error: %v", err)
}
if len(result.Messages) != 2 {
t.Fatalf("expected 2 messages, got %d", len(result.Messages))
}
if result.Messages[0].Content != "You are helpful. Be concise." {
t.Errorf("unexpected system message content: %q", result.Messages[0].Content)
}
}
func TestFromMessagesRequest_WithOptions(t *testing.T) {
temp := 0.7
topP := 0.9
topK := 40
req := MessagesRequest{
Model: "test-model",
MaxTokens: 2048,
Messages: []MessageParam{{Role: "user", Content: "Hello"}},
Temperature: &temp,
TopP: &topP,
TopK: &topK,
StopSequences: []string{"\n", "END"},
}
result, err := FromMessagesRequest(req)
if err != nil {
t.Fatalf("unexpected error: %v", err)
}
if result.Options["temperature"] != 0.7 {
t.Errorf("expected temperature 0.7, got %v", result.Options["temperature"])
}
if result.Options["top_p"] != 0.9 {
t.Errorf("expected top_p 0.9, got %v", result.Options["top_p"])
}
if result.Options["top_k"] != 40 {
t.Errorf("expected top_k 40, got %v", result.Options["top_k"])
}
if diff := cmp.Diff([]string{"\n", "END"}, result.Options["stop"]); diff != "" {
t.Errorf("stop sequences mismatch: %s", diff)
}
}
func TestFromMessagesRequest_WithImage(t *testing.T) {
imgData, _ := base64.StdEncoding.DecodeString(testImage)
req := MessagesRequest{
Model: "test-model",
MaxTokens: 1024,
Messages: []MessageParam{
{
Role: "user",
Content: []any{
map[string]any{"type": "text", "text": "What's in this image?"},
map[string]any{
"type": "image",
"source": map[string]any{
"type": "base64",
"media_type": "image/png",
"data": testImage,
},
},
},
},
},
}
result, err := FromMessagesRequest(req)
if err != nil {
t.Fatalf("unexpected error: %v", err)
}
if len(result.Messages) != 1 {
t.Fatalf("expected 1 message, got %d", len(result.Messages))
}
if result.Messages[0].Content != "What's in this image?" {
t.Errorf("expected content 'What's in this image?', got %q", result.Messages[0].Content)
}
if len(result.Messages[0].Images) != 1 {
t.Fatalf("expected 1 image, got %d", len(result.Messages[0].Images))
}
if string(result.Messages[0].Images[0]) != string(imgData) {
t.Error("image data mismatch")
}
}
func TestFromMessagesRequest_WithToolUse(t *testing.T) {
req := MessagesRequest{
Model: "test-model",
MaxTokens: 1024,
Messages: []MessageParam{
{Role: "user", Content: "What's the weather in Paris?"},
{
Role: "assistant",
Content: []any{
map[string]any{
"type": "tool_use",
"id": "call_123",
"name": "get_weather",
"input": map[string]any{"location": "Paris"},
},
},
},
},
}
result, err := FromMessagesRequest(req)
if err != nil {
t.Fatalf("unexpected error: %v", err)
}
if len(result.Messages) != 2 {
t.Fatalf("expected 2 messages, got %d", len(result.Messages))
}
if len(result.Messages[1].ToolCalls) != 1 {
t.Fatalf("expected 1 tool call, got %d", len(result.Messages[1].ToolCalls))
}
tc := result.Messages[1].ToolCalls[0]
if tc.ID != "call_123" {
t.Errorf("expected tool call ID 'call_123', got %q", tc.ID)
}
if tc.Function.Name != "get_weather" {
t.Errorf("expected tool name 'get_weather', got %q", tc.Function.Name)
}
}
func TestFromMessagesRequest_WithToolResult(t *testing.T) {
req := MessagesRequest{
Model: "test-model",
MaxTokens: 1024,
Messages: []MessageParam{
{
Role: "user",
Content: []any{
map[string]any{
"type": "tool_result",
"tool_use_id": "call_123",
"content": "The weather in Paris is sunny, 22°C",
},
},
},
},
}
result, err := FromMessagesRequest(req)
if err != nil {
t.Fatalf("unexpected error: %v", err)
}
if len(result.Messages) != 1 {
t.Fatalf("expected 1 message, got %d", len(result.Messages))
}
msg := result.Messages[0]
if msg.Role != "tool" {
t.Errorf("expected role 'tool', got %q", msg.Role)
}
if msg.ToolCallID != "call_123" {
t.Errorf("expected tool_call_id 'call_123', got %q", msg.ToolCallID)
}
if msg.Content != "The weather in Paris is sunny, 22°C" {
t.Errorf("unexpected content: %q", msg.Content)
}
}
func TestFromMessagesRequest_WithTools(t *testing.T) {
req := MessagesRequest{
Model: "test-model",
MaxTokens: 1024,
Messages: []MessageParam{{Role: "user", Content: "Hello"}},
Tools: []Tool{
{
Name: "get_weather",
Description: "Get current weather",
InputSchema: json.RawMessage(`{"type":"object","properties":{"location":{"type":"string"}},"required":["location"]}`),
},
},
}
result, err := FromMessagesRequest(req)
if err != nil {
t.Fatalf("unexpected error: %v", err)
}
if len(result.Tools) != 1 {
t.Fatalf("expected 1 tool, got %d", len(result.Tools))
}
tool := result.Tools[0]
if tool.Type != "function" {
t.Errorf("expected type 'function', got %q", tool.Type)
}
if tool.Function.Name != "get_weather" {
t.Errorf("expected name 'get_weather', got %q", tool.Function.Name)
}
if tool.Function.Description != "Get current weather" {
t.Errorf("expected description 'Get current weather', got %q", tool.Function.Description)
}
}
func TestFromMessagesRequest_WithThinking(t *testing.T) {
req := MessagesRequest{
Model: "test-model",
MaxTokens: 1024,
Messages: []MessageParam{{Role: "user", Content: "Hello"}},
Thinking: &ThinkingConfig{Type: "enabled", BudgetTokens: 1000},
}
result, err := FromMessagesRequest(req)
if err != nil {
t.Fatalf("unexpected error: %v", err)
}
if result.Think == nil {
t.Fatal("expected Think to be set")
}
if v, ok := result.Think.Value.(bool); !ok || !v {
t.Errorf("expected Think.Value to be true, got %v", result.Think.Value)
}
}
func TestFromMessagesRequest_ToolUseMissingID(t *testing.T) {
req := MessagesRequest{
Model: "test-model",
MaxTokens: 1024,
Messages: []MessageParam{
{
Role: "assistant",
Content: []any{
map[string]any{
"type": "tool_use",
"name": "get_weather",
},
},
},
},
}
_, err := FromMessagesRequest(req)
if err == nil {
t.Fatal("expected error for missing tool_use id")
}
if err.Error() != "tool_use block missing required 'id' field" {
t.Errorf("unexpected error message: %v", err)
}
}
func TestFromMessagesRequest_ToolUseMissingName(t *testing.T) {
req := MessagesRequest{
Model: "test-model",
MaxTokens: 1024,
Messages: []MessageParam{
{
Role: "assistant",
Content: []any{
map[string]any{
"type": "tool_use",
"id": "call_123",
},
},
},
},
}
_, err := FromMessagesRequest(req)
if err == nil {
t.Fatal("expected error for missing tool_use name")
}
if err.Error() != "tool_use block missing required 'name' field" {
t.Errorf("unexpected error message: %v", err)
}
}
func TestFromMessagesRequest_InvalidToolSchema(t *testing.T) {
req := MessagesRequest{
Model: "test-model",
MaxTokens: 1024,
Messages: []MessageParam{{Role: "user", Content: "Hello"}},
Tools: []Tool{
{
Name: "bad_tool",
InputSchema: json.RawMessage(`{invalid json`),
},
},
}
_, err := FromMessagesRequest(req)
if err == nil {
t.Fatal("expected error for invalid tool schema")
}
}
func TestToMessagesResponse_Basic(t *testing.T) {
resp := api.ChatResponse{
Model: "test-model",
Message: api.Message{
Role: "assistant",
Content: "Hello there!",
},
Done: true,
DoneReason: "stop",
Metrics: api.Metrics{
PromptEvalCount: 10,
EvalCount: 5,
},
}
result := ToMessagesResponse("msg_123", resp)
if result.ID != "msg_123" {
t.Errorf("expected ID 'msg_123', got %q", result.ID)
}
if result.Type != "message" {
t.Errorf("expected type 'message', got %q", result.Type)
}
if result.Role != "assistant" {
t.Errorf("expected role 'assistant', got %q", result.Role)
}
if len(result.Content) != 1 {
t.Fatalf("expected 1 content block, got %d", len(result.Content))
}
if result.Content[0].Type != "text" || result.Content[0].Text != "Hello there!" {
t.Errorf("unexpected content: %+v", result.Content[0])
}
if result.StopReason != "end_turn" {
t.Errorf("expected stop_reason 'end_turn', got %q", result.StopReason)
}
if result.Usage.InputTokens != 10 || result.Usage.OutputTokens != 5 {
t.Errorf("unexpected usage: %+v", result.Usage)
}
}
func TestToMessagesResponse_WithToolCalls(t *testing.T) {
resp := api.ChatResponse{
Model: "test-model",
Message: api.Message{
Role: "assistant",
ToolCalls: []api.ToolCall{
{
ID: "call_123",
Function: api.ToolCallFunction{
Name: "get_weather",
Arguments: map[string]any{"location": "Paris"},
},
},
},
},
Done: true,
DoneReason: "stop",
}
result := ToMessagesResponse("msg_123", resp)
if len(result.Content) != 1 {
t.Fatalf("expected 1 content block, got %d", len(result.Content))
}
if result.Content[0].Type != "tool_use" {
t.Errorf("expected type 'tool_use', got %q", result.Content[0].Type)
}
if result.Content[0].ID != "call_123" {
t.Errorf("expected ID 'call_123', got %q", result.Content[0].ID)
}
if result.Content[0].Name != "get_weather" {
t.Errorf("expected name 'get_weather', got %q", result.Content[0].Name)
}
if result.StopReason != "tool_use" {
t.Errorf("expected stop_reason 'tool_use', got %q", result.StopReason)
}
}
func TestToMessagesResponse_WithThinking(t *testing.T) {
resp := api.ChatResponse{
Model: "test-model",
Message: api.Message{
Role: "assistant",
Content: "The answer is 42.",
Thinking: "Let me think about this...",
},
Done: true,
DoneReason: "stop",
}
result := ToMessagesResponse("msg_123", resp)
if len(result.Content) != 2 {
t.Fatalf("expected 2 content blocks, got %d", len(result.Content))
}
if result.Content[0].Type != "thinking" {
t.Errorf("expected first block type 'thinking', got %q", result.Content[0].Type)
}
if result.Content[0].Thinking != "Let me think about this..." {
t.Errorf("unexpected thinking content: %q", result.Content[0].Thinking)
}
if result.Content[1].Type != "text" {
t.Errorf("expected second block type 'text', got %q", result.Content[1].Type)
}
}
func TestMapStopReason(t *testing.T) {
tests := []struct {
reason string
hasToolCalls bool
want string
}{
{"stop", false, "end_turn"},
{"length", false, "max_tokens"},
{"stop", true, "tool_use"},
{"other", false, "stop_sequence"},
{"", false, ""},
}
for _, tt := range tests {
got := mapStopReason(tt.reason, tt.hasToolCalls)
if got != tt.want {
t.Errorf("mapStopReason(%q, %v) = %q, want %q", tt.reason, tt.hasToolCalls, got, tt.want)
}
}
}
func TestNewError(t *testing.T) {
tests := []struct {
code int
want string
}{
{400, "invalid_request_error"},
{401, "authentication_error"},
{403, "permission_error"},
{404, "not_found_error"},
{429, "rate_limit_error"},
{500, "api_error"},
{503, "overloaded_error"},
{529, "overloaded_error"},
}
for _, tt := range tests {
result := NewError(tt.code, "test message")
if result.Type != "error" {
t.Errorf("NewError(%d) type = %q, want 'error'", tt.code, result.Type)
}
if result.Error.Type != tt.want {
t.Errorf("NewError(%d) error.type = %q, want %q", tt.code, result.Error.Type, tt.want)
}
if result.Error.Message != "test message" {
t.Errorf("NewError(%d) message = %q, want 'test message'", tt.code, result.Error.Message)
}
if result.RequestID == "" {
t.Errorf("NewError(%d) request_id should not be empty", tt.code)
}
}
}
func TestGenerateMessageID(t *testing.T) {
id1 := GenerateMessageID()
id2 := GenerateMessageID()
if id1 == "" {
t.Error("GenerateMessageID returned empty string")
}
if id1 == id2 {
t.Error("GenerateMessageID returned duplicate IDs")
}
if len(id1) < 10 {
t.Errorf("GenerateMessageID returned short ID: %q", id1)
}
if id1[:4] != "msg_" {
t.Errorf("GenerateMessageID should start with 'msg_', got %q", id1[:4])
}
}
func TestStreamConverter_Basic(t *testing.T) {
conv := NewStreamConverter("msg_123", "test-model")
// First chunk
resp1 := api.ChatResponse{
Model: "test-model",
Message: api.Message{
Role: "assistant",
Content: "Hello",
},
Metrics: api.Metrics{PromptEvalCount: 10},
}
events1 := conv.Process(resp1)
if len(events1) < 3 {
t.Fatalf("expected at least 3 events for first chunk, got %d", len(events1))
}
// Should have message_start, content_block_start, content_block_delta
if events1[0].Event != "message_start" {
t.Errorf("expected first event 'message_start', got %q", events1[0].Event)
}
if events1[1].Event != "content_block_start" {
t.Errorf("expected second event 'content_block_start', got %q", events1[1].Event)
}
if events1[2].Event != "content_block_delta" {
t.Errorf("expected third event 'content_block_delta', got %q", events1[2].Event)
}
// Final chunk
resp2 := api.ChatResponse{
Model: "test-model",
Message: api.Message{
Role: "assistant",
Content: " world!",
},
Done: true,
DoneReason: "stop",
Metrics: api.Metrics{EvalCount: 5},
}
events2 := conv.Process(resp2)
// Should have content_block_delta, content_block_stop, message_delta, message_stop
hasStop := false
for _, e := range events2 {
if e.Event == "message_stop" {
hasStop = true
}
}
if !hasStop {
t.Error("expected message_stop event in final chunk")
}
}
func TestStreamConverter_WithToolCalls(t *testing.T) {
conv := NewStreamConverter("msg_123", "test-model")
resp := api.ChatResponse{
Model: "test-model",
Message: api.Message{
Role: "assistant",
ToolCalls: []api.ToolCall{
{
ID: "call_123",
Function: api.ToolCallFunction{
Name: "get_weather",
Arguments: map[string]any{"location": "Paris"},
},
},
},
},
Done: true,
DoneReason: "stop",
Metrics: api.Metrics{PromptEvalCount: 10, EvalCount: 5},
}
events := conv.Process(resp)
hasToolStart := false
hasToolDelta := false
for _, e := range events {
if e.Event == "content_block_start" {
if start, ok := e.Data.(ContentBlockStartEvent); ok {
if start.ContentBlock.Type == "tool_use" {
hasToolStart = true
}
}
}
if e.Event == "content_block_delta" {
if delta, ok := e.Data.(ContentBlockDeltaEvent); ok {
if delta.Delta.Type == "input_json_delta" {
hasToolDelta = true
}
}
}
}
if !hasToolStart {
t.Error("expected tool_use content_block_start event")
}
if !hasToolDelta {
t.Error("expected input_json_delta event")
}
}

View File

@@ -14,6 +14,7 @@
* [API Reference](https://docs.ollama.com/api)
* [Modelfile Reference](https://docs.ollama.com/modelfile)
* [OpenAI Compatibility](https://docs.ollama.com/api/openai-compatibility)
* [Anthropic Compatibility](./api/anthropic-compatibility.mdx)
### Resources

View File

@@ -0,0 +1,339 @@
---
title: Anthropic compatibility
---
Ollama provides compatibility with the [Anthropic Messages API](https://docs.anthropic.com/en/api/messages) to help connect existing applications to Ollama, including tools like Claude Code.
## Usage
### Environment variables
To use Ollama with tools that expect the Anthropic API (like Claude Code), set these environment variables:
```shell
export ANTHROPIC_BASE_URL=http://localhost:11434
export ANTHROPIC_API_KEY=ollama # required but ignored
```
### Simple `/v1/messages` example
<CodeGroup dropdown>
```python basic.py
import anthropic
client = anthropic.Anthropic(
base_url='http://localhost:11434',
api_key='ollama', # required but ignored
)
message = client.messages.create(
model='llama3.2:3b',
max_tokens=1024,
messages=[
{'role': 'user', 'content': 'Hello, how are you?'}
]
)
print(message.content[0].text)
```
```javascript basic.js
import Anthropic from "@anthropic-ai/sdk";
const anthropic = new Anthropic({
baseURL: "http://localhost:11434",
apiKey: "ollama", // required but ignored
});
const message = await anthropic.messages.create({
model: "llama3.2:3b",
max_tokens: 1024,
messages: [{ role: "user", content: "Hello, how are you?" }],
});
console.log(message.content[0].text);
```
```shell basic.sh
curl -X POST http://localhost:11434/v1/messages \
-H "Content-Type: application/json" \
-H "x-api-key: ollama" \
-H "anthropic-version: 2023-06-01" \
-d '{
"model": "llama3.2:3b",
"max_tokens": 1024,
"messages": [{ "role": "user", "content": "Hello, how are you?" }]
}'
```
</CodeGroup>
### Streaming example
<CodeGroup dropdown>
```python streaming.py
import anthropic
client = anthropic.Anthropic(
base_url='http://localhost:11434',
api_key='ollama',
)
with client.messages.stream(
model='llama3.2:3b',
max_tokens=1024,
messages=[{'role': 'user', 'content': 'Count from 1 to 10'}]
) as stream:
for text in stream.text_stream:
print(text, end='', flush=True)
```
```javascript streaming.js
import Anthropic from "@anthropic-ai/sdk";
const anthropic = new Anthropic({
baseURL: "http://localhost:11434",
apiKey: "ollama",
});
const stream = await anthropic.messages.stream({
model: "llama3.2:3b",
max_tokens: 1024,
messages: [{ role: "user", content: "Count from 1 to 10" }],
});
for await (const event of stream) {
if (
event.type === "content_block_delta" &&
event.delta.type === "text_delta"
) {
process.stdout.write(event.delta.text);
}
}
```
```shell streaming.sh
curl -X POST http://localhost:11434/v1/messages \
-H "Content-Type: application/json" \
-d '{
"model": "llama3.2:3b",
"max_tokens": 1024,
"stream": true,
"messages": [{ "role": "user", "content": "Count from 1 to 10" }]
}'
```
</CodeGroup>
### Tool calling example
<CodeGroup dropdown>
```python tools.py
import anthropic
client = anthropic.Anthropic(
base_url='http://localhost:11434',
api_key='ollama',
)
message = client.messages.create(
model='llama3.2:3b',
max_tokens=1024,
tools=[
{
'name': 'get_weather',
'description': 'Get the current weather in a location',
'input_schema': {
'type': 'object',
'properties': {
'location': {
'type': 'string',
'description': 'The city and state, e.g. San Francisco, CA'
}
},
'required': ['location']
}
}
],
messages=[{'role': 'user', 'content': "What's the weather in San Francisco?"}]
)
for block in message.content:
if block.type == 'tool_use':
print(f'Tool: {block.name}')
print(f'Input: {block.input}')
```
```shell tools.sh
curl -X POST http://localhost:11434/v1/messages \
-H "Content-Type: application/json" \
-d '{
"model": "llama3.2:3b",
"max_tokens": 1024,
"tools": [
{
"name": "get_weather",
"description": "Get the current weather in a location",
"input_schema": {
"type": "object",
"properties": {
"location": {
"type": "string",
"description": "The city and state"
}
},
"required": ["location"]
}
}
],
"messages": [{ "role": "user", "content": "What is the weather in San Francisco?" }]
}'
```
</CodeGroup>
## Using with Claude Code
[Claude Code](https://docs.anthropic.com/en/docs/claude-code) can be configured to use Ollama as its backend:
```shell
ANTHROPIC_BASE_URL=http://localhost:11434 ANTHROPIC_API_KEY=ollama claude --model llama3.2:3b
```
Or set the environment variables in your shell profile:
```shell
export ANTHROPIC_BASE_URL=http://localhost:11434
export ANTHROPIC_API_KEY=ollama
```
Then run Claude Code with any Ollama model:
```shell
claude --model llama3.2:3b
claude --model qwen3:8b
claude --model deepseek-r1:14b
```
## Endpoints
### `/v1/messages`
#### Supported features
- [x] Messages
- [x] Streaming
- [x] System prompts
- [x] Multi-turn conversations
- [x] Vision (images)
- [x] Tools (function calling)
- [x] Tool results
- [x] Thinking/extended thinking
#### Supported request fields
- [x] `model`
- [x] `max_tokens`
- [x] `messages`
- [x] Text `content`
- [x] Image `content` (base64)
- [x] Array of content blocks
- [x] `tool_use` blocks
- [x] `tool_result` blocks
- [x] `thinking` blocks
- [x] `system` (string or array)
- [x] `stream`
- [x] `temperature`
- [x] `top_p`
- [x] `top_k`
- [x] `stop_sequences`
- [x] `tools`
- [x] `thinking`
- [ ] `tool_choice`
- [ ] `metadata`
#### Supported response fields
- [x] `id`
- [x] `type`
- [x] `role`
- [x] `model`
- [x] `content` (text, tool_use, thinking blocks)
- [x] `stop_reason` (end_turn, max_tokens, tool_use)
- [x] `usage` (input_tokens, output_tokens)
#### Streaming events
- [x] `message_start`
- [x] `content_block_start`
- [x] `content_block_delta` (text_delta, input_json_delta, thinking_delta)
- [x] `content_block_stop`
- [x] `message_delta`
- [x] `message_stop`
- [x] `ping`
- [x] `error`
## Models
Before using a model, pull it locally with `ollama pull`:
```shell
ollama pull llama3.2:3b
```
### Default model names
For tooling that relies on default Anthropic model names such as `claude-3-5-sonnet`, use `ollama cp` to copy an existing model name:
```shell
ollama cp llama3.2:3b claude-3-5-sonnet
```
Afterwards, this new model name can be specified in the `model` field:
```shell
curl http://localhost:11434/v1/messages \
-H "Content-Type: application/json" \
-d '{
"model": "claude-3-5-sonnet",
"max_tokens": 1024,
"messages": [
{
"role": "user",
"content": "Hello!"
}
]
}'
```
## Differences from the Anthropic API
### Behavior differences
- API key is accepted but not validated
- `anthropic-version` header is accepted but not used
- Token counts are approximations based on the underlying model's tokenizer
### Not supported
The following Anthropic API features are not currently supported:
| Feature | Description |
|---------|-------------|
| `/v1/messages/count_tokens` | Token counting endpoint |
| `tool_choice` | Forcing specific tool use or disabling tools |
| `metadata` | Request metadata (user_id) |
| Prompt caching | `cache_control` blocks for caching prefixes |
| Batches API | `/v1/messages/batches` for async batch processing |
| Citations | `citations` content blocks |
| PDF support | `document` content blocks with PDF files |
| Server-sent errors | `error` events during streaming (errors return HTTP status) |
### Partial support
| Feature | Status |
|---------|--------|
| Image content | Base64 images supported; URL images not supported |
| Extended thinking | Basic support; `budget_tokens` accepted but not enforced |

View File

@@ -139,7 +139,8 @@
"/api/streaming",
"/api/usage",
"/api/errors",
"/api/openai-compatibility"
"/api/openai-compatibility",
"/api/anthropic-compatibility"
]
},
{

152
middleware/anthropic.go Normal file
View File

@@ -0,0 +1,152 @@
package middleware
import (
"bytes"
"encoding/json"
"fmt"
"io"
"net/http"
"github.com/gin-gonic/gin"
"github.com/ollama/ollama/anthropic"
"github.com/ollama/ollama/api"
)
// AnthropicWriter wraps the response writer to transform Ollama responses to Anthropic format
type AnthropicWriter struct {
BaseWriter
stream bool
id string
model string
converter *anthropic.StreamConverter
}
func (w *AnthropicWriter) writeError(data []byte) (int, error) {
var serr api.StatusError
err := json.Unmarshal(data, &serr)
if err != nil {
return 0, err
}
w.ResponseWriter.Header().Set("Content-Type", "application/json")
err = json.NewEncoder(w.ResponseWriter).Encode(anthropic.NewError(serr.StatusCode, serr.Error()))
if err != nil {
return 0, err
}
return len(data), nil
}
func (w *AnthropicWriter) writeEvent(eventType string, data any) error {
d, err := json.Marshal(data)
if err != nil {
return err
}
_, err = w.ResponseWriter.Write([]byte(fmt.Sprintf("event: %s\ndata: %s\n\n", eventType, d)))
if err != nil {
return err
}
if f, ok := w.ResponseWriter.(http.Flusher); ok {
f.Flush()
}
return nil
}
func (w *AnthropicWriter) writeResponse(data []byte) (int, error) {
var chatResponse api.ChatResponse
err := json.Unmarshal(data, &chatResponse)
if err != nil {
return 0, err
}
if w.stream {
w.ResponseWriter.Header().Set("Content-Type", "text/event-stream")
events := w.converter.Process(chatResponse)
for _, event := range events {
if err := w.writeEvent(event.Event, event.Data); err != nil {
return 0, err
}
}
return len(data), nil
}
// Non-streaming response
w.ResponseWriter.Header().Set("Content-Type", "application/json")
response := anthropic.ToMessagesResponse(w.id, chatResponse)
return len(data), json.NewEncoder(w.ResponseWriter).Encode(response)
}
func (w *AnthropicWriter) Write(data []byte) (int, error) {
code := w.ResponseWriter.Status()
if code != http.StatusOK {
return w.writeError(data)
}
return w.writeResponse(data)
}
// AnthropicMessagesMiddleware handles Anthropic Messages API requests
func AnthropicMessagesMiddleware() gin.HandlerFunc {
return func(c *gin.Context) {
var req anthropic.MessagesRequest
err := c.ShouldBindJSON(&req)
if err != nil {
c.AbortWithStatusJSON(http.StatusBadRequest, anthropic.NewError(http.StatusBadRequest, err.Error()))
return
}
// Validate required fields
if req.Model == "" {
c.AbortWithStatusJSON(http.StatusBadRequest, anthropic.NewError(http.StatusBadRequest, "model is required"))
return
}
if req.MaxTokens <= 0 {
c.AbortWithStatusJSON(http.StatusBadRequest, anthropic.NewError(http.StatusBadRequest, "max_tokens is required and must be positive"))
return
}
if len(req.Messages) == 0 {
c.AbortWithStatusJSON(http.StatusBadRequest, anthropic.NewError(http.StatusBadRequest, "messages is required"))
return
}
// Convert to internal format
chatReq, err := anthropic.FromMessagesRequest(req)
if err != nil {
c.AbortWithStatusJSON(http.StatusBadRequest, anthropic.NewError(http.StatusBadRequest, err.Error()))
return
}
var b bytes.Buffer
if err := json.NewEncoder(&b).Encode(chatReq); err != nil {
c.AbortWithStatusJSON(http.StatusInternalServerError, anthropic.NewError(http.StatusInternalServerError, err.Error()))
return
}
c.Request.Body = io.NopCloser(&b)
messageID := anthropic.GenerateMessageID()
w := &AnthropicWriter{
BaseWriter: BaseWriter{ResponseWriter: c.Writer},
stream: req.Stream,
id: messageID,
model: req.Model,
converter: anthropic.NewStreamConverter(messageID, req.Model),
}
// Set headers based on streaming mode
if req.Stream {
c.Writer.Header().Set("Content-Type", "text/event-stream")
c.Writer.Header().Set("Cache-Control", "no-cache")
c.Writer.Header().Set("Connection", "keep-alive")
}
c.Writer = w
c.Next()
}
}

View File

@@ -0,0 +1,487 @@
package middleware
import (
"bytes"
"encoding/json"
"io"
"net/http"
"net/http/httptest"
"strings"
"testing"
"github.com/gin-gonic/gin"
"github.com/google/go-cmp/cmp"
"github.com/ollama/ollama/anthropic"
"github.com/ollama/ollama/api"
)
func captureAnthropicRequest(capturedRequest any) gin.HandlerFunc {
return func(c *gin.Context) {
bodyBytes, _ := io.ReadAll(c.Request.Body)
c.Request.Body = io.NopCloser(bytes.NewReader(bodyBytes))
_ = json.Unmarshal(bodyBytes, capturedRequest)
c.Next()
}
}
func TestAnthropicMessagesMiddleware(t *testing.T) {
type testCase struct {
name string
body string
req api.ChatRequest
err anthropic.ErrorResponse
}
var capturedRequest *api.ChatRequest
stream := true
testCases := []testCase{
{
name: "basic message",
body: `{
"model": "test-model",
"max_tokens": 1024,
"messages": [
{"role": "user", "content": "Hello"}
]
}`,
req: api.ChatRequest{
Model: "test-model",
Messages: []api.Message{
{Role: "user", Content: "Hello"},
},
Options: map[string]any{"num_predict": 1024},
Stream: &False,
},
},
{
name: "with system prompt",
body: `{
"model": "test-model",
"max_tokens": 1024,
"system": "You are helpful.",
"messages": [
{"role": "user", "content": "Hello"}
]
}`,
req: api.ChatRequest{
Model: "test-model",
Messages: []api.Message{
{Role: "system", Content: "You are helpful."},
{Role: "user", Content: "Hello"},
},
Options: map[string]any{"num_predict": 1024},
Stream: &False,
},
},
{
name: "with options",
body: `{
"model": "test-model",
"max_tokens": 2048,
"temperature": 0.7,
"top_p": 0.9,
"top_k": 40,
"stop_sequences": ["\n", "END"],
"messages": [
{"role": "user", "content": "Hello"}
]
}`,
req: api.ChatRequest{
Model: "test-model",
Messages: []api.Message{
{Role: "user", Content: "Hello"},
},
Options: map[string]any{
"num_predict": 2048,
"temperature": 0.7,
"top_p": 0.9,
"top_k": 40,
"stop": []string{"\n", "END"},
},
Stream: &False,
},
},
{
name: "streaming",
body: `{
"model": "test-model",
"max_tokens": 1024,
"stream": true,
"messages": [
{"role": "user", "content": "Hello"}
]
}`,
req: api.ChatRequest{
Model: "test-model",
Messages: []api.Message{
{Role: "user", Content: "Hello"},
},
Options: map[string]any{"num_predict": 1024},
Stream: &stream,
},
},
{
name: "with tools",
body: `{
"model": "test-model",
"max_tokens": 1024,
"messages": [
{"role": "user", "content": "What's the weather?"}
],
"tools": [{
"name": "get_weather",
"description": "Get current weather",
"input_schema": {
"type": "object",
"properties": {
"location": {"type": "string"}
},
"required": ["location"]
}
}]
}`,
req: api.ChatRequest{
Model: "test-model",
Messages: []api.Message{
{Role: "user", Content: "What's the weather?"},
},
Tools: []api.Tool{
{
Type: "function",
Function: api.ToolFunction{
Name: "get_weather",
Description: "Get current weather",
Parameters: api.ToolFunctionParameters{
Type: "object",
Required: []string{"location"},
Properties: map[string]api.ToolProperty{
"location": {Type: api.PropertyType{"string"}},
},
},
},
},
},
Options: map[string]any{"num_predict": 1024},
Stream: &False,
},
},
{
name: "with tool result",
body: `{
"model": "test-model",
"max_tokens": 1024,
"messages": [
{"role": "user", "content": "What's the weather?"},
{"role": "assistant", "content": [
{"type": "tool_use", "id": "call_123", "name": "get_weather", "input": {"location": "Paris"}}
]},
{"role": "user", "content": [
{"type": "tool_result", "tool_use_id": "call_123", "content": "Sunny, 22°C"}
]}
]
}`,
req: api.ChatRequest{
Model: "test-model",
Messages: []api.Message{
{Role: "user", Content: "What's the weather?"},
{
Role: "assistant",
ToolCalls: []api.ToolCall{
{
ID: "call_123",
Function: api.ToolCallFunction{
Name: "get_weather",
Arguments: api.ToolCallFunctionArguments{"location": "Paris"},
},
},
},
},
{Role: "tool", Content: "Sunny, 22°C", ToolCallID: "call_123"},
},
Options: map[string]any{"num_predict": 1024},
Stream: &False,
},
},
{
name: "with thinking enabled",
body: `{
"model": "test-model",
"max_tokens": 1024,
"thinking": {"type": "enabled", "budget_tokens": 1000},
"messages": [
{"role": "user", "content": "Hello"}
]
}`,
req: api.ChatRequest{
Model: "test-model",
Messages: []api.Message{
{Role: "user", Content: "Hello"},
},
Options: map[string]any{"num_predict": 1024},
Stream: &False,
Think: &api.ThinkValue{Value: true},
},
},
{
name: "missing model error",
body: `{
"max_tokens": 1024,
"messages": [
{"role": "user", "content": "Hello"}
]
}`,
err: anthropic.ErrorResponse{
Type: "error",
Error: anthropic.Error{
Type: "invalid_request_error",
Message: "model is required",
},
},
},
{
name: "missing max_tokens error",
body: `{
"model": "test-model",
"messages": [
{"role": "user", "content": "Hello"}
]
}`,
err: anthropic.ErrorResponse{
Type: "error",
Error: anthropic.Error{
Type: "invalid_request_error",
Message: "max_tokens is required and must be positive",
},
},
},
{
name: "missing messages error",
body: `{
"model": "test-model",
"max_tokens": 1024
}`,
err: anthropic.ErrorResponse{
Type: "error",
Error: anthropic.Error{
Type: "invalid_request_error",
Message: "messages is required",
},
},
},
{
name: "tool_use missing id error",
body: `{
"model": "test-model",
"max_tokens": 1024,
"messages": [
{"role": "assistant", "content": [
{"type": "tool_use", "name": "test"}
]}
]
}`,
err: anthropic.ErrorResponse{
Type: "error",
Error: anthropic.Error{
Type: "invalid_request_error",
Message: "tool_use block missing required 'id' field",
},
},
},
}
endpoint := func(c *gin.Context) {
c.Status(http.StatusOK)
}
gin.SetMode(gin.TestMode)
router := gin.New()
router.Use(AnthropicMessagesMiddleware(), captureAnthropicRequest(&capturedRequest))
router.Handle(http.MethodPost, "/v1/messages", endpoint)
for _, tc := range testCases {
t.Run(tc.name, func(t *testing.T) {
req, _ := http.NewRequest(http.MethodPost, "/v1/messages", strings.NewReader(tc.body))
req.Header.Set("Content-Type", "application/json")
defer func() { capturedRequest = nil }()
resp := httptest.NewRecorder()
router.ServeHTTP(resp, req)
if tc.err.Type != "" {
// Expect error
if resp.Code == http.StatusOK {
t.Fatalf("expected error response, got 200 OK")
}
var errResp anthropic.ErrorResponse
if err := json.Unmarshal(resp.Body.Bytes(), &errResp); err != nil {
t.Fatalf("failed to unmarshal error: %v", err)
}
if errResp.Type != tc.err.Type {
t.Errorf("expected error type %q, got %q", tc.err.Type, errResp.Type)
}
if errResp.Error.Type != tc.err.Error.Type {
t.Errorf("expected error.type %q, got %q", tc.err.Error.Type, errResp.Error.Type)
}
if errResp.Error.Message != tc.err.Error.Message {
t.Errorf("expected error.message %q, got %q", tc.err.Error.Message, errResp.Error.Message)
}
return
}
if resp.Code != http.StatusOK {
t.Fatalf("unexpected status code: %d, body: %s", resp.Code, resp.Body.String())
}
if capturedRequest == nil {
t.Fatal("request was not captured")
}
// Compare relevant fields
if capturedRequest.Model != tc.req.Model {
t.Errorf("model mismatch: got %q, want %q", capturedRequest.Model, tc.req.Model)
}
if diff := cmp.Diff(tc.req.Messages, capturedRequest.Messages); diff != "" {
t.Errorf("messages mismatch (-want +got):\n%s", diff)
}
if tc.req.Stream != nil && capturedRequest.Stream != nil {
if *tc.req.Stream != *capturedRequest.Stream {
t.Errorf("stream mismatch: got %v, want %v", *capturedRequest.Stream, *tc.req.Stream)
}
}
if tc.req.Think != nil {
if capturedRequest.Think == nil {
t.Error("expected Think to be set")
} else if capturedRequest.Think.Value != tc.req.Think.Value {
t.Errorf("Think mismatch: got %v, want %v", capturedRequest.Think.Value, tc.req.Think.Value)
}
}
})
}
}
func TestAnthropicMessagesMiddleware_Headers(t *testing.T) {
gin.SetMode(gin.TestMode)
t.Run("streaming sets correct headers", func(t *testing.T) {
router := gin.New()
router.Use(AnthropicMessagesMiddleware())
router.POST("/v1/messages", func(c *gin.Context) {
// Check headers were set
if c.Writer.Header().Get("Content-Type") != "text/event-stream" {
t.Errorf("expected Content-Type text/event-stream, got %q", c.Writer.Header().Get("Content-Type"))
}
if c.Writer.Header().Get("Cache-Control") != "no-cache" {
t.Errorf("expected Cache-Control no-cache, got %q", c.Writer.Header().Get("Cache-Control"))
}
c.Status(http.StatusOK)
})
body := `{"model": "test", "max_tokens": 100, "stream": true, "messages": [{"role": "user", "content": "Hi"}]}`
req, _ := http.NewRequest(http.MethodPost, "/v1/messages", strings.NewReader(body))
req.Header.Set("Content-Type", "application/json")
resp := httptest.NewRecorder()
router.ServeHTTP(resp, req)
})
}
func TestAnthropicMessagesMiddleware_InvalidJSON(t *testing.T) {
gin.SetMode(gin.TestMode)
router := gin.New()
router.Use(AnthropicMessagesMiddleware())
router.POST("/v1/messages", func(c *gin.Context) {
c.Status(http.StatusOK)
})
req, _ := http.NewRequest(http.MethodPost, "/v1/messages", strings.NewReader(`{invalid json`))
req.Header.Set("Content-Type", "application/json")
resp := httptest.NewRecorder()
router.ServeHTTP(resp, req)
if resp.Code != http.StatusBadRequest {
t.Errorf("expected status 400, got %d", resp.Code)
}
var errResp anthropic.ErrorResponse
if err := json.Unmarshal(resp.Body.Bytes(), &errResp); err != nil {
t.Fatalf("failed to unmarshal error: %v", err)
}
if errResp.Type != "error" {
t.Errorf("expected type 'error', got %q", errResp.Type)
}
if errResp.Error.Type != "invalid_request_error" {
t.Errorf("expected error type 'invalid_request_error', got %q", errResp.Error.Type)
}
}
func TestAnthropicWriter_NonStreaming(t *testing.T) {
gin.SetMode(gin.TestMode)
router := gin.New()
router.Use(AnthropicMessagesMiddleware())
router.POST("/v1/messages", func(c *gin.Context) {
// Simulate Ollama response
resp := api.ChatResponse{
Model: "test-model",
Message: api.Message{
Role: "assistant",
Content: "Hello there!",
},
Done: true,
DoneReason: "stop",
Metrics: api.Metrics{
PromptEvalCount: 10,
EvalCount: 5,
},
}
data, _ := json.Marshal(resp)
c.Writer.WriteHeader(http.StatusOK)
_, _ = c.Writer.Write(data)
})
body := `{"model": "test-model", "max_tokens": 100, "messages": [{"role": "user", "content": "Hi"}]}`
req, _ := http.NewRequest(http.MethodPost, "/v1/messages", strings.NewReader(body))
req.Header.Set("Content-Type", "application/json")
resp := httptest.NewRecorder()
router.ServeHTTP(resp, req)
if resp.Code != http.StatusOK {
t.Fatalf("expected status 200, got %d", resp.Code)
}
var result anthropic.MessagesResponse
if err := json.Unmarshal(resp.Body.Bytes(), &result); err != nil {
t.Fatalf("failed to unmarshal response: %v", err)
}
if result.Type != "message" {
t.Errorf("expected type 'message', got %q", result.Type)
}
if result.Role != "assistant" {
t.Errorf("expected role 'assistant', got %q", result.Role)
}
if len(result.Content) != 1 {
t.Fatalf("expected 1 content block, got %d", len(result.Content))
}
if result.Content[0].Text != "Hello there!" {
t.Errorf("expected text 'Hello there!', got %q", result.Content[0].Text)
}
if result.StopReason != "end_turn" {
t.Errorf("expected stop_reason 'end_turn', got %q", result.StopReason)
}
if result.Usage.InputTokens != 10 {
t.Errorf("expected input_tokens 10, got %d", result.Usage.InputTokens)
}
if result.Usage.OutputTokens != 5 {
t.Errorf("expected output_tokens 5, got %d", result.Usage.OutputTokens)
}
}

View File

@@ -1535,6 +1535,9 @@ func (s *Server) GenerateRoutes(rc *ollama.Registry) (http.Handler, error) {
r.GET("/v1/models/:model", middleware.RetrieveMiddleware(), s.ShowHandler)
r.POST("/v1/responses", middleware.ResponsesMiddleware(), s.ChatHandler)
// Inference (Anthropic compatibility)
r.POST("/v1/messages", middleware.AnthropicMessagesMiddleware(), s.ChatHandler)
if rc != nil {
// wrap old with new
rs := &registry.Local{