Files
ollama/middleware/anthropic.go
Jeffrey Morgan 4eab60c1e2 Reapply "don't require pulling stubs for cloud models" again (#14608)
* Revert "Revert "Reapply "don't require pulling stubs for cloud models"" (#14606)"

This reverts commit 39982a954e.

* fix test + do cloud lookup only when seeing cloud models

---------

Co-authored-by: ParthSareen <parth.sareen@ollama.com>
2026-03-06 14:27:47 -08:00

957 lines
27 KiB
Go

package middleware
import (
"bytes"
"context"
"encoding/json"
"fmt"
"io"
"log/slog"
"net/http"
"strings"
"time"
"github.com/gin-gonic/gin"
"github.com/ollama/ollama/anthropic"
"github.com/ollama/ollama/api"
"github.com/ollama/ollama/envconfig"
internalcloud "github.com/ollama/ollama/internal/cloud"
"github.com/ollama/ollama/internal/modelref"
"github.com/ollama/ollama/logutil"
)
// AnthropicWriter wraps the response writer to transform Ollama responses to Anthropic format
type AnthropicWriter struct {
BaseWriter
stream bool
id string
converter *anthropic.StreamConverter
}
func (w *AnthropicWriter) writeError(data []byte) (int, error) {
var errData struct {
Error string `json:"error"`
}
if err := json.Unmarshal(data, &errData); err != nil {
return 0, err
}
w.ResponseWriter.Header().Set("Content-Type", "application/json")
err := json.NewEncoder(w.ResponseWriter).Encode(anthropic.NewError(w.Status(), errData.Error))
if err != nil {
return 0, err
}
return len(data), nil
}
func (w *AnthropicWriter) writeEvent(eventType string, data any) error {
return writeSSE(w.ResponseWriter, eventType, data)
}
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)
logutil.Trace("anthropic middleware: stream chunk", "resp", anthropic.TraceChatResponse(chatResponse), "events", len(events))
for _, event := range events {
if err := w.writeEvent(event.Event, event.Data); err != nil {
return 0, err
}
}
return len(data), nil
}
w.ResponseWriter.Header().Set("Content-Type", "application/json")
response := anthropic.ToMessagesResponse(w.id, chatResponse)
logutil.Trace("anthropic middleware: converted response", "resp", anthropic.TraceMessagesResponse(response))
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)
}
// WebSearchAnthropicWriter intercepts responses containing web_search tool calls,
// executes the search, re-invokes the model with results, and assembles the
// Anthropic-format response (server_tool_use + web_search_tool_result + text).
type WebSearchAnthropicWriter struct {
BaseWriter
newLoopContext func() (context.Context, context.CancelFunc)
inner *AnthropicWriter
req anthropic.MessagesRequest // original Anthropic request
chatReq *api.ChatRequest // converted Ollama request (for followup calls)
stream bool
estimatedInputTokens int
terminalSent bool
observedPromptEvalCount int
observedEvalCount int
loopInFlight bool
loopBaseInputTok int
loopBaseOutputTok int
loopResultCh chan webSearchLoopResult
streamMessageStarted bool
streamHasOpenBlock bool
streamOpenBlockIndex int
streamNextIndex int
}
const maxWebSearchLoops = 3
type webSearchLoopResult struct {
response anthropic.MessagesResponse
loopErr *webSearchLoopError
}
type webSearchLoopError struct {
code string
query string
usage anthropic.Usage
err error
}
func (e *webSearchLoopError) Error() string {
if e.err == nil {
return e.code
}
return fmt.Sprintf("%s: %v", e.code, e.err)
}
func (w *WebSearchAnthropicWriter) Write(data []byte) (int, error) {
if w.terminalSent {
return len(data), nil
}
code := w.Status()
if code != http.StatusOK {
return w.inner.writeError(data)
}
var chatResponse api.ChatResponse
if err := json.Unmarshal(data, &chatResponse); err != nil {
return 0, err
}
w.recordObservedUsage(chatResponse.Metrics)
if w.stream && w.loopInFlight {
if !chatResponse.Done {
return len(data), nil
}
if err := w.writeLoopResult(); err != nil {
return len(data), err
}
return len(data), nil
}
webSearchCall, hasWebSearch, hasOtherTools := findWebSearchToolCall(chatResponse.Message.ToolCalls)
logutil.Trace("anthropic middleware: upstream chunk",
"resp", anthropic.TraceChatResponse(chatResponse),
"web_search", hasWebSearch,
"other_tools", hasOtherTools,
)
if hasWebSearch && hasOtherTools {
// Prefer web_search if both server and client tools are present in one chunk.
slog.Debug("preferring web_search tool call over client tool calls in mixed tool response")
}
if !hasWebSearch {
if w.stream {
if err := w.writePassthroughStreamChunk(chatResponse); err != nil {
return 0, err
}
return len(data), nil
}
return w.inner.writeResponse(data)
}
if w.stream {
// Let the original generation continue to completion while web search runs in parallel.
logutil.Trace("anthropic middleware: starting async web_search loop",
"tool_call", anthropic.TraceToolCall(webSearchCall),
"resp", anthropic.TraceChatResponse(chatResponse),
)
w.startLoopWorker(chatResponse, webSearchCall)
if chatResponse.Done {
if err := w.writeLoopResult(); err != nil {
return len(data), err
}
}
return len(data), nil
}
loopCtx, cancel := w.startLoopContext()
defer cancel()
initialUsage := anthropic.Usage{
InputTokens: max(w.observedPromptEvalCount, chatResponse.Metrics.PromptEvalCount),
OutputTokens: max(w.observedEvalCount, chatResponse.Metrics.EvalCount),
}
logutil.Trace("anthropic middleware: starting sync web_search loop",
"tool_call", anthropic.TraceToolCall(webSearchCall),
"resp", anthropic.TraceChatResponse(chatResponse),
"usage", initialUsage,
)
response, loopErr := w.runWebSearchLoop(loopCtx, chatResponse, webSearchCall, initialUsage)
if loopErr != nil {
return len(data), w.sendError(loopErr.code, loopErr.query, loopErr.usage)
}
if err := w.writeTerminalResponse(response); err != nil {
return 0, err
}
return len(data), nil
}
func (w *WebSearchAnthropicWriter) runWebSearchLoop(ctx context.Context, initialResponse api.ChatResponse, initialToolCall api.ToolCall, initialUsage anthropic.Usage) (anthropic.MessagesResponse, *webSearchLoopError) {
followUpMessages := make([]api.Message, 0, len(w.chatReq.Messages)+maxWebSearchLoops*2)
followUpMessages = append(followUpMessages, w.chatReq.Messages...)
followUpTools := append(api.Tools(nil), w.chatReq.Tools...)
usage := initialUsage
logutil.TraceContext(ctx, "anthropic middleware: web_search loop init",
"model", w.req.Model,
"tool_call", anthropic.TraceToolCall(initialToolCall),
"messages", len(followUpMessages),
"tools", len(followUpTools),
"max_loops", maxWebSearchLoops,
)
currentResponse := initialResponse
currentToolCall := initialToolCall
var serverContent []anthropic.ContentBlock
if !isCloudModelName(w.req.Model) {
logutil.TraceContext(ctx, "anthropic middleware: web_search execution blocked", "reason", "non_cloud_model")
return anthropic.MessagesResponse{}, &webSearchLoopError{
code: "web_search_not_supported_for_local_models",
query: extractQueryFromToolCall(&initialToolCall),
usage: usage,
}
}
for loop := 1; loop <= maxWebSearchLoops; loop++ {
query := extractQueryFromToolCall(&currentToolCall)
logutil.TraceContext(ctx, "anthropic middleware: web_search loop iteration",
"loop", loop,
"query", anthropic.TraceTruncateString(query),
"messages", len(followUpMessages),
)
if query == "" {
return anthropic.MessagesResponse{}, &webSearchLoopError{
code: "invalid_request",
query: "",
usage: usage,
}
}
const defaultMaxResults = 5
searchResp, err := anthropic.WebSearch(ctx, query, defaultMaxResults)
if err != nil {
logutil.TraceContext(ctx, "anthropic middleware: web_search request failed",
"loop", loop,
"query", query,
"error", err,
)
return anthropic.MessagesResponse{}, &webSearchLoopError{
code: "unavailable",
query: query,
usage: usage,
err: err,
}
}
logutil.TraceContext(ctx, "anthropic middleware: web_search results",
"loop", loop,
"results", len(searchResp.Results),
)
toolUseID := loopServerToolUseID(w.inner.id, loop)
searchResults := anthropic.ConvertOllamaToAnthropicResults(searchResp)
serverContent = append(serverContent,
anthropic.ContentBlock{
Type: "server_tool_use",
ID: toolUseID,
Name: "web_search",
Input: map[string]any{"query": query},
},
anthropic.ContentBlock{
Type: "web_search_tool_result",
ToolUseID: toolUseID,
Content: searchResults,
},
)
assistantMsg := buildWebSearchAssistantMessage(currentResponse, currentToolCall)
toolResultMsg := api.Message{
Role: "tool",
Content: formatWebSearchResultsForToolMessage(searchResp.Results),
ToolCallID: currentToolCall.ID,
}
followUpMessages = append(followUpMessages, assistantMsg, toolResultMsg)
followUpResponse, err := w.callFollowUpChat(ctx, followUpMessages, followUpTools)
if err != nil {
logutil.TraceContext(ctx, "anthropic middleware: followup /api/chat failed",
"loop", loop,
"query", query,
"error", err,
)
return anthropic.MessagesResponse{}, &webSearchLoopError{
code: "api_error",
query: query,
usage: usage,
err: err,
}
}
logutil.TraceContext(ctx, "anthropic middleware: followup response",
"loop", loop,
"resp", anthropic.TraceChatResponse(followUpResponse),
)
usage.InputTokens += followUpResponse.Metrics.PromptEvalCount
usage.OutputTokens += followUpResponse.Metrics.EvalCount
nextToolCall, hasWebSearch, hasOtherTools := findWebSearchToolCall(followUpResponse.Message.ToolCalls)
if hasWebSearch && hasOtherTools {
// Prefer web_search if both server and client tools are present in one chunk.
slog.Debug("preferring web_search tool call over client tool calls in mixed followup response")
}
if !hasWebSearch {
finalResponse := w.combineServerAndFinalContent(serverContent, followUpResponse, usage)
logutil.TraceContext(ctx, "anthropic middleware: web_search loop complete",
"loop", loop,
"resp", anthropic.TraceMessagesResponse(finalResponse),
)
return finalResponse, nil
}
currentResponse = followUpResponse
currentToolCall = nextToolCall
}
maxLoopQuery := extractQueryFromToolCall(&currentToolCall)
maxLoopToolUseID := loopServerToolUseID(w.inner.id, maxWebSearchLoops+1)
serverContent = append(serverContent,
anthropic.ContentBlock{
Type: "server_tool_use",
ID: maxLoopToolUseID,
Name: "web_search",
Input: map[string]any{"query": maxLoopQuery},
},
anthropic.ContentBlock{
Type: "web_search_tool_result",
ToolUseID: maxLoopToolUseID,
Content: anthropic.WebSearchToolResultError{
Type: "web_search_tool_result_error",
ErrorCode: "max_uses_exceeded",
},
},
)
maxResponse := anthropic.MessagesResponse{
ID: w.inner.id,
Type: "message",
Role: "assistant",
Model: w.req.Model,
Content: serverContent,
StopReason: "end_turn",
Usage: usage,
}
logutil.TraceContext(ctx, "anthropic middleware: web_search loop max reached",
"resp", anthropic.TraceMessagesResponse(maxResponse),
)
return maxResponse, nil
}
func (w *WebSearchAnthropicWriter) startLoopWorker(initialResponse api.ChatResponse, initialToolCall api.ToolCall) {
if w.loopInFlight {
return
}
initialUsage := anthropic.Usage{
InputTokens: max(w.observedPromptEvalCount, initialResponse.Metrics.PromptEvalCount),
OutputTokens: max(w.observedEvalCount, initialResponse.Metrics.EvalCount),
}
w.loopBaseInputTok = initialUsage.InputTokens
w.loopBaseOutputTok = initialUsage.OutputTokens
w.loopResultCh = make(chan webSearchLoopResult, 1)
w.loopInFlight = true
logutil.Trace("anthropic middleware: loop worker started",
"usage", initialUsage,
"tool_call", anthropic.TraceToolCall(initialToolCall),
)
go func() {
ctx, cancel := w.startLoopContext()
defer cancel()
response, loopErr := w.runWebSearchLoop(ctx, initialResponse, initialToolCall, initialUsage)
w.loopResultCh <- webSearchLoopResult{
response: response,
loopErr: loopErr,
}
}()
}
func (w *WebSearchAnthropicWriter) writeLoopResult() error {
if w.loopResultCh == nil {
return w.sendError("api_error", "", w.currentObservedUsage())
}
result := <-w.loopResultCh
w.loopResultCh = nil
w.loopInFlight = false
if result.loopErr != nil {
logutil.Trace("anthropic middleware: loop worker returned error",
"code", result.loopErr.code,
"query", result.loopErr.query,
"usage", result.loopErr.usage,
"error", result.loopErr.err,
)
usage := result.loopErr.usage
w.applyObservedUsageDeltaToUsage(&usage)
return w.sendError(result.loopErr.code, result.loopErr.query, usage)
}
logutil.Trace("anthropic middleware: loop worker done", "resp", anthropic.TraceMessagesResponse(result.response))
w.applyObservedUsageDelta(&result.response)
return w.writeTerminalResponse(result.response)
}
func (w *WebSearchAnthropicWriter) applyObservedUsageDelta(response *anthropic.MessagesResponse) {
w.applyObservedUsageDeltaToUsage(&response.Usage)
}
func (w *WebSearchAnthropicWriter) recordObservedUsage(metrics api.Metrics) {
if metrics.PromptEvalCount > w.observedPromptEvalCount {
w.observedPromptEvalCount = metrics.PromptEvalCount
}
if metrics.EvalCount > w.observedEvalCount {
w.observedEvalCount = metrics.EvalCount
}
}
func (w *WebSearchAnthropicWriter) applyObservedUsageDeltaToUsage(usage *anthropic.Usage) {
if deltaIn := w.observedPromptEvalCount - w.loopBaseInputTok; deltaIn > 0 {
usage.InputTokens += deltaIn
}
if deltaOut := w.observedEvalCount - w.loopBaseOutputTok; deltaOut > 0 {
usage.OutputTokens += deltaOut
}
}
func (w *WebSearchAnthropicWriter) currentObservedUsage() anthropic.Usage {
return anthropic.Usage{
InputTokens: w.observedPromptEvalCount,
OutputTokens: w.observedEvalCount,
}
}
func (w *WebSearchAnthropicWriter) startLoopContext() (context.Context, context.CancelFunc) {
if w.newLoopContext != nil {
return w.newLoopContext()
}
return context.WithTimeout(context.Background(), 5*time.Minute)
}
func (w *WebSearchAnthropicWriter) combineServerAndFinalContent(serverContent []anthropic.ContentBlock, finalResponse api.ChatResponse, usage anthropic.Usage) anthropic.MessagesResponse {
converted := anthropic.ToMessagesResponse(w.inner.id, finalResponse)
content := make([]anthropic.ContentBlock, 0, len(serverContent)+len(converted.Content))
content = append(content, serverContent...)
content = append(content, converted.Content...)
return anthropic.MessagesResponse{
ID: w.inner.id,
Type: "message",
Role: "assistant",
Model: w.req.Model,
Content: content,
StopReason: converted.StopReason,
StopSequence: converted.StopSequence,
Usage: usage,
}
}
func buildWebSearchAssistantMessage(response api.ChatResponse, webSearchCall api.ToolCall) api.Message {
assistantMsg := api.Message{
Role: "assistant",
ToolCalls: []api.ToolCall{webSearchCall},
}
if response.Message.Content != "" {
assistantMsg.Content = response.Message.Content
}
if response.Message.Thinking != "" {
assistantMsg.Thinking = response.Message.Thinking
}
return assistantMsg
}
func formatWebSearchResultsForToolMessage(results []anthropic.OllamaWebSearchResult) string {
var resultText strings.Builder
for _, r := range results {
fmt.Fprintf(&resultText, "Title: %s\nURL: %s\n", r.Title, r.URL)
if r.Content != "" {
fmt.Fprintf(&resultText, "Content: %s\n", r.Content)
}
resultText.WriteString("\n")
}
return resultText.String()
}
func findWebSearchToolCall(toolCalls []api.ToolCall) (api.ToolCall, bool, bool) {
var webSearchCall api.ToolCall
hasWebSearch := false
hasOtherTools := false
for _, toolCall := range toolCalls {
if toolCall.Function.Name == "web_search" {
if !hasWebSearch {
webSearchCall = toolCall
hasWebSearch = true
}
continue
}
hasOtherTools = true
}
return webSearchCall, hasWebSearch, hasOtherTools
}
func loopServerToolUseID(messageID string, loop int) string {
base := serverToolUseID(messageID)
if loop <= 1 {
return base
}
return fmt.Sprintf("%s_%d", base, loop)
}
func (w *WebSearchAnthropicWriter) callFollowUpChat(ctx context.Context, messages []api.Message, tools api.Tools) (api.ChatResponse, error) {
streaming := false
followUp := api.ChatRequest{
Model: w.chatReq.Model,
Messages: messages,
Stream: &streaming,
Tools: tools,
Options: w.chatReq.Options,
}
body, err := json.Marshal(followUp)
if err != nil {
return api.ChatResponse{}, err
}
chatURL := envconfig.Host().String() + "/api/chat"
logutil.TraceContext(ctx, "anthropic middleware: followup request",
"url", chatURL,
"req", anthropic.TraceChatRequest(&followUp),
)
httpReq, err := http.NewRequestWithContext(ctx, "POST", chatURL, bytes.NewReader(body))
if err != nil {
return api.ChatResponse{}, err
}
httpReq.Header.Set("Content-Type", "application/json")
resp, err := http.DefaultClient.Do(httpReq)
if err != nil {
return api.ChatResponse{}, err
}
defer resp.Body.Close()
if resp.StatusCode != http.StatusOK {
respBody, _ := io.ReadAll(resp.Body)
logutil.TraceContext(ctx, "anthropic middleware: followup non-200 response",
"status", resp.StatusCode,
"response", strings.TrimSpace(string(respBody)),
)
return api.ChatResponse{}, fmt.Errorf("followup /api/chat returned status %d: %s", resp.StatusCode, strings.TrimSpace(string(respBody)))
}
var chatResp api.ChatResponse
if err := json.NewDecoder(resp.Body).Decode(&chatResp); err != nil {
return api.ChatResponse{}, err
}
logutil.TraceContext(ctx, "anthropic middleware: followup decoded", "resp", anthropic.TraceChatResponse(chatResp))
return chatResp, nil
}
func (w *WebSearchAnthropicWriter) writePassthroughStreamChunk(chatResponse api.ChatResponse) error {
events := w.inner.converter.Process(chatResponse)
for _, event := range events {
switch e := event.Data.(type) {
case anthropic.MessageStartEvent:
w.streamMessageStarted = true
case anthropic.ContentBlockStartEvent:
w.streamHasOpenBlock = true
w.streamOpenBlockIndex = e.Index
if e.Index+1 > w.streamNextIndex {
w.streamNextIndex = e.Index + 1
}
case anthropic.ContentBlockStopEvent:
if w.streamHasOpenBlock && w.streamOpenBlockIndex == e.Index {
w.streamHasOpenBlock = false
}
if e.Index+1 > w.streamNextIndex {
w.streamNextIndex = e.Index + 1
}
case anthropic.MessageStopEvent:
w.terminalSent = true
}
if err := writeSSE(w.ResponseWriter, event.Event, event.Data); err != nil {
return err
}
}
return nil
}
func (w *WebSearchAnthropicWriter) ensureStreamMessageStart(usage anthropic.Usage) error {
if w.streamMessageStarted {
return nil
}
inputTokens := usage.InputTokens
if inputTokens == 0 {
inputTokens = w.estimatedInputTokens
}
if err := writeSSE(w.ResponseWriter, "message_start", anthropic.MessageStartEvent{
Type: "message_start",
Message: anthropic.MessagesResponse{
ID: w.inner.id,
Type: "message",
Role: "assistant",
Model: w.req.Model,
Content: []anthropic.ContentBlock{},
Usage: anthropic.Usage{
InputTokens: inputTokens,
},
},
}); err != nil {
return err
}
w.streamMessageStarted = true
return nil
}
func (w *WebSearchAnthropicWriter) closeOpenStreamBlock() error {
if !w.streamHasOpenBlock {
return nil
}
if err := writeSSE(w.ResponseWriter, "content_block_stop", anthropic.ContentBlockStopEvent{
Type: "content_block_stop",
Index: w.streamOpenBlockIndex,
}); err != nil {
return err
}
if w.streamOpenBlockIndex+1 > w.streamNextIndex {
w.streamNextIndex = w.streamOpenBlockIndex + 1
}
w.streamHasOpenBlock = false
return nil
}
func (w *WebSearchAnthropicWriter) writeStreamContentBlocks(content []anthropic.ContentBlock) error {
for _, block := range content {
index := w.streamNextIndex
if block.Type == "text" {
emptyText := ""
if err := writeSSE(w.ResponseWriter, "content_block_start", anthropic.ContentBlockStartEvent{
Type: "content_block_start",
Index: index,
ContentBlock: anthropic.ContentBlock{
Type: "text",
Text: &emptyText,
},
}); err != nil {
return err
}
text := ""
if block.Text != nil {
text = *block.Text
}
if err := writeSSE(w.ResponseWriter, "content_block_delta", anthropic.ContentBlockDeltaEvent{
Type: "content_block_delta",
Index: index,
Delta: anthropic.Delta{
Type: "text_delta",
Text: text,
},
}); err != nil {
return err
}
} else {
if err := writeSSE(w.ResponseWriter, "content_block_start", anthropic.ContentBlockStartEvent{
Type: "content_block_start",
Index: index,
ContentBlock: block,
}); err != nil {
return err
}
}
if err := writeSSE(w.ResponseWriter, "content_block_stop", anthropic.ContentBlockStopEvent{
Type: "content_block_stop",
Index: index,
}); err != nil {
return err
}
w.streamNextIndex++
}
return nil
}
func (w *WebSearchAnthropicWriter) writeTerminalResponse(response anthropic.MessagesResponse) error {
if w.terminalSent {
return nil
}
if !w.stream {
w.ResponseWriter.Header().Set("Content-Type", "application/json")
if err := json.NewEncoder(w.ResponseWriter).Encode(response); err != nil {
return err
}
w.terminalSent = true
return nil
}
if err := w.ensureStreamMessageStart(response.Usage); err != nil {
return err
}
if err := w.closeOpenStreamBlock(); err != nil {
return err
}
if err := w.writeStreamContentBlocks(response.Content); err != nil {
return err
}
if err := writeSSE(w.ResponseWriter, "message_delta", anthropic.MessageDeltaEvent{
Type: "message_delta",
Delta: anthropic.MessageDelta{
StopReason: response.StopReason,
},
Usage: anthropic.DeltaUsage{
InputTokens: response.Usage.InputTokens,
OutputTokens: response.Usage.OutputTokens,
},
}); err != nil {
return err
}
if err := writeSSE(w.ResponseWriter, "message_stop", anthropic.MessageStopEvent{
Type: "message_stop",
}); err != nil {
return err
}
w.terminalSent = true
return nil
}
// streamResponse emits a complete MessagesResponse as SSE events.
func (w *WebSearchAnthropicWriter) streamResponse(response anthropic.MessagesResponse) error {
return w.writeTerminalResponse(response)
}
func (w *WebSearchAnthropicWriter) webSearchErrorResponse(errorCode, query string, usage anthropic.Usage) anthropic.MessagesResponse {
toolUseID := serverToolUseID(w.inner.id)
return anthropic.MessagesResponse{
ID: w.inner.id,
Type: "message",
Role: "assistant",
Model: w.req.Model,
Content: []anthropic.ContentBlock{
{
Type: "server_tool_use",
ID: toolUseID,
Name: "web_search",
Input: map[string]any{"query": query},
},
{
Type: "web_search_tool_result",
ToolUseID: toolUseID,
Content: anthropic.WebSearchToolResultError{
Type: "web_search_tool_result_error",
ErrorCode: errorCode,
},
},
},
StopReason: "end_turn",
Usage: usage,
}
}
// sendError sends a web search error response.
func (w *WebSearchAnthropicWriter) sendError(errorCode, query string, usage anthropic.Usage) error {
response := w.webSearchErrorResponse(errorCode, query, usage)
logutil.Trace("anthropic middleware: web_search error", "code", errorCode, "query", query, "usage", usage)
return w.writeTerminalResponse(response)
}
// AnthropicMessagesMiddleware handles Anthropic Messages API requests
func AnthropicMessagesMiddleware() gin.HandlerFunc {
return func(c *gin.Context) {
requestCtx := c.Request.Context()
var req anthropic.MessagesRequest
err := c.ShouldBindJSON(&req)
if err != nil {
c.AbortWithStatusJSON(http.StatusBadRequest, anthropic.NewError(http.StatusBadRequest, err.Error()))
return
}
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
}
chatReq, err := anthropic.FromMessagesRequest(req)
if err != nil {
c.AbortWithStatusJSON(http.StatusBadRequest, anthropic.NewError(http.StatusBadRequest, err.Error()))
return
}
// Set think to nil when being used with Anthropic API to connect to tools like claude code
c.Set("relax_thinking", true)
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()
// Estimate input tokens for streaming (actual count not available until generation completes)
estimatedTokens := anthropic.EstimateInputTokens(req)
innerWriter := &AnthropicWriter{
BaseWriter: BaseWriter{ResponseWriter: c.Writer},
stream: req.Stream,
id: messageID,
converter: anthropic.NewStreamConverter(messageID, req.Model, estimatedTokens),
}
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")
}
if hasWebSearchTool(req.Tools) {
// Guard against runtime cloud-disable policy (OLLAMA_NO_CLOUD/server.json)
// for cloud models. Local models may still receive web_search tool definitions;
// execution is validated when the model actually emits a web_search tool call.
if isCloudModelName(req.Model) {
if disabled, _ := internalcloud.Status(); disabled {
c.AbortWithStatusJSON(http.StatusForbidden, anthropic.NewError(http.StatusForbidden, internalcloud.DisabledError("web search is unavailable")))
return
}
}
c.Writer = &WebSearchAnthropicWriter{
BaseWriter: BaseWriter{ResponseWriter: c.Writer},
newLoopContext: func() (context.Context, context.CancelFunc) {
return context.WithTimeout(requestCtx, 5*time.Minute)
},
inner: innerWriter,
req: req,
chatReq: chatReq,
stream: req.Stream,
estimatedInputTokens: estimatedTokens,
}
} else {
c.Writer = innerWriter
}
c.Next()
}
}
// hasWebSearchTool checks if the request tools include a web_search tool
func hasWebSearchTool(tools []anthropic.Tool) bool {
for _, tool := range tools {
if strings.HasPrefix(tool.Type, "web_search") {
return true
}
}
return false
}
func isCloudModelName(name string) bool {
return modelref.HasExplicitCloudSource(name)
}
// extractQueryFromToolCall extracts the search query from a web_search tool call
func extractQueryFromToolCall(tc *api.ToolCall) string {
q, ok := tc.Function.Arguments.Get("query")
if !ok {
return ""
}
if s, ok := q.(string); ok {
return s
}
return ""
}
// writeSSE writes a Server-Sent Event
func writeSSE(w http.ResponseWriter, eventType string, data any) error {
d, err := json.Marshal(data)
if err != nil {
return err
}
if _, err := fmt.Fprintf(w, "event: %s\ndata: %s\n\n", eventType, d); err != nil {
return err
}
if f, ok := w.(http.Flusher); ok {
f.Flush()
}
return nil
}
// serverToolUseID derives a server tool use ID from a message ID
func serverToolUseID(messageID string) string {
return "srvtoolu_" + strings.TrimPrefix(messageID, "msg_")
}