feat: add tool/function calling support to Anthropic Messages API (#7956)

* Initial plan * Add tool/function calling schema support to Anthropic Messages API Co-authored-by: mudler <2420543+mudler@users.noreply.github.com> * Add E2E tests for Anthropic tool calling Co-authored-by: mudler <2420543+mudler@users.noreply.github.com> * Make tool calling tests require model to use tools - First test now expects hasToolUse to be true with clear error message - Third test now expects toolUseID to be non-empty (removed conditional) - Both tests will now fail if model doesn't call the expected tools Co-authored-by: mudler <2420543+mudler@users.noreply.github.com> * Add E2E test for tool calling with streaming responses - Tests that streaming events are properly emitted (content_block_start/delta/stop) - Verifies tool_use blocks are accumulated correctly in streaming mode - Ensures model calls tools and stop_reason is set to tool_use Co-authored-by: mudler <2420543+mudler@users.noreply.github.com> --------- Co-authored-by: copilot-swe-agent[bot] <198982749+Copilot@users.noreply.github.com> Co-authored-by: mudler <2420543+mudler@users.noreply.github.com>
2026-07-14 18:23:55 -04:00 · 2026-01-10 18:44:22 +01:00
parent 84234e531f
commit 5ca8f0aea0
4 changed files with 569 additions and 33 deletions
--- a/core/http/endpoints/anthropic/messages.go
+++ b/core/http/endpoints/anthropic/messages.go
@@ -11,6 +11,7 @@ import (
 	"github.com/mudler/LocalAI/core/http/middleware"
 	"github.com/mudler/LocalAI/core/schema"
 	"github.com/mudler/LocalAI/core/templates"
+	"github.com/mudler/LocalAI/pkg/functions"
 	"github.com/mudler/LocalAI/pkg/model"
 	"github.com/mudler/xlog"
 )
@@ -44,6 +45,9 @@ func MessagesEndpoint(cl *config.ModelConfigLoader, ml *model.ModelLoader, evalu
 		// Convert Anthropic messages to OpenAI format for internal processing
 		openAIMessages := convertAnthropicToOpenAIMessages(input)

+		// Convert Anthropic tools to internal Functions format
+		funcs, shouldUseFn := convertAnthropicTools(input, cfg)
+
 		// Create an OpenAI-compatible request for internal processing
 		openAIReq := &schema.OpenAIRequest{
 			PredictionOptions: schema.PredictionOptions{
@@ -79,19 +83,19 @@ func MessagesEndpoint(cl *config.ModelConfigLoader, ml *model.ModelLoader, evalu
 			cfg.StopWords = append(cfg.StopWords, input.StopSequences...)
 		}

-		// Template the prompt
-		predInput := evaluator.TemplateMessages(*openAIReq, openAIReq.Messages, cfg, nil, false)
+		// Template the prompt with tools if available
+		predInput := evaluator.TemplateMessages(*openAIReq, openAIReq.Messages, cfg, funcs, shouldUseFn)
 		xlog.Debug("Anthropic Messages - Prompt (after templating)", "prompt", predInput)

 		if input.Stream {
-			return handleAnthropicStream(c, id, input, cfg, ml, predInput)
+			return handleAnthropicStream(c, id, input, cfg, ml, predInput, openAIReq, funcs, shouldUseFn)
 		}

-		return handleAnthropicNonStream(c, id, input, cfg, ml, predInput, openAIReq)
+		return handleAnthropicNonStream(c, id, input, cfg, ml, predInput, openAIReq, funcs, shouldUseFn)
 	}
 }

-func handleAnthropicNonStream(c echo.Context, id string, input *schema.AnthropicRequest, cfg *config.ModelConfig, ml *model.ModelLoader, predInput string, openAIReq *schema.OpenAIRequest) error {
+func handleAnthropicNonStream(c echo.Context, id string, input *schema.AnthropicRequest, cfg *config.ModelConfig, ml *model.ModelLoader, predInput string, openAIReq *schema.OpenAIRequest, funcs functions.Functions, shouldUseFn bool) error {
 	images := []string{}
 	for _, m := range openAIReq.Messages {
 		images = append(images, m.StringImages...)
@@ -111,7 +115,45 @@ func handleAnthropicNonStream(c echo.Context, id string, input *schema.Anthropic
 	}

 	result := backend.Finetune(*cfg, predInput, prediction.Response)
-	stopReason := "end_turn"
+	
+	// Check if the result contains tool calls
+	toolCalls := functions.ParseFunctionCall(result, cfg.FunctionsConfig)
+	
+	var contentBlocks []schema.AnthropicContentBlock
+	var stopReason string
+	
+	if shouldUseFn && len(toolCalls) > 0 {
+		// Model wants to use tools
+		stopReason = "tool_use"
+		for _, tc := range toolCalls {
+			// Parse arguments as JSON
+			var inputArgs map[string]interface{}
+			if err := json.Unmarshal([]byte(tc.Arguments), &inputArgs); err != nil {
+				xlog.Warn("Failed to parse tool call arguments as JSON", "error", err, "args", tc.Arguments)
+				inputArgs = map[string]interface{}{"raw": tc.Arguments}
+			}
+			
+			contentBlocks = append(contentBlocks, schema.AnthropicContentBlock{
+				Type:  "tool_use",
+				ID:    fmt.Sprintf("toolu_%s_%d", id, len(contentBlocks)),
+				Name:  tc.Name,
+				Input: inputArgs,
+			})
+		}
+		
+		// Add any text content before the tool calls
+		textContent := functions.ParseTextContent(result, cfg.FunctionsConfig)
+		if textContent != "" {
+			// Prepend text block
+			contentBlocks = append([]schema.AnthropicContentBlock{{Type: "text", Text: textContent}}, contentBlocks...)
+		}
+	} else {
+		// Normal text response
+		stopReason = "end_turn"
+		contentBlocks = []schema.AnthropicContentBlock{
+			{Type: "text", Text: result},
+		}
+	}

 	resp := &schema.AnthropicResponse{
 		ID:         fmt.Sprintf("msg_%s", id),
@@ -119,9 +161,7 @@ func handleAnthropicNonStream(c echo.Context, id string, input *schema.Anthropic
 		Role:       "assistant",
 		Model:      input.Model,
 		StopReason: &stopReason,
-		Content: []schema.AnthropicContentBlock{
-			{Type: "text", Text: result},
-		},
+		Content:    contentBlocks,
 		Usage: schema.AnthropicUsage{
 			InputTokens:  prediction.Usage.Prompt,
 			OutputTokens: prediction.Usage.Completion,
@@ -135,13 +175,13 @@ func handleAnthropicNonStream(c echo.Context, id string, input *schema.Anthropic
 	return c.JSON(200, resp)
 }

-func handleAnthropicStream(c echo.Context, id string, input *schema.AnthropicRequest, cfg *config.ModelConfig, ml *model.ModelLoader, predInput string) error {
+func handleAnthropicStream(c echo.Context, id string, input *schema.AnthropicRequest, cfg *config.ModelConfig, ml *model.ModelLoader, predInput string, openAIReq *schema.OpenAIRequest, funcs functions.Functions, shouldUseFn bool) error {
 	c.Response().Header().Set("Content-Type", "text/event-stream")
 	c.Response().Header().Set("Cache-Control", "no-cache")
 	c.Response().Header().Set("Connection", "keep-alive")

 	// Create OpenAI messages for inference
-	openAIMessages := convertAnthropicToOpenAIMessages(input)
+	openAIMessages := openAIReq.Messages

 	images := []string{}
 	for _, m := range openAIMessages {
@@ -162,25 +202,93 @@ func handleAnthropicStream(c echo.Context, id string, input *schema.AnthropicReq
 	}
 	sendAnthropicSSE(c, messageStart)

-	// Send content_block_start event
+	// Track accumulated content for tool call detection
+	accumulatedContent := ""
+	currentBlockIndex := 0
+	inToolCall := false
+	toolCallsEmitted := 0
+	
+	// Send initial content_block_start event
 	contentBlockStart := schema.AnthropicStreamEvent{
 		Type:         "content_block_start",
-		Index:        0,
+		Index:        currentBlockIndex,
 		ContentBlock: &schema.AnthropicContentBlock{Type: "text", Text: ""},
 	}
 	sendAnthropicSSE(c, contentBlockStart)

 	// Stream content deltas
 	tokenCallback := func(token string, usage backend.TokenUsage) bool {
-		delta := schema.AnthropicStreamEvent{
-			Type:  "content_block_delta",
-			Index: 0,
-			Delta: &schema.AnthropicStreamDelta{
-				Type: "text_delta",
-				Text: token,
-			},
+		accumulatedContent += token
+		
+		// If we're using functions, try to detect tool calls incrementally
+		if shouldUseFn {
+			cleanedResult := functions.CleanupLLMResult(accumulatedContent, cfg.FunctionsConfig)
+			
+			// Try parsing for tool calls
+			toolCalls := functions.ParseFunctionCall(cleanedResult, cfg.FunctionsConfig)
+			
+			// If we detected new tool calls and haven't emitted them yet
+			if len(toolCalls) > toolCallsEmitted {
+				// Stop the current text block if we were in one
+				if !inToolCall && currentBlockIndex == 0 {
+					sendAnthropicSSE(c, schema.AnthropicStreamEvent{
+						Type:  "content_block_stop",
+						Index: currentBlockIndex,
+					})
+					currentBlockIndex++
+					inToolCall = true
+				}
+				
+				// Emit new tool calls
+				for i := toolCallsEmitted; i < len(toolCalls); i++ {
+					tc := toolCalls[i]
+					
+					// Send content_block_start for tool_use
+					sendAnthropicSSE(c, schema.AnthropicStreamEvent{
+						Type:  "content_block_start",
+						Index: currentBlockIndex,
+						ContentBlock: &schema.AnthropicContentBlock{
+							Type: "tool_use",
+							ID:   fmt.Sprintf("toolu_%s_%d", id, i),
+							Name: tc.Name,
+						},
+					})
+					
+					// Send input_json_delta with the arguments
+					sendAnthropicSSE(c, schema.AnthropicStreamEvent{
+						Type:  "content_block_delta",
+						Index: currentBlockIndex,
+						Delta: &schema.AnthropicStreamDelta{
+							Type:        "input_json_delta",
+							PartialJSON: tc.Arguments,
+						},
+					})
+					
+					// Send content_block_stop
+					sendAnthropicSSE(c, schema.AnthropicStreamEvent{
+						Type:  "content_block_stop",
+						Index: currentBlockIndex,
+					})
+					
+					currentBlockIndex++
+				}
+				toolCallsEmitted = len(toolCalls)
+				return true
+			}
+		}
+		
+		// Send regular text delta if not in tool call mode
+		if !inToolCall {
+			delta := schema.AnthropicStreamEvent{
+				Type:  "content_block_delta",
+				Index: 0,
+				Delta: &schema.AnthropicStreamDelta{
+					Type: "text_delta",
+					Text: token,
+				},
+			}
+			sendAnthropicSSE(c, delta)
 		}
-		sendAnthropicSSE(c, delta)
 		return true
 	}

@@ -197,15 +305,22 @@ func handleAnthropicStream(c echo.Context, id string, input *schema.AnthropicReq
 		return sendAnthropicError(c, 500, "api_error", fmt.Sprintf("prediction failed: %v", err))
 	}

-	// Send content_block_stop event
-	contentBlockStop := schema.AnthropicStreamEvent{
-		Type:  "content_block_stop",
-		Index: 0,
+	// Send content_block_stop event for last block if we didn't close it yet
+	if !inToolCall {
+		contentBlockStop := schema.AnthropicStreamEvent{
+			Type:  "content_block_stop",
+			Index: 0,
+		}
+		sendAnthropicSSE(c, contentBlockStop)
+	}
+
+	// Determine stop reason
+	stopReason := "end_turn"
+	if toolCallsEmitted > 0 {
+		stopReason = "tool_use"
 	}
-	sendAnthropicSSE(c, contentBlockStop)

 	// Send message_delta event with stop_reason
-	stopReason := "end_turn"
 	messageDelta := schema.AnthropicStreamEvent{
 		Type: "message_delta",
 		Delta: &schema.AnthropicStreamDelta{
@@ -274,6 +389,8 @@ func convertAnthropicToOpenAIMessages(input *schema.AnthropicRequest) []schema.M
 			// Handle array of content blocks
 			var textContent string
 			var stringImages []string
+			var toolCalls []schema.ToolCall
+			toolCallIndex := 0

 			for _, block := range content {
 				if blockMap, ok := block.(map[string]interface{}); ok {
@@ -295,12 +412,79 @@ func convertAnthropicToOpenAIMessages(input *schema.AnthropicRequest) []schema.M
 								}
 							}
 						}
+					case "tool_use":
+						// Convert tool_use to ToolCall format
+						toolID, _ := blockMap["id"].(string)
+						toolName, _ := blockMap["name"].(string)
+						toolInput := blockMap["input"]
+						
+						// Serialize input to JSON string
+						inputJSON, err := json.Marshal(toolInput)
+						if err != nil {
+							xlog.Warn("Failed to marshal tool input", "error", err)
+							inputJSON = []byte("{}")
+						}
+						
+						toolCalls = append(toolCalls, schema.ToolCall{
+							Index: toolCallIndex,
+							ID:    toolID,
+							Type:  "function",
+							FunctionCall: schema.FunctionCall{
+								Name:      toolName,
+								Arguments: string(inputJSON),
+							},
+						})
+						toolCallIndex++
+					case "tool_result":
+						// Convert tool_result to a message with role "tool"
+						// This is handled by creating a separate message after this block
+						// For now, we'll add it as text content
+						toolUseID, _ := blockMap["tool_use_id"].(string)
+						isError := false
+						if isErrorPtr, ok := blockMap["is_error"].(*bool); ok && isErrorPtr != nil {
+							isError = *isErrorPtr
+						}
+						
+						var resultText string
+						if resultContent, ok := blockMap["content"]; ok {
+							switch rc := resultContent.(type) {
+							case string:
+								resultText = rc
+							case []interface{}:
+								// Array of content blocks
+								for _, cb := range rc {
+									if cbMap, ok := cb.(map[string]interface{}); ok {
+										if cbMap["type"] == "text" {
+											if text, ok := cbMap["text"].(string); ok {
+												resultText += text
+											}
+										}
+									}
+								}
+							}
+						}
+						
+						// Add tool result as a tool role message
+						// We need to handle this differently - create a new message
+						if msg.Role == "user" {
+							// Store tool result info for creating separate message
+							prefix := ""
+							if isError {
+								prefix = "Error: "
+							}
+							textContent += fmt.Sprintf("\n[Tool Result for %s]: %s%s", toolUseID, prefix, resultText)
+						}
 					}
 				}
 			}
 			openAIMsg.StringContent = textContent
 			openAIMsg.Content = textContent
 			openAIMsg.StringImages = stringImages
+			
+			// Add tool calls if present
+			if len(toolCalls) > 0 {
+				openAIMsg.ToolCalls = toolCalls
+			}
 		}

 		messages = append(messages, openAIMsg)
@@ -308,3 +492,46 @@ func convertAnthropicToOpenAIMessages(input *schema.AnthropicRequest) []schema.M

 	return messages
 }
+
+// convertAnthropicTools converts Anthropic tools to internal Functions format
+func convertAnthropicTools(input *schema.AnthropicRequest, cfg *config.ModelConfig) (functions.Functions, bool) {
+	if len(input.Tools) == 0 {
+		return nil, false
+	}
+	
+	var funcs functions.Functions
+	for _, tool := range input.Tools {
+		f := functions.Function{
+			Name:        tool.Name,
+			Description: tool.Description,
+			Parameters:  tool.InputSchema,
+		}
+		funcs = append(funcs, f)
+	}
+	
+	// Handle tool_choice
+	if input.ToolChoice != nil {
+		switch tc := input.ToolChoice.(type) {
+		case string:
+			// "auto", "any", or "none"
+			if tc == "any" {
+				// Force the model to use one of the tools
+				cfg.SetFunctionCallString("required")
+			} else if tc == "none" {
+				// Don't use tools
+				return nil, false
+			}
+			// "auto" is the default - let model decide
+		case map[string]interface{}:
+			// Specific tool selection: {"type": "tool", "name": "tool_name"}
+			if tcType, ok := tc["type"].(string); ok && tcType == "tool" {
+				if name, ok := tc["name"].(string); ok {
+					// Force specific tool
+					cfg.SetFunctionCallString(name)
+				}
+			}
+		}
+	}
+	
+	return funcs, len(funcs) > 0 && cfg.ShouldUseFunctions()
+}
--- a/core/schema/anthropic.go
+++ b/core/schema/anthropic.go
@@ -18,6 +18,8 @@ type AnthropicRequest struct {
 	Temperature   *float64           `json:"temperature,omitempty"`
 	TopK          *int               `json:"top_k,omitempty"`
 	TopP          *float64           `json:"top_p,omitempty"`
+	Tools         []AnthropicTool    `json:"tools,omitempty"`
+	ToolChoice    interface{}        `json:"tool_choice,omitempty"`

 	// Internal fields for request handling
 	Context context.Context    `json:"-"`
@@ -32,6 +34,13 @@ func (ar *AnthropicRequest) ModelName(s *string) string {
 	return ar.Model
 }

+// AnthropicTool represents a tool definition in the Anthropic format
+type AnthropicTool struct {
+	Name        string                 `json:"name"`
+	Description string                 `json:"description,omitempty"`
+	InputSchema map[string]interface{} `json:"input_schema"`
+}
+
 // AnthropicMessage represents a message in the Anthropic format
 type AnthropicMessage struct {
 	Role    string      `json:"role"`
@@ -40,12 +49,15 @@ type AnthropicMessage struct {

 // AnthropicContentBlock represents a content block in an Anthropic message
 type AnthropicContentBlock struct {
-	Type   string                 `json:"type"`
-	Text   string                 `json:"text,omitempty"`
-	Source *AnthropicImageSource  `json:"source,omitempty"`
-	ID     string                 `json:"id,omitempty"`
-	Name   string                 `json:"name,omitempty"`
-	Input  map[string]interface{} `json:"input,omitempty"`
+	Type       string                 `json:"type"`
+	Text       string                 `json:"text,omitempty"`
+	Source     *AnthropicImageSource  `json:"source,omitempty"`
+	ID         string                 `json:"id,omitempty"`
+	Name       string                 `json:"name,omitempty"`
+	Input      map[string]interface{} `json:"input,omitempty"`
+	ToolUseID  string                 `json:"tool_use_id,omitempty"`
+	Content    interface{}            `json:"content,omitempty"`
+	IsError    *bool                  `json:"is_error,omitempty"`
 }

 // AnthropicImageSource represents an image source in Anthropic format
@@ -87,6 +99,7 @@ type AnthropicStreamEvent struct {
 type AnthropicStreamDelta struct {
 	Type         string  `json:"type,omitempty"`
 	Text         string  `json:"text,omitempty"`
+	PartialJSON  string  `json:"partial_json,omitempty"`
 	StopReason   *string `json:"stop_reason,omitempty"`
 	StopSequence *string `json:"stop_sequence,omitempty"`
 }
--- a/core/schema/anthropic_test.go
+++ b/core/schema/anthropic_test.go
@@ -31,6 +31,37 @@ var _ = Describe("Anthropic Schema", func() {
 			Expect(*req.Temperature).To(Equal(0.7))
 		})

+		It("should unmarshal a request with tools", func() {
+			jsonData := `{
+				"model": "claude-3-sonnet-20240229",
+				"max_tokens": 1024,
+				"messages": [
+					{"role": "user", "content": "What's the weather?"}
+				],
+				"tools": [
+					{
+						"name": "get_weather",
+						"description": "Get the current weather",
+						"input_schema": {
+							"type": "object",
+							"properties": {
+								"location": {"type": "string"}
+							}
+						}
+					}
+				],
+				"tool_choice": {"type": "tool", "name": "get_weather"}
+			}`
+
+			var req schema.AnthropicRequest
+			err := json.Unmarshal([]byte(jsonData), &req)
+			Expect(err).ToNot(HaveOccurred())
+			Expect(len(req.Tools)).To(Equal(1))
+			Expect(req.Tools[0].Name).To(Equal("get_weather"))
+			Expect(req.Tools[0].Description).To(Equal("Get the current weather"))
+			Expect(req.ToolChoice).ToNot(BeNil())
+		})
+
 		It("should implement LocalAIRequest interface", func() {
 			req := &schema.AnthropicRequest{Model: "test-model"}
 			Expect(req.ModelName(nil)).To(Equal("test-model"))
@@ -117,6 +148,46 @@ var _ = Describe("Anthropic Schema", func() {
 			Expect(result["role"]).To(Equal("assistant"))
 			Expect(result["stop_reason"]).To(Equal("end_turn"))
 		})
+
+		It("should marshal a response with tool use", func() {
+			stopReason := "tool_use"
+			resp := schema.AnthropicResponse{
+				ID:         "msg_123",
+				Type:       "message",
+				Role:       "assistant",
+				Model:      "claude-3-sonnet-20240229",
+				StopReason: &stopReason,
+				Content: []schema.AnthropicContentBlock{
+					{
+						Type: "tool_use",
+						ID:   "toolu_123",
+						Name: "get_weather",
+						Input: map[string]interface{}{
+							"location": "San Francisco",
+						},
+					},
+				},
+				Usage: schema.AnthropicUsage{
+					InputTokens:  10,
+					OutputTokens: 5,
+				},
+			}
+
+			data, err := json.Marshal(resp)
+			Expect(err).ToNot(HaveOccurred())
+
+			var result map[string]interface{}
+			err = json.Unmarshal(data, &result)
+			Expect(err).ToNot(HaveOccurred())
+
+			Expect(result["stop_reason"]).To(Equal("tool_use"))
+			content := result["content"].([]interface{})
+			Expect(len(content)).To(Equal(1))
+			toolUse := content[0].(map[string]interface{})
+			Expect(toolUse["type"]).To(Equal("tool_use"))
+			Expect(toolUse["id"]).To(Equal("toolu_123"))
+			Expect(toolUse["name"]).To(Equal("get_weather"))
+		})
 	})

 	Describe("AnthropicErrorResponse", func() {
--- a/tests/e2e/e2e_anthropic_test.go
+++ b/tests/e2e/e2e_anthropic_test.go
@@ -146,5 +146,230 @@ var _ = Describe("Anthropic API E2E test", func() {
 				Expect(message.Content).ToNot(BeEmpty())
 			})
 		})
+
+		Context("Tool calling", func() {
+			It("handles tool calls in non-streaming mode", func() {
+				message, err := client.Messages.New(context.TODO(), anthropic.MessageNewParams{
+					Model:     "gpt-4",
+					MaxTokens: 1024,
+					Messages: []anthropic.MessageParam{
+						anthropic.NewUserMessage(anthropic.NewTextBlock("What's the weather like in San Francisco?")),
+					},
+					Tools: []anthropic.ToolParam{
+						{
+							Name:        "get_weather",
+							Description: anthropic.F("Get the current weather in a given location"),
+							InputSchema: anthropic.F(map[string]interface{}{
+								"type": "object",
+								"properties": map[string]interface{}{
+									"location": map[string]interface{}{
+										"type":        "string",
+										"description": "The city and state, e.g. San Francisco, CA",
+									},
+								},
+								"required": []string{"location"},
+							}),
+						},
+					},
+				})
+
+				Expect(err).ToNot(HaveOccurred())
+				Expect(message.Content).ToNot(BeEmpty())
+
+				// The model must use tools - find the tool use in the response
+				hasToolUse := false
+				for _, block := range message.Content {
+					if block.Type == anthropic.ContentBlockTypeToolUse {
+						hasToolUse = true
+						Expect(block.Name).To(Equal("get_weather"))
+						Expect(block.ID).ToNot(BeEmpty())
+						// Verify that input contains location
+						inputMap, ok := block.Input.(map[string]interface{})
+						Expect(ok).To(BeTrue())
+						_, hasLocation := inputMap["location"]
+						Expect(hasLocation).To(BeTrue())
+					}
+				}
+
+				// Model must have called the tool
+				Expect(hasToolUse).To(BeTrue(), "Model should have called the get_weather tool")
+				Expect(message.StopReason).To(Equal(anthropic.MessageStopReasonToolUse))
+			})
+
+			It("handles tool_choice parameter", func() {
+				message, err := client.Messages.New(context.TODO(), anthropic.MessageNewParams{
+					Model:     "gpt-4",
+					MaxTokens: 1024,
+					Messages: []anthropic.MessageParam{
+						anthropic.NewUserMessage(anthropic.NewTextBlock("Tell me about the weather")),
+					},
+					Tools: []anthropic.ToolParam{
+						{
+							Name:        "get_weather",
+							Description: anthropic.F("Get the current weather"),
+							InputSchema: anthropic.F(map[string]interface{}{
+								"type": "object",
+								"properties": map[string]interface{}{
+									"location": map[string]interface{}{
+										"type": "string",
+									},
+								},
+							}),
+						},
+					},
+					ToolChoice: anthropic.F[anthropic.ToolChoiceUnionParam](
+						anthropic.ToolChoiceAutoParam{
+							Type: anthropic.F(anthropic.ToolChoiceAutoTypeAuto),
+						},
+					),
+				})
+
+				Expect(err).ToNot(HaveOccurred())
+				Expect(message.Content).ToNot(BeEmpty())
+			})
+
+			It("handles tool results in messages", func() {
+				// First, make a request that should trigger a tool call
+				firstMessage, err := client.Messages.New(context.TODO(), anthropic.MessageNewParams{
+					Model:     "gpt-4",
+					MaxTokens: 1024,
+					Messages: []anthropic.MessageParam{
+						anthropic.NewUserMessage(anthropic.NewTextBlock("What's the weather in SF?")),
+					},
+					Tools: []anthropic.ToolParam{
+						{
+							Name:        "get_weather",
+							Description: anthropic.F("Get weather"),
+							InputSchema: anthropic.F(map[string]interface{}{
+								"type": "object",
+								"properties": map[string]interface{}{
+									"location": map[string]interface{}{"type": "string"},
+								},
+							}),
+						},
+					},
+				})
+
+				Expect(err).ToNot(HaveOccurred())
+
+				// Find the tool use block - model must call the tool
+				var toolUseID string
+				var toolUseName string
+				for _, block := range firstMessage.Content {
+					if block.Type == anthropic.ContentBlockTypeToolUse {
+						toolUseID = block.ID
+						toolUseName = block.Name
+						break
+					}
+				}
+
+				// Model must have called the tool
+				Expect(toolUseID).ToNot(BeEmpty(), "Model should have called the get_weather tool")
+
+				// Send back a tool result and verify it's handled correctly
+				secondMessage, err := client.Messages.New(context.TODO(), anthropic.MessageNewParams{
+					Model:     "gpt-4",
+					MaxTokens: 1024,
+					Messages: []anthropic.MessageParam{
+						anthropic.NewUserMessage(anthropic.NewTextBlock("What's the weather in SF?")),
+						anthropic.NewAssistantMessage(firstMessage.Content...),
+						anthropic.NewUserMessage(
+							anthropic.NewToolResultBlock(toolUseID, "Sunny, 72°F", false),
+						),
+					},
+					Tools: []anthropic.ToolParam{
+						{
+							Name:        toolUseName,
+							Description: anthropic.F("Get weather"),
+							InputSchema: anthropic.F(map[string]interface{}{
+								"type": "object",
+								"properties": map[string]interface{}{
+									"location": map[string]interface{}{"type": "string"},
+								},
+							}),
+						},
+					},
+				})
+
+				Expect(err).ToNot(HaveOccurred())
+				Expect(secondMessage.Content).ToNot(BeEmpty())
+			})
+
+			It("handles tool calls in streaming mode", func() {
+				stream := client.Messages.NewStreaming(context.TODO(), anthropic.MessageNewParams{
+					Model:     "gpt-4",
+					MaxTokens: 1024,
+					Messages: []anthropic.MessageParam{
+						anthropic.NewUserMessage(anthropic.NewTextBlock("What's the weather like in San Francisco?")),
+					},
+					Tools: []anthropic.ToolParam{
+						{
+							Name:        "get_weather",
+							Description: anthropic.F("Get the current weather in a given location"),
+							InputSchema: anthropic.F(map[string]interface{}{
+								"type": "object",
+								"properties": map[string]interface{}{
+									"location": map[string]interface{}{
+										"type":        "string",
+										"description": "The city and state, e.g. San Francisco, CA",
+									},
+								},
+								"required": []string{"location"},
+							}),
+						},
+					},
+				})
+
+				message := anthropic.Message{}
+				eventCount := 0
+				hasToolUseBlock := false
+				hasContentBlockStart := false
+				hasContentBlockDelta := false
+				hasContentBlockStop := false
+
+				for stream.Next() {
+					event := stream.Current()
+					err := message.Accumulate(event)
+					Expect(err).ToNot(HaveOccurred())
+					eventCount++
+
+					// Check for different event types related to tool use
+					switch e := event.AsAny().(type) {
+					case anthropic.ContentBlockStartEvent:
+						hasContentBlockStart = true
+						if e.ContentBlock.Type == anthropic.ContentBlockTypeToolUse {
+							hasToolUseBlock = true
+						}
+					case anthropic.ContentBlockDeltaEvent:
+						hasContentBlockDelta = true
+					case anthropic.ContentBlockStopEvent:
+						hasContentBlockStop = true
+					}
+				}
+
+				Expect(stream.Err()).ToNot(HaveOccurred())
+				Expect(eventCount).To(BeNumerically(">", 0))
+
+				// Verify streaming events were emitted
+				Expect(hasContentBlockStart).To(BeTrue(), "Should have content_block_start event")
+				Expect(hasContentBlockDelta).To(BeTrue(), "Should have content_block_delta event")
+				Expect(hasContentBlockStop).To(BeTrue(), "Should have content_block_stop event")
+
+				// Check accumulated message has tool use
+				Expect(message.Content).ToNot(BeEmpty())
+				
+				// Model must have called the tool
+				foundToolUse := false
+				for _, block := range message.Content {
+					if block.Type == anthropic.ContentBlockTypeToolUse {
+						foundToolUse = true
+						Expect(block.Name).To(Equal("get_weather"))
+						Expect(block.ID).ToNot(BeEmpty())
+					}
+				}
+				Expect(foundToolUse).To(BeTrue(), "Model should have called the get_weather tool in streaming mode")
+				Expect(message.StopReason).To(Equal(anthropic.MessageStopReasonToolUse))
+			})
+		})
 	})
 })