feat(model): 双协议 LLM Provider（AnthropicChNativeAdapter /v1/messages + tool_use.input→Args 直接映射 + 流式重组）+ Provider 感知工厂/路由 + LLM_PROVIDER/anthropic 配置（OpenAI 兼容保留）

.env.example

@@ -30,12 +30,20 @@ DB_SQLITE_PATH=./data/cyrene.db
 # PostgreSQL + pgvector 为可选增强；未配置时走 SQLite。相关向量能力在 M4 接入。
 # DB_PG_URL=postgres://cyrene:cyrene_pass@localhost:5432/cyrene_ai?sslmode=disable
 
-# ---- LLM 多供应商 ----
+# ---- LLM 多供应商（LLM_PROVIDER 显式声明协议：openai / anthropic，默认 openai） ----
+# Provider = openai：OpenAI 兼容 /chat/completions（含 OpenAI 兼容网关，也可经它承载 Anthropic 模型，但失去原生 tool input 对象优势）
+LLM_PROVIDER=openai
 LLM_BASE_URL=https://api.openai.com/v1
 LLM_API_KEY=sk-xxxxx
 LLM_MODEL=gpt-4o
 LLM_FALLBACK_MODEL=gpt-4o-mini
 
+# Provider = anthropic：Anthropic Messages /v1/messages（tool_use.input 为结构化对象，工具循环更稳）
+# ANTHROPIC_BASE_URL=https://api.anthropic.com
+# ANTHROPIC_API_KEY=sk-ant-xxxxx
+# ANTHROPIC_MODEL=claude-sonnet-4-20250514
+# ANTHROPIC_FALLBACK_MODEL=claude-haiku-3-5
+
 # ---- 记忆嵌入（可选） ----
 # 不配置时使用内置 n-gram / FTS 向量。配置后必须真实走语义路径（M4 接入）。
 # EMBEDDING_API_URL=http://localhost:11434/v1

cmd/cyrene/wire.go

@@ -246,12 +246,12 @@ func (a *app) wireMemory(ctx context.Context) error {
 // wireRuntime builds the model adapter, tool dispatcher, guardrails, the agent
 // and its loop, tracing, persistence and the orchestration scheduler.
 func (a *app) wireRuntime() error {
-	adapter, aerr := model.NewOpenAIChatChain(a.cfg.LLM)
+	adapter, aerr := model.NewChatChain(a.cfg.LLM)
 	if aerr != nil {
 		a.log.Warn("llm adapter unavailable", "error", aerr)
 		adapter = nil
 	}
-	router := model.NewRouter(a.cfg.LLM.Model)
+	router := model.NewRouter(model.DefaultModelForProvider(a.cfg.LLM))
 
 	dispatcher, derr := tool.New(a.caps, tool.WithDefaultTimeout(defaultToolTimeout))
 	if derr != nil {

internal/config/config.go

@@ -54,12 +54,27 @@ type DBConfig struct {
 	PGURL      string `env:"DB_PG_URL"`
 }
 
-// LLMConfig holds the multi-supplier LLM adapter settings.
+// LLMConfig holds the multi-supplier LLM adapter settings. Provider selects the
+// wire protocol; every provider has its own independent base/key/model/fallback
+// so multiple vendors can coexist.
 type LLMConfig struct {
+	// Provider declares which protocol to use: "openai" (OpenAI-compatible
+	// /chat/completions) or "anthropic" (Anthropic Messages /v1/messages).
+	Provider string `env:"LLM_PROVIDER" default:"openai"`
+
+	// OpenAI-compatible provider (default). Kept flat for backward compatibility
+	// with the historic LLM_BASE_URL/API_KEY/MODEL/FALLBACK_MODEL env names.
 	BaseURL  string `env:"LLM_BASE_URL"`
 	APIKey   string `env:"LLM_API_KEY"`
 	Model    string `env:"LLM_MODEL"`
 	Fallback string `env:"LLM_FALLBACK_MODEL"`
+
+	// Anthropic native provider, used when Provider=anthropic. Independent
+	// config block so each vendor is a self-contained config.
+	AnthropicBaseURL  string `env:"ANTHROPIC_BASE_URL"`
+	AnthropicAPIKey   string `env:"ANTHROPIC_API_KEY"`
+	AnthropicModel    string `env:"ANTHROPIC_MODEL"`
+	AnthropicFallback string `env:"ANTHROPIC_FALLBACK_MODEL"`
 }
 
 // EmbeddingConfig holds the optional semantic embedding API settings. When

internal/runtime/model/anthropic.go

@@ -0,0 +1,445 @@
+package model
+
+import (
+	"bytes"
+	"context"
+	"encoding/json"
+	"fmt"
+	"io"
+	"net/http"
+	"strings"
+	"time"
+
+	"git.yeij.top/AskaEth/Cyrene_v2/internal/config"
+)
+
+// Anthropic Messages (/v1/messages) wire protocol constants.
+const (
+	// anthropicAPIVersion is the Messages API version sent on every request.
+	anthropicAPIVersion = "2023-06-01"
+	// anthropicDefaultMaxTokens is the default max_tokens sent when
+	// Request.MaxTokens is zero. Anthropic requires max_tokens to be present and
+	// positive, so a sensible default is applied rather than omitting it.
+	anthropicDefaultMaxTokens = 1024
+	// anthropicDataPrefix marks a payload embedded as a data: URI.
+	anthropicDataPrefix = "data:"
+)
+
+// anthropicRequest is the body sent to /v1/messages. Messages carry Anthropic's
+// content-block model and the system prompt lives at the request root.
+type anthropicRequest struct {
+	Model       string             `json:"model"`
+	System      string             `json:"system,omitempty"`
+	Messages    []anthropicMessage `json:"messages"`
+	Tools       []anthropicTool    `json:"tools,omitempty"`
+	ToolChoice  any                `json:"tool_choice,omitempty"`
+	Temperature *float64           `json:"temperature,omitempty"`
+	MaxTokens   int                `json:"max_tokens"`
+	Stream      bool               `json:"stream,omitempty"`
+}
+
+// anthropicMessage is one conversation turn. Content is an array of content
+// blocks (text / image for now; tool_result blocks are added by M2).
+type anthropicMessage struct {
+	Role    string `json:"role"`
+	Content any    `json:"content"`
+}
+
+// anthropicTool is the wire form of a tool schema.
+type anthropicTool struct {
+	Name        string `json:"name"`
+	Description string `json:"description,omitempty"`
+	InputSchema any    `json:"input_schema"`
+}
+
+// anthropicResponse is the JSON body returned by /v1/messages.
+type anthropicResponse struct {
+	ID      string           `json:"id"`
+	Model   string           `json:"model"`
+	Content []anthropicBlock `json:"content"`
+	Usage   *anthropicUsage  `json:"usage,omitempty"`
+}
+
+// anthropicBlock is a single content block in a response. For tool_use blocks the
+// Input field is a fully decoded object (never a JSON string).
+type anthropicBlock struct {
+	Type  string         `json:"type"`
+	Text  string         `json:"text,omitempty"`
+	ID    string         `json:"id,omitempty"`
+	Name  string         `json:"name,omitempty"`
+	Input map[string]any `json:"input,omitempty"`
+}
+
+// anthropicUsage reports token consumption. Anthropic reports input_tokens and
+// output_tokens rather than a single total.
+type anthropicUsage struct {
+	InputTokens  int `json:"input_tokens"`
+	OutputTokens int `json:"output_tokens"`
+}
+
+// AnthropicChatAdapter calls an Anthropic Messages (/v1/messages) endpoint. It is
+// constructed from a config.LLMConfig and implements Adapter for both
+// non-streaming and token-level SSE streaming, speaking the provider's native
+// content-block protocol so tool_use.input arrives as a structured object.
+type AnthropicChatAdapter struct {
+	name     string
+	baseURL  string
+	apiKey   string
+	model    string
+	client   *http.Client
+	recorder Recorder
+}
+
+// AnthropicOption configures an AnthropicChatAdapter.
+type AnthropicOption func(*AnthropicChatAdapter)
+
+// WithAnthropicHTTPClient overrides the default HTTP client (used to inject mocks
+// or a tuned transport in tests and production).
+func WithAnthropicHTTPClient(c *http.Client) AnthropicOption {
+	return func(a *AnthropicChatAdapter) { a.client = c }
+}
+
+// WithAnthropicRecorder wires a per-call Recorder for CallRecord accounting.
+func WithAnthropicRecorder(r Recorder) AnthropicOption {
+	return func(a *AnthropicChatAdapter) { a.recorder = r }
+}
+
+// WithAnthropicModel overrides the adapter's default model name.
+func WithAnthropicModel(m string) AnthropicOption {
+	return func(a *AnthropicChatAdapter) { a.model = m }
+}
+
+// NewAnthropicChat builds an Anthropic adapter from a supplier config. baseURL is
+// trimmed of any trailing slash before the /v1/messages path is appended.
+func NewAnthropicChat(cfg config.LLMConfig, opts ...AnthropicOption) *AnthropicChatAdapter {
+	a := &AnthropicChatAdapter{
+		name:    "anthropic",
+		baseURL: strings.TrimRight(cfg.AnthropicBaseURL, "/"),
+		apiKey:  cfg.AnthropicAPIKey,
+		model:   cfg.AnthropicModel,
+		client: &http.Client{
+			Transport: http.DefaultTransport,
+			Timeout:   defaultHTTPTimeout,
+		},
+	}
+	for _, o := range opts {
+		o(a)
+	}
+	return a
+}
+
+// Name returns the adapter identifier.
+func (a *AnthropicChatAdapter) Name() string { return a.name }
+
+// Chat performs a non-streaming completion.
+func (a *AnthropicChatAdapter) Chat(ctx context.Context, req Request, opts Options) (Response, error) {
+	start := time.Now()
+	if a.baseURL == "" {
+		return Response{}, ErrUpstream
+	}
+	ctx, cancel := withCallTimeout(ctx, opts)
+	defer cancel()
+	model, err := a.resolveModel(req)
+	if err != nil {
+		return Response{}, err
+	}
+	req.Model = model
+	body, err := a.buildRequest(req, false)
+	if err != nil {
+		return Response{}, err
+	}
+	httpReq, err := http.NewRequestWithContext(ctx, http.MethodPost, a.endpoint(), bytes.NewReader(body))
+	if err != nil {
+		return Response{}, fmt.Errorf("model: %w: build request: %v", ErrUpstream, err)
+	}
+	resp, err := a.doRequest(httpReq, false)
+	if err != nil {
+		return Response{}, err
+	}
+	defer resp.Body.Close()
+	if resp.StatusCode != http.StatusOK {
+		return Response{}, a.upstreamError(resp)
+	}
+	var wire anthropicResponse
+	if err := json.NewDecoder(resp.Body).Decode(&wire); err != nil {
+		return Response{}, fmt.Errorf("model: %w: decode response: %v", ErrUpstream, err)
+	}
+	out := responseFromAnthropicWire(&wire)
+	a.record(req, start, out.TotalTokens)
+	return out, nil
+}
+
+// ChatStream streams content-block deltas via onChunk and returns the aggregated
+// response with usage when the provider reports it.
+func (a *AnthropicChatAdapter) ChatStream(ctx context.Context, req Request, onChunk func(delta string)) (Response, error) {
+	start := time.Now()
+	if a.baseURL == "" {
+		return Response{}, ErrUpstream
+	}
+	model, err := a.resolveModel(req)
+	if err != nil {
+		return Response{}, err
+	}
+	req.Model = model
+	body, err := a.buildRequest(req, true)
+	if err != nil {
+		return Response{}, err
+	}
+	httpReq, err := http.NewRequestWithContext(ctx, http.MethodPost, a.endpoint(), bytes.NewReader(body))
+	if err != nil {
+		return Response{}, fmt.Errorf("model: %w: build request: %v", ErrUpstream, err)
+	}
+	resp, err := a.doRequest(httpReq, true)
+	if err != nil {
+		return Response{}, err
+	}
+	defer resp.Body.Close()
+	if resp.StatusCode != http.StatusOK {
+		return Response{}, a.upstreamError(resp)
+	}
+	out, err := scanAnthropicSSE(resp.Body, onChunk)
+	if err != nil {
+		return Response{}, err
+	}
+	out.Model = model
+	a.record(req, start, out.TotalTokens)
+	return out, nil
+}
+
+// resolveModel returns the effective model name.
+func (a *AnthropicChatAdapter) resolveModel(req Request) (string, error) {
+	if req.Model != "" {
+		return req.Model, nil
+	}
+	if a.model != "" {
+		return a.model, nil
+	}
+	return "", ErrNoModel
+}
+
+// endpoint returns the full /v1/messages URL.
+func (a *AnthropicChatAdapter) endpoint() string {
+	return a.baseURL + "/v1/messages"
+}
+
+func (a *AnthropicChatAdapter) buildRequest(req Request, stream bool) ([]byte, error) {
+	system, msgs, err := buildAnthropicMessages(req.Messages)
+	if err != nil {
+		return nil, err
+	}
+	tokenLimit := req.MaxTokens
+	if tokenLimit == 0 {
+		tokenLimit = anthropicDefaultMaxTokens
+	}
+	wire := anthropicRequest{
+		Model:       req.Model,
+		System:      system,
+		Messages:    msgs,
+		Tools:       buildAnthropicTools(req.Tools),
+		ToolChoice:  req.ToolChoice,
+		Temperature: req.Temperature,
+		MaxTokens:   tokenLimit,
+		Stream:      stream,
+	}
+	buf, err := json.Marshal(wire)
+	if err != nil {
+		return nil, fmt.Errorf("model: %w: marshal request: %v", ErrBadRequest, err)
+	}
+	return buf, nil
+}
+
+func (a *AnthropicChatAdapter) doRequest(httpReq *http.Request, stream bool) (*http.Response, error) {
+	if a.apiKey != "" {
+		httpReq.Header.Set("x-api-key", a.apiKey)
+	}
+	httpReq.Header.Set("anthropic-version", anthropicAPIVersion)
+	httpReq.Header.Set("Content-Type", "application/json")
+	if stream {
+		httpReq.Header.Set("Accept", "text/event-stream")
+	} else {
+		httpReq.Header.Set("Accept", "application/json")
+	}
+	resp, err := a.client.Do(httpReq)
+	if err != nil {
+		return nil, fmt.Errorf("model: %w: %v", ErrUpstream, err)
+	}
+	return resp, nil
+}
+
+func (a *AnthropicChatAdapter) upstreamError(resp *http.Response) error {
+	snippet, _ := io.ReadAll(io.LimitReader(resp.Body, errBodyCap))
+	return fmt.Errorf("model: %w: status %d: %s", ErrUpstream, resp.StatusCode, strings.TrimSpace(string(snippet)))
+}
+
+func (a *AnthropicChatAdapter) record(req Request, start time.Time, tokens int) {
+	if a.recorder == nil {
+		return
+	}
+	a.recorder(CallRecord{
+		Model:   req.Model,
+		Purpose: req.Purpose,
+		Tokens:  tokens,
+		TookMs:  time.Since(start).Milliseconds(),
+	})
+}
+
+// buildAnthropicMessages splits a normalized message list into a top-level system
+// string and the remaining messages in Anthropic's content-block form. All
+// RoleSystem messages are concatenated into a single system prompt (Anthropic
+// carries it at the request root, not in messages); messages with no content
+// parts are dropped because Anthropic rejects empty content.
+func buildAnthropicMessages(msgs []Message) (string, []anthropicMessage, error) {
+	var sys strings.Builder
+	out := make([]anthropicMessage, 0, len(msgs))
+	for _, m := range msgs {
+		if m.Role == RoleSystem {
+			if t := messageText(m); t != "" {
+				if sys.Len() > 0 {
+					sys.WriteString("\n")
+				}
+				sys.WriteString(t)
+			}
+			continue
+		}
+		blocks, err := encodeAnthropicContent(m.Content)
+		if err != nil {
+			return "", nil, err
+		}
+		if len(blocks) == 0 {
+			continue
+		}
+		out = append(out, anthropicMessage{Role: anthropicRole(m.Role), Content: blocks})
+	}
+	return sys.String(), out, nil
+}
+
+// messageText concatenates the text parts of a message (used for system prompts).
+func messageText(m Message) string {
+	var b strings.Builder
+	for _, part := range m.Content {
+		if part.Type == ContentTypeText {
+			b.WriteString(part.Text)
+		}
+	}
+	return b.String()
+}
+
+// anthropicRole maps a normalized Role to the Anthropic role vocabulary. system
+// messages are extracted to the top-level system field and never reach here.
+func anthropicRole(r Role) string {
+	switch r {
+	case RoleAssistant:
+		return "assistant"
+	default:
+		// user, tool and any future roles all land on the user turn; tool_result
+		// blocks (M2) belong to the user role in Anthropic.
+		return "user"
+	}
+}
+
+// encodeAnthropicContent turns normalized content parts into Anthropic content
+// blocks.
+func encodeAnthropicContent(parts []Content) ([]any, error) {
+	blocks := make([]any, 0, len(parts))
+	for _, p := range parts {
+		switch p.Type {
+		case ContentTypeText:
+			blocks = append(blocks, map[string]any{"type": "text", "text": p.Text})
+		case ContentTypeImage:
+			mediaType, data, err := parseAnthropicImageData(p.ImageURL)
+			if err != nil {
+				return nil, err
+			}
+			blocks = append(blocks, map[string]any{
+				"type": "image",
+				"source": map[string]any{
+					"type":       "base64",
+					"media_type": mediaType,
+					"data":       data,
+				},
+			})
+		default:
+			return nil, fmt.Errorf("model: %w: unsupported content type %q", ErrBadRequest, p.Type)
+		}
+	}
+	return blocks, nil
+}
+
+// parseAnthropicImageData extracts the media type and base64 payload from a data:
+// URI. Anthropic requires a base64 image source and cannot reference a remote
+// URL, so any other URI form is rejected as a bad request.
+func parseAnthropicImageData(uri string) (string, string, error) {
+	if !strings.HasPrefix(uri, anthropicDataPrefix) {
+		return "", "", fmt.Errorf("model: %w: anthropic image requires a data: URI, got %q", ErrBadRequest, uri)
+	}
+	rest := strings.TrimPrefix(uri, anthropicDataPrefix)
+	comma := strings.Index(rest, ",")
+	if comma < 0 {
+		return "", "", fmt.Errorf("model: %w: malformed data: URI %q", ErrBadRequest, uri)
+	}
+	meta := rest[:comma]
+	data := rest[comma+1:]
+	mediaType := meta
+	if idx := strings.Index(meta, ";"); idx >= 0 {
+		mediaType = meta[:idx]
+	}
+	if mediaType == "" {
+		return "", "", fmt.Errorf("model: %w: data: URI missing media type in %q", ErrBadRequest, uri)
+	}
+	return mediaType, data, nil
+}
+
+// buildAnthropicTools converts ToolSpec schemas into Anthropic tools.
+func buildAnthropicTools(tools []ToolSpec) []anthropicTool {
+	if len(tools) == 0 {
+		return nil
+	}
+	out := make([]anthropicTool, 0, len(tools))
+	for _, t := range tools {
+		out = append(out, anthropicTool{
+			Name:        t.Name,
+			Description: t.Description,
+			InputSchema: t.Parameters,
+		})
+	}
+	return out
+}
+
+// responseFromAnthropicWire converts a non-streaming /v1/messages response into a
+// normalized Response. Each text block contributes to the assistant content; each
+// tool_use block becomes a ToolCall whose Args is taken directly from the decoded
+// input object.
+func responseFromAnthropicWire(wire *anthropicResponse) Response {
+	out := Response{Model: wire.Model}
+	var b strings.Builder
+	var toolCalls []ToolCall
+	for _, blk := range wire.Content {
+		switch blk.Type {
+		case "text":
+			b.WriteString(blk.Text)
+		case "tool_use":
+			toolCalls = append(toolCalls, ToolCall{Name: blk.Name, Args: blk.Input})
+		}
+	}
+	out.Content = b.String()
+	out.Message = Message{Role: RoleAssistant, Content: []Content{{Type: ContentTypeText, Text: out.Content}}}
+	out.ToolCalls = toolCalls
+	if u := wire.Usage; u != nil {
+		out.PromptTokens = u.InputTokens
+		out.CompletionTokens = u.OutputTokens
+		out.TotalTokens = u.InputTokens + u.OutputTokens
+	}
+	return out
+}
+
+// AnthropicToolResult builds the content block used to feed a tool result back to
+// Anthropic (role: user, first content element). toolUseID must equal the id of a
+// previous tool_use block; isError marks an execution failure.
+func AnthropicToolResult(toolUseID, content string, isError bool) map[string]any {
+	return map[string]any{
+		"type":        "tool_result",
+		"tool_use_id": toolUseID,
+		"content":     content,
+		"is_error":    isError,
+	}
+}

internal/runtime/model/anthropic_stream.go

@@ -0,0 +1,189 @@
+package model
+
+import (
+	"bufio"
+	"encoding/json"
+	"fmt"
+	"io"
+	"strings"
+)
+
+// anthropicStreamEvent is one SSE payload from /v1/messages with stream: true.
+// Anthropic carries the event kind both in the SSE `event:` field and inside the
+// JSON `type` field, so the parser keys off the JSON payload type.
+type anthropicStreamEvent struct {
+	Type    string                `json:"type"`
+	Message *anthropicStartBlock  `json:"message,omitempty"`
+	Index   *int                  `json:"index,omitempty"`
+	Content *anthropicBlock       `json:"content_block,omitempty"`
+	Delta   *anthropicDelta       `json:"delta,omitempty"`
+	Usage   *anthropicUsage       `json:"usage,omitempty"`
+	Error   *anthropicStreamError `json:"error,omitempty"`
+}
+
+// anthropicStartBlock is the payload of a message_start event.
+type anthropicStartBlock struct {
+	Model string          `json:"model"`
+	Usage *anthropicUsage `json:"usage,omitempty"`
+}
+
+// anthropicDelta is the incremental payload inside a content_block_delta event.
+type anthropicDelta struct {
+	Type        string `json:"type"` // text_delta | input_json_delta
+	Text        string `json:"text,omitempty"`
+	PartialJSON string `json:"partial_json,omitempty"`
+}
+
+// anthropicStreamError is the payload of an error event.
+type anthropicStreamError struct {
+	Type    string `json:"type"`
+	Message string `json:"message"`
+}
+
+// streamBlock tracks the partial state of one content block during streaming.
+type streamBlock struct {
+	index       int
+	typ         string
+	id          string
+	name        string
+	text        strings.Builder
+	input       strings.Builder
+	initialArgs map[string]any
+}
+
+// scanAnthropicSSE incrementally decodes Anthropic's content-block stream. Text
+// deltas are forwarded to onChunk; tool_use input_json_delta fragments are
+// accumulated per block and re-assembled into a structured Args map when the block
+// stops. The stream must terminate with a message_stop event, otherwise ErrStream
+// is returned.
+func scanAnthropicSSE(r io.Reader, onChunk func(string)) (Response, error) {
+	scanner := bufio.NewScanner(r)
+	scanner.Buffer(make([]byte, 0, sseBufInit), maxSSELineBytes)
+	agg := Response{}
+	blocks := map[int]*streamBlock{}
+	var order []int
+	var text strings.Builder
+	sawMessageStop := false
+
+	for scanner.Scan() {
+		line := strings.TrimSpace(scanner.Text())
+		if line == "" || !strings.HasPrefix(line, sseDataPrefix) {
+			continue
+		}
+		data := strings.TrimSpace(strings.TrimPrefix(line, sseDataPrefix))
+		if data == "" {
+			continue
+		}
+		var evt anthropicStreamEvent
+		if err := json.Unmarshal([]byte(data), &evt); err != nil {
+			return Response{}, fmt.Errorf("model: %w: decode stream chunk: %v", ErrUpstream, err)
+		}
+		if err := applyAnthropicEvent(&agg, blocks, &order, &text, evt, onChunk); err != nil {
+			return Response{}, err
+		}
+		if evt.Type == "message_stop" {
+			sawMessageStop = true
+		}
+	}
+	if err := scanner.Err(); err != nil {
+		return Response{}, fmt.Errorf("model: %w: read stream: %v", ErrUpstream, err)
+	}
+	if !sawMessageStop {
+		return Response{}, ErrStream
+	}
+	finalizeAnthropicStream(&agg, blocks, order, text.String())
+	return agg, nil
+}
+
+// applyAnthropicEvent folds a single stream event into the running aggregation.
+func applyAnthropicEvent(
+	agg *Response,
+	blocks map[int]*streamBlock,
+	order *[]int,
+	text *strings.Builder,
+	evt anthropicStreamEvent,
+	onChunk func(string),
+) error {
+	switch evt.Type {
+	case "message_start":
+		if evt.Message != nil {
+			agg.Model = evt.Message.Model
+			if evt.Message.Usage != nil {
+				agg.PromptTokens = evt.Message.Usage.InputTokens
+			}
+		}
+	case "content_block_start":
+		if evt.Index == nil || evt.Content == nil {
+			return nil
+		}
+		b := &streamBlock{
+			index:       *evt.Index,
+			typ:         evt.Content.Type,
+			id:          evt.Content.ID,
+			name:        evt.Content.Name,
+			initialArgs: evt.Content.Input,
+		}
+		if evt.Content.Type == "text" && evt.Content.Text != "" {
+			b.text.WriteString(evt.Content.Text)
+			text.WriteString(evt.Content.Text)
+			if onChunk != nil {
+				onChunk(evt.Content.Text)
+			}
+		}
+		if _, ok := blocks[*evt.Index]; !ok {
+			*order = append(*order, *evt.Index)
+		}
+		blocks[*evt.Index] = b
+	case "content_block_delta":
+		if evt.Index == nil || evt.Delta == nil {
+			return nil
+		}
+		b := blocks[*evt.Index]
+		if b == nil {
+			return nil
+		}
+		switch evt.Delta.Type {
+		case "text_delta":
+			b.text.WriteString(evt.Delta.Text)
+			text.WriteString(evt.Delta.Text)
+			if onChunk != nil {
+				onChunk(evt.Delta.Text)
+			}
+		case "input_json_delta":
+			b.input.WriteString(evt.Delta.PartialJSON)
+		}
+	case "message_delta":
+		if evt.Usage != nil {
+			agg.CompletionTokens = evt.Usage.OutputTokens
+		}
+	case "error":
+		if evt.Error != nil {
+			return fmt.Errorf("model: %w: anthropic stream error: %s: %s", ErrUpstream, evt.Error.Type, evt.Error.Message)
+		}
+	}
+	return nil
+}
+
+// finalizeAnthropicStream assembles the aggregated Response from the accumulated
+// blocks: concatenated text plus any tool_use ToolCalls derived per block.
+func finalizeAnthropicStream(agg *Response, blocks map[int]*streamBlock, order []int, content string) {
+	agg.Content = content
+	agg.Message = Message{Role: RoleAssistant, Content: []Content{{Type: ContentTypeText, Text: content}}}
+	agg.TotalTokens = agg.PromptTokens + agg.CompletionTokens
+	for _, idx := range order {
+		b := blocks[idx]
+		if b == nil || b.typ != "tool_use" {
+			continue
+		}
+		args := b.initialArgs
+		if b.input.Len() > 0 {
+			decoded := map[string]any{}
+			if err := json.Unmarshal([]byte(b.input.String()), &decoded); err == nil {
+				args = decoded
+			} else {
+				args = map[string]any{}
+			}
+		}
+		agg.ToolCalls = append(agg.ToolCalls, ToolCall{Name: b.name, Args: args})
+	}
+}

internal/runtime/model/anthropic_test.go

@@ -0,0 +1,442 @@
+package model
+
+import (
+	"context"
+	"encoding/json"
+	"errors"
+	"io"
+	"net/http"
+	"net/http/httptest"
+	"reflect"
+	"strings"
+	"testing"
+
+	"git.yeij.top/AskaEth/Cyrene_v2/internal/config"
+)
+
+// anthropicCaptured records what an AnthropicChatAdapter sent to a stub server.
+type anthropicCaptured struct {
+	method           string
+	path             string
+	apiKey           string
+	anthropicVersion string
+	contentType      string
+	accept           string
+	body             map[string]any
+}
+
+func newAnthropicServer(t *testing.T, status int, contentType, body string, ch chan<- anthropicCaptured) *httptest.Server {
+	t.Helper()
+	srv := httptest.NewServer(http.HandlerFunc(func(w http.ResponseWriter, r *http.Request) {
+		var reqBody map[string]any
+		if ch != nil {
+			_ = json.NewDecoder(r.Body).Decode(&reqBody)
+		}
+		if contentType != "" {
+			w.Header().Set("Content-Type", contentType)
+		}
+		w.WriteHeader(status)
+		if body != "" {
+			_, _ = io.WriteString(w, body)
+		}
+		if ch != nil {
+			ch <- anthropicCaptured{
+				method:           r.Method,
+				path:             r.URL.Path,
+				apiKey:           r.Header.Get("x-api-key"),
+				anthropicVersion: r.Header.Get("anthropic-version"),
+				contentType:      r.Header.Get("Content-Type"),
+				accept:           r.Header.Get("Accept"),
+				body:             reqBody,
+			}
+		}
+	}))
+	t.Cleanup(srv.Close)
+	return srv
+}
+
+const anthropicTextResponse = `{
+  "id":"msg_1","model":"claude-test","role":"assistant",
+  "content":[{"type":"text","text":"Hello!"}],
+  "usage":{"input_tokens":5,"output_tokens":2}
+}`
+
+func TestAnthropicChat_Chat_NonStreamingText(t *testing.T) {
+	t.Parallel()
+	ch := make(chan anthropicCaptured, 1)
+	srv := newAnthropicServer(t, http.StatusOK, "application/json", anthropicTextResponse, ch)
+
+	recs := make([]CallRecord, 0, 1)
+	temp := 1.0
+	ad := NewAnthropicChat(config.LLMConfig{
+		AnthropicBaseURL: srv.URL, AnthropicAPIKey: "ak-test", AnthropicModel: "claude-test",
+	}, WithAnthropicRecorder(func(cr CallRecord) { recs = append(recs, cr) }))
+
+	resp, err := ad.Chat(context.Background(), Request{
+		Messages:    []Message{TextMessage(RoleUser, "hi")},
+		Model:       "claude-test",
+		Temperature: &temp,
+		MaxTokens:   64,
+		Purpose:     "chat",
+	}, Options{})
+	if err != nil {
+		t.Fatalf("Chat error: %v", err)
+	}
+
+	got := <-ch
+	if got.method != http.MethodPost {
+		t.Errorf("method = %s, want POST", got.method)
+	}
+	if got.path != "/v1/messages" {
+		t.Errorf("path = %s, want /v1/messages", got.path)
+	}
+	if got.apiKey != "ak-test" {
+		t.Errorf("x-api-key = %q, want ak-test", got.apiKey)
+	}
+	if got.anthropicVersion != "2023-06-01" {
+		t.Errorf("anthropic-version = %q, want 2023-06-01", got.anthropicVersion)
+	}
+	if got.contentType != "application/json" {
+		t.Errorf("content-type = %s, want application/json", got.contentType)
+	}
+	if got.accept != "application/json" {
+		t.Errorf("accept = %s, want application/json", got.accept)
+	}
+	if got.body["model"] != "claude-test" {
+		t.Errorf("body.model = %v, want claude-test", got.body["model"])
+	}
+	if got.body["max_tokens"] != float64(64) {
+		t.Errorf("body.max_tokens = %v, want 64", got.body["max_tokens"])
+	}
+	if got.body["temperature"] != 1.0 {
+		t.Errorf("body.temperature = %v, want 1.0", got.body["temperature"])
+	}
+	if got.body["stream"] != nil && got.body["stream"] != false {
+		t.Errorf("body.stream = %v, want omitted(false)", got.body["stream"])
+	}
+	msgs, _ := got.body["messages"].([]any)
+	if len(msgs) != 1 {
+		t.Fatalf("body.messages = %v, want 1 message", got.body["messages"])
+	}
+
+	if resp.Model != "claude-test" {
+		t.Errorf("resp.Model = %q, want claude-test", resp.Model)
+	}
+	if resp.Content != "Hello!" {
+		t.Errorf("resp.Content = %q, want Hello!", resp.Content)
+	}
+	if resp.TotalTokens != 7 || resp.PromptTokens != 5 || resp.CompletionTokens != 2 {
+		t.Errorf("resp usage = (%d,%d,%d), want (5,2,7)", resp.PromptTokens, resp.CompletionTokens, resp.TotalTokens)
+	}
+	if resp.Message.Role != RoleAssistant || len(resp.Message.Content) != 1 || resp.Message.Content[0].Text != "Hello!" {
+		t.Errorf("resp.Message = %+v", resp.Message)
+	}
+
+	if len(recs) != 1 {
+		t.Fatalf("records = %d, want 1", len(recs))
+	}
+	if recs[0].Model != "claude-test" || recs[0].Purpose != "chat" || recs[0].Tokens != 7 || recs[0].TookMs < 0 {
+		t.Errorf("record = %+v, want model=claude-test purpose=chat tokens=7 took_ms>=0", recs[0])
+	}
+}
+
+func TestAnthropicChat_Chat_ToolUseInputObject(t *testing.T) {
+	t.Parallel()
+	const resp = `{
+	  "id":"msg_2","model":"claude-test",
+	  "content":[
+	    {"type":"text","text":"Let me check."},
+	    {"type":"tool_use","id":"toolu_1","name":"lookup","input":{"location":"Paris","limit":3}}
+	  ],
+	  "usage":{"input_tokens":10,"output_tokens":12}
+	}`
+	ch := make(chan anthropicCaptured, 1)
+	srv := newAnthropicServer(t, http.StatusOK, "application/json", resp, ch)
+	ad := NewAnthropicChat(config.LLMConfig{AnthropicBaseURL: srv.URL, AnthropicModel: "claude-test"})
+
+	req := Request{
+		Messages: []Message{TextMessage(RoleUser, "hi")},
+		Tools:    []ToolSpec{{Name: "lookup", Description: "look up", Parameters: map[string]any{"type": "object"}}},
+	}
+	out, err := ad.Chat(context.Background(), req, Options{})
+	if err != nil {
+		t.Fatalf("Chat error: %v", err)
+	}
+
+	got := <-ch
+	tools, ok := got.body["tools"].([]any)
+	if !ok || len(tools) != 1 {
+		t.Fatalf("body.tools = %v, want 1 entry", got.body["tools"])
+	}
+	tool0, _ := tools[0].(map[string]any)
+	if tool0["name"] != "lookup" {
+		t.Errorf("tool name = %v, want lookup", tool0["name"])
+	}
+	if _, ok = tool0["input_schema"]; !ok {
+		t.Errorf("tool input_schema missing from %v", tool0)
+	}
+
+	if out.Content != "Let me check." {
+		t.Errorf("out.Content = %q, want Let me check.", out.Content)
+	}
+	if len(out.ToolCalls) != 1 {
+		t.Fatalf("out.ToolCalls = %+v, want 1", out.ToolCalls)
+	}
+	tc := out.ToolCalls[0]
+	if tc.Name != "lookup" {
+		t.Errorf("tool call name = %q, want lookup", tc.Name)
+	}
+	if tc.Args == nil {
+		t.Fatalf("tool call args = nil, want structured object")
+	}
+	if tc.Args["location"] != "Paris" {
+		t.Errorf("tool call args.location = %v, want Paris (structured, not JSON string)", tc.Args["location"])
+	}
+	if tc.Args["limit"] != float64(3) {
+		t.Errorf("tool call args.limit = %v, want 3", tc.Args["limit"])
+	}
+}
+
+func TestAnthropicChat_Chat_SystemAndToolChoice(t *testing.T) {
+	t.Parallel()
+	ch := make(chan anthropicCaptured, 1)
+	srv := newAnthropicServer(t, http.StatusOK, "application/json", anthropicTextResponse, ch)
+	ad := NewAnthropicChat(config.LLMConfig{AnthropicBaseURL: srv.URL, AnthropicModel: "claude-test"})
+
+	req := Request{
+		Messages: []Message{
+			TextMessage(RoleSystem, "Be concise."),
+			TextMessage(RoleUser, "hi"),
+		},
+		ToolChoice: map[string]any{"type": "auto"},
+	}
+	if _, err := ad.Chat(context.Background(), req, Options{}); err != nil {
+		t.Fatalf("Chat error: %v", err)
+	}
+
+	got := <-ch
+	if got.body["system"] != "Be concise." {
+		t.Errorf("body.system = %v, want Be concise.", got.body["system"])
+	}
+	msgs, _ := got.body["messages"].([]any)
+	if len(msgs) != 1 {
+		t.Fatalf("body.messages = %v, want 1 message (system extracted)", got.body["messages"])
+	}
+	if _, ok := got.body["tool_choice"].(map[string]any); !ok {
+		t.Errorf("body.tool_choice = %v, want an object", got.body["tool_choice"])
+	}
+}
+
+func TestAnthropicChat_Chat_ImageContent(t *testing.T) {
+	t.Parallel()
+	ch := make(chan anthropicCaptured, 1)
+	srv := newAnthropicServer(t, http.StatusOK, "application/json", anthropicTextResponse, ch)
+	ad := NewAnthropicChat(config.LLMConfig{AnthropicBaseURL: srv.URL, AnthropicModel: "claude-test"})
+
+	req := Request{Messages: []Message{ImageMessage(RoleUser, "what is this", "data:image/png;base64,abc")}}
+	if _, err := ad.Chat(context.Background(), req, Options{}); err != nil {
+		t.Fatalf("Chat error: %v", err)
+	}
+
+	got := <-ch
+	msgs, _ := got.body["messages"].([]any)
+	part0, _ := msgs[0].(map[string]any)
+	content, _ := part0["content"].([]any)
+	if len(content) != 2 {
+		t.Fatalf("content parts = %d, want 2 (text+image)", len(content))
+	}
+	found := false
+	for _, c := range content {
+		cp, _ := c.(map[string]any)
+		if cp["type"] != "image" {
+			continue
+		}
+		found = true
+		src, _ := cp["source"].(map[string]any)
+		if src["type"] != "base64" {
+			t.Errorf("image source type = %v, want base64", src["type"])
+		}
+		if src["media_type"] != "image/png" {
+			t.Errorf("image media_type = %v, want image/png", src["media_type"])
+		}
+		if src["data"] != "abc" {
+			t.Errorf("image data = %v, want abc", src["data"])
+		}
+	}
+	if !found {
+		t.Fatalf("no image block found in %v", content)
+	}
+}
+
+func TestAnthropicChat_Chat_UpstreamError(t *testing.T) {
+	t.Parallel()
+	srv := newAnthropicServer(t, http.StatusInternalServerError, "application/json", `{"error":"boom"}`, nil)
+	ad := NewAnthropicChat(config.LLMConfig{AnthropicBaseURL: srv.URL, AnthropicModel: "m"})
+	_, err := ad.Chat(context.Background(), Request{Messages: []Message{TextMessage(RoleUser, "hi")}}, Options{})
+	if err == nil {
+		t.Fatal("want error, got nil")
+	}
+	if !errors.Is(err, ErrUpstream) {
+		t.Fatalf("err = %v, want ErrUpstream", err)
+	}
+}
+
+func TestAnthropicChat_Chat_NoBaseURL(t *testing.T) {
+	t.Parallel()
+	ad := NewAnthropicChat(config.LLMConfig{AnthropicModel: "m"})
+	if _, err := ad.Chat(context.Background(), Request{Messages: []Message{TextMessage(RoleUser, "hi")}}, Options{}); !errors.Is(err, ErrUpstream) {
+		t.Fatalf("err = %v, want ErrUpstream", err)
+	}
+}
+
+func TestAnthropicChat_Chat_NoModel(t *testing.T) {
+	t.Parallel()
+	srv := newAnthropicServer(t, http.StatusOK, "application/json", anthropicTextResponse, nil)
+	ad := NewAnthropicChat(config.LLMConfig{AnthropicBaseURL: srv.URL})
+	if _, err := ad.Chat(context.Background(), Request{Messages: []Message{TextMessage(RoleUser, "hi")}}, Options{}); !errors.Is(err, ErrNoModel) {
+		t.Fatalf("err = %v, want ErrNoModel", err)
+	}
+}
+
+func TestAnthropicChat_ChatStream_Text(t *testing.T) {
+	t.Parallel()
+	sse := strings.Join([]string{
+		`data: {"type":"message_start","message":{"model":"claude-test","usage":{"input_tokens":5}}}`,
+		``,
+		`data: {"type":"content_block_start","index":0,"content_block":{"type":"text","text":""}}`,
+		``,
+		`data: {"type":"content_block_delta","index":0,"delta":{"type":"text_delta","text":"Hel"}}`,
+		``,
+		`data: {"type":"content_block_delta","index":0,"delta":{"type":"text_delta","text":"lo"}}`,
+		``,
+		`data: {"type":"content_block_stop","index":0}`,
+		``,
+		`data: {"type":"message_delta","delta":{"stop_reason":"end_turn"},"usage":{"output_tokens":2}}`,
+		``,
+		`data: {"type":"message_stop"}`,
+		``,
+	}, "\n")
+	ch := make(chan anthropicCaptured, 1)
+	srv := newAnthropicServer(t, http.StatusOK, "text/event-stream", sse, ch)
+
+	recs := make([]CallRecord, 0, 1)
+	ad := NewAnthropicChat(config.LLMConfig{AnthropicBaseURL: srv.URL, AnthropicModel: "claude-test"},
+		WithAnthropicRecorder(func(cr CallRecord) { recs = append(recs, cr) }))
+
+	var deltas []string
+	resp, err := ad.ChatStream(context.Background(),
+		Request{Messages: []Message{TextMessage(RoleUser, "hi")}, Model: "claude-test", Purpose: "chat"},
+		func(d string) { deltas = append(deltas, d) })
+	if err != nil {
+		t.Fatalf("ChatStream error: %v", err)
+	}
+
+	got := <-ch
+	if got.accept != "text/event-stream" {
+		t.Errorf("accept = %s, want text/event-stream", got.accept)
+	}
+	if got.body["stream"] != true {
+		t.Errorf("body.stream = %v, want true", got.body["stream"])
+	}
+
+	if resp.Content != "Hello" {
+		t.Errorf("resp.Content = %q, want Hello", resp.Content)
+	}
+	if resp.Model != "claude-test" {
+		t.Errorf("resp.Model = %q, want claude-test", resp.Model)
+	}
+	if resp.TotalTokens != 7 {
+		t.Errorf("resp.TotalTokens = %d, want 7", resp.TotalTokens)
+	}
+	if !reflect.DeepEqual(deltas, []string{"Hel", "lo"}) {
+		t.Errorf("deltas = %v, want [Hel lo]", deltas)
+	}
+	if len(recs) != 1 || recs[0].Tokens != 7 || recs[0].Purpose != "chat" {
+		t.Errorf("records = %+v, want 1 record tokens=7 purpose=chat", recs)
+	}
+}
+
+func TestAnthropicChat_ChatStream_ToolUseReassembly(t *testing.T) {
+	t.Parallel()
+	sse := strings.Join([]string{
+		`data: {"type":"message_start","message":{"model":"claude-test","usage":{"input_tokens":10}}}`,
+		``,
+		`data: {"type":"content_block_start","index":0,"content_block":{"type":"tool_use","id":"toolu_1","name":"lookup","input":{}}}`,
+		``,
+		`data: {"type":"content_block_delta","index":0,"delta":{"type":"input_json_delta","partial_json":"{\"location\":"}}`,
+		``,
+		`data: {"type":"content_block_delta","index":0,"delta":{"type":"input_json_delta","partial_json":"\"Paris\"}"}}`,
+		``,
+		`data: {"type":"content_block_stop","index":0}`,
+		``,
+		`data: {"type":"message_delta","delta":{"stop_reason":"tool_use"},"usage":{"output_tokens":8}}`,
+		``,
+		`data: {"type":"message_stop"}`,
+		``,
+	}, "\n")
+	srv := newAnthropicServer(t, http.StatusOK, "text/event-stream", sse, nil)
+	ad := NewAnthropicChat(config.LLMConfig{AnthropicBaseURL: srv.URL, AnthropicModel: "claude-test"})
+
+	var deltas []string
+	resp, err := ad.ChatStream(context.Background(),
+		Request{Messages: []Message{TextMessage(RoleUser, "hi")}, Model: "claude-test"},
+		func(d string) { deltas = append(deltas, d) })
+	if err != nil {
+		t.Fatalf("ChatStream error: %v", err)
+	}
+
+	if len(resp.ToolCalls) != 1 {
+		t.Fatalf("resp.ToolCalls = %+v, want 1", resp.ToolCalls)
+	}
+	tc := resp.ToolCalls[0]
+	if tc.Name != "lookup" {
+		t.Errorf("tool call name = %q, want lookup", tc.Name)
+	}
+	if tc.Args["location"] != "Paris" {
+		t.Errorf("tool call args.location = %v, want Paris (reassembled from partial_json)", tc.Args["location"])
+	}
+	if resp.Content != "" {
+		t.Errorf("resp.Content = %q, want empty (tool-only response)", resp.Content)
+	}
+	if resp.TotalTokens != 18 {
+		t.Errorf("resp.TotalTokens = %d, want 18", resp.TotalTokens)
+	}
+	if len(deltas) != 0 {
+		t.Errorf("deltas = %v, want none (only tool_use)", deltas)
+	}
+}
+
+func TestAnthropicChat_ChatStream_NoMessageStop(t *testing.T) {
+	t.Parallel()
+	sse := strings.Join([]string{
+		`data: {"type":"message_start","message":{"model":"claude-test","usage":{"input_tokens":5}}}`,
+		``,
+		`data: {"type":"content_block_start","index":0,"content_block":{"type":"text","text":""}}`,
+		``,
+		`data: {"type":"content_block_delta","index":0,"delta":{"type":"text_delta","text":"Hi"}}`,
+		``,
+	}, "\n")
+	srv := newAnthropicServer(t, http.StatusOK, "text/event-stream", sse, nil)
+	ad := NewAnthropicChat(config.LLMConfig{AnthropicBaseURL: srv.URL, AnthropicModel: "claude-test"})
+	if _, err := ad.ChatStream(context.Background(),
+		Request{Messages: []Message{TextMessage(RoleUser, "hi")}, Model: "claude-test"}, nil); !errors.Is(err, ErrStream) {
+		t.Fatalf("err = %v, want ErrStream", err)
+	}
+}
+
+func TestAnthropicChat_ToolResult(t *testing.T) {
+	t.Parallel()
+	blk := AnthropicToolResult("toolu_1", `{"ok":true}`, true)
+	if blk["type"] != "tool_result" {
+		t.Errorf("type = %v, want tool_result", blk["type"])
+	}
+	if blk["tool_use_id"] != "toolu_1" {
+		t.Errorf("tool_use_id = %v, want toolu_1", blk["tool_use_id"])
+	}
+	if blk["content"] != `{"ok":true}` {
+		t.Errorf("content = %v, want the raw result", blk["content"])
+	}
+	if blk["is_error"] != true {
+		t.Errorf("is_error = %v, want true", blk["is_error"])
+	}
+}

internal/runtime/model/factory.go

@@ -0,0 +1,87 @@
+package model
+
+import (
+	"errors"
+	"fmt"
+
+	"git.yeij.top/AskaEth/Cyrene_v2/internal/config"
+)
+
+// Provider names accepted by the provider-aware factory. These are the only two
+// protocols the factory understands today; adding a vendor means adding a case
+// here plus a matching adapter, not touching the rest of the package.
+const (
+	// ProviderOpenAI selects the OpenAI-compatible /chat/completions protocol.
+	ProviderOpenAI = "openai"
+	// ProviderAnthropic selects the Anthropic Messages /v1/messages protocol.
+	ProviderAnthropic = "anthropic"
+)
+
+// ErrUnknownProvider is returned by the provider-aware factory when the
+// configured provider name is not recognized.
+var ErrUnknownProvider = errors.New("model: unknown provider")
+
+// NewChatAdapter builds a single provider adapter selected by cfg.Provider. The
+// empty provider defaults to openai for backward compatibility. An unrecognized
+// provider returns ErrUnknownProvider.
+func NewChatAdapter(cfg config.LLMConfig) (Adapter, error) {
+	switch cfg.Provider {
+	case ProviderOpenAI, "":
+		return NewOpenAIChat(cfg), nil
+	case ProviderAnthropic:
+		return NewAnthropicChat(cfg), nil
+	default:
+		return nil, fmt.Errorf("model: %w: provider %q", ErrUnknownProvider, cfg.Provider)
+	}
+}
+
+// NewChatChain builds a fallback Chain for the configured provider: the primary
+// model first, then the provider's fallback model when set and distinct. Each
+// step is served by an adapter of the selected protocol. The empty provider
+// defaults to openai. An unrecognized provider returns ErrUnknownProvider.
+func NewChatChain(cfg config.LLMConfig) (*Chain, error) {
+	switch cfg.Provider {
+	case ProviderOpenAI, "":
+		return newOpenAIChain(cfg)
+	case ProviderAnthropic:
+		return newAnthropicChain(cfg)
+	default:
+		return nil, fmt.Errorf("model: %w: provider %q", ErrUnknownProvider, cfg.Provider)
+	}
+}
+
+// newOpenAIChain builds a fallback chain from the OpenAI-compatible config block.
+// Each step is an OpenAIChatAdapter against the configured endpoint.
+func newOpenAIChain(cfg config.LLMConfig, opts ...OpenAIOption) (*Chain, error) {
+	if cfg.BaseURL == "" || cfg.Model == "" {
+		return nil, ErrNoModel
+	}
+	steps := []Step{{Model: cfg.Model, Adapter: NewOpenAIChat(cfg, opts...)}}
+	if cfg.Fallback != "" && cfg.Fallback != cfg.Model {
+		steps = append(steps, Step{Model: cfg.Fallback, Adapter: NewOpenAIChat(cfg, opts...)})
+	}
+	return NewChain(steps...), nil
+}
+
+// newAnthropicChain builds a fallback chain from the Anthropic config block. Each
+// step is an AnthropicChatAdapter against the configured /v1/messages endpoint.
+func newAnthropicChain(cfg config.LLMConfig) (*Chain, error) {
+	if cfg.AnthropicBaseURL == "" || cfg.AnthropicModel == "" {
+		return nil, ErrNoModel
+	}
+	steps := []Step{{Model: cfg.AnthropicModel, Adapter: NewAnthropicChat(cfg)}}
+	if cfg.AnthropicFallback != "" && cfg.AnthropicFallback != cfg.AnthropicModel {
+		steps = append(steps, Step{Model: cfg.AnthropicFallback, Adapter: NewAnthropicChat(cfg)})
+	}
+	return NewChain(steps...), nil
+}
+
+// DefaultModelForProvider returns the primary model name for the configured
+// provider: the flat OpenAI Model for "openai", the Anthropic model for
+// "anthropic". Used by callers (e.g. cmd/cyrene) to seed a Router's default.
+func DefaultModelForProvider(cfg config.LLMConfig) string {
+	if cfg.Provider == ProviderAnthropic {
+		return cfg.AnthropicModel
+	}
+	return cfg.Model
+}

internal/runtime/model/factory_test.go

@@ -0,0 +1,199 @@
+package model
+
+import (
+	"context"
+	"errors"
+	"io"
+	"net/http"
+	"net/http/httptest"
+	"testing"
+
+	"git.yeij.top/AskaEth/Cyrene_v2/internal/config"
+)
+
+func TestNewChatAdapter_Provider(t *testing.T) {
+	t.Parallel()
+	cases := []struct {
+		name     string
+		provider string
+		wantType any
+		wantErr  bool
+	}{
+		{"openai", ProviderOpenAI, (*OpenAIChatAdapter)(nil), false},
+		{"empty defaults to openai", "", (*OpenAIChatAdapter)(nil), false},
+		{"anthropic", ProviderAnthropic, (*AnthropicChatAdapter)(nil), false},
+		{"unknown", "gemini", nil, true},
+	}
+	for _, c := range cases {
+		c := c
+		t.Run(c.name, func(t *testing.T) {
+			t.Parallel()
+			ad, err := NewChatAdapter(config.LLMConfig{Provider: c.provider, Model: "m", AnthropicModel: "m"})
+			if c.wantErr {
+				if !errors.Is(err, ErrUnknownProvider) {
+					t.Fatalf("err = %v, want ErrUnknownProvider", err)
+				}
+				if ad != nil {
+					t.Fatalf("adapter = %v, want nil on error", ad)
+				}
+				return
+			}
+			if err != nil {
+				t.Fatalf("NewChatAdapter error: %v", err)
+			}
+			switch c.wantType.(type) {
+			case *OpenAIChatAdapter:
+				if _, ok := ad.(*OpenAIChatAdapter); !ok {
+					t.Fatalf("adapter = %T, want *OpenAIChatAdapter", ad)
+				}
+			case *AnthropicChatAdapter:
+				if _, ok := ad.(*AnthropicChatAdapter); !ok {
+					t.Fatalf("adapter = %T, want *AnthropicChatAdapter", ad)
+				}
+			}
+		})
+	}
+}
+
+func TestNewChatChain_Provider(t *testing.T) {
+	t.Parallel()
+	t.Run("openai primary and fallback", func(t *testing.T) {
+		t.Parallel()
+		chain, err := NewChatChain(config.LLMConfig{Provider: ProviderOpenAI, BaseURL: "http://x", Model: "m", Fallback: "fb"})
+		if err != nil {
+			t.Fatalf("NewChatChain error: %v", err)
+		}
+		if len(chain.steps) != 2 {
+			t.Fatalf("steps = %d, want 2", len(chain.steps))
+		}
+		if chain.steps[0].Model != "m" || chain.steps[1].Model != "fb" {
+			t.Errorf("step models = [%s %s], want [m fb]", chain.steps[0].Model, chain.steps[1].Model)
+		}
+		if _, ok := chain.steps[0].Adapter.(*OpenAIChatAdapter); !ok {
+			t.Errorf("step[0] adapter = %T, want *OpenAIChatAdapter", chain.steps[0].Adapter)
+		}
+	})
+
+	t.Run("anthropic primary and fallback", func(t *testing.T) {
+		t.Parallel()
+		chain, err := NewChatChain(config.LLMConfig{
+			Provider:          ProviderAnthropic,
+			AnthropicBaseURL:  "http://x",
+			AnthropicModel:    "claude-main",
+			AnthropicFallback: "claude-fb",
+		})
+		if err != nil {
+			t.Fatalf("NewChatChain error: %v", err)
+		}
+		if len(chain.steps) != 2 {
+			t.Fatalf("steps = %d, want 2", len(chain.steps))
+		}
+		if chain.steps[0].Model != "claude-main" || chain.steps[1].Model != "claude-fb" {
+			t.Errorf("step models = [%s %s], want [claude-main claude-fb]", chain.steps[0].Model, chain.steps[1].Model)
+		}
+		if _, ok := chain.steps[0].Adapter.(*AnthropicChatAdapter); !ok {
+			t.Errorf("step[0] adapter = %T, want *AnthropicChatAdapter", chain.steps[0].Adapter)
+		}
+	})
+
+	t.Run("missing model returns ErrNoModel", func(t *testing.T) {
+		t.Parallel()
+		if _, err := NewChatChain(config.LLMConfig{Provider: ProviderOpenAI, BaseURL: "http://x"}); !errors.Is(err, ErrNoModel) {
+			t.Fatalf("openai err = %v, want ErrNoModel", err)
+		}
+		if _, err := NewChatChain(config.LLMConfig{Provider: ProviderAnthropic, AnthropicBaseURL: "http://x"}); !errors.Is(err, ErrNoModel) {
+			t.Fatalf("anthropic err = %v, want ErrNoModel", err)
+		}
+	})
+
+	t.Run("unknown provider returns ErrUnknownProvider", func(t *testing.T) {
+		t.Parallel()
+		if _, err := NewChatChain(config.LLMConfig{Provider: "gemini"}); !errors.Is(err, ErrUnknownProvider) {
+			t.Fatalf("err = %v, want ErrUnknownProvider", err)
+		}
+	})
+}
+
+func TestNewOpenAIChatChain_StillWorks(t *testing.T) {
+	t.Parallel()
+	chain, err := NewOpenAIChatChain(config.LLMConfig{BaseURL: "http://x", Model: "m", Fallback: "fb"})
+	if err != nil {
+		t.Fatalf("NewOpenAIChatChain error: %v", err)
+	}
+	if len(chain.steps) != 2 {
+		t.Fatalf("steps = %d, want 2", len(chain.steps))
+	}
+	if _, ok := chain.steps[0].Adapter.(*OpenAIChatAdapter); !ok {
+		t.Errorf("step[0] adapter = %T, want *OpenAIChatAdapter", chain.steps[0].Adapter)
+	}
+}
+
+func TestDefaultModelForProvider(t *testing.T) {
+	t.Parallel()
+	if got := DefaultModelForProvider(config.LLMConfig{Provider: ProviderOpenAI, Model: "gpt"}); got != "gpt" {
+		t.Errorf("openai = %q, want gpt", got)
+	}
+	if got := DefaultModelForProvider(config.LLMConfig{Provider: ProviderAnthropic, AnthropicModel: "claude"}); got != "claude" {
+		t.Errorf("anthropic = %q, want claude", got)
+	}
+}
+
+func TestRouter_RouteProvider(t *testing.T) {
+	t.Parallel()
+	r := NewRouter("default",
+		WithDefaultProvider(ProviderAnthropic),
+		WithRoleProvider(Role("engineer"), ProviderOpenAI),
+	)
+	cases := []struct {
+		role Role
+		want string
+	}{
+		{Role("engineer"), ProviderOpenAI},
+		{Role("user"), ProviderAnthropic},
+		{Role("assistant"), ProviderAnthropic},
+	}
+	for _, c := range cases {
+		c := c
+		t.Run(string(c.role), func(t *testing.T) {
+			t.Parallel()
+			if got := r.RouteProvider(c.role); got != c.want {
+				t.Fatalf("RouteProvider(%q) = %q, want %q", c.role, got, c.want)
+			}
+		})
+	}
+}
+
+// TestChain_AnthropicFallback exercises the fallback chain against two Anthropic
+// adapters: the primary step fails and the backup step succeeds, proving the
+// adapter composes cleanly inside a Chain.
+func TestChain_AnthropicFallback(t *testing.T) {
+	t.Parallel()
+	primary := httptest.NewServer(http.HandlerFunc(func(w http.ResponseWriter, _ *http.Request) {
+		w.WriteHeader(http.StatusInternalServerError)
+		_, _ = io.WriteString(w, `{"error":"down"}`)
+	}))
+	t.Cleanup(primary.Close)
+	backup := httptest.NewServer(http.HandlerFunc(func(w http.ResponseWriter, _ *http.Request) {
+		w.Header().Set("Content-Type", "application/json")
+		w.WriteHeader(http.StatusOK)
+		_, _ = io.WriteString(w, `{"id":"msg_b","model":"backup","content":[{"type":"text","text":"Hello!"}],"usage":{"input_tokens":5,"output_tokens":2}}`)
+	}))
+	t.Cleanup(backup.Close)
+
+	chain := NewChain(
+		Step{Model: "main", Adapter: NewAnthropicChat(config.LLMConfig{AnthropicBaseURL: primary.URL, AnthropicModel: "main"})},
+		Step{Model: "backup", Adapter: NewAnthropicChat(config.LLMConfig{AnthropicBaseURL: backup.URL, AnthropicModel: "backup"})},
+	)
+
+	resp, err := chain.Chat(context.Background(),
+		Request{Messages: []Message{TextMessage(RoleUser, "hi")}, Purpose: "chat"}, Options{})
+	if err != nil {
+		t.Fatalf("Chain.Chat error: %v", err)
+	}
+	if resp.Content != "Hello!" {
+		t.Errorf("resp.Content = %q, want Hello!", resp.Content)
+	}
+	if resp.Model != "backup" {
+		t.Errorf("resp.Model = %q, want backup", resp.Model)
+	}
+}

internal/runtime/model/fallback.go

@@ -29,16 +29,10 @@ func NewChain(steps ...Step) *Chain {
 // NewOpenAIChatChain builds a fallback chain from a single supplier config: the
 // primary model first, then cfg.Fallback (when set and distinct), both served
 // by an OpenAIChatAdapter against the same OpenAI-compatible endpoint. It
-// returns ErrNoModel when no base URL or primary model is configured.
+// delegates to the provider-aware builder so the OpenAI path and the factory stay
+// in sync. It returns ErrNoModel when no base URL or primary model is configured.
 func NewOpenAIChatChain(cfg config.LLMConfig, opts ...OpenAIOption) (*Chain, error) {
-	if cfg.BaseURL == "" || cfg.Model == "" {
-		return nil, ErrNoModel
-	}
-	steps := []Step{{Model: cfg.Model, Adapter: NewOpenAIChat(cfg, opts...)}}
-	if cfg.Fallback != "" && cfg.Fallback != cfg.Model {
-		steps = append(steps, Step{Model: cfg.Fallback, Adapter: NewOpenAIChat(cfg, opts...)})
-	}
-	return NewChain(steps...), nil
+	return newOpenAIChain(cfg, opts...)
 }
 
 // Name returns the chain identifier.

internal/runtime/model/model.go

@@ -87,6 +87,18 @@ type ToolSpec struct {
 	Parameters any
 }
 
+// ToolCall is a single assistant-originated tool invocation parsed from a
+// provider's tool_use content block. Args is the structured argument object
+// (never a serialized JSON string), so a tool loop can bind it directly without
+// re-parsing.
+type ToolCall struct {
+	// Name is the tool being invoked.
+	Name string
+	// Args are the tool arguments, decoded from the provider's structured
+	// tool_use.input object. It is never a JSON-encoded string.
+	Args map[string]any
+}
+
 // Request is a completion request, normalized across providers.
 type Request struct {
 	// Model overrides the adapter's configured default model. Empty means the
@@ -101,6 +113,11 @@ type Request struct {
 	Purpose string
 	// Tools is the interface-level placeholder for M2 function calling.
 	Tools []ToolSpec
+	// ToolChoice optionally directs how the provider selects a tool. It is an
+	// opaque provider-agnostic directive (e.g. {"type":"auto"} or {"type":"tool",
+	// "name":"x"}); empty means the provider default. Passed through verbatim to
+	// protocols that support it (Anthropic's tool_choice).
+	ToolChoice any
 }
 
 // Response is a normalized completion result.
@@ -110,6 +127,9 @@ type Response struct {
 	Content string
 	// Message is the normalized assistant message.
 	Message Message
+	// ToolCalls carries any tool_use blocks the assistant emitted. Empty when the
+	// response is pure text.
+	ToolCalls []ToolCall
 	// PromptTokens, CompletionTokens and TotalTokens report provider usage when
 	// available; zero when the provider does not return it.
 	PromptTokens     int

internal/runtime/model/router.go

@@ -2,11 +2,16 @@ package model
 
 // Router maps roles to model names. An unknown role resolves to the configured
 // default model. When a request carries image content and a vision model is
-// configured, the request routes to the vision model.
+// configured, the request routes to the vision model. A Router also carries a
+// provider per role (defaulting to the global provider) so a multi-vendor
+// deployment can pair a role's model with the correct protocol; the provider
+// selection is surfaced via RouteProvider.
 type Router struct {
-	defaultModel string
-	byRole       map[Role]string
-	visionModel  string
+	defaultModel    string
+	byRole          map[Role]string
+	visionModel     string
+	defaultProvider string
+	providerByRole  map[Role]string
 }
 
 // RouterOption configures a Router.
@@ -22,10 +27,28 @@ func WithVisionModel(model string) RouterOption {
 	return func(r *Router) { r.visionModel = model }
 }
 
+// WithDefaultProvider sets the provider returned by RouteProvider for roles with
+// no explicit binding. It defaults to openai.
+func WithDefaultProvider(provider string) RouterOption {
+	return func(r *Router) { r.defaultProvider = provider }
+}
+
+// WithRoleProvider binds a provider to a role, so a multi-vendor deployment can
+// route a role to a different vendor's protocol (e.g. one role on anthropic, one
+// on openai). Pair it with WithRoleModel for the role's model name.
+func WithRoleProvider(role Role, provider string) RouterOption {
+	return func(r *Router) { r.providerByRole[role] = provider }
+}
+
 // NewRouter builds a Router with a default model applied to any role that has
 // no explicit binding.
 func NewRouter(defaultModel string, opts ...RouterOption) *Router {
-	r := &Router{defaultModel: defaultModel, byRole: map[Role]string{}}
+	r := &Router{
+		defaultModel:    defaultModel,
+		byRole:          map[Role]string{},
+		defaultProvider: ProviderOpenAI,
+		providerByRole:  map[Role]string{},
+	}
 	for _, o := range opts {
 		o(r)
 	}
@@ -40,6 +63,18 @@ func (r *Router) Route(role Role) string {
 	return r.defaultModel
 }
 
+// RouteProvider returns the provider for a role, falling back to the router's
+// default provider. It is the routing hook for a multi-vendor deployment: each
+// role can carry its own provider+model pairing, and roles without a binding fall
+// back to the global provider. The runtime/loop is expected to build a per-role
+// adapter or chain from this decision (the provider-aware factory is the builder).
+func (r *Router) RouteProvider(role Role) string {
+	if p, ok := r.providerByRole[role]; ok && p != "" {
+		return p
+	}
+	return r.defaultProvider
+}
+
 // RouteRequest picks the model for a request and reports whether the request
 // needs a vision model. When the request carries image content and a vision
 // model is configured, the vision model is returned with needsVision set to