- 新增 reasoning_shape.go:**每个 provider 形状一个 resolver,只发自己形状的字段**
· deepseek:thinking{type} + reasoning_effort(依据 DevDocs/reference/deepseek 官方本地副本)
· vllm:chat_template_kwargs.enable_thinking · dashscope:顶层 enable_thinking(**只允许显式声明**)
· openai:仅 reasoning_effort · anthropic:自己的 thinking{budget_tokens}(未改)
· 未知 kind → WARN 且一个字段都不发(不许静默失效)
- 形状载体:models.json 组级 `reasoning.kind`(可热更新,未声明则不写该键)+ env `LLM_REASONING_KIND`
- 红线:`effort:none` 在只有布尔开关的形状上翻成**显式关思考**,绝不降成任何强度档
- 03.4.1 余项:`Request.PersonaID` + `RuntimeLLM.ForPersona(pid)` 视图;
每 persona 协议一条链并消费 `RouteProviderForPersona`;`agent/request.go` 非流式路径同一钩子
- **生产装配(主会话补)**:默认 agent 与 personaAgentPool 都改用 `ForPersona(pid)` 视图——
否则角色级模型/提供商路由在生产里永不被选中(形同虚设)
- 复核:build/vet 绿 + model/agent/config/cmd 包测试绿;5 条变异反证先红后还原
(其中一条「红但没钉住」已改用例:通道读取加 2s 超时,避免整包 panic 掩盖信号)
- 未落:DashScope 的 auto 推断(缺官方依据,只允许显式声明);Qwen `/think` 前导消息
(design/01 §2.1 与 design/11 §3 口径冲突,停手报告)
247 lines
8.6 KiB
Go
247 lines
8.6 KiB
Go
package model
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import (
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"encoding/json"
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"fmt"
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)
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// openAIChatRequest is the JSON body sent to /chat/completions. Field names
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// match the provider protocol so the struct marshals directly.
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type openAIChatRequest struct {
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Model string `json:"model"`
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Messages []openAIMessage `json:"messages"`
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Temperature *float64 `json:"temperature,omitempty"`
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MaxTokens int `json:"max_tokens,omitempty"`
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Stream bool `json:"stream,omitempty"`
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StreamOptions *openAIStreamOpts `json:"stream_options,omitempty"`
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Tools []openAITool `json:"tools,omitempty"`
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// Thinking is DeepSeek's top-level thinking switch. It is sent only for
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// DeepSeek and only from an explicit switch (or an explicit off that must be
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// honoured): leaving it out keeps the provider default, which is ENABLED, so
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// an omitted field is not a way to switch thinking off (design/04 §3.2
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// fact 2).
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Thinking *openAIThinking `json:"thinking,omitempty"`
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// ReasoningEffort is the OpenAI-compatible reasoning strength knob. It is set
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// only after validation against the detected vendor's whitelist (design/04
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// §3.2); an unrecognized value is dropped, never turned into a different tier.
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ReasoningEffort string `json:"reasoning_effort,omitempty"`
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// ChatTemplateKwargs carries the vLLM-style thinking switch
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// (chat_template_kwargs.enable_thinking, design/04 §3.2 Qwen3 行). It is sent
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// only to an endpoint whose provider declared reasoning.kind=vllm.
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ChatTemplateKwargs *openAIChatTemplateKwargs `json:"chat_template_kwargs,omitempty"`
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// EnableThinking carries the DashScope compatible-mode thinking switch (the
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// top-level enable_thinking). It is sent only to an endpoint whose provider
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// declared reasoning.kind=dashscope — the shape is never inferred, because a
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// wrong shape 400s the request.
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EnableThinking *bool `json:"enable_thinking,omitempty"`
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}
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// openAIThinking is the wire form of DeepSeek's thinking switch: enabled or
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// disabled. It is only ever sent to a DeepSeek endpoint.
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type openAIThinking struct {
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Type string `json:"type"`
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}
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// openAIChatTemplateKwargs is the wire form of the vLLM (Qwen3) thinking switch:
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// the boolean lives nested under chat_template_kwargs.
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type openAIChatTemplateKwargs struct {
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EnableThinking *bool `json:"enable_thinking,omitempty"`
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}
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// openAIStreamOpts asks the provider to include usage in the final stream chunk.
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type openAIStreamOpts struct {
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IncludeUsage bool `json:"include_usage"`
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}
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// openAIMessage is one request message in the wire body. Content is either a
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// plain string (text-only) or an array of {type,text|image_url} parts. Tool
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// messages carry ToolCallID (required by OpenAI); assistant messages that
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// requested functions carry ToolCalls so the following tool messages can be
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// correlated.
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type openAIMessage struct {
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Role string `json:"role"`
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Content any `json:"content"`
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ToolCallID string `json:"tool_call_id,omitempty"`
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ToolCalls []openAIToolCall `json:"tool_calls,omitempty"`
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}
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// openAIToolCall is the wire form of one assistant tool_call in a request. OpenAI
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// requires each subsequent tool message to reference the id back to these calls.
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type openAIToolCall struct {
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ID string `json:"id"`
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Type string `json:"type"`
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Function openAIToolCallFn `json:"function"`
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}
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// openAITool is the wire form of a function tool schema (M2 placeholder).
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type openAITool struct {
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Type string `json:"type"`
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Function openAIToolFn `json:"function"`
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}
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// openAIToolFn carries the function definition.
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type openAIToolFn struct {
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Name string `json:"name"`
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Description string `json:"description,omitempty"`
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Parameters any `json:"parameters,omitempty"`
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}
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// openAIToolCallFn is the function part of a streaming tool-call fragment.
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type openAIToolCallFn struct {
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Name string `json:"name"`
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Arguments string `json:"arguments"`
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}
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func (a *OpenAIChatAdapter) buildRequest(req Request, stream bool) ([]byte, error) {
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msgs, err := buildMessages(req.Messages)
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if err != nil {
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return nil, err
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}
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// The vendor behind an OpenAI-compatible endpoint decides which
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// reasoning_effort tiers are legal and whether it has a thinking switch;
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// classify it from the resolved model (and the base URL as a fallback) before
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// touching the request. The endpoint's configured shape (models.json
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// reasoning.kind, 裁决 03.4.2/08.4.1) wins over that classification, because
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// the same wire protocol carries different switch shapes (vLLM vs DashScope).
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vendor := reasoningVendorFor(req.Model, a.baseURL)
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plan := resolveOpenAIReasoning(a.log, a.reasoningKind, vendor, req.Model, req.Thinking, req.ReasoningEffort)
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reportForcedToolChoiceWithThinking(a.log, plan.provider, req.Model, req.ToolChoice, plan.thinkingOn())
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wire := openAIChatRequest{
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Model: req.Model,
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Messages: msgs,
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Temperature: req.Temperature,
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MaxTokens: req.MaxTokens,
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Stream: stream,
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Tools: buildTools(req.Tools),
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Thinking: plan.thinking,
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ReasoningEffort: plan.effort,
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ChatTemplateKwargs: plan.template,
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EnableThinking: plan.enable,
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}
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if stream {
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wire.StreamOptions = &openAIStreamOpts{IncludeUsage: true}
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}
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buf, err := json.Marshal(wire)
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if err != nil {
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return nil, fmt.Errorf("model: %w: marshal request: %v", ErrBadRequest, err)
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}
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return buf, nil
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}
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func buildMessages(msgs []Message) ([]openAIMessage, error) {
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out := make([]openAIMessage, 0, len(msgs))
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for _, m := range msgs {
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wire, err := encodeOpenAIMessage(m)
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if err != nil {
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return nil, err
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}
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out = append(out, wire)
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}
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return out, nil
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}
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// encodeOpenAIMessage renders one normalized message in OpenAI wire form. A
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// RoleTool turn becomes a tool message carrying tool_call_id (required by OpenAI,
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// and the audit's gap); an assistant turn that advertised tool calls carries the
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// corresponding tool_calls array so the provider can correlate the tool messages.
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func encodeOpenAIMessage(m Message) (openAIMessage, error) {
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if m.Role == RoleTool {
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return openAIMessage{
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Role: string(RoleTool),
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ToolCallID: toolMessageCallID(m),
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Content: messageText(m),
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}, nil
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}
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content, err := encodeContent(m.Content)
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if err != nil {
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return openAIMessage{}, err
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}
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return openAIMessage{Role: string(m.Role), Content: content, ToolCalls: encodeToolCalls(m.Content)}, nil
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}
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// toolMessageCallID resolves the tool_call_id for a RoleTool turn: the
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// message-level id, else the id carried on the first tool-result part.
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func toolMessageCallID(m Message) string {
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if m.ToolCallID != "" {
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return m.ToolCallID
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}
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for _, p := range m.Content {
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if p.ToolCallID != "" {
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return p.ToolCallID
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}
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}
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return ""
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}
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// encodeToolCalls builds the assistant tool_calls array from a turn's tool-call
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// parts. Arguments are serialized to JSON because OpenAI expects a string.
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func encodeToolCalls(parts []Content) []openAIToolCall {
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calls := make([]openAIToolCall, 0, len(parts))
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for _, p := range parts {
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if p.Type != ContentTypeToolCall {
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continue
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}
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arguments := "{}"
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if len(p.ToolArgs) > 0 {
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if b, err := json.Marshal(p.ToolArgs); err == nil {
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arguments = string(b)
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}
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}
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calls = append(calls, openAIToolCall{
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ID: p.ToolCallID,
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Type: "function",
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Function: openAIToolCallFn{Name: p.ToolCallName, Arguments: arguments},
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})
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}
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return calls
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}
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func encodeContent(parts []Content) (any, error) {
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if len(parts) == 0 {
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return "", nil
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}
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arr := make([]any, 0, len(parts))
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for _, p := range parts {
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switch p.Type {
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case ContentTypeText:
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arr = append(arr, map[string]any{"type": "text", "text": p.Text})
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case ContentTypeImage:
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arr = append(arr, map[string]any{
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"type": "image_url",
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"image_url": map[string]any{"url": p.ImageURL},
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})
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case ContentTypeToolCall, ContentTypeToolResult:
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// Tool-call and tool-result parts are encoded at the message level
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// (tool_calls array / tool_call_id), never as text-image content.
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continue
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default:
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return nil, fmt.Errorf("model: %w: unsupported content type %q", ErrBadRequest, p.Type)
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}
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}
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if len(arr) == 0 {
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return "", nil
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}
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if len(arr) == 1 {
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if blk, ok := arr[0].(map[string]any); ok && blk["type"] == "image_url" {
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return arr, nil
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}
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return arr[0].(map[string]any)["text"], nil
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}
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return arr, nil
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}
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func buildTools(tools []ToolSpec) []openAITool {
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if len(tools) == 0 {
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return nil
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}
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out := make([]openAITool, 0, len(tools))
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for _, t := range tools {
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out = append(out, openAITool{Type: "function", Function: openAIToolFn{
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Name: t.Name,
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Description: t.Description,
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Parameters: t.Parameters,
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}})
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}
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return out
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}
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