Files
Cyrene_v2/internal/runtime/model/openai.go
T
Aska 2248ddce15
CI / Backend (build / vet / test / cross-compile) (push) Has been cancelled
CI / Frontend (tsc + vite build) (push) Has been cancelled
feat(web): 用户侧体验补齐——思维链/工具卡数据源 + 图片附件 + 语音上行 + home/vision/voice 真表现
- 打通 thinking/tool_call 运行时数据源:openai 发 thinking_*(reasoning_content)/tool_call_*
  (delta.tool_calls 累积重新组装 Args 非 JSON 串);anthropic_stream 发 thinking_*(content_block
  thinking start/delta/stop)。ws_bridge 已映射 thinking.*/tool_call.*,前端渲染活。
- 前端消息模型 + 附件:ChatMessage 加 image?;ChatInput 加附件按钮(file→base64)、预览/移除、
  image-aware onSend(text,image);VisionMessageBody 升级图像卡+识别 chip;VoiceMessageBody
  升级通话控制卡(live2D预留/波形/静音/挂断);HomeMessageBody 读真实 deviceUpdates(去掉
  sampleDevices 猜)。
- 激活 voice_input:ChatShell onVoice 不再 no-op → sendUp voice_input + 切 voice mode。
- addTool 改按工具名 upsert(修复 tool_call.start/end 重复卡);ws_mode_switch 应用 agent 驱动
  mode;addUserMessage/beginAssistant 带 image/mode;chatStream/useChat.send 带 image。
- 新增 image/phone 图标。

已知限制(标注):图片仅前端收集(后端 chatRequest 无 image 字段未接真推理);流式工具卡无真实
工具名(StreamEvent 只带 ID,回退 tool_<id前缀>);mode 由 agent 驱动但后端未逐消息下发 mode
(mode_switch 回显+默认当前 mode 兜底);voice 为 UI+voice_input 上行(真实通话后置)。
go build/vet/test + 前端 tsc 绿。
2026-09-06 17:43:03 +08:00

562 lines
17 KiB
Go

package model
import (
"bufio"
"bytes"
"context"
"encoding/json"
"fmt"
"io"
"net/http"
"strings"
"time"
"git.yeij.top/AskaEth/Cyrene_v2/internal/config"
)
// Wire constraints for the OpenAI-compatible /chat/completions protocol.
const (
// sseDataPrefix marks an SSE event line carrying a JSON payload.
sseDataPrefix = "data: "
// sseDone is the terminal SSE sentinel.
sseDone = "[DONE]"
// sseBufInit is the initial bufio.Scanner read buffer size.
sseBufInit = 64 * 1024
// maxSSELineBytes caps a single SSE event line.
maxSSELineBytes = 1024 * 1024
// errBodyCap bounds how much of an error body is read for the message.
errBodyCap = 512
// defaultHTTPTimeout bounds a single provider call when Options.Timeout is 0.
defaultHTTPTimeout = 180 * time.Second
)
// openAIChatRequest is the JSON body sent to /chat/completions. Field names
// match the provider protocol so the struct marshals directly.
type openAIChatRequest struct {
Model string `json:"model"`
Messages []openAIMessage `json:"messages"`
Temperature *float64 `json:"temperature,omitempty"`
MaxTokens int `json:"max_tokens,omitempty"`
Stream bool `json:"stream,omitempty"`
StreamOptions *openAIStreamOpts `json:"stream_options,omitempty"`
Tools []openAITool `json:"tools,omitempty"`
}
// openAIStreamOpts asks the provider to include usage in the final stream chunk.
type openAIStreamOpts struct {
IncludeUsage bool `json:"include_usage"`
}
// openAIMessage is one request message in the wire body. Content is either a
// plain string (text-only) or an array of {type,text|image_url} parts.
type openAIMessage struct {
Role string `json:"role"`
Content any `json:"content"`
}
// openAITool is the wire form of a function tool schema (M2 placeholder).
type openAITool struct {
Type string `json:"type"`
Function openAIToolFn `json:"function"`
}
// openAIToolFn carries the function definition.
type openAIToolFn struct {
Name string `json:"name"`
Description string `json:"description,omitempty"`
Parameters any `json:"parameters,omitempty"`
}
// openAIChatResponse is the JSON body returned by /chat/completions, for both
// the non-streaming payload and each SSE stream chunk.
type openAIChatResponse struct {
ID string `json:"id"`
Model string `json:"model"`
Choices []openAIChoice `json:"choices"`
Usage *openAIUsage `json:"usage,omitempty"`
}
// openAIChoice is one candidate completion.
type openAIChoice struct {
Index int `json:"index"`
Message openAIResponseMessage `json:"message"`
Delta *openAIDelta `json:"delta,omitempty"`
FinishReason string `json:"finish_reason,omitempty"`
}
// openAIResponseMessage is the assistant message inside a non-streaming choice.
type openAIResponseMessage struct {
Role string `json:"role"`
Content string `json:"content"`
}
// openAIDelta is the incremental payload inside a stream chunk. Reasoning content
// (OpenAI o-series / DeepSeek / DashScope) arrives in ReasoningContent; streaming
// function calls arrive in ToolCalls, accumulated per fragment index.
type openAIDelta struct {
Role string `json:"role"`
Content string `json:"content"`
ReasoningContent string `json:"reasoning_content"`
ToolCalls []openAIToolCallDelta `json:"tool_calls"`
}
// openAIToolCallDelta is one streaming function-call fragment. OpenAI emits a
// sequence of these sharing the same Index: the ID and Function.Name usually
// arrive once (in the first fragment) while Function.Arguments streams across
// fragments.
type openAIToolCallDelta struct {
Index int `json:"index"`
ID string `json:"id"`
Function openAIToolCallFn `json:"function"`
}
// openAIToolCallFn is the function part of a streaming tool-call fragment.
type openAIToolCallFn struct {
Name string `json:"name"`
Arguments string `json:"arguments"`
}
// openAIToolAcc accumulates the partial state of one streaming tool call (keyed
// by the provider's tool_calls[].index) so its arguments re-assemble across the
// delta fragments. started guards a single ToolCallStart emission per block.
type openAIToolAcc struct {
id string
name string
args strings.Builder
started bool
}
// idOrName resolves the block identifier used to correlate start/delta/end: the
// provider tool-call id when present, else the function name.
func (a *openAIToolAcc) idOrName() string {
if a.id != "" {
return a.id
}
return a.name
}
// openAIUsage reports token consumption.
type openAIUsage struct {
PromptTokens int `json:"prompt_tokens"`
CompletionTokens int `json:"completion_tokens"`
TotalTokens int `json:"total_tokens"`
}
// OpenAIChatAdapter calls an OpenAI-compatible /chat/completions endpoint. It is
// constructed from a config.LLMConfig and implements Adapter for both
// non-streaming and token-level SSE streaming.
type OpenAIChatAdapter struct {
name string
baseURL string
apiKey string
model string
client *http.Client
recorder Recorder
}
// OpenAIOption configures an OpenAIChatAdapter.
type OpenAIOption func(*OpenAIChatAdapter)
// WithHTTPClient overrides the default HTTP client (used to inject mocks or a
// tuned transport in tests and production).
func WithHTTPClient(c *http.Client) OpenAIOption {
return func(a *OpenAIChatAdapter) { a.client = c }
}
// WithRecorder wires a per-call Recorder for CallRecord accounting.
func WithRecorder(r Recorder) OpenAIOption {
return func(a *OpenAIChatAdapter) { a.recorder = r }
}
// WithModel overrides the adapter's default model name.
func WithModel(m string) OpenAIOption {
return func(a *OpenAIChatAdapter) { a.model = m }
}
// NewOpenAIChat builds an adapter from a supplier config. baseURL is trimmed of
// any trailing slash before the /chat/completions path is appended.
func NewOpenAIChat(cfg config.LLMConfig, opts ...OpenAIOption) *OpenAIChatAdapter {
a := &OpenAIChatAdapter{
name: "openai",
baseURL: strings.TrimRight(cfg.BaseURL, "/"),
apiKey: cfg.APIKey,
model: cfg.Model,
client: &http.Client{
Transport: http.DefaultTransport,
Timeout: defaultHTTPTimeout,
},
}
for _, o := range opts {
o(a)
}
return a
}
// Name returns the adapter identifier.
func (a *OpenAIChatAdapter) Name() string { return a.name }
// Chat performs a non-streaming completion.
func (a *OpenAIChatAdapter) 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 openAIChatResponse
if err := json.NewDecoder(resp.Body).Decode(&wire); err != nil {
return Response{}, fmt.Errorf("model: %w: decode response: %v", ErrUpstream, err)
}
out := responseFromWire(&wire)
a.record(req, start, out.TotalTokens)
return out, nil
}
// ChatStream streams structured events via onEvent and returns the aggregated
// response with usage when the provider reports it in the final chunk.
func (a *OpenAIChatAdapter) ChatStream(ctx context.Context, req Request, onEvent func(StreamEvent)) (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 := scanSSE(resp.Body, onEvent)
if err != nil {
return Response{}, err
}
out.Model = model
a.record(req, start, out.TotalTokens)
return out, nil
}
// withCallTimeout wraps ctx with opts.Timeout when it is positive.
func withCallTimeout(parent context.Context, opts Options) (context.Context, context.CancelFunc) {
if opts.Timeout > 0 {
return context.WithTimeout(parent, opts.Timeout)
}
return parent, func() {}
}
// resolveModel returns the effective model name.
func (a *OpenAIChatAdapter) 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 /chat/completions URL.
func (a *OpenAIChatAdapter) endpoint() string {
return a.baseURL + "/chat/completions"
}
func (a *OpenAIChatAdapter) buildRequest(req Request, stream bool) ([]byte, error) {
msgs, err := buildMessages(req.Messages)
if err != nil {
return nil, err
}
wire := openAIChatRequest{
Model: req.Model,
Messages: msgs,
Temperature: req.Temperature,
MaxTokens: req.MaxTokens,
Stream: stream,
Tools: buildTools(req.Tools),
}
if stream {
wire.StreamOptions = &openAIStreamOpts{IncludeUsage: true}
}
buf, err := json.Marshal(wire)
if err != nil {
return nil, fmt.Errorf("model: %w: marshal request: %v", ErrBadRequest, err)
}
return buf, nil
}
func buildMessages(msgs []Message) ([]openAIMessage, error) {
out := make([]openAIMessage, 0, len(msgs))
for _, m := range msgs {
content, err := encodeContent(m.Content)
if err != nil {
return nil, err
}
out = append(out, openAIMessage{Role: string(m.Role), Content: content})
}
return out, nil
}
func encodeContent(parts []Content) (any, error) {
if len(parts) == 0 {
return "", nil
}
if len(parts) == 1 && parts[0].Type == ContentTypeText {
return parts[0].Text, nil
}
arr := make([]any, 0, len(parts))
for _, p := range parts {
switch p.Type {
case ContentTypeText:
arr = append(arr, map[string]any{"type": "text", "text": p.Text})
case ContentTypeImage:
arr = append(arr, map[string]any{
"type": "image_url",
"image_url": map[string]any{"url": p.ImageURL},
})
default:
return nil, fmt.Errorf("model: %w: unsupported content type %q", ErrBadRequest, p.Type)
}
}
return arr, nil
}
func buildTools(tools []ToolSpec) []openAITool {
if len(tools) == 0 {
return nil
}
out := make([]openAITool, 0, len(tools))
for _, t := range tools {
out = append(out, openAITool{Type: "function", Function: openAIToolFn{
Name: t.Name,
Description: t.Description,
Parameters: t.Parameters,
}})
}
return out
}
func (a *OpenAIChatAdapter) doRequest(httpReq *http.Request, stream bool) (*http.Response, error) {
if a.apiKey != "" {
httpReq.Header.Set("Authorization", "Bearer "+a.apiKey)
}
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 *OpenAIChatAdapter) 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 *OpenAIChatAdapter) 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(),
})
}
func responseFromWire(wire *openAIChatResponse) Response {
out := Response{Model: wire.Model}
if len(wire.Choices) > 0 {
text := wire.Choices[0].Message.Content
out.Content = text
out.Message = Message{Role: RoleAssistant, Content: []Content{{Type: ContentTypeText, Text: text}}}
}
if u := wire.Usage; u != nil {
out.PromptTokens = u.PromptTokens
out.CompletionTokens = u.CompletionTokens
out.TotalTokens = u.TotalTokens
}
return out
}
// scanSSE incrementally decodes stream chunks, accumulates the full body text
// with a strings.Builder (never reading the whole body at once) and captures
// usage from the final chunk. It splits each delta into its segment and brackets
// them: reasoning_content as thinking_start/delta/end, tool_calls fragments as
// tool_call_start/delta/end, and body text as text_start/delta/end. The
// accumulated tool-call arguments re-assemble across fragments into a structured
// Args map, and are attached to the returned Response alongside the text.
func scanSSE(r io.Reader, onEvent func(StreamEvent)) (Response, error) {
scanner := bufio.NewScanner(r)
scanner.Buffer(make([]byte, 0, sseBufInit), maxSSELineBytes)
agg := Response{}
var text strings.Builder
textStarted := false
thinkingStarted := false
toolCalls := map[int]*openAIToolAcc{}
var toolOrder []int
endThinking := func() {
if onEvent != nil && thinkingStarted {
thinkingStarted = false
onEvent(StreamEvent{Kind: StreamKindThinkingEnd})
}
}
for scanner.Scan() {
line := strings.TrimSpace(scanner.Text())
if line == "" || !strings.HasPrefix(line, sseDataPrefix) {
continue
}
data := strings.TrimSpace(strings.TrimPrefix(line, sseDataPrefix))
if data == sseDone {
break
}
var chunk openAIChatResponse
if err := json.Unmarshal([]byte(data), &chunk); err != nil {
return Response{}, fmt.Errorf("model: %w: decode stream chunk: %v", ErrUpstream, err)
}
if u := chunk.Usage; u != nil {
agg.PromptTokens = u.PromptTokens
agg.CompletionTokens = u.CompletionTokens
agg.TotalTokens = u.TotalTokens
}
if len(chunk.Choices) == 0 || chunk.Choices[0].Delta == nil {
continue
}
delta := chunk.Choices[0].Delta
// Reasoning / thinking segment (OpenAI o-series, DeepSeek, DashScope).
if delta.ReasoningContent != "" {
if onEvent != nil && !thinkingStarted {
thinkingStarted = true
onEvent(StreamEvent{Kind: StreamKindThinkingStart})
}
if onEvent != nil {
onEvent(StreamEvent{Kind: StreamKindThinkingDelta, Delta: delta.ReasoningContent})
}
continue
}
// Streaming tool-call fragments.
if len(delta.ToolCalls) > 0 {
endThinking()
for _, tc := range delta.ToolCalls {
acc := toolCalls[tc.Index]
if acc == nil {
acc = &openAIToolAcc{}
toolCalls[tc.Index] = acc
toolOrder = append(toolOrder, tc.Index)
}
if acc.id == "" {
acc.id = tc.ID
}
if acc.name == "" {
acc.name = tc.Function.Name
}
if onEvent != nil && !acc.started && acc.idOrName() != "" {
acc.started = true
onEvent(StreamEvent{Kind: StreamKindToolCallStart, Index: tc.Index, ID: acc.idOrName()})
}
if tc.Function.Arguments != "" {
acc.args.WriteString(tc.Function.Arguments)
if onEvent != nil {
onEvent(StreamEvent{Kind: StreamKindToolCallDelta, Index: tc.Index, ID: acc.idOrName(), Delta: tc.Function.Arguments})
}
}
}
continue
}
// Body-text segment.
if delta.Content == "" {
continue
}
endThinking()
text.WriteString(delta.Content)
if onEvent != nil {
if !textStarted {
textStarted = true
onEvent(StreamEvent{Kind: StreamKindTextStart})
}
onEvent(StreamEvent{Kind: StreamKindTextDelta, Delta: delta.Content})
}
}
if err := scanner.Err(); err != nil {
return Response{}, fmt.Errorf("model: %w: read stream: %v", ErrUpstream, err)
}
if onEvent != nil {
if thinkingStarted {
onEvent(StreamEvent{Kind: StreamKindThinkingEnd})
}
if textStarted {
onEvent(StreamEvent{Kind: StreamKindTextEnd})
}
// OpenAI has no per-block stop event, so each tool_call block is closed
// when the stream terminates.
for _, idx := range toolOrder {
acc := toolCalls[idx]
if acc == nil || !acc.started {
continue
}
onEvent(StreamEvent{Kind: StreamKindToolCallEnd, Index: idx, ID: acc.idOrName()})
}
}
for _, idx := range toolOrder {
acc := toolCalls[idx]
if acc == nil {
continue
}
args := map[string]any{}
if acc.args.Len() > 0 {
if err := json.Unmarshal([]byte(acc.args.String()), &args); err != nil {
args = map[string]any{}
}
}
agg.ToolCalls = append(agg.ToolCalls, ToolCall{Name: acc.name, Args: args})
}
agg.Content = text.String()
agg.Message = Message{Role: RoleAssistant, Content: []Content{{Type: ContentTypeText, Text: agg.Content}}}
return agg, nil
}