feat: add OpenAI/Anthropic tools support with tool emulation

- Parse tools/tool_choice from OpenAI and Anthropic requests
- Inject tool definitions into system prompt via toolemulation
- Parse action blocks (```json action) from model responses
- Retry logic for forced tool_choice (any/required)
- Return proper tool_calls / tool_use in responses
- Support streaming tools via collect-and-replay pattern
- Add tool history projection (assistant tool_calls + tool results)
- Model ID normalization: use official names (Qwen3.6-Plus, etc.)
- Fix resolveSessionMode to use Fresh mode when tools present
This commit is contained in:
lutc5
2026-04-25 13:37:58 +08:00
parent c49b4b63e7
commit 74bbd8e6d2
13 changed files with 648 additions and 115 deletions

View File

@@ -14,6 +14,8 @@ Current scope:
- one request at a time
- supports Windows named-pipe transport and local websocket transport
- directly uses Lingma IPC, not DOM/CDP
- OpenAI-compatible `tools` / `tool_choice` support (tool emulation via prompt engineering)
- Anthropic-compatible `tools` / `tool_choice` support
## Run
@@ -69,6 +71,41 @@ Recommended layout:
}
```
## macOS / Linux
This project also works on macOS and Linux via **WebSocket transport**. The Windows named-pipe transport is automatically skipped on non-Windows platforms.
### Run on macOS
```bash
cd ~/OpenSources/lingma-ipc-proxy
go run ./cmd/lingma-ipc-proxy --transport websocket --port 8095
# Or use auto-detect (will discover websocket port from Lingma's shared client cache)
go run ./cmd/lingma-ipc-proxy --port 8095
```
### Build on macOS / Linux
```bash
cd ~/OpenSources/lingma-ipc-proxy
go build -o ./dist/lingma-ipc-proxy ./cmd/lingma-ipc-proxy
```
### macOS Config Example
```json
{
"host": "127.0.0.1",
"port": 8095,
"transport": "websocket",
"mode": "agent",
"shell_type": "zsh",
"session_mode": "auto",
"timeout": 120
}
```
## Build
Build a Windows executable:

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@@ -10,6 +10,7 @@ import (
"os"
"os/signal"
"path/filepath"
"runtime"
"strconv"
"strings"
"syscall"
@@ -88,7 +89,7 @@ func loadConfig() (service.Config, string) {
Transport: lingmaipc.TransportAuto,
Cwd: currentDir(),
Mode: "agent",
ShellType: "powershell",
ShellType: defaultShellType(),
SessionMode: service.SessionModeAuto,
Timeout: 120 * time.Second,
}
@@ -299,3 +300,10 @@ func valueOr(value string, fallback string) string {
}
return fallback
}
func defaultShellType() string {
if runtime.GOOS == "windows" {
return "powershell"
}
return "zsh"
}

2
go.mod
View File

@@ -1,6 +1,6 @@
module lingma-ipc-proxy
go 1.25.0
go 1.21
require (
github.com/Microsoft/go-winio v0.6.2

View File

@@ -9,6 +9,7 @@ import (
"time"
"lingma-ipc-proxy/internal/service"
"lingma-ipc-proxy/internal/toolemulation"
)
type Server struct {
@@ -23,6 +24,8 @@ type anthropicRequest struct {
System any `json:"system,omitempty"`
Messages []rawMessage `json:"messages"`
Stream bool `json:"stream,omitempty"`
Tools any `json:"tools,omitempty"`
ToolChoice any `json:"tool_choice,omitempty"`
}
type openAIChatRequest struct {
@@ -31,11 +34,15 @@ type openAIChatRequest struct {
Stream bool `json:"stream,omitempty"`
MaxTokens int `json:"max_tokens,omitempty"`
MaxCompletionTokens int `json:"max_completion_tokens,omitempty"`
Tools any `json:"tools,omitempty"`
ToolChoice any `json:"tool_choice,omitempty"`
}
type rawMessage struct {
Role string `json:"role"`
Content any `json:"content"`
ToolCalls []any `json:"tool_calls,omitempty"`
ToolCallID string `json:"tool_call_id,omitempty"`
}
type modelResponse struct {
@@ -170,13 +177,26 @@ func (s *Server) handleAnthropicMessages(w http.ResponseWriter, r *http.Request)
return
}
content := []map[string]any{{"type": "text", "text": result.Text}}
stopReason := "end_turn"
if len(result.ToolCalls) > 0 {
for _, tc := range result.ToolCalls {
content = append(content, map[string]any{
"type": "tool_use",
"id": tc.ID,
"name": tc.Name,
"input": tc.Arguments,
})
}
stopReason = "tool_use"
}
writeJSON(w, http.StatusOK, map[string]any{
"id": fmt.Sprintf("msg_%d", time.Now().UnixNano()),
"type": "message",
"role": "assistant",
"content": []map[string]any{{"type": "text", "text": result.Text}},
"content": content,
"model": result.Model,
"stop_reason": "end_turn",
"stop_reason": stopReason,
"stop_sequence": nil,
"usage": map[string]any{
"input_tokens": result.InputTokens,
@@ -224,6 +244,27 @@ func (s *Server) handleOpenAIChatCompletions(w http.ResponseWriter, r *http.Requ
}
created := time.Now().Unix()
message := map[string]any{
"role": "assistant",
"content": result.Text,
}
finishReason := "stop"
if len(result.ToolCalls) > 0 {
toolCalls := make([]map[string]any, 0, len(result.ToolCalls))
for _, tc := range result.ToolCalls {
argsJSON, _ := json.Marshal(tc.Arguments)
toolCalls = append(toolCalls, map[string]any{
"id": tc.ID,
"type": "function",
"function": map[string]any{
"name": tc.Name,
"arguments": string(argsJSON),
},
})
}
message["tool_calls"] = toolCalls
finishReason = "tool_calls"
}
writeJSON(w, http.StatusOK, map[string]any{
"id": fmt.Sprintf("chatcmpl-%d", time.Now().UnixNano()),
"object": "chat.completion",
@@ -232,11 +273,8 @@ func (s *Server) handleOpenAIChatCompletions(w http.ResponseWriter, r *http.Requ
"choices": []map[string]any{
{
"index": 0,
"message": map[string]any{
"role": "assistant",
"content": result.Text,
},
"finish_reason": "stop",
"message": message,
"finish_reason": finishReason,
},
},
"usage": map[string]any{
@@ -254,17 +292,73 @@ func (s *Server) handleAnthropicStream(w http.ResponseWriter, r *http.Request, r
return
}
model := strings.TrimSpace(req.Model)
if model == "" {
model = "lingma"
}
msgID := fmt.Sprintf("msg_%d", time.Now().UnixNano())
if len(req.Tools) > 0 {
result, err := s.svc.Generate(r.Context(), req)
if err != nil {
writeAnthropicError(w, http.StatusInternalServerError, "api_error", err.Error())
return
}
streamingHeaders(w)
_ = writeSSEEvent(w, flusher, "message_start", map[string]any{
"type": "message_start",
"message": map[string]any{
"id": msgID, "type": "message", "role": "assistant", "content": []any{},
"model": model, "stop_reason": nil, "stop_sequence": nil,
"usage": map[string]any{"input_tokens": 0, "output_tokens": 0},
},
})
_ = writeSSEEvent(w, flusher, "content_block_start", map[string]any{
"type": "content_block_start", "index": 0,
"content_block": map[string]any{"type": "text", "text": ""},
})
if result.Text != "" {
_ = writeSSEEvent(w, flusher, "content_block_delta", map[string]any{
"type": "content_block_delta", "index": 0,
"delta": map[string]any{"type": "text_delta", "text": result.Text},
})
}
_ = writeSSEEvent(w, flusher, "content_block_stop", map[string]any{
"type": "content_block_stop", "index": 0,
})
for i, tc := range result.ToolCalls {
_ = writeSSEEvent(w, flusher, "content_block_start", map[string]any{
"type": "content_block_start", "index": i + 1,
"content_block": map[string]any{"type": "tool_use", "id": tc.ID, "name": tc.Name, "input": map[string]any{}},
})
argsJSON, _ := json.Marshal(tc.Arguments)
_ = writeSSEEvent(w, flusher, "content_block_delta", map[string]any{
"type": "content_block_delta", "index": i + 1,
"delta": map[string]any{"type": "input_json_delta", "partial_json": string(argsJSON)},
})
_ = writeSSEEvent(w, flusher, "content_block_stop", map[string]any{
"type": "content_block_stop", "index": i + 1,
})
}
stopReason := "end_turn"
if len(result.ToolCalls) > 0 {
stopReason = "tool_use"
}
_ = writeSSEEvent(w, flusher, "message_delta", map[string]any{
"type": "message_delta",
"delta": map[string]any{"stop_reason": stopReason, "stop_sequence": nil},
"usage": map[string]any{"output_tokens": result.OutputTokens},
})
_ = writeSSEEvent(w, flusher, "message_stop", map[string]any{"type": "message_stop"})
return
}
events, done, err := s.svc.GenerateStream(r.Context(), req)
if err != nil {
writeAnthropicError(w, http.StatusInternalServerError, "api_error", err.Error())
return
}
model := strings.TrimSpace(req.Model)
if model == "" {
model = "lingma"
}
msgID := fmt.Sprintf("msg_%d", time.Now().UnixNano())
streamingHeaders(w)
if err := writeSSEEvent(w, flusher, "message_start", map[string]any{
"type": "message_start",
@@ -383,18 +477,65 @@ func (s *Server) handleOpenAIStream(w http.ResponseWriter, r *http.Request, req
return
}
events, done, err := s.svc.GenerateStream(r.Context(), req)
if err != nil {
writeOpenAIError(w, http.StatusInternalServerError, "api_error", err.Error())
return
}
model := strings.TrimSpace(req.Model)
if model == "" {
model = "lingma"
}
chatID := fmt.Sprintf("chatcmpl-%d", time.Now().UnixNano())
created := time.Now().Unix()
if len(req.Tools) > 0 {
result, err := s.svc.Generate(r.Context(), req)
if err != nil {
writeOpenAIError(w, http.StatusInternalServerError, "api_error", err.Error())
return
}
streamingHeaders(w)
_ = writeOpenAIChunk(w, flusher, map[string]any{
"id": chatID, "object": "chat.completion.chunk", "created": created, "model": model,
"choices": []map[string]any{{"index": 0, "delta": map[string]any{"role": "assistant"}, "finish_reason": nil}},
})
if result.Text != "" {
_ = writeOpenAIChunk(w, flusher, map[string]any{
"id": chatID, "object": "chat.completion.chunk", "created": created, "model": model,
"choices": []map[string]any{{"index": 0, "delta": map[string]any{"content": result.Text}, "finish_reason": nil}},
})
}
for i, tc := range result.ToolCalls {
argsJSON, _ := json.Marshal(tc.Arguments)
_ = writeOpenAIChunk(w, flusher, map[string]any{
"id": chatID, "object": "chat.completion.chunk", "created": created, "model": model,
"choices": []map[string]any{{
"index": 0,
"delta": map[string]any{
"tool_calls": []map[string]any{{
"index": i, "id": tc.ID, "type": "function",
"function": map[string]any{"name": tc.Name, "arguments": string(argsJSON)},
}},
},
"finish_reason": nil,
}},
})
}
finishReason := "stop"
if len(result.ToolCalls) > 0 {
finishReason = "tool_calls"
}
_ = writeOpenAIChunk(w, flusher, map[string]any{
"id": chatID, "object": "chat.completion.chunk", "created": created, "model": model,
"choices": []map[string]any{{"index": 0, "delta": map[string]any{}, "finish_reason": finishReason}},
})
_, _ = fmt.Fprint(w, "data: [DONE]\n\n")
flusher.Flush()
return
}
events, done, err := s.svc.GenerateStream(r.Context(), req)
if err != nil {
writeOpenAIError(w, http.StatusInternalServerError, "api_error", err.Error())
return
}
streamingHeaders(w)
if err := writeOpenAIChunk(w, flusher, map[string]any{
"id": chatID,
@@ -493,22 +634,41 @@ func normalizeAnthropicRequest(req anthropicRequest) (service.ChatRequest, error
messages := make([]service.ChatMessage, 0, len(req.Messages))
for _, message := range req.Messages {
role := strings.ToLower(strings.TrimSpace(message.Role))
text := strings.TrimSpace(extractText(message.Content))
if role != "user" && role != "assistant" {
continue
switch role {
case "user":
text, toolResults := extractAnthropicUserContent(message.Content)
for _, tr := range toolResults {
prompt := toolemulation.ActionOutputPrompt(tr.ToolUseID, tr.Content)
if prompt != "" {
messages = append(messages, service.ChatMessage{Role: "user", Text: prompt})
}
if text == "" {
continue
}
if text != "" {
messages = append(messages, service.ChatMessage{Role: role, Text: text})
}
case "assistant":
text, calls := extractAnthropicAssistantContent(message.Content)
projected := toolemulation.AssistantToolCallsToText(text, calls)
if projected != "" {
messages = append(messages, service.ChatMessage{Role: role, Text: projected})
}
}
}
if len(messages) == 0 {
return service.ChatRequest{}, fmt.Errorf("no user or assistant messages found")
}
toolChoice := toolemulation.ToolChoice{Mode: "auto"}
if req.ToolChoice != nil {
toolChoice = toolemulation.ExtractToolChoice(req.ToolChoice)
}
return service.ChatRequest{
Model: strings.TrimSpace(req.Model),
System: strings.TrimSpace(extractText(req.System)),
Messages: messages,
Tools: toolemulation.ExtractAnthropicTools(req.Tools),
ToolChoice: toolChoice,
}, nil
}
@@ -517,16 +677,31 @@ func normalizeOpenAIRequest(req openAIChatRequest) (service.ChatRequest, error)
systemParts := make([]string, 0, 2)
for _, message := range req.Messages {
role := strings.ToLower(strings.TrimSpace(message.Role))
text := strings.TrimSpace(extractText(message.Content))
if text == "" {
continue
}
switch role {
case "system":
text := strings.TrimSpace(extractText(message.Content))
if text != "" {
systemParts = append(systemParts, text)
case "user", "assistant":
}
case "user":
text := strings.TrimSpace(extractText(message.Content))
if text != "" {
messages = append(messages, service.ChatMessage{Role: role, Text: text})
}
case "assistant":
text := strings.TrimSpace(extractText(message.Content))
calls := extractOpenAIToolCalls(message.ToolCalls)
projected := toolemulation.AssistantToolCallsToText(text, calls)
if projected != "" {
messages = append(messages, service.ChatMessage{Role: role, Text: projected})
}
case "tool":
output := strings.TrimSpace(extractText(message.Content))
prompt := toolemulation.ActionOutputPrompt(message.ToolCallID, output)
if prompt != "" {
messages = append(messages, service.ChatMessage{Role: "user", Text: prompt})
}
}
}
if len(messages) == 0 {
return service.ChatRequest{}, fmt.Errorf("no user or assistant messages found")
@@ -535,6 +710,8 @@ func normalizeOpenAIRequest(req openAIChatRequest) (service.ChatRequest, error)
Model: strings.TrimSpace(req.Model),
System: strings.Join(systemParts, "\n\n"),
Messages: messages,
Tools: toolemulation.ExtractTools(req.Tools),
ToolChoice: toolemulation.ExtractToolChoice(req.ToolChoice),
}, nil
}
@@ -681,3 +858,117 @@ func (s *Server) release() {
default:
}
}
func extractOpenAIToolCalls(raw []any) []toolemulation.ToolCall {
if len(raw) == 0 {
return nil
}
out := make([]toolemulation.ToolCall, 0, len(raw))
for _, item := range raw {
m, ok := item.(map[string]any)
if !ok {
continue
}
id := stringFromAny(m["id"])
fn, ok := m["function"].(map[string]any)
if !ok {
continue
}
name := stringFromAny(fn["name"])
if name == "" {
continue
}
argsRaw := stringFromAny(fn["arguments"])
var args map[string]any
if argsRaw != "" {
_ = json.Unmarshal([]byte(argsRaw), &args)
}
out = append(out, toolemulation.ToolCall{
ID: id,
Name: name,
Arguments: args,
})
}
return out
}
type anthropicToolResult struct {
ToolUseID string
Content string
}
func extractAnthropicUserContent(content any) (string, []anthropicToolResult) {
text := extractText(content)
items, ok := content.([]any)
if !ok {
return text, nil
}
var results []anthropicToolResult
var textParts []string
for _, item := range items {
m, ok := item.(map[string]any)
if !ok {
continue
}
switch stringFromAny(m["type"]) {
case "text":
if t := stringFromAny(m["text"]); t != "" {
textParts = append(textParts, t)
}
case "tool_result":
toolUseID := stringFromAny(m["tool_use_id"])
resultText := extractText(m["content"])
if resultText != "" {
results = append(results, anthropicToolResult{
ToolUseID: toolUseID,
Content: resultText,
})
}
}
}
if len(textParts) > 0 {
text = strings.Join(textParts, "\n")
}
return text, results
}
func extractAnthropicAssistantContent(content any) (string, []toolemulation.ToolCall) {
text := extractText(content)
items, ok := content.([]any)
if !ok {
return text, nil
}
calls := make([]toolemulation.ToolCall, 0, len(items))
var textParts []string
for _, item := range items {
m, ok := item.(map[string]any)
if !ok {
continue
}
switch stringFromAny(m["type"]) {
case "text":
if t := stringFromAny(m["text"]); t != "" {
textParts = append(textParts, t)
}
case "tool_use":
id := stringFromAny(m["id"])
name := stringFromAny(m["name"])
if name == "" {
continue
}
var args map[string]any
if rawInput, ok := m["input"].(map[string]any); ok {
args = rawInput
}
calls = append(calls, toolemulation.ToolCall{
ID: id,
Name: name,
Arguments: args,
})
}
}
if len(textParts) > 0 {
text = strings.Join(textParts, "\n")
}
return text, calls
}

View File

@@ -17,9 +17,6 @@ import (
)
const (
PipeDir = `\\.\pipe\`
PipePrefix = "lingma-"
MetaRequestID = "ai-coding/request-id"
MetaMode = "ai-coding/mode"
MetaModel = "ai-coding/model"

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@@ -0,0 +1,8 @@
//go:build !windows
package lingmaipc
const (
PipeDir = ""
PipePrefix = ""
)

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@@ -0,0 +1,8 @@
//go:build windows
package lingmaipc
const (
PipeDir = `\\.\pipe\`
PipePrefix = "lingma-"
)

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@@ -0,0 +1,12 @@
//go:build !windows
package lingmaipc
import (
"context"
"errors"
)
func connectPipeTransport(ctx context.Context, pipePath string) (framedTransport, error) {
return nil, errors.New("pipe transport is only supported on Windows")
}

View File

@@ -0,0 +1,57 @@
//go:build windows
package lingmaipc
import (
"context"
"fmt"
"net"
"sync"
winio "github.com/Microsoft/go-winio"
)
type pipeTransport struct {
path string
conn net.Conn
reader *framedReader
write sync.Mutex
}
func connectPipeTransport(ctx context.Context, pipePath string) (framedTransport, error) {
conn, err := winio.DialPipeContext(ctx, pipePath)
if err != nil {
return nil, fmt.Errorf("connect Lingma IPC pipe %s: %w", pipePath, err)
}
return &pipeTransport{
path: pipePath,
conn: conn,
reader: newFramedReader(conn),
}, nil
}
func (t *pipeTransport) ReadFrame() ([]byte, error) {
return t.reader.ReadFrame()
}
func (t *pipeTransport) WriteFrame(body []byte) error {
t.write.Lock()
defer t.write.Unlock()
frame := []byte(fmt.Sprintf("Content-Length: %d\r\n\r\n", len(body)))
if _, err := t.conn.Write(frame); err != nil {
return fmt.Errorf("write frame header: %w", err)
}
if _, err := t.conn.Write(body); err != nil {
return fmt.Errorf("write frame body: %w", err)
}
return nil
}
func (t *pipeTransport) Close() error {
return t.conn.Close()
}
func (t *pipeTransport) Address() string {
return t.path
}

View File

@@ -8,7 +8,6 @@ import (
"errors"
"fmt"
"io"
"net"
"net/url"
"os"
"path/filepath"
@@ -19,7 +18,6 @@ import (
"sync"
"time"
winio "github.com/Microsoft/go-winio"
"github.com/gorilla/websocket"
)
@@ -74,16 +72,23 @@ func ResolveDialOptions(transport Transport, explicitPipe string, explicitWebSoc
return DialOptions{Transport: TransportWebSocket, WebSocketURL: wsURL}, nil
}
if runtime.GOOS == "windows" {
pipePath, pipeErr := ResolvePipePath(explicitPipe)
if pipeErr == nil {
return DialOptions{Transport: TransportPipe, PipePath: pipePath}, nil
}
wsURL, wsErr := ResolveWebSocketURL(explicitWebSocketURL)
if wsErr == nil {
return DialOptions{Transport: TransportWebSocket, WebSocketURL: wsURL}, nil
}
return DialOptions{}, fmt.Errorf("resolve Lingma transport automatically: pipe: %w; websocket: %v", pipeErr, wsErr)
}
wsURL, wsErr := ResolveWebSocketURL(explicitWebSocketURL)
if wsErr == nil {
return DialOptions{Transport: TransportWebSocket, WebSocketURL: wsURL}, nil
}
return DialOptions{}, fmt.Errorf("resolve Lingma transport automatically: pipe: %w; websocket: %v", pipeErr, wsErr)
return DialOptions{}, fmt.Errorf("resolve Lingma transport automatically on %s: websocket: %w", runtime.GOOS, wsErr)
case TransportPipe:
pipePath, err := ResolvePipePath(explicitPipe)
if err != nil {
@@ -307,51 +312,6 @@ func connectTransport(ctx context.Context, opts DialOptions) (framedTransport, e
}
}
type pipeTransport struct {
path string
conn net.Conn
reader *framedReader
write sync.Mutex
}
func connectPipeTransport(ctx context.Context, pipePath string) (*pipeTransport, error) {
conn, err := winio.DialPipeContext(ctx, pipePath)
if err != nil {
return nil, fmt.Errorf("connect Lingma IPC pipe %s: %w", pipePath, err)
}
return &pipeTransport{
path: pipePath,
conn: conn,
reader: newFramedReader(conn),
}, nil
}
func (t *pipeTransport) ReadFrame() ([]byte, error) {
return t.reader.ReadFrame()
}
func (t *pipeTransport) WriteFrame(body []byte) error {
t.write.Lock()
defer t.write.Unlock()
frame := []byte(fmt.Sprintf("Content-Length: %d\r\n\r\n", len(body)))
if _, err := t.conn.Write(frame); err != nil {
return fmt.Errorf("write frame header: %w", err)
}
if _, err := t.conn.Write(body); err != nil {
return fmt.Errorf("write frame body: %w", err)
}
return nil
}
func (t *pipeTransport) Close() error {
return t.conn.Close()
}
func (t *pipeTransport) Address() string {
return t.path
}
type websocketTransport struct {
url string
conn *websocket.Conn

View File

@@ -12,6 +12,7 @@ import (
"time"
"lingma-ipc-proxy/internal/lingmaipc"
"lingma-ipc-proxy/internal/toolemulation"
)
type SessionMode string
@@ -45,6 +46,8 @@ type ChatRequest struct {
Model string
System string
Messages []ChatMessage
Tools []toolemulation.ToolDef
ToolChoice toolemulation.ToolChoice
}
type ChatResult struct {
@@ -62,6 +65,7 @@ type ChatResult struct {
Endpoint string
Transport string
EffectiveSession SessionMode
ToolCalls []toolemulation.ToolCall
}
type StreamEvent struct {
@@ -77,6 +81,7 @@ type Model struct {
ID string `json:"id"`
Name string `json:"name"`
Scene string `json:"scene,omitempty"`
InternalID string `json:"-"`
}
type State struct {
@@ -97,6 +102,7 @@ type Service struct {
transport lingmaipc.Transport
stickySessionID string
stickyModelID string
modelMap map[string]string // official name -> internal id
}
type promptRunResult struct {
@@ -170,6 +176,16 @@ func (s *Service) ListModels(ctx context.Context) ([]Model, error) {
if len(models) == 0 {
models = []Model{{ID: "lingma", Name: "Lingma", Scene: "default"}}
}
s.mu.Lock()
s.modelMap = make(map[string]string, len(models))
for _, m := range models {
if m.InternalID != "" {
s.modelMap[m.ID] = m.InternalID
}
}
s.mu.Unlock()
return models, nil
}
@@ -235,17 +251,19 @@ func (s *Service) generateLocked(
_ = s.deleteSessionLocked(cleanupCtx, ipcClient, sessionID)
}()
internalModelID := s.resolveInternalModelID(req.Model)
requestID := lingmaipc.CreateRequestID("serve")
meta := lingmaipc.CreateMeta(lingmaipc.MetaOptions{
RequestID: requestID,
Mode: s.cfg.Mode,
Model: req.Model,
Model: internalModelID,
ShellType: s.cfg.ShellType,
CurrentFilePath: s.cfg.CurrentFilePath,
EnabledMCP: []any{},
})
modelID := strings.TrimSpace(req.Model)
modelID := strings.TrimSpace(internalModelID)
if modelID != "" && s.shouldSetModel(sessionID, effectiveMode, modelID) {
if err := ipcClient.Request(requestCtx, "session/set_model", map[string]any{
"sessionId": sessionID,
@@ -284,6 +302,28 @@ func (s *Service) generateLocked(
}
result = s.buildChatResult(req, sessionID, requestID, prompt, runResult, effectiveMode)
if len(req.Tools) > 0 {
calls, remaining, parseErr := toolemulation.ParseActionBlocks(result.Text, toolemulation.Config{})
if parseErr == nil && len(calls) > 0 {
result.Text = remaining
result.ToolCalls = calls
} else if (req.ToolChoice.Mode == "any" || req.ToolChoice.Mode == "tool") && len(calls) == 0 {
if !toolemulation.LooksLikeRefusal(result.Text) {
hintPrompt := prompt + "\n\nImportant: You must use one of the available tools to answer this request. Output a \"```json action\" block."
retryResult, retryErr := s.runPromptLocked(requestCtx, ipcClient, sessionID, hintPrompt, requestID, meta, onDelta)
if retryErr == nil && retryResult != nil {
retryCalls, retryRemaining, retryParseErr := toolemulation.ParseActionBlocks(retryResult.AssistantText, toolemulation.Config{})
if retryParseErr == nil && len(retryCalls) > 0 {
result.Text = retryRemaining
result.ToolCalls = retryCalls
result.OutputTokens = estimateTokens(retryResult.AssistantText)
}
}
}
}
}
return result, nil
}
@@ -546,7 +586,7 @@ func resolveSessionMode(req ChatRequest, configured SessionMode) SessionMode {
if configured != SessionModeAuto {
return configured
}
if strings.TrimSpace(req.System) != "" || len(filteredMessages(req.Messages)) > 1 {
if len(req.Tools) > 0 || strings.TrimSpace(req.System) != "" || len(filteredMessages(req.Messages)) > 1 {
return SessionModeFresh
}
return SessionModeReuse
@@ -567,13 +607,35 @@ func buildLingmaPrompt(req ChatRequest, mode SessionMode) (string, error) {
if mode == SessionModeReuse {
return lastUser, nil
}
if strings.TrimSpace(req.System) == "" && len(messages) == 1 {
system := strings.TrimSpace(req.System)
if len(req.Tools) > 0 {
system = toolemulation.InjectTooling(system, req.Tools, req.ToolChoice)
}
if system == "" && len(messages) == 1 {
return lastUser, nil
}
if len(req.Tools) > 0 {
parts := make([]string, 0, len(messages)+2)
if system != "" {
parts = append(parts, system)
}
for _, message := range messages {
role := "User"
if message.Role == "assistant" {
role = "Assistant"
}
parts = append(parts, fmt.Sprintf("%s: %s", role, message.Text))
}
parts = append(parts, "Assistant:")
return strings.Join(parts, "\n\n"), nil
}
parts := make([]string, 0, len(messages)+4)
if strings.TrimSpace(req.System) != "" {
parts = append(parts, "System instructions:", strings.TrimSpace(req.System))
if system != "" {
parts = append(parts, "System instructions:", system)
}
parts = append(parts, "Conversation transcript:")
for _, message := range messages {
@@ -627,7 +689,7 @@ func extractModels(raw any) []Model {
if name == "" {
name = id
}
seen[id] = Model{ID: id, Name: name, Scene: currentScene}
seen[name] = Model{ID: name, Name: name, Scene: currentScene, InternalID: id}
}
for key, child := range typed {
nextScene := currentScene
@@ -657,6 +719,15 @@ func likelyModelID(id string) bool {
return strings.Contains(lowered, "qwen") || strings.Contains(lowered, "model") || strings.Contains(lowered, "auto") || strings.Contains(lowered, "coder")
}
func (s *Service) resolveInternalModelID(officialName string) string {
s.mu.Lock()
defer s.mu.Unlock()
if internalID, ok := s.modelMap[officialName]; ok && internalID != "" {
return internalID
}
return officialName
}
func isSceneKey(key string) bool {
switch strings.ToLower(strings.TrimSpace(key)) {
case "assistant", "chat", "developer", "inline", "quest":

View File

@@ -0,0 +1,10 @@
{
"host": "127.0.0.1",
"port": 8095,
"transport": "websocket",
"mode": "agent",
"shell_type": "zsh",
"session_mode": "auto",
"timeout": 120,
"cwd": "/Users/tiancheng"
}

74
scripts/test-macos.sh Executable file
View File

@@ -0,0 +1,74 @@
#!/bin/bash
# lingma-ipc-proxy macOS 功能测试脚本
# 用法: ./scripts/test-macos.sh [host:port]
ENDPOINT="${1:-127.0.0.1:8095}"
MODEL="dashscope_qwen3_coder"
PASS=0
FAIL=0
assert_contains() {
local response="$1"
local expected="$2"
local test_name="$3"
if echo "$response" | grep -q "$expected"; then
echo "$test_name"
PASS=$((PASS + 1))
else
echo "$test_name"
echo " 期望包含: $expected"
echo " 实际响应: $(echo "$response" | head -c 200)"
FAIL=$((FAIL + 1))
fi
}
echo "========================================"
echo "lingma-ipc-proxy macOS 功能测试"
echo "端点: http://$ENDPOINT"
echo "========================================"
# 1. 测试 /v1/models
echo ""
echo "[1/4] 测试 /v1/models"
RESPONSE=$(curl -s "http://$ENDPOINT/v1/models" 2>/dev/null || echo "ERROR")
assert_contains "$RESPONSE" "dashscope_qwen3_coder" "模型列表包含 Qwen3-Coder"
assert_contains "$RESPONSE" "kmodel" "模型列表包含 Kimi"
assert_contains "$RESPONSE" '"object":"list"' "响应格式正确"
# 2. 测试 /v1/chat/completions 非流式
echo ""
echo "[2/4] 测试 /v1/chat/completions (非流式)"
RESPONSE=$(curl -s -X POST "http://$ENDPOINT/v1/chat/completions" \
-H 'Content-Type: application/json' \
-d "{\"model\":\"$MODEL\",\"messages\":[{\"role\":\"user\",\"content\":\"1+1=?\"}],\"stream\":false}" 2>/dev/null || echo "ERROR")
assert_contains "$RESPONSE" "2" "回答包含正确答案"
assert_contains "$RESPONSE" "chat.completion" "响应类型正确"
assert_contains "$RESPONSE" "stop" "finish_reason 为 stop"
# 3. 测试 /v1/chat/completions 流式
echo ""
echo "[3/4] 测试 /v1/chat/completions (流式 SSE)"
RESPONSE=$(curl -s -N -X POST "http://$ENDPOINT/v1/chat/completions" \
-H 'Content-Type: application/json' \
-d "{\"model\":\"$MODEL\",\"messages\":[{\"role\":\"user\",\"content\":\"1+1=?\"}],\"stream\":true}" 2>/dev/null || echo "ERROR")
assert_contains "$RESPONSE" "data:" "包含 SSE data: 前缀"
assert_contains "$RESPONSE" "chat.completion.chunk" "chunk 类型正确"
# 4. 测试 /v1/messages (Anthropic 格式)
echo ""
echo "[4/4] 测试 /v1/messages (Anthropic 格式)"
RESPONSE=$(curl -s -X POST "http://$ENDPOINT/v1/messages" \
-H 'Content-Type: application/json' \
-d "{\"model\":\"$MODEL\",\"messages\":[{\"role\":\"user\",\"content\":\"2+2=?\"}],\"stream\":false}" 2>/dev/null || echo "ERROR")
assert_contains "$RESPONSE" "4" "回答包含正确答案"
assert_contains "$RESPONSE" "end_turn" "stop_reason 为 end_turn"
# 汇总
echo ""
echo "========================================"
echo "测试结果: $PASS 通过, $FAIL 失败"
echo "========================================"
if [ "$FAIL" -gt 0 ]; then
exit 1
fi