init: initial commit

2026-04-07 17:35:09 +08:00
commit 680ecc320f
129 changed files with 10562 additions and 0 deletions
@@ -0,0 +1,239 @@
+package chat
+
+import (
+	"context"
+	"fmt"
+	"log/slog"
+	"strings"
+
+	"engimind/internal/config"
+	"engimind/internal/project"
+	"engimind/internal/vector"
+
+	"github.com/wailsapp/wails/v3/pkg/application"
+)
+
+// ChatService handles chat interactions and chapter generation (A+C→B).
+type ChatService struct {
+	llm        *LLMClient
+	rag        *vector.RAGService
+	configSvc  *config.ConfigService
+	projectSvc *project.ProjectService
+}
+
+// NewChatService creates a chat service.
+func NewChatService(
+	configSvc *config.ConfigService,
+	projectSvc *project.ProjectService,
+	rag *vector.RAGService,
+) *ChatService {
+	return &ChatService{
+		llm:        NewLLMClient(),
+		rag:        rag,
+		configSvc:  configSvc,
+		projectSvc: projectSvc,
+	}
+}
+
+// SendMessage handles a user chat message with RAG context.
+func (s *ChatService) SendMessage(content string, selectedFileIDs []string, modelID string) (string, error) {
+	providers, _ := s.configSvc.GetAllProviders()
+	var provider *struct{ URL, Key, Model, ProviderType string }
+	for _, p := range providers {
+		if p.ID == modelID && p.Enabled {
+			provider = &struct{ URL, Key, Model, ProviderType string }{p.BaseURL, p.APIKey, p.ModelID, p.Provider}
+			break
+		}
+	}
+	if provider == nil {
+		return "", fmt.Errorf("model %s not found or disabled", modelID)
+	}
+
+	// RAG: search context
+	projectID := s.projectSvc.GetCurrentProjectID()
+	var contextText string
+	if projectID != "" && len(selectedFileIDs) > 0 {
+		embCfg := s.getEmbeddingConfig()
+		chunks, err := s.rag.SearchContext(context.Background(), projectID, content, 5, embCfg)
+		if err != nil {
+			slog.Warn("RAG search failed, proceeding without context", "err", err)
+		} else {
+			var parts []string
+			for _, c := range chunks {
+				parts = append(parts, c.Text)
+			}
+			contextText = strings.Join(parts, "\n\n---\n\n")
+		}
+	}
+
+	messages := []Message{
+		{Role: "system", Content: "你是一位专业的工程技术助手。基于提供的工程素材回答问题，引用来源时使用 [N] 标注。"},
+	}
+	if contextText != "" {
+		messages = append(messages, Message{
+			Role:    "user",
+			Content: fmt.Sprintf("参考以下工程素材：\n\n%s\n\n---\n\n用户提问：%s", contextText, content),
+		})
+	} else {
+		messages = append(messages, Message{Role: "user", Content: content})
+	}
+
+	resp, err := s.llm.Complete(provider.URL, provider.Key, provider.Model, messages)
+	if err != nil {
+		return "", err
+	}
+	if len(resp.Choices) == 0 {
+		return "", fmt.Errorf("no response from model")
+	}
+	return resp.Choices[0].Message.Content, nil
+}
+
+// StreamMessage handles a user chat message and streams the response via Wails events.
+func (s *ChatService) StreamMessage(content string, selectedFileIDs []string, modelID string, messageID string) (string, error) {
+	providers, _ := s.configSvc.GetAllProviders()
+	var provider *struct{ URL, Key, Model, ProviderType string }
+	for _, p := range providers {
+		if p.ID == modelID && p.Enabled {
+			provider = &struct{ URL, Key, Model, ProviderType string }{p.BaseURL, p.APIKey, p.ModelID, p.Provider}
+			break
+		}
+	}
+	if provider == nil {
+		return "", fmt.Errorf("model %s not found or disabled", modelID)
+	}
+
+	projectID := s.projectSvc.GetCurrentProjectID()
+	var contextText string
+	if projectID != "" && len(selectedFileIDs) > 0 {
+		embCfg := s.getEmbeddingConfig()
+		chunks, err := s.rag.SearchContext(context.Background(), projectID, content, 5, embCfg)
+		if err == nil {
+			var parts []string
+			for _, c := range chunks {
+				parts = append(parts, c.Text)
+			}
+			contextText = strings.Join(parts, "\n\n---\n\n")
+		}
+	}
+
+	messages := []Message{
+		{Role: "system", Content: "你是一位专业的工程技术助手。基于提供的工程素材回答问题，引用来源时使用 [N] 标注。"},
+	}
+	if contextText != "" {
+		messages = append(messages, Message{
+			Role:    "user",
+			Content: fmt.Sprintf("参考以下工程素材：\n\n%s\n\n---\n\n用户提问：%s", contextText, content),
+		})
+	} else {
+		messages = append(messages, Message{Role: "user", Content: content})
+	}
+
+	var fullText string
+	err := s.llm.StreamComplete(provider.URL, provider.Key, provider.Model, messages, func(chunk string) {
+		fullText += chunk
+		application.Get().Event.Emit("chat_stream_"+messageID, fullText)
+	})
+	return fullText, err
+}
+
+// GenerateChapter implements the A+C→B logic for a single chapter.
+func (s *ChatService) GenerateChapter(chapterTitle string, selectedFileIDs []string, modelID string) (string, error) {
+	providers, _ := s.configSvc.GetAllProviders()
+	var provider *struct{ URL, Key, Model string }
+	for _, p := range providers {
+		if p.ID == modelID && p.Enabled {
+			provider = &struct{ URL, Key, Model string }{p.BaseURL, p.APIKey, p.ModelID}
+			break
+		}
+	}
+	if provider == nil {
+		return "", fmt.Errorf("model %s not found or disabled", modelID)
+	}
+
+	// RAG: search context for chapter topic
+	projectID := s.projectSvc.GetCurrentProjectID()
+	embCfg := s.getEmbeddingConfig()
+	chunks, err := s.rag.SearchContext(context.Background(), projectID, chapterTitle, 8, embCfg)
+	if err != nil {
+		slog.Warn("RAG search failed for chapter generation", "err", err)
+	}
+
+	var contextParts []string
+	for _, c := range chunks {
+		contextParts = append(contextParts, c.Text)
+	}
+	contextText := strings.Join(contextParts, "\n\n---\n\n")
+
+	prompt := fmt.Sprintf(
+		"你是工程报告撰写专家。请根据以下工程素材，按照章节要求撰写报告内容。\n\n"+
+			"## 章节要求\n%s\n\n"+
+			"## 参考素材\n%s\n\n"+
+			"## 输出要求\n"+
+			"1. 使用 Markdown 格式\n"+
+			"2. 引用素材时使用 [N] 标注\n"+
+			"3. 内容专业、结构清晰\n"+
+			"4. 包含具体数据和分析结论",
+		chapterTitle, contextText,
+	)
+
+	messages := []Message{
+		{Role: "system", Content: "你是一位资深工程报告撰写专家，擅长根据工程素材生成结构化的技术报告章节。"},
+		{Role: "user", Content: prompt},
+	}
+
+	resp, err := s.llm.Complete(provider.URL, provider.Key, provider.Model, messages)
+	if err != nil {
+		return "", err
+	}
+	if len(resp.Choices) == 0 {
+		return "", fmt.Errorf("no response from model")
+	}
+	return resp.Choices[0].Message.Content, nil
+}
+
+// StreamTemplateDirectory uses the active LLM to extract a structured chapter outline from delivery standard text, streaming to frontend.
+func (s *ChatService) StreamTemplateDirectory(content string, modelID string, messageID string) (string, error) {
+	providers, _ := s.configSvc.GetAllProviders()
+	var provider *struct{ URL, Key, Model, ProviderType string }
+	for _, p := range providers {
+		if p.ID == modelID && p.Enabled {
+			provider = &struct{ URL, Key, Model, ProviderType string }{p.BaseURL, p.APIKey, p.ModelID, p.Provider}
+			break
+		}
+	}
+	if provider == nil {
+		return "", fmt.Errorf("model %s not found or disabled", modelID)
+	}
+
+	prompt := fmt.Sprintf(
+		"你是一个工程标准的目录解析助手。请从下面提供的交付标准文本中提取工程的主干章节，并以 JSON 数组的格式返回。\n\n"+
+			"### 要求：\n"+
+			"1. 只返回 JSON 数组，不包含其他废话或者回答前缀。\n"+
+			"2. 输出格式必须严格符合：[{ \"id\": \"chapter-1\", \"title\": \"1. 原材料进场检验\", \"content\": \"...如果标准里有简要描述可附上\" }]\n\n"+
+			"### 交付标准内容：\n%s",
+		content,
+	)
+
+	messages := []Message{
+		{Role: "system", Content: "你是一个专业的结构化数据抽取工具。你只输出合法的 JSON，不要使用 Markdown 代码块包裹，也不要给出任何其他解释。"},
+		{Role: "user", Content: prompt},
+	}
+
+	var fullText string
+	err := s.llm.StreamComplete(provider.URL, provider.Key, provider.Model, messages, func(chunk string) {
+		fullText += chunk
+		application.Get().Event.Emit("chat_stream_"+messageID, fullText)
+	})
+
+	return fullText, err
+}
+
+func (s *ChatService) getEmbeddingConfig() vector.EmbeddingConfig {
+	// Use bge-m3 via Ollama as default embedding model
+	return vector.EmbeddingConfig{
+		BaseURL:  "http://localhost:11434",
+		Model:    "bge-m3",
+		APIKey:   "",
+		Provider: "Ollama",
+	}
+}
@@ -0,0 +1,133 @@
+package chat
+
+import (
+	"bufio"
+	"bytes"
+	"encoding/json"
+	"fmt"
+	"io"
+	"net/http"
+	"strings"
+	"time"
+)
+
+// LLMClient provides a unified interface for OpenAI-compatible LLM APIs.
+type LLMClient struct {
+	client *http.Client
+}
+
+// NewLLMClient creates a new LLM client.
+func NewLLMClient() *LLMClient {
+	return &LLMClient{
+		client: &http.Client{Timeout: 120 * time.Second},
+	}
+}
+
+// Message represents a chat message in OpenAI format.
+type Message struct {
+	Role    string `json:"role"`
+	Content string `json:"content"`
+}
+
+// ChatRequest is the OpenAI chat completion request.
+type ChatRequest struct {
+	Model       string    `json:"model"`
+	Messages    []Message `json:"messages"`
+	Stream      bool      `json:"stream"`
+	Temperature float64   `json:"temperature,omitempty"`
+	MaxTokens   int       `json:"max_tokens,omitempty"`
+}
+
+// ChatResponse is a non-streaming response.
+type ChatResponse struct {
+	Choices []struct {
+		Message Message `json:"message"`
+	} `json:"choices"`
+	Usage struct {
+		PromptTokens     int `json:"prompt_tokens"`
+		CompletionTokens int `json:"completion_tokens"`
+	} `json:"usage"`
+}
+
+// StreamDelta from SSE streaming.
+type streamChunk struct {
+	Choices []struct {
+		Delta struct {
+			Content string `json:"content"`
+		} `json:"delta"`
+		FinishReason *string `json:"finish_reason"`
+	} `json:"choices"`
+}
+
+// Complete sends a non-streaming chat request.
+func (c *LLMClient) Complete(baseURL, apiKey, model string, messages []Message) (*ChatResponse, error) {
+	reqBody := ChatRequest{
+		Model:    model,
+		Messages: messages,
+		Stream:   false,
+	}
+	body, _ := json.Marshal(reqBody)
+
+	req, _ := http.NewRequest("POST", baseURL+"/v1/chat/completions", bytes.NewReader(body))
+	req.Header.Set("Content-Type", "application/json")
+	if apiKey != "" {
+		req.Header.Set("Authorization", "Bearer "+apiKey)
+	}
+
+	resp, err := c.client.Do(req)
+	if err != nil {
+		return nil, fmt.Errorf("llm request: %w", err)
+	}
+	defer resp.Body.Close()
+
+	data, _ := io.ReadAll(resp.Body)
+	var result ChatResponse
+	if err := json.Unmarshal(data, &result); err != nil {
+		return nil, fmt.Errorf("parse llm response: %w", err)
+	}
+	return &result, nil
+}
+
+// StreamComplete sends a streaming chat request, calling onChunk for each token.
+func (c *LLMClient) StreamComplete(baseURL, apiKey, model string, messages []Message, onChunk func(string)) error {
+	reqBody := ChatRequest{
+		Model:    model,
+		Messages: messages,
+		Stream:   true,
+	}
+	body, _ := json.Marshal(reqBody)
+
+	req, _ := http.NewRequest("POST", baseURL+"/v1/chat/completions", bytes.NewReader(body))
+	req.Header.Set("Content-Type", "application/json")
+	req.Header.Set("Accept", "text/event-stream")
+	if apiKey != "" {
+		req.Header.Set("Authorization", "Bearer "+apiKey)
+	}
+
+	resp, err := c.client.Do(req)
+	if err != nil {
+		return fmt.Errorf("llm stream request: %w", err)
+	}
+	defer resp.Body.Close()
+
+	scanner := bufio.NewScanner(resp.Body)
+	for scanner.Scan() {
+		line := scanner.Text()
+		if !strings.HasPrefix(line, "data: ") {
+			continue
+		}
+		data := strings.TrimPrefix(line, "data: ")
+		if data == "[DONE]" {
+			break
+		}
+
+		var chunk streamChunk
+		if err := json.Unmarshal([]byte(data), &chunk); err != nil {
+			continue
+		}
+		if len(chunk.Choices) > 0 && chunk.Choices[0].Delta.Content != "" {
+			onChunk(chunk.Choices[0].Delta.Content)
+		}
+	}
+	return scanner.Err()
+}