feat: implement QuestionBank CRUD with pagination and template query
- Add pagination support to findAll (page, limit query params) - Add findByTemplateId method to service - Add GET /by-template/:templateId endpoint to controller - Service already includes CRUD for QuestionBank and QuestionBankItem
This commit is contained in:
Developer
@@ -0,0 +1,231 @@
|
||||
import {
|
||||
Body,
|
||||
Controller,
|
||||
Post,
|
||||
Request,
|
||||
Res,
|
||||
UseGuards,
|
||||
} from '@nestjs/common';
|
||||
import { Response } from 'express';
|
||||
import { ChatMessage, ChatService } from './chat.service';
|
||||
import { CombinedAuthGuard } from '../auth/combined-auth.guard';
|
||||
import { ModelConfigService } from '../model-config/model-config.service';
|
||||
import { TenantService } from '../tenant/tenant.service';
|
||||
import { ModelType } from '../types';
|
||||
|
||||
class StreamChatDto {
|
||||
message: string;
|
||||
history: ChatMessage[];
|
||||
userLanguage?: string;
|
||||
selectedEmbeddingId?: string;
|
||||
selectedLLMId?: string;
|
||||
selectedGroups?: string[];
|
||||
selectedFiles?: string[];
|
||||
historyId?: string;
|
||||
enableRerank?: boolean;
|
||||
selectedRerankId?: string;
|
||||
temperature?: number;
|
||||
maxTokens?: number;
|
||||
topK?: number;
|
||||
similarityThreshold?: number;
|
||||
rerankSimilarityThreshold?: number;
|
||||
enableQueryExpansion?: boolean;
|
||||
enableHyDE?: boolean;
|
||||
}
|
||||
|
||||
@Controller('chat')
|
||||
@UseGuards(CombinedAuthGuard)
|
||||
export class ChatController {
|
||||
constructor(
|
||||
private chatService: ChatService,
|
||||
private modelConfigService: ModelConfigService,
|
||||
private tenantService: TenantService,
|
||||
) {}
|
||||
|
||||
@Post('stream')
|
||||
async streamChat(
|
||||
@Request() req,
|
||||
@Body() body: StreamChatDto,
|
||||
@Res() res: Response,
|
||||
) {
|
||||
try {
|
||||
console.log('Full Request Body:', JSON.stringify(body, null, 2));
|
||||
const {
|
||||
message,
|
||||
history = [],
|
||||
userLanguage = 'zh',
|
||||
selectedEmbeddingId,
|
||||
selectedLLMId,
|
||||
selectedGroups,
|
||||
selectedFiles,
|
||||
historyId,
|
||||
enableRerank,
|
||||
selectedRerankId,
|
||||
temperature,
|
||||
maxTokens,
|
||||
topK,
|
||||
similarityThreshold,
|
||||
rerankSimilarityThreshold,
|
||||
enableQueryExpansion,
|
||||
enableHyDE,
|
||||
} = body;
|
||||
const userId = req.user.id;
|
||||
|
||||
console.log('=== Chat Debug Info ===');
|
||||
console.log('User ID:', userId);
|
||||
console.log('Message:', message);
|
||||
console.log('User Language:', userLanguage);
|
||||
console.log('Selected Embedding ID:', selectedEmbeddingId);
|
||||
console.log('Selected LLM ID:', selectedLLMId);
|
||||
console.log('Selected Groups:', selectedGroups);
|
||||
console.log('Selected Files:', selectedFiles);
|
||||
console.log('History ID:', historyId);
|
||||
console.log('Temperature:', temperature);
|
||||
console.log('Max Tokens:', maxTokens);
|
||||
console.log('Top K:', topK);
|
||||
console.log('Similarity Threshold:', similarityThreshold);
|
||||
console.log('Rerank Similarity Threshold:', rerankSimilarityThreshold);
|
||||
console.log('Query Expansion:', enableQueryExpansion);
|
||||
console.log('HyDE:', enableHyDE);
|
||||
|
||||
const role = req.user.role;
|
||||
const tenantId = req.user.tenantId;
|
||||
|
||||
// 获取用户的LLM模型配置
|
||||
let models = await this.modelConfigService.findAll();
|
||||
|
||||
if (role !== 'SUPER_ADMIN') {
|
||||
const tenantSettings = await this.tenantService.getSettings(tenantId);
|
||||
const enabledIds = tenantSettings?.enabledModelIds || [];
|
||||
// Only allow models that are enabled by the tenant admin
|
||||
models = models.filter((m) => enabledIds.includes(m.id));
|
||||
}
|
||||
|
||||
let llmModel;
|
||||
if (selectedLLMId) {
|
||||
// Find specifically selected model
|
||||
llmModel = await this.modelConfigService.findOne(selectedLLMId);
|
||||
console.log('使用选中的LLM模型:', llmModel.name);
|
||||
} else {
|
||||
// Use organization's default LLM from Index Chat Config (strict)
|
||||
llmModel = await this.modelConfigService.findDefaultByType(
|
||||
tenantId,
|
||||
ModelType.LLM,
|
||||
);
|
||||
console.log(
|
||||
'最终使用的LLM模型 (默认):',
|
||||
llmModel ? llmModel.name : '无',
|
||||
);
|
||||
}
|
||||
|
||||
// 设置 SSE 响应头
|
||||
res.setHeader('Content-Type', 'text/event-stream');
|
||||
res.setHeader('Cache-Control', 'no-cache');
|
||||
res.setHeader('Connection', 'keep-alive');
|
||||
res.setHeader('Access-Control-Allow-Origin', '*');
|
||||
|
||||
if (!llmModel) {
|
||||
res.write(
|
||||
`data: ${JSON.stringify({ type: 'error', data: 'Please add LLM model and configure API key in model management' })}\n\n`,
|
||||
);
|
||||
res.write('data: [DONE]\n\n');
|
||||
res.end();
|
||||
return;
|
||||
}
|
||||
|
||||
const stream = this.chatService.streamChat(
|
||||
message,
|
||||
history,
|
||||
userId,
|
||||
llmModel,
|
||||
userLanguage,
|
||||
selectedEmbeddingId,
|
||||
selectedGroups,
|
||||
selectedFiles,
|
||||
historyId,
|
||||
enableRerank,
|
||||
selectedRerankId,
|
||||
temperature, // 传递 temperature 参数
|
||||
maxTokens, // 传递 maxTokens 参数
|
||||
topK, // 传递 topK 参数
|
||||
similarityThreshold, // 传递 similarityThreshold 参数
|
||||
rerankSimilarityThreshold, // 传递 rerankSimilarityThreshold 参数
|
||||
enableQueryExpansion, // 传递 enableQueryExpansion
|
||||
enableHyDE, // 传递 enableHyDE
|
||||
req.user.tenantId, // Pass tenant ID
|
||||
);
|
||||
|
||||
for await (const chunk of stream) {
|
||||
res.write(`data: ${JSON.stringify(chunk)}\n\n`);
|
||||
}
|
||||
|
||||
res.write('data: [DONE]\n\n');
|
||||
res.end();
|
||||
} catch (error) {
|
||||
console.error('Stream chat error:', error);
|
||||
try {
|
||||
res.write(
|
||||
`data: ${JSON.stringify({ type: 'error', data: error.message || 'Server Error' })}\n\n`,
|
||||
);
|
||||
res.write('data: [DONE]\n\n');
|
||||
res.end();
|
||||
} catch (writeError) {
|
||||
console.error('Failed to write error response:', writeError);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
@Post('assist')
|
||||
async streamAssist(
|
||||
@Request() req,
|
||||
@Body() body: { instruction: string; context: string },
|
||||
@Res() res: Response,
|
||||
) {
|
||||
try {
|
||||
const { instruction, context } = body;
|
||||
const userId = req.user.id; // Corrected to use req.user.id
|
||||
const tenantId = req.user.tenantId;
|
||||
const role = req.user.role;
|
||||
|
||||
// Use organization's default LLM from Index Chat Config (strict)
|
||||
const llmModel = await this.modelConfigService.findDefaultByType(
|
||||
tenantId,
|
||||
ModelType.LLM,
|
||||
);
|
||||
|
||||
res.setHeader('Content-Type', 'text/event-stream');
|
||||
res.setHeader('Cache-Control', 'no-cache');
|
||||
res.setHeader('Connection', 'keep-alive');
|
||||
res.setHeader('Access-Control-Allow-Origin', '*');
|
||||
|
||||
if (!llmModel) {
|
||||
res.write(
|
||||
`data: ${JSON.stringify({ type: 'error', data: 'LLM model configuration not found' })}\n\n`,
|
||||
);
|
||||
res.write('data: [DONE]\n\n');
|
||||
res.end();
|
||||
return;
|
||||
}
|
||||
|
||||
const stream = this.chatService.streamAssist(
|
||||
instruction,
|
||||
context,
|
||||
llmModel as any,
|
||||
);
|
||||
|
||||
for await (const chunk of stream) {
|
||||
res.write(`data: ${JSON.stringify(chunk)}\n\n`);
|
||||
}
|
||||
|
||||
res.write('data: [DONE]\n\n');
|
||||
res.end();
|
||||
} catch (error) {
|
||||
console.error('Stream assist error:', error);
|
||||
res.write(
|
||||
`data: ${JSON.stringify({ type: 'error', data: error.message || 'Server Error' })}\n\n`,
|
||||
);
|
||||
res.write('data: [DONE]\n\n');
|
||||
res.end();
|
||||
}
|
||||
}
|
||||
}
|
||||
@@ -0,0 +1,28 @@
|
||||
import { Module, forwardRef } from '@nestjs/common';
|
||||
import { ChatController } from './chat.controller';
|
||||
import { ChatService } from './chat.service';
|
||||
import { ElasticsearchModule } from '../elasticsearch/elasticsearch.module';
|
||||
import { KnowledgeBaseModule } from '../knowledge-base/knowledge-base.module';
|
||||
import { ModelConfigModule } from '../model-config/model-config.module';
|
||||
import { KnowledgeGroupModule } from '../knowledge-group/knowledge-group.module';
|
||||
import { SearchHistoryModule } from '../search-history/search-history.module';
|
||||
import { RagModule } from '../rag/rag.module';
|
||||
import { TenantModule } from '../tenant/tenant.module';
|
||||
import { UserModule } from '../user/user.module';
|
||||
|
||||
@Module({
|
||||
imports: [
|
||||
forwardRef(() => ElasticsearchModule),
|
||||
forwardRef(() => KnowledgeBaseModule),
|
||||
ModelConfigModule,
|
||||
forwardRef(() => KnowledgeGroupModule),
|
||||
SearchHistoryModule,
|
||||
RagModule,
|
||||
TenantModule,
|
||||
UserModule,
|
||||
],
|
||||
controllers: [ChatController],
|
||||
providers: [ChatService],
|
||||
exports: [ChatService],
|
||||
})
|
||||
export class ChatModule {}
|
||||
@@ -0,0 +1,714 @@
|
||||
import { Injectable, Logger, Inject, forwardRef } from '@nestjs/common';
|
||||
import { ConfigService } from '@nestjs/config';
|
||||
import { ChatOpenAI } from '@langchain/openai';
|
||||
import { PromptTemplate } from '@langchain/core/prompts';
|
||||
import { ElasticsearchService } from '../elasticsearch/elasticsearch.service';
|
||||
import { EmbeddingService } from '../knowledge-base/embedding.service';
|
||||
import { ModelConfigService } from '../model-config/model-config.service';
|
||||
import { KnowledgeGroupService } from '../knowledge-group/knowledge-group.service';
|
||||
import { SearchHistoryService } from '../search-history/search-history.service';
|
||||
import { ModelConfig, ModelType } from '../types';
|
||||
import { RagService } from '../rag/rag.service';
|
||||
|
||||
import {
|
||||
DEFAULT_VECTOR_DIMENSIONS,
|
||||
DEFAULT_LANGUAGE,
|
||||
} from '../common/constants';
|
||||
import { I18nService } from '../i18n/i18n.service';
|
||||
import { TenantService } from '../tenant/tenant.service';
|
||||
import { UserSettingService } from '../user/user-setting.service';
|
||||
|
||||
export interface ChatMessage {
|
||||
role: 'user' | 'assistant';
|
||||
content: string;
|
||||
}
|
||||
|
||||
@Injectable()
|
||||
export class ChatService {
|
||||
private readonly logger = new Logger(ChatService.name);
|
||||
private readonly defaultDimensions: number;
|
||||
|
||||
constructor(
|
||||
@Inject(forwardRef(() => ElasticsearchService))
|
||||
private elasticsearchService: ElasticsearchService,
|
||||
private embeddingService: EmbeddingService,
|
||||
private modelConfigService: ModelConfigService,
|
||||
@Inject(forwardRef(() => KnowledgeGroupService))
|
||||
private knowledgeGroupService: KnowledgeGroupService,
|
||||
private searchHistoryService: SearchHistoryService,
|
||||
private configService: ConfigService,
|
||||
private ragService: RagService,
|
||||
private i18nService: I18nService,
|
||||
private tenantService: TenantService,
|
||||
private userSettingService: UserSettingService,
|
||||
) {
|
||||
this.defaultDimensions = parseInt(
|
||||
this.configService.get<string>(
|
||||
'DEFAULT_VECTOR_DIMENSIONS',
|
||||
String(DEFAULT_VECTOR_DIMENSIONS),
|
||||
),
|
||||
);
|
||||
}
|
||||
|
||||
async *streamChat(
|
||||
message: string,
|
||||
history: ChatMessage[],
|
||||
userId: string,
|
||||
modelConfig: ModelConfig,
|
||||
userLanguage: string = DEFAULT_LANGUAGE,
|
||||
selectedEmbeddingId?: string,
|
||||
selectedGroups?: string[], // New: Selected groups
|
||||
selectedFiles?: string[], // New: Selected files
|
||||
historyId?: string, // New: Chat history ID
|
||||
enableRerank: boolean = false,
|
||||
selectedRerankId?: string,
|
||||
temperature?: number, // New: temperature parameter
|
||||
maxTokens?: number, // New: maxTokens parameter
|
||||
topK?: number, // New: topK parameter
|
||||
similarityThreshold?: number, // New: similarityThreshold parameter
|
||||
rerankSimilarityThreshold?: number, // New: rerankSimilarityThreshold parameter
|
||||
enableQueryExpansion?: boolean, // New
|
||||
enableHyDE?: boolean, // New
|
||||
tenantId?: string, // New: tenant isolation
|
||||
): AsyncGenerator<{ type: 'content' | 'sources' | 'historyId'; data: any }> {
|
||||
console.log('=== ChatService.streamChat ===');
|
||||
console.log('User ID:', userId);
|
||||
console.log('User language:', userLanguage);
|
||||
console.log('Selected embedding model ID:', selectedEmbeddingId);
|
||||
console.log('Selected groups:', selectedGroups);
|
||||
console.log('Selected files:', selectedFiles);
|
||||
console.log('History ID:', historyId);
|
||||
console.log('Temperature:', temperature);
|
||||
console.log('Max Tokens:', maxTokens);
|
||||
console.log('Top K:', topK);
|
||||
console.log('Similarity threshold:', similarityThreshold);
|
||||
console.log('Rerank threshold:', rerankSimilarityThreshold);
|
||||
console.log('Query expansion:', enableQueryExpansion);
|
||||
console.log('HyDE:', enableHyDE);
|
||||
console.log('Model configuration:', {
|
||||
name: modelConfig.name,
|
||||
modelId: modelConfig.modelId,
|
||||
baseUrl: modelConfig.baseUrl,
|
||||
});
|
||||
console.log(
|
||||
'API Key prefix:',
|
||||
modelConfig.apiKey?.substring(0, 10) + '...',
|
||||
);
|
||||
console.log('API Key length:', modelConfig.apiKey?.length);
|
||||
|
||||
// Get current language setting (keeping LANGUAGE_CONFIG for backward compatibility, now uses i18n service)
|
||||
// Use actual language based on user settings
|
||||
const effectiveUserLanguage = userLanguage || DEFAULT_LANGUAGE;
|
||||
|
||||
let currentHistoryId = historyId;
|
||||
let fullResponse = '';
|
||||
|
||||
try {
|
||||
// Create new chat history if no historyId
|
||||
if (!currentHistoryId) {
|
||||
const searchHistory = await this.searchHistoryService.create(
|
||||
userId,
|
||||
tenantId || 'default', // New
|
||||
message,
|
||||
selectedGroups,
|
||||
);
|
||||
currentHistoryId = searchHistory.id;
|
||||
console.log(
|
||||
this.i18nService.getMessage(
|
||||
'creatingHistory',
|
||||
effectiveUserLanguage,
|
||||
) + currentHistoryId,
|
||||
);
|
||||
yield { type: 'historyId', data: currentHistoryId };
|
||||
}
|
||||
|
||||
// Save user message
|
||||
await this.searchHistoryService.addMessage(
|
||||
currentHistoryId,
|
||||
'user',
|
||||
message,
|
||||
);
|
||||
// 1. Get user's embedding model settings
|
||||
let embeddingModel: any;
|
||||
|
||||
if (selectedEmbeddingId) {
|
||||
// Find specifically selected model
|
||||
embeddingModel =
|
||||
await this.modelConfigService.findOne(selectedEmbeddingId);
|
||||
} else {
|
||||
// Use organization's default from Index Chat Config (strict)
|
||||
embeddingModel = await this.modelConfigService.findDefaultByType(
|
||||
tenantId || 'default',
|
||||
ModelType.EMBEDDING,
|
||||
);
|
||||
}
|
||||
|
||||
console.log(
|
||||
this.i18nService.getMessage(
|
||||
'usingEmbeddingModel',
|
||||
effectiveUserLanguage,
|
||||
) +
|
||||
embeddingModel.name +
|
||||
' ' +
|
||||
embeddingModel.modelId +
|
||||
' ID:' +
|
||||
embeddingModel.id,
|
||||
);
|
||||
|
||||
// 2. Search using user's query directly
|
||||
console.log(
|
||||
this.i18nService.getMessage('startingSearch', effectiveUserLanguage),
|
||||
);
|
||||
yield {
|
||||
type: 'content',
|
||||
data:
|
||||
this.i18nService.getMessage('searching', effectiveUserLanguage) +
|
||||
'\n',
|
||||
};
|
||||
|
||||
let searchResults: any[] = [];
|
||||
let context = '';
|
||||
|
||||
try {
|
||||
// 3. If knowledge groups are selected, get file IDs from those groups first
|
||||
let effectiveFileIds = selectedFiles; // Prioritize explicitly specified files
|
||||
if (!effectiveFileIds && selectedGroups && selectedGroups.length > 0) {
|
||||
// Get file IDs from knowledge groups
|
||||
effectiveFileIds =
|
||||
await this.knowledgeGroupService.getFileIdsByGroups(
|
||||
selectedGroups,
|
||||
userId,
|
||||
tenantId as string,
|
||||
);
|
||||
}
|
||||
|
||||
// 3. Use RagService for search (supports hybrid search + Rerank)
|
||||
const ragResults = await this.ragService.searchKnowledge(
|
||||
message,
|
||||
userId,
|
||||
topK,
|
||||
similarityThreshold,
|
||||
embeddingModel.id,
|
||||
true, // enableFullTextSearch (Chat defaults to hybrid)
|
||||
enableRerank,
|
||||
selectedRerankId,
|
||||
undefined, // selectedGroups
|
||||
effectiveFileIds,
|
||||
rerankSimilarityThreshold,
|
||||
tenantId,
|
||||
enableQueryExpansion,
|
||||
enableHyDE,
|
||||
);
|
||||
|
||||
// Convert RagSearchResult to format needed by ChatService (any[])
|
||||
// HybridSearch returns ES hit structure, but RagSearchResult is normalized
|
||||
// BuildContext expects {fileName, content}. RagSearchResult has these
|
||||
searchResults = ragResults;
|
||||
console.log(
|
||||
this.i18nService.getMessage(
|
||||
'searchResultsCount',
|
||||
effectiveUserLanguage,
|
||||
) + searchResults.length,
|
||||
);
|
||||
|
||||
// 4. Build context
|
||||
context = this.buildContext(searchResults, effectiveUserLanguage);
|
||||
|
||||
if (searchResults.length === 0) {
|
||||
if (selectedGroups && selectedGroups.length > 0) {
|
||||
// User selected knowledge groups but no matches found
|
||||
const noMatchMsg = this.i18nService.getMessage(
|
||||
'noMatchInKnowledgeGroup',
|
||||
effectiveUserLanguage,
|
||||
);
|
||||
yield { type: 'content', data: `⚠️ ${noMatchMsg}\n\n` };
|
||||
} else {
|
||||
yield {
|
||||
type: 'content',
|
||||
data:
|
||||
this.i18nService.getMessage(
|
||||
'noResults',
|
||||
effectiveUserLanguage,
|
||||
) + '\n\n',
|
||||
};
|
||||
}
|
||||
yield {
|
||||
type: 'content',
|
||||
data: `[Debug] ${this.i18nService.getMessage('searchScope', effectiveUserLanguage)}: ${selectedFiles ? selectedFiles.length + ' ' + this.i18nService.getMessage('files', effectiveUserLanguage) : selectedGroups ? selectedGroups.length + ' ' + this.i18nService.getMessage('notebooks', effectiveUserLanguage) : this.i18nService.getMessage('all', effectiveUserLanguage)}\n`,
|
||||
};
|
||||
yield {
|
||||
type: 'content',
|
||||
data: `[Debug] ${this.i18nService.getMessage('searchResults', effectiveUserLanguage)}: 0 ${this.i18nService.getMessage('items', effectiveUserLanguage)}\n`,
|
||||
};
|
||||
} else {
|
||||
yield {
|
||||
type: 'content',
|
||||
data: `${searchResults.length} ${this.i18nService.getMessage('relevantInfoFound', effectiveUserLanguage)}。${this.i18nService.getMessage('generatingResponse', effectiveUserLanguage)}...\n\n`,
|
||||
};
|
||||
// Debug info
|
||||
const scores = searchResults
|
||||
.map((r) => {
|
||||
if (
|
||||
r.originalScore !== undefined &&
|
||||
r.originalScore !== r.score
|
||||
) {
|
||||
return `${r.originalScore.toFixed(2)} → ${r.score.toFixed(2)}`;
|
||||
}
|
||||
return r.score.toFixed(2);
|
||||
})
|
||||
.join(', ');
|
||||
const files = [...new Set(searchResults.map((r) => r.fileName))].join(
|
||||
', ',
|
||||
);
|
||||
yield {
|
||||
type: 'content',
|
||||
data: `> [Debug] ${this.i18nService.getMessage('searchHits', effectiveUserLanguage)}: ${searchResults.length} ${this.i18nService.getMessage('items', effectiveUserLanguage)}\n`,
|
||||
};
|
||||
yield {
|
||||
type: 'content',
|
||||
data: `> [Debug] ${this.i18nService.getMessage('relevance', effectiveUserLanguage)}: ${scores}\n`,
|
||||
};
|
||||
yield {
|
||||
type: 'content',
|
||||
data: `> [Debug] ${this.i18nService.getMessage('sourceFiles', effectiveUserLanguage)}: ${files}\n\n---\n\n`,
|
||||
};
|
||||
}
|
||||
} catch (searchError) {
|
||||
console.error(
|
||||
this.i18nService.getMessage(
|
||||
'searchFailedLog',
|
||||
effectiveUserLanguage,
|
||||
) + ':',
|
||||
searchError,
|
||||
);
|
||||
yield {
|
||||
type: 'content',
|
||||
data:
|
||||
this.i18nService.getMessage('searchFailed', effectiveUserLanguage) +
|
||||
'\n\n',
|
||||
};
|
||||
}
|
||||
|
||||
// 5. Stream response generation
|
||||
this.logger.log(
|
||||
this.i18nService.formatMessage(
|
||||
'modelCall',
|
||||
{
|
||||
type: 'LLM',
|
||||
model: `${modelConfig.name} (${modelConfig.modelId})`,
|
||||
user: userId,
|
||||
},
|
||||
effectiveUserLanguage,
|
||||
),
|
||||
);
|
||||
const llm = new ChatOpenAI({
|
||||
apiKey: modelConfig.apiKey || 'ollama',
|
||||
streaming: true,
|
||||
temperature: temperature !== undefined ? temperature : 0.3,
|
||||
maxTokens: maxTokens !== undefined ? maxTokens : undefined,
|
||||
modelName: modelConfig.modelId,
|
||||
configuration: {
|
||||
baseURL: modelConfig.baseUrl || 'http://localhost:11434/v1',
|
||||
},
|
||||
});
|
||||
|
||||
const promptTemplate =
|
||||
context.length > 0
|
||||
? this.i18nService.getPrompt(
|
||||
effectiveUserLanguage,
|
||||
'withContext',
|
||||
selectedGroups && selectedGroups.length > 0,
|
||||
)
|
||||
: this.i18nService.getPrompt(effectiveUserLanguage, 'withoutContext');
|
||||
|
||||
const prompt = PromptTemplate.fromTemplate(promptTemplate);
|
||||
|
||||
const chain = prompt.pipe(llm);
|
||||
|
||||
const stream = await chain.stream({
|
||||
context,
|
||||
history: this.formatHistory(history, userLanguage),
|
||||
question: message,
|
||||
});
|
||||
|
||||
for await (const chunk of stream) {
|
||||
if (chunk.content) {
|
||||
fullResponse += chunk.content;
|
||||
yield { type: 'content', data: chunk.content };
|
||||
}
|
||||
}
|
||||
|
||||
// Save AI response
|
||||
await this.searchHistoryService.addMessage(
|
||||
currentHistoryId,
|
||||
'assistant',
|
||||
fullResponse,
|
||||
searchResults.map((result) => ({
|
||||
fileName: result.fileName,
|
||||
title: result.metadata?.title || result.metadata?.originalName, // ES metadata contains these
|
||||
content: String(result.content).substring(0, 200) + '...',
|
||||
score: result.score,
|
||||
chunkIndex: result.chunkIndex,
|
||||
fileId: result.fileId,
|
||||
})),
|
||||
);
|
||||
|
||||
// 7. Auto-generate chat title (executed after first exchange)
|
||||
const messagesInHistory = await this.searchHistoryService.findOne(
|
||||
currentHistoryId,
|
||||
userId,
|
||||
tenantId,
|
||||
);
|
||||
if (messagesInHistory.messages.length === 2) {
|
||||
this.generateChatTitle(currentHistoryId, userId, tenantId).catch(
|
||||
(err) => {
|
||||
this.logger.error(
|
||||
`Failed to generate chat title for ${currentHistoryId}`,
|
||||
err,
|
||||
);
|
||||
},
|
||||
);
|
||||
}
|
||||
|
||||
// 6. Return sources
|
||||
yield {
|
||||
type: 'sources',
|
||||
data: searchResults.map((result) => ({
|
||||
fileName: result.fileName,
|
||||
content: String(result.content).substring(0, 200) + '...',
|
||||
score: result.score,
|
||||
chunkIndex: result.chunkIndex,
|
||||
fileId: result.fileId,
|
||||
})),
|
||||
};
|
||||
} catch (error) {
|
||||
this.logger.error(
|
||||
this.i18nService.getMessage('chatStreamError', effectiveUserLanguage),
|
||||
error,
|
||||
);
|
||||
yield {
|
||||
type: 'content',
|
||||
data: `${this.i18nService.getMessage('error', effectiveUserLanguage)}: ${error.message}`,
|
||||
};
|
||||
}
|
||||
}
|
||||
|
||||
async *streamAssist(
|
||||
instruction: string,
|
||||
context: string,
|
||||
modelConfig: ModelConfig,
|
||||
userLanguage: string = DEFAULT_LANGUAGE,
|
||||
): AsyncGenerator<{ type: 'content'; data: any }> {
|
||||
try {
|
||||
this.logger.log(
|
||||
this.i18nService.formatMessage(
|
||||
'modelCall',
|
||||
{
|
||||
type: 'LLM (Assist)',
|
||||
model: `${modelConfig.name} (${modelConfig.modelId})`,
|
||||
user: 'N/A',
|
||||
},
|
||||
userLanguage,
|
||||
),
|
||||
);
|
||||
const llm = new ChatOpenAI({
|
||||
apiKey: modelConfig.apiKey || 'ollama',
|
||||
streaming: true,
|
||||
temperature: 0.7,
|
||||
modelName: modelConfig.modelId,
|
||||
configuration: {
|
||||
baseURL: modelConfig.baseUrl || 'http://localhost:11434/v1',
|
||||
},
|
||||
});
|
||||
|
||||
const systemPrompt = `${this.i18nService.getMessage('intelligentAssistant', userLanguage)}
|
||||
${this.i18nService.getMessage('assistSystemPrompt', userLanguage)}
|
||||
|
||||
${this.i18nService.getMessage('contextLabel', userLanguage)}:
|
||||
${context}
|
||||
|
||||
${this.i18nService.getMessage('userInstructionLabel', userLanguage)}:
|
||||
${instruction}`;
|
||||
|
||||
const stream = await llm.stream(systemPrompt);
|
||||
|
||||
for await (const chunk of stream) {
|
||||
if (chunk.content) {
|
||||
yield { type: 'content', data: chunk.content };
|
||||
}
|
||||
}
|
||||
} catch (error) {
|
||||
this.logger.error(
|
||||
this.i18nService.getMessage('assistStreamError', userLanguage),
|
||||
error,
|
||||
);
|
||||
yield {
|
||||
type: 'content',
|
||||
data: `${this.i18nService.getMessage('error', userLanguage)}: ${error.message}`,
|
||||
};
|
||||
}
|
||||
}
|
||||
|
||||
private async hybridSearch(
|
||||
keywords: string[],
|
||||
userId: string,
|
||||
embeddingModelId?: string,
|
||||
selectedGroups?: string[], // New parameter
|
||||
explicitFileIds?: string[], // New parameter
|
||||
tenantId?: string, // Added
|
||||
userLanguage: string = DEFAULT_LANGUAGE,
|
||||
): Promise<any[]> {
|
||||
try {
|
||||
// Join keywords into search string
|
||||
const combinedQuery = keywords.join(' ');
|
||||
console.log(
|
||||
this.i18nService.getMessage('searchString', userLanguage) +
|
||||
combinedQuery,
|
||||
);
|
||||
|
||||
// Check if embedding model ID is provided
|
||||
if (!embeddingModelId) {
|
||||
console.log(
|
||||
this.i18nService.getMessage(
|
||||
'embeddingModelIdNotProvided',
|
||||
userLanguage,
|
||||
),
|
||||
);
|
||||
return [];
|
||||
}
|
||||
|
||||
// Use actual embedding vector
|
||||
console.log(
|
||||
this.i18nService.getMessage('generatingEmbeddings', userLanguage),
|
||||
);
|
||||
const queryEmbedding = await this.embeddingService.getEmbeddings(
|
||||
[combinedQuery],
|
||||
embeddingModelId,
|
||||
);
|
||||
const queryVector = queryEmbedding[0];
|
||||
console.log(
|
||||
this.i18nService.getMessage('embeddingsGenerated', userLanguage) +
|
||||
this.i18nService.getMessage('dimensions', userLanguage) +
|
||||
':',
|
||||
queryVector.length,
|
||||
);
|
||||
|
||||
// Hybrid search
|
||||
console.log(
|
||||
this.i18nService.getMessage('performingHybridSearch', userLanguage),
|
||||
);
|
||||
const results = await this.elasticsearchService.hybridSearch(
|
||||
queryVector,
|
||||
combinedQuery,
|
||||
userId,
|
||||
10,
|
||||
0.6,
|
||||
selectedGroups, // Pass selected groups
|
||||
explicitFileIds, // Pass explicit file IDs
|
||||
tenantId, // Pass tenant ID
|
||||
);
|
||||
console.log(
|
||||
this.i18nService.getMessage('esSearchCompleted', userLanguage) +
|
||||
this.i18nService.getMessage('resultsCount', userLanguage) +
|
||||
':',
|
||||
results.length,
|
||||
);
|
||||
|
||||
return results.slice(0, 10);
|
||||
} catch (error) {
|
||||
console.error(
|
||||
this.i18nService.getMessage('hybridSearchFailed', userLanguage) + ':',
|
||||
error,
|
||||
);
|
||||
return [];
|
||||
}
|
||||
}
|
||||
|
||||
private buildContext(
|
||||
results: any[],
|
||||
language: string = DEFAULT_LANGUAGE,
|
||||
): string {
|
||||
return results
|
||||
.map(
|
||||
(result, index) =>
|
||||
`[${index + 1}] ${this.i18nService.getMessage('file', language)}：${result.fileName}\n${this.i18nService.getMessage('content', language)}：${result.content}\n`,
|
||||
)
|
||||
.join('\n');
|
||||
}
|
||||
|
||||
private formatHistory(
|
||||
history: ChatMessage[],
|
||||
userLanguage: string = DEFAULT_LANGUAGE,
|
||||
): string {
|
||||
const userLabel = this.i18nService.getMessage('userLabel', userLanguage);
|
||||
const assistantLabel = this.i18nService.getMessage(
|
||||
'assistantLabel',
|
||||
userLanguage,
|
||||
);
|
||||
|
||||
return history
|
||||
.slice(-6)
|
||||
.map(
|
||||
(msg) =>
|
||||
`${msg.role === 'user' ? userLabel : assistantLabel}：${msg.content}`,
|
||||
)
|
||||
.join('\n');
|
||||
}
|
||||
async getContextForTopic(
|
||||
topic: string,
|
||||
userId: string,
|
||||
tenantId?: string,
|
||||
groupId?: string,
|
||||
fileIds?: string[],
|
||||
userLanguage: string = DEFAULT_LANGUAGE,
|
||||
): Promise<string> {
|
||||
try {
|
||||
// Use organization's default embedding from Index Chat Config (strict)
|
||||
const embeddingModel = await this.modelConfigService.findDefaultByType(
|
||||
tenantId || 'default',
|
||||
ModelType.EMBEDDING,
|
||||
);
|
||||
|
||||
const results = await this.hybridSearch(
|
||||
[topic],
|
||||
userId,
|
||||
embeddingModel.id,
|
||||
groupId ? [groupId] : undefined,
|
||||
fileIds,
|
||||
tenantId,
|
||||
userLanguage,
|
||||
);
|
||||
|
||||
return this.buildContext(results);
|
||||
} catch (err) {
|
||||
this.logger.error(
|
||||
`${this.i18nService.getMessage('getContextForTopicFailed', userLanguage)}: ${err.message}`,
|
||||
);
|
||||
return '';
|
||||
}
|
||||
}
|
||||
|
||||
async generateSimpleChat(
|
||||
messages: ChatMessage[],
|
||||
userId: string,
|
||||
tenantId?: string,
|
||||
modelConfig?: ModelConfig, // Optional, looks up if not provided
|
||||
userLanguage: string = DEFAULT_LANGUAGE,
|
||||
): Promise<string> {
|
||||
try {
|
||||
let config = modelConfig;
|
||||
if (!config) {
|
||||
// Use organization's default LLM from Index Chat Config (strict)
|
||||
const found = await this.modelConfigService.findDefaultByType(
|
||||
tenantId || 'default',
|
||||
ModelType.LLM,
|
||||
);
|
||||
config = found as unknown as ModelConfig;
|
||||
}
|
||||
|
||||
this.logger.log(
|
||||
this.i18nService.formatMessage(
|
||||
'modelCall',
|
||||
{
|
||||
type: 'LLM (Simple)',
|
||||
model: `${config.name} (${config.modelId})`,
|
||||
user: userId,
|
||||
},
|
||||
DEFAULT_LANGUAGE,
|
||||
),
|
||||
);
|
||||
const settings = await this.tenantService.getSettings(
|
||||
tenantId || 'default',
|
||||
);
|
||||
const llm = new ChatOpenAI({
|
||||
apiKey: config.apiKey || 'ollama',
|
||||
temperature: settings?.temperature ?? 0.7,
|
||||
modelName: config.modelId,
|
||||
configuration: {
|
||||
baseURL: config.baseUrl || 'http://localhost:11434/v1',
|
||||
},
|
||||
});
|
||||
|
||||
const response = await llm.invoke(
|
||||
messages.map((m) => [m.role, m.content]),
|
||||
);
|
||||
|
||||
return String(response.content);
|
||||
} catch (error) {
|
||||
this.logger.error(
|
||||
this.i18nService.getMessage('simpleChatGenerationError', userLanguage),
|
||||
error,
|
||||
);
|
||||
throw error;
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Automatically generate chat title based on conversation content
|
||||
*/
|
||||
async generateChatTitle(
|
||||
historyId: string,
|
||||
userId: string,
|
||||
tenantId?: string,
|
||||
): Promise<string | null> {
|
||||
this.logger.log(`Generating automatic title for chat session ${historyId}`);
|
||||
|
||||
try {
|
||||
const history = await this.searchHistoryService.findOne(
|
||||
historyId,
|
||||
userId,
|
||||
tenantId || 'default',
|
||||
);
|
||||
if (!history || history.messages.length < 2) {
|
||||
return null;
|
||||
}
|
||||
|
||||
const userMessage =
|
||||
history.messages.find((m) => m.role === 'user')?.content || '';
|
||||
const aiResponse =
|
||||
history.messages.find((m) => m.role === 'assistant')?.content || '';
|
||||
|
||||
if (!userMessage || !aiResponse) {
|
||||
return null;
|
||||
}
|
||||
|
||||
// Get language from user settings
|
||||
const userSettings = await this.userSettingService.getByUser(userId);
|
||||
const language = userSettings?.language || DEFAULT_LANGUAGE;
|
||||
|
||||
// Build prompt
|
||||
const prompt = this.i18nService.getChatTitlePrompt(
|
||||
language,
|
||||
userMessage,
|
||||
aiResponse,
|
||||
);
|
||||
|
||||
// Call LLM to generate title
|
||||
const generatedTitle = await this.generateSimpleChat(
|
||||
[{ role: 'user', content: prompt }],
|
||||
userId,
|
||||
tenantId || 'default',
|
||||
);
|
||||
|
||||
if (generatedTitle && generatedTitle.trim().length > 0) {
|
||||
// Remove extra quotes
|
||||
const cleanedTitle = generatedTitle
|
||||
.trim()
|
||||
.replace(/^["']|["']$/g, '')
|
||||
.substring(0, 50);
|
||||
await this.searchHistoryService.updateTitle(historyId, cleanedTitle);
|
||||
this.logger.log(
|
||||
`Successfully generated title for chat ${historyId}: ${cleanedTitle}`,
|
||||
);
|
||||
return cleanedTitle;
|
||||
}
|
||||
} catch (error) {
|
||||
this.logger.error(
|
||||
`Failed to generate chat title for ${historyId}`,
|
||||
error,
|
||||
);
|
||||
}
|
||||
|
||||
return null;
|
||||
}
|
||||
}
|
||||
Reference in New Issue
Block a user