152 lines
5.2 KiB
Markdown
152 lines
5.2 KiB
Markdown
# Project Overview
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Perplexica is an open-source AI-powered search engine that uses advanced machine learning to provide intelligent search results. It combines web search capabilities with LLM-based processing to understand and answer user questions, similar to Perplexity AI but fully open source.
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## Architecture
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The system works through these main steps:
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- User submits a query
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- The system determines if web search is needed
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- If needed, it searches the web using SearXNG
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- Results are ranked using embedding-based similarity search
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- LLMs are used to generate a comprehensive response with cited sources
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## Architecture Details
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### Technology Stack
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- **Frontend**: React, Next.js, Tailwind CSS
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- **Backend**: Node.js
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- **Database**: SQLite with Drizzle ORM
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- **AI/ML**: LangChain + LangGraph for orchestration
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- **Search**: SearXNG integration
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- **Content Processing**: Mozilla Readability, Cheerio, Playwright
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### Database (SQLite + Drizzle ORM)
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- Schema: `src/lib/db/schema.ts`
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- Tables: `messages`, `chats`, `systemPrompts`
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- Configuration: `drizzle.config.ts`
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- Local file: `data/db.sqlite`
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### AI/ML Stack
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- **LLM Providers**: OpenAI, Anthropic, Groq, Ollama, Gemini, DeepSeek, LM Studio
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- **Embeddings**: Xenova Transformers, similarity search (cosine/dot product)
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- **Agents**: `webSearchAgent`, `analyzerAgent`, `synthesizerAgent`, `taskManagerAgent`
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### External Services
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- **Search Engine**: SearXNG integration (`src/lib/searxng.ts`)
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- **Configuration**: TOML-based config file
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### Data Flow
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1. User query → Task Manager Agent
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2. Web Search Agent → SearXNG → Content extraction
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3. Analyzer Agent → Content processing + embedding
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4. Synthesizer Agent → LLM response generation
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5. Response with cited sources
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## Project Structure
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- `/src/app`: Next.js app directory with page components and API routes
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- `/src/app/api`: API endpoints for search and LLM interactions
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- `/src/components`: Reusable UI components
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- `/src/lib`: Backend functionality
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- `lib/search`: Search functionality and meta search agent
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- `lib/db`: Database schema and operations
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- `lib/providers`: LLM and embedding model integrations
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- `lib/prompts`: Prompt templates for LLMs
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- `lib/chains`: LangChain chains for various operations
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- `lib/agents`: LangGraph agents for advanced processing
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- `lib/utils`: Utility functions and types including web content retrieval and processing
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## Focus Modes
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Perplexica supports multiple specialized search modes:
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- All Mode: General web search
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- Local Research Mode: Research and interact with local files with citations
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- Chat Mode: Have a creative conversation
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- Academic Search Mode: For academic research
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- YouTube Search Mode: For video content
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- Wolfram Alpha Search Mode: For calculations and data analysis
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- Reddit Search Mode: For community discussions
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## Core Commands
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- **Development**: `npm run dev` (uses Turbopack for faster builds)
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- **Build**: `npm run build` (includes automatic DB push)
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- **Production**: `npm run start`
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- **Linting**: `npm run lint` (Next.js ESLint)
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- **Formatting**: `npm run format:write` (Prettier)
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- **Database**: `npm run db:push` (Drizzle migrations)
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## Configuration
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The application uses a `config.toml` file (created from `sample.config.toml`) for configuration, including:
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- API keys for various LLM providers
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- Database settings
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- Search engine configuration
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- Similarity measure settings
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## Common Tasks
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When working on this codebase, you might need to:
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- Add new API endpoints in `/src/app/api`
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- Modify UI components in `/src/components`
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- Extend search functionality in `/src/lib/search`
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- Add new LLM providers in `/src/lib/providers`
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- Update database schema in `/src/lib/db/schema.ts`
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- Create new prompt templates in `/src/lib/prompts`
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- Build new chains in `/src/lib/chains`
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- Implement new LangGraph agents in `/src/lib/agents`
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## AI Behavior Guidelines
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- Focus on factual, technical responses without unnecessary pleasantries
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- Avoid conciliatory language and apologies
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- Ask for clarification when requirements are unclear
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- Do not add dependencies unless explicitly requested
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- Only make changes relevant to the specific task
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- **Do not create test files or run the application unless requested**
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- Prioritize existing patterns and architectural decisions
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- Use the established component structure and styling patterns
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## Code Style & Standards
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### TypeScript Configuration
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- Strict mode enabled
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- ES2017 target
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- Path aliases: `@/*` → `src/*`
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- No test files (testing not implemented)
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### Formatting & Linting
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- ESLint: Next.js core web vitals rules
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- Prettier: Use `npm run format:write` before commits
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- Import style: Use `@/` prefix for internal imports
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### File Organization
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- Components: React functional components with TypeScript
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- API routes: Next.js App Router (`src/app/api/`)
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- Utilities: Grouped by domain (`src/lib/`)
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- Naming: camelCase for functions/variables, PascalCase for components
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### Error Handling
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- Use try/catch blocks for async operations
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- Return structured error responses from API routes
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## Available Tools and Help
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- You can use the context7 tool to get help using the following identifiers for libraries used in this project
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- `/langchain-ai/langchainjs` for LangChain
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- `/langchain-ai/langgraph` for LangGraph
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- `/quantizor/markdown-to-jsx` for Markdown to JSX conversion
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