backend-fastapi
Documentation for the FastAPI backend, endpoints, and dependency injection.
安装与使用
请根据来源仓库和你的 AI 工具说明安装此技能。先阅读技能文件和依赖要求,再添加到工作流。
查看来源 ↗使用指南技能说明
Backend Architecture (FastAPI)
Overview
The backend is a FastAPI application located in backend/. It powers the chatbot and RAG functionality.
Entry Point
-
File:
backend/main.py -
Run:
uvicorn backend.main:app --reload(or vianpm run dev) -
Port: Defaults to
8000.
Endpoints
POST /api/chat
- Purpose: Main RAG chat endpoint.
-
Input:
ChatRequest(query, history, user_context). -
Process:
- Embed query.
- Search Qdrant (
search_qdrant). - Build prompt (
build_rag_prompt). - Generate Agent response.
-
Output:
ChatResponse(answer, contexts).
POST /api/ask-selection
- Purpose: Targeted Q&A on selected text.
-
Input:
AskSelectionRequest(question, selected_text). -
Process:
- Validates selection length.
- Builds selection-specific prompt.
- specific Agent instructions.
Dependencies & Utils
-
backend/utils/config.py: Qdrant initialization. -
backend/utils/helpers.py: Embedding and Prompt building logic. -
backend/models.py: OpenAI/Gemini client setup.
Environment Variables
-
GEMINI_API_KEY: For LLM and Embeddings. -
QDRANT_URL,QDRANT_API_KEY: Vector DB connection.
使用示例
查看来源仓库中的使用示例与配置说明。
查看来源 ↗来源历史
- 收录时间
- 2026-01-20
- 索引更新时间
- 2026-01-28
- Branch
- main
收录与同步日期属于本站记录。源码修改历史请查看来源仓库。
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