multiAI Summary Pending

backend-fastapi

Documentation for the FastAPI backend, endpoints, and dependency injection.

231 stars

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/backend-fastapi/SKILL.md --create-dirs "https://raw.githubusercontent.com/aiskillstore/marketplace/main/skills/abdulsamad94/backend-fastapi/SKILL.md"

Manual Installation

Download SKILL.md from GitHub
Place it in .claude/skills/backend-fastapi/SKILL.md inside your project
Restart your AI agent — it will auto-discover the skill

How backend-fastapi Compares

Feature / Agent	backend-fastapi	Standard Approach
Platform Support	multi	Limited / Varies
Context Awareness	High	Baseline
Installation Complexity	Unknown	N/A

Frequently Asked Questions

What does this skill do?

Documentation for the FastAPI backend, endpoints, and dependency injection.

Which AI agents support this skill?

This skill is compatible with multi.

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

SKILL.md Source

# 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 via `npm run dev`)
- **Port**: Defaults to `8000`.

## Endpoints

### `POST /api/chat`

- **Purpose**: Main RAG chat endpoint.
- **Input**: `ChatRequest` (query, history, user_context).
- **Process**:
  1. Embed query.
  2. Search Qdrant (`search_qdrant`).
  3. Build prompt (`build_rag_prompt`).
  4. Generate Agent response.
- **Output**: `ChatResponse` (answer, contexts).

### `POST /api/ask-selection`

- **Purpose**: Targeted Q&A on selected text.
- **Input**: `AskSelectionRequest` (question, selected_text).
- **Process**:
  1. Validates selection length.
  2. Builds selection-specific prompt.
  3. 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.