update API_Documentation
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# API Documentation
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## Base URL
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```
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http://localhost:8000
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```
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## Endpoints
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### Generate Marketing Copy
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**POST** `/generate`
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Generate marketing copy based on prompt and brand guidelines.
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#### Request Body
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```json
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{
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"prompt": "string",
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"content_type": "general",
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"tone": "string"
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}
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```
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#### Response
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```json
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"Generated marketing copy text"
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```
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### Add Campaign
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**POST** `/add-campaign`
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Add a marketing campaign to the vector store for future reference.
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#### Request Body
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```json
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{
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"content": "string",
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"content_type": "string",
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"metadata": {}
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}
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```
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### Search Campaigns
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**GET** `/search`
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Search for similar campaigns using vector similarity.
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#### Query Parameters
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- `query` (string): Search query
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- `content_type` (string, optional): Filter by content type
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- `k` (int, optional): Number of results to return (default: 3)
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#### Response
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```json
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[
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{
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"content": "string",
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"content_type": "string",
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"metadata": {},
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"_search_distance": 0.0
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}
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]
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```
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### Health Check
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**GET** `/health`
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Check API health status.
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#### Response
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```json
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{
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"status": "healthy"
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}
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```
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### Root
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**GET** `/`
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API root endpoint with basic information.
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## Content Types
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- `general` - General marketing content
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- `email` - Email campaigns
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- `social` - Social media posts
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- `ad` - Advertisement copy
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- `blog` - Blog content
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## Error Responses
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All endpoints may return:
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- **422 Validation Error** - Invalid request format
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- **500 Internal Server Error** - Server error
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```json
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{
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"detail": [
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{
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"loc": ["field_name"],
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"msg": "Error message",
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"type": "error_type"
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}
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]
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}
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```
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## Vector Store Features
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- Uses `all-MiniLM-L6-v2` model for embeddings (384 dimensions)
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- FAISS index for fast similarity search
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- Persistent storage of campaigns
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- Automatic index rebuilding on startup
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