ds_task_marketing_assistant_ai/docs/API_Documendation.md

API Documentation

Base URL

http://localhost:8000

Endpoints

Generate Marketing Copy

POST /generate

Generate marketing copy based on prompt and brand guidelines.

Request Body

{
  "prompt": "string",
  "content_type": "general",
  "tone": "string"
}

Response

"Generated marketing copy text"

Add Campaign

POST /add-campaign

Add a marketing campaign to the vector store for future reference.

Request Body

{
  "content": "string",
  "content_type": "string",
  "metadata": {}
}

Search Campaigns

GET /search

Search for similar campaigns using vector similarity.

Query Parameters

• query (string): Search query
• content_type (string, optional): Filter by content type
• k (int, optional): Number of results to return (default: 3)

Response

[
  {
    "content": "string",
    "content_type": "string",
    "metadata": {},
    "_search_distance": 0.0
  }
]

Health Check

GET /health

Check API health status.

Response

{
  "status": "healthy"
}

Root

GET /

API root endpoint with basic information.

Content Types

• general - General marketing content
• email - Email campaigns
• social - Social media posts
• ad - Advertisement copy
• blog - Blog content

Error Responses

All endpoints may return:

• 422 Validation Error - Invalid request format
• 500 Internal Server Error - Server error

{
  "detail": [
    {
      "loc": ["field_name"],
      "msg": "Error message",
      "type": "error_type"
    }
  ]
}

Vector Store Features

• Uses all-MiniLM-L6-v2 model for embeddings (384 dimensions)
• FAISS index for fast similarity search
• Persistent storage of campaigns
• Automatic index rebuilding on startup