Data Analysis API

This repository contains a FastAPI application that provides endpoints for data clustering and similarity search operations.

Features

1. Clustering: Performs DBSCAN clustering on CSV datasets.
2. Similarity Search: Conducts vector embedding and similarity search for a given query in a CSV dataset.

Setup

1. Clone the repository: git clone https://github.com/yourusername/curotec_task.git cd curotec_task

2. Install the required dependencies: pip install -r requirements.txt

Usage

Run the FastAPI application: python src/main.py

The server will start at http://127.0.0.1:8000/.

API Endpoints

Root

• GET / : Welcome message and basic API information.

Clustering

• POST /clustering : Perform DBSCAN clustering on a CSV file.
  • Parameters:
    • file: CSV file (required)
    • params: JSON string of clustering parameters (optional)

Similarity Search

• POST /similarity : Perform similarity search on text data in a CSV file.
  • Parameters:
    • file: CSV file (required)
    • params: JSON string of similarity search parameters (optional)

Docs

• /docs : You can always access the FastAPI docs at /docs (e.g., http://127.0.0.1:8000/docs). This will provide a "friendly UI" for interacting with the API.

Parameters

Clustering Parameters

• eps_range: List of float values for DBSCAN epsilon parameter
• min_samples_range: List of integer values for DBSCAN min_samples parameter
• label_column_index: Index of the label column (if exists)
• max_grid_search_combinations: Maximum number of parameter combinations for grid search
• n_components_global: Number of global components for MFA
• do_mfa: Boolean flag to enable MFA

Similarity Parameters

• text_column: Column name containing text to embed
• query_text: Optional text to compare against
• top_k: Number of most similar items to return

Dependencies

• FastAPI
• pandas
• numpy
• scikit-learn
• sentence-transformers
• uvicorn
• pydantic

For a complete list of dependencies, see requirements.txt.