mapping-agent 0.1.1

LLM-driven agent for creating detailed column-to-attribute mappings

Mapping Agent

LLM-driven intelligent attribute-to-column mapping agent for domain schema validation and refinement.

---

🌟 Features

• Intelligent Entity Mapping – Uses LLM reasoning to map entities from a domain schema to columns across multiple tables.
• Confidence Scoring – Provides confidence scores for each mapping.
• Transformation Suggestions – Suggests data transformations for better alignment.
• Context-Aware Analysis – Generates column profiles (types, nulls, uniqueness, distributions) to improve mapping accuracy.

---

🚀 Quick Start

Installation

Prerequisites

• uv – package & environment manager
  Please refer to the official installation guide for the most up-to-date instructions.
  For quick setup on macOS/Linux, you can currently use:

  curl -LsSf https://astral.sh/uv/install.sh | sh
  

• Git

Steps

1. Clone the repository

   git clone https://github.com/stepfnAI/mapping_agent.git
   cd mapping_agent
   git switch dev
   

2. Install dependencies

   uv sync --extra dev
   

3. Activate the virtual environment

   source .venv/bin/activate
   

4. Clone and install the blueprint dependency

   cd ../
   git clone https://github.com/stepfnAI/sfn_blueprint.git
   cd sfn_blueprint
   git switch dev
   uv pip install -e .
   

5. Return to Mapping Agent

   cd ../mapping_agent/
   

6. Set environment variables
   The agent requires an API key (e.g., OpenAI).

   export LLM_PROVIDER="your-llm-provider"   #"openai/anthropic"
   export LLM_MODEL="your-llm-model"         #"gpt-4.1-mini"
   export LLM_API_KEY="your-api-key-here"    
   

---

Basic Usage

Example: Mapping the Borrower Profile entity to columns across two CSV files.

python examples/basic_usage.py

---

🧪 Testing

Run the test suite with pytest:

# Run all tests
pytest tests/ -s

# Run with coverage
pytest tests/test_models.py
pytest tests/test_utils.py
pytest tests/test_agent_integration.py

---

📝 Prompt Management

Prompts are centralized in
src/mapping_agent/constants.py.

• format_mapping_prompt_with_system_prompt constructs structured prompts with a system message.
• Ensures the LLM consistently acts as a data mapping expert.
• Easy to extend or fine-tune reasoning strategies in one place.

---

🤝 Contributing

Contributions are welcome!
Please see the Contributing Guide before submitting a PR.

---

📄 License

Licensed under the MIT License. See LICENSE for details.