ariamehr-gemini-pandas-agent


Nameariamehr-gemini-pandas-agent JSON
Version 0.1.0 PyPI version JSON
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home_pageNone
SummaryGoogle‑native alternative to LangChain's create_pandas_dataframe_agent by Ariamehr A
upload_time2025-04-20 23:26:58
maintainerNone
docs_urlNone
authorNone
requires_python>=3.10
licenseMIT License Copyright (c) 2024 Ariamehr A Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
keywords gemini pandas agent langgraph google-generativeai ariamehr
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            # Ariamehr's Gemini Pandas Agent

A Google-native alternative to LangChain's create_pandas_dataframe_agent, powered by Gemini and LangGraph.

Created by Ariamehr A

## Installation

```bash
pip install ariamehr-gemini-pandas-agent
```

## Quick Start

```python
import pandas as pd
import google.generativeai as genai
from ariamehr_gpandas_agent import create_pandas_dataframe_agent

# Configure Gemini
genai.configure(api_key="YOUR_API_KEY")
model = genai.GenerativeModel("gemini-2.0-pro")

# Load your data
df = pd.read_csv("your_data.csv")

# Create the agent
agent = create_pandas_dataframe_agent(model, df, allow_dangerous_code=False)

# Ask questions about your data
response = agent.run("What is the average value in column X?")
print(response)
```

## Features

- 🚀 Powered by Google's Gemini API and LangGraph
- 🔒 Secure Python AST-based code execution
- 📊 Support for single or multiple DataFrames
- 🎯 Simple, LangChain-compatible interface
- 🛡️ Safe by default with optional dangerous code allowance

## Security Note

By default, the agent runs in a secure mode that prevents potentially dangerous imports. If you need to allow specific imports, use `allow_dangerous_code=True`, but be aware of the security implications.

## License

MIT License - see LICENSE file for details.

## Author

Created by Ariamehr A

## Contributing

Contributions are welcome! Please feel free to submit a Pull Request. 

            

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