https://github.com/ali-jalil88/ai-code-reviews-using-langchain-ollama-and-streamlit
An AI-powered code reviewer supporting multiple programming languages, including: Python, JavaScript, Ruby, Java, SQL, C++, and PHP.
https://github.com/ali-jalil88/ai-code-reviews-using-langchain-ollama-and-streamlit
langchain llama3 mlflow ollama peewee python streamlit
Last synced: 7 months ago
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An AI-powered code reviewer supporting multiple programming languages, including: Python, JavaScript, Ruby, Java, SQL, C++, and PHP.
- Host: GitHub
- URL: https://github.com/ali-jalil88/ai-code-reviews-using-langchain-ollama-and-streamlit
- Owner: Ali-jalil88
- Created: 2024-11-24T11:48:49.000Z (11 months ago)
- Default Branch: main
- Last Pushed: 2024-11-24T11:51:25.000Z (11 months ago)
- Last Synced: 2025-03-18T09:13:03.135Z (7 months ago)
- Topics: langchain, llama3, mlflow, ollama, peewee, python, streamlit
- Language: Python
- Homepage:
- Size: 70.3 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# AI-Code-Reviews-using-langchain-Ollama-and-Streamlit
# AI Code Reviewer
An AI-powered code reviewer supporting multiple programming languages, including:
`Python`, `JavaScript`, `Ruby`, `Java`, `SQL`, `C++`, and `PHP`.
Built using **LangChain**, **Ollama**, and **Streamlit**.
---
### Project Structure:
- **`ai.py`**: Handles AI functions.
- **`database.py`**: Manages database functions.
- **`config.py`**: Stores configuration variables.
- **`app.py`**: Manages the UI using Streamlit.
- **`review.py`**: Contains the code review schema.
---
### Installation:
1. Install required libraries:
```bash
pip install mlflow streamlit peewee langchain-community langchain-ollama
pip freeze > requirements.txt
## Tools Overview
- **LangChain**: Uses LlamaIndex for AI functionalities.
- **LLM**: Supports Ollama (local) or OpenAI as the language model.
- **Application Frameworks**: Flask, FastAPI, Streamlit.
- **Tracking**: MLflow, GitHub Actions.
- **Database ORM**: Peewee, SQLAlchemy.
---
## Run
To start the application and MLflow UI, execute the following command:
```bash
python -m streamlit run app.py && mlflow ui