https://github.com/haseebulhassan437/langchain-using-api-of-different-models-
A minimal example demonstrating the integration of LangChain with OpenAI's GPT-3.5-turbo-instruct model. This script loads configuration from a .env file using dotenv and generates AI-powered explanations for topics like machine learning, deep learning.
https://github.com/haseebulhassan437/langchain-using-api-of-different-models-
Last synced: 2 months ago
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A minimal example demonstrating the integration of LangChain with OpenAI's GPT-3.5-turbo-instruct model. This script loads configuration from a .env file using dotenv and generates AI-powered explanations for topics like machine learning, deep learning.
- Host: GitHub
- URL: https://github.com/haseebulhassan437/langchain-using-api-of-different-models-
- Owner: HaseebUlHassan437
- License: apache-2.0
- Created: 2025-03-18T10:38:11.000Z (3 months ago)
- Default Branch: main
- Last Pushed: 2025-03-18T11:07:27.000Z (3 months ago)
- Last Synced: 2025-03-18T12:22:46.544Z (3 months ago)
- Language: Python
- Size: 9.77 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# LangChain OpenAI Integration Example
This repository demonstrates how to integrate LangChain with OpenAI's GPT-3.5-turbo-instruct model using a simple Python script. The project loads API keys from a `.env` file and generates AI-powered explanations for topics such as machine learning, deep learning, and computer vision.
## Repository Structure
- **main.py**
The primary Python script that loads environment variables, invokes the language model, and prints the generated output.
- **requirements.txt**
Contains the list of required libraries to run the project.
## Prerequisites
- Python 3.7 or higher
- pip
## Setup Instructions
### 1. Clone the Repository
Clone this repository to your local machine:
```bash
git clone
cd
```
### 2. Create a Virtual Environment (Optional but Recommended)
Create and activate a virtual environment:
- **On macOS/Linux:**
```bash
python3 -m venv venv
source venv/bin/activate
```
- **On Windows:**
```bash
python -m venv venv
venv\Scripts\activate
```
### 3. Install Dependencies
Install the required libraries using the `requirements.txt` file:
```bash
pip install -r requirements.txt
```
### 4. Configure Environment Variables
Create a `.env` file in the root directory of the repository to store your API keys. For example, add your OpenAI API key as follows:
```env
OPENAI_API_KEY=your_openai_api_key_here
```
> **Note:** Ensure you have a valid API key from OpenAI and any other providers you intend to use.
## Running the Script
To run the project, execute the main script:
```bash
python main.py
```
The script will load your API key from the `.env` file, invoke the language model, and print the generated explanation to the console.
## Libraries and Integrations
This project utilizes several libraries and integrations:
- **LangChain & LangChain Core:** Frameworks for developing applications with language models.
- **OpenAI & langchain-openai:** Integration for interacting with OpenAI's GPT models.
- **Anthropic Integration:** For potential use with Anthropic's language models.
- **Google Gemini (PaLM) Integration:** For future integration with Google’s generative AI models.
- **Hugging Face Integration:** Provides support for transformers and accessing models via Hugging Face.
- **Python-Dotenv:** Manages environment variables loaded from the `.env` file.
- **Machine Learning Utilities:** Libraries such as `numpy` and `scikit-learn` for potential ML enhancements.
## Contributing
Contributions are welcome! If you have suggestions or improvements, please submit a pull request or open an issue.
## License
This project is licensed under the MIT License.