Langchain Laboratory is an open-source application built using Streamlit to provide developers and those interested in building Language Model (LLM) applications with LangChain.

• Document Embedding: The application provides a dashboard that allows users to upload PDF (.pdf) files, Mircosoft Word (.docx) files, and plain text (.txt) files. It creates embeddings of these documents and uploads the embeddings to a Chroma Vector Store.

• Conversational Memory: The application also provides a feature for conversational memory.

This project is a work in progress and contributions are encouraged. For more information, please contact [email protected].

This project is open source through MIT licensing.

At this time, this application is only designed to work with the OpenAI GPT-3.5-turbo and GPT-4 LLMs. However, in order to showcase the LangChain modularity and extensibility, we plan to add the ability to allow this tool to be used with any LLM in the future.

This application was developed with a Python 3.11 environment. Follow the steps below to install and run the application:

1. Prerequisites: Ensure that Python 3.11 or greater is installed on your system.

2. Clone the project - Use the command: git clone https://github.com/barweiss45/langchain-laboratory.git to clone the project and cd langchain-laboratory to navigate to the project directory.

3. Set up a virtual environment - Set up your virtual environment with your favorite Python Virtual Environment Software. For example, you can use venv or virtualenv.

4. Install the necessary libraries - Run pip install -r requirements.txt to install the necessary libraries.

5. Add your OpenAI API key - Add a .env file to the main directory that contains your OpenAI API key. The key should be stored with the name OPENAI_KEY_API.

6. Run the application - Execute the command streamlit run Home.py. Your browser should open to http://localhost:8501.

Please note that we will be containerizing this application in the next day or so, which will simplify installation and usage.

If you prefer to use Docker, follow the steps below:

1. Prerequisites: Ensure that Docker is installed on your system. If not, visit Docker for installation instructions. You can verify the installation by running docker --version.

2. Clone the project: Use the command git clone https://github.com/barweiss45/langchain-laboratory.git to clone the project. Next be sure you have moded to the new langchain-laboratory directory, use the command cd langchain-laboratory.

3. Create symbolic links: Create two symbolic links to point back to the Docker folder for the Dockerfile and docker-compose.yml file. Use the following commands:

   ln -s docker/Dockerfile Dockerfile
   ln -s docker/docker-compose.yml docker-compose.yml

4. Build the container: Run docker compose up -d. Please note that the build may take up to 3 to 4 minutes.

5. Verify the status: You can verify the status of the container with the Docker command docker compose ps.

After the container is up and running, you can connect to the application via http://localhost:8501.

This is a new project and we're still working on setting up a comprehensive guide for contributions. In the meantime, if you're interested in contributing or have any questions, please feel free to contact [email protected]. We appreciate your interest and patience.

This project is licensed under the terms of the MIT license. See LICENSE for more details.