TextWeaver
TextWeaver is a FastAPI-based web server designed for working with Large Language Models (LLMs), specifically with Embeddings-style models. It simplifies the process of handling complex natural language processing tasks and offers a robust and scalable solution for both developers and researchers to store and query against embeddings in Pinecone.
Features
- FastAPI Integration: Leverage the power of FastAPI for creating modern and efficient web APIs.
- LLM and Embedding Support: Easily work with LLMs and various embedding models for rich textual analysis.
- Scalable Architecture: Designed to grow with your needs, TextWeaver can be deployed across various environments.
- User-Friendly Configuration: Get started quickly with intuitive configuration options.
Installation
Please note that TextWeaver requires the use of Amazon Cognito for authentication. You can find more information on how to set up Cognito here. Once you have Cognito set up, you can pass the required id tokens to the server using the Authorization
header.
Please note that TextWeaver requires the use of SNS for sending errors and server events. You can find more information on how to set up SNS here. Once you have SNS set up, you will need to create a topic and pass the required topic name to the server using the .env
file.
Please note that TextWeaver requires the use of Pinecone for storing and querying against embeddings. You can find more information on how to set up Pinecone here. Once you have Pinecone set up, you will need to create two indexes: one for the embeddings and one for the user embeddings. You can then pass the required API key and index names to the server using the .env
file.
To install TextWeaver, you need to have a .env file in the root directory of your project. This file should contain the following variables:
HOST_IP=""
PORT=""
AWS_ACCESS_KEY_ID=""
AWS_SECRET_ACCESS_KEY=""
AWS_DEFAULT_REGION=""
AWS_COGNITO_REGION=""
AWS_USER_POOL_ID=""
AWS_USER_POOL_CLIENT_ID=""
SNS_TOPIC_NAME=""
PINECONE_API_KEY=""
PINECONE_ENVIRONMENT=""
PINECONE_INDEX_NAME=""
PINECONE_USER_INDEX_NAME=""
MODEL_PATH=""
Install TextWeaver directly from PyPI using the following command:
pip install textweaver
Usage
Once installed, you can start the TextWeaver server using the following command:
textweaver
For further customization and detailed documentation, please refer to the project's repository.
Contribution
We welcome contributions from the community! Please check the contributing guidelines in the repository for more information on how you can get involved.
License
TextWeaver is released under the MIT License. See the LICENSE file in the repository for more details.
Contact
For any inquiries, support, or collaboration, please contact the author at wesladd@traingrc.com or open an issue on the project's GitHub page.