Hey Hitesh, thanks to our contributors, we've introduced some exciting new features to Cognita:
1. Added VLM-based PDF parser
2. Integrated an intelligent summary query controller. Now, you can input multiple questions at once, and the controller will break them down into individual queries, answering each in a streaming format. Finally, it provides a summary of all responses.
Roadmap / Anticipated Contribution Scope:
1. Enabling hybrid and sparse vector search support
2. Implementing Embedding Quantization support
3. Integrating with GraphDBs and relevant retrievers
4. Enabling RAG Evaluation across various retrievers
5. Implementing RAG Visualization features
...and many other enhancements are awaiting.
Excited for the community's backing! Let's maintain the momentum of open source.
TrueFoundry has recently introduced a new open-source framework called Cognita, which utilizes Retriever-Augmented Generation (RAG) technology to simplify the transition by providing robust, scalable solutions for deploying AI applications.
TrueFoundry has recently introduced a new open-source framework called Cognita, which utilizes Retriever-Augmented Generation (RAG) technology to simplify the transition by providing robust, scalable solutions for deploying AI applications.
TrueFoundry has recently introduced a new open-source framework called Cognita, which utilizes Retriever-Augmented Generation (RAG) technology to simplify the transition by providing robust, scalable solutions for deploying AI applications.
TrueFoundry has recently introduced a new open-source framework called Cognita, which utilizes Retriever-Augmented Generation (RAG) technology to simplify the transition by providing robust, scalable solutions for deploying AI applications.
TrueFoundry has recently introduced a new open-source framework called Cognita, which utilizes Retriever-Augmented Generation (RAG) technology to simplify the transition by providing robust, scalable solutions for deploying AI applications.
TrueFoundry has recently introduced a new open-source framework called Cognita, which utilizes Retriever-Augmented Generation (RAG) technology to simplify the transition by providing robust, scalable solutions for deploying AI applications.
Hi, I've come across an open-source API-driven RAG framework launched recently. It's different from other frameworks in a lot of context. Give it a try and let me know your thoughts: https://github.com/truefoundry/cognita
1. Added VLM-based PDF parser 2. Integrated an intelligent summary query controller. Now, you can input multiple questions at once, and the controller will break them down into individual queries, answering each in a streaming format. Finally, it provides a summary of all responses.
Roadmap / Anticipated Contribution Scope:
1. Enabling hybrid and sparse vector search support 2. Implementing Embedding Quantization support 3. Integrating with GraphDBs and relevant retrievers 4. Enabling RAG Evaluation across various retrievers 5. Implementing RAG Visualization features ...and many other enhancements are awaiting.
Excited for the community's backing! Let's maintain the momentum of open source.