ChatPDF
FreeChatGPT + Enterprise data with Azure OpenAI 
FreeFree tier
Outputs: text
About ChatPDF
This open-source accelerator from akshata29 provides a framework for building ChatGPT-like experiences over enterprise data using Azure OpenAI Service. It supports multiple vector stores (Pinecone, Redis, Azure Cognitive Search) for indexing and retrieval, enabling users to upload their own data and ask questions via chat, streaming, Q&A, and admin interfaces. The project includes advanced RAG techniques, multi-modal RAG patterns, and evaluation flows (Groundedness, Ada Similarity) for measuring response quality.
Key Features
Azure OpenAI integration (GPT-35-turbo and GPT3)
Support for multiple vector stores (Pinecone, Redis, Azure Cognitive Search)
Upload your own data and ask questions
Chat, Chat Stream, QnA, Upload, and Admin functionalities
Advanced RAG techniques and multi-modal RAG patterns
Evaluation flows for groundedness and Ada similarity
Open-source and customizable
Pros & Cons
Pros
- Open-source and free to use
- Leverages powerful Azure OpenAI models
- Flexible vector store options (Pinecone, Redis, etc.)
- Includes evaluation pipelines for response quality
- Designed for enterprise scalability and security with Azure
Cons
- Requires an Azure subscription and deployment effort
- Not a managed or hosted service; self-setup needed
- Technical expertise needed for installation and configuration
- Documentation and community support may be limited
Best For
Enterprise document Q&A and knowledge retrievalBuilding custom ChatGPT-like assistants on proprietary dataResearch and analysis over uploaded documentsRapid prototyping of retrieval-augmented generation applications