llmware and End-to-End-LLM-Projects
These are complements: llmware provides a production-ready framework for building RAG pipelines, while End-to-End-LLM-Projects serves as educational reference implementations demonstrating similar RAG, function-calling, and agent patterns that practitioners could integrate into a llmware-based system.
About llmware
llmware-ai/llmware
Unified framework for building enterprise RAG pipelines with small, specialized models
This framework helps businesses build secure, private, and cost-effective AI applications that can answer questions using their own specific documents and data. It takes your various business documents (like PDFs, spreadsheets, presentations, etc.) and combines them with specialized AI models to generate accurate answers or insights. This is ideal for organizations that need to leverage their internal knowledge base for tasks such as research, compliance checks, or customer support without sending sensitive data to external AI services.
About End-to-End-LLM-Projects
pd2871/End-to-End-LLM-Projects
This repo contains code related to development of LLM based projects with Langchain and LLamaIndex. It uses RAG, Function calling, agents and tools as of now for interaction with data.
This collection of projects helps developers build applications that can interact with various types of data, including PDFs, CSVs, Excel files, websites, and even images and YouTube links. It takes your raw data sources and allows you to create conversational interfaces or intelligent assistants. Developers who want to integrate natural language processing capabilities into their applications would use this.
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