Best Retrieval-Augmented Generation (RAG) Software for Llama
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Compare the Top Retrieval-Augmented Generation (RAG) Software that integrates with Llama as of October 2025
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This a list of Retrieval-Augmented Generation (RAG) software that integrates with Llama. Use the filters on the left to add additional filters for products that have integrations with Llama. View the products that work with Llama in the table below.
What is Retrieval-Augmented Generation (RAG) Software for Llama?
Retrieval-Augmented Generation (RAG) tools are advanced AI systems that combine information retrieval with text generation to produce more accurate and contextually relevant outputs. These tools first retrieve relevant data from a vast corpus or database, and then use that information to generate responses or content, enhancing the accuracy and detail of the generated text. RAG tools are particularly useful in applications requiring up-to-date information or specialized knowledge, such as customer support, content creation, and research. By leveraging both retrieval and generation capabilities, RAG tools improve the quality of responses in tasks like question-answering and summarization. This approach bridges the gap between static knowledge bases and dynamic content generation, providing more reliable and context-aware results. Compare and read user reviews of the best Retrieval-Augmented Generation (RAG) software for Llama currently available using the table below. This list is updated regularly.
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1
Amazon Bedrock
Amazon
Amazon Bedrock is a fully managed service that simplifies building and scaling generative AI applications by providing access to a variety of high-performing foundation models (FMs) from leading AI companies such as AI21 Labs, Anthropic, Cohere, Meta, Mistral AI, Stability AI, and Amazon itself. Through a single API, developers can experiment with these models, customize them using techniques like fine-tuning and Retrieval Augmented Generation (RAG), and create agents that interact with enterprise systems and data sources. As a serverless platform, Amazon Bedrock eliminates the need for infrastructure management, allowing seamless integration of generative AI capabilities into applications with a focus on security, privacy, and responsible AI practices. -
2
AnythingLLM
AnythingLLM
Any LLM, any document, and any agent, fully private. Install AnythingLLM and its full suite of tools as a single application on your desktop. Desktop AnythingLLM only talks to the services you explicitly connect to and can run fully on your machine without internet connectivity. We don't lock you into a single LLM provider. Use enterprise models like GPT-4, a custom model, or an open-source model like Llama, Mistral, and more. PDFs, word documents, and so much more make up your business, now you can use them all. AnythingLLM comes with sensible and locally running defaults for your LLM, embedder, and storage for full privacy out of the box. AnythingLLM is free for desktop or self-hosted via our GitHub. AnythingLLM cloud hosting starts at $50/month and is built for businesses or teams that need the power of AnythingLLM, but want to have a managed instance of AnythingLLM so they don't have to sweat the technical details.Starting Price: $50 per month -
3
Entry Point AI
Entry Point AI
Entry Point AI is the modern AI optimization platform for proprietary and open source language models. Manage prompts, fine-tunes, and evals all in one place. When you reach the limits of prompt engineering, it’s time to fine-tune a model, and we make it easy. Fine-tuning is showing a model how to behave, not telling. It works together with prompt engineering and retrieval-augmented generation (RAG) to leverage the full potential of AI models. Fine-tuning can help you to get better quality from your prompts. Think of it like an upgrade to few-shot learning that bakes the examples into the model itself. For simpler tasks, you can train a lighter model to perform at or above the level of a higher-quality model, greatly reducing latency and cost. Train your model not to respond in certain ways to users, for safety, to protect your brand, and to get the formatting right. Cover edge cases and steer model behavior by adding examples to your dataset.Starting Price: $49 per month -
4
Klee
Klee
Local and secure AI on your desktop, ensuring comprehensive insights with complete data security and privacy. Experience unparalleled efficiency, privacy, and intelligence with our cutting-edge macOS-native app and advanced AI features. RAG can utilize data from a local knowledge base to supplement the large language model (LLM). This means you can keep sensitive data on-premises while leveraging it to enhance the model‘s response capabilities. To implement RAG locally, you first need to segment documents into smaller chunks and then encode these chunks into vectors, storing them in a vector database. These vectorized data will be used for subsequent retrieval processes. When a user query is received, the system retrieves the most relevant chunks from the local knowledge base and inputs these chunks along with the original query into the LLM to generate the final response. We promise lifetime free access for individual users. -
5
FalkorDB
FalkorDB
FalkorDB is an ultra-fast, multi-tenant graph database optimized for GraphRAG, delivering accurate, relevant AI/ML results with reduced hallucinations and enhanced performance. It leverages sparse matrix representations and linear algebra to efficiently handle complex, interconnected data in real-time, resulting in fewer hallucinations and more accurate responses from large language models. FalkorDB supports the OpenCypher query language with proprietary enhancements, enabling expressive and efficient querying of graph data. It offers built-in vector indexing and full-text search capabilities, allowing for complex searches and similarity matching within the same database environment. FalkorDB's architecture includes multi-graph support, enabling multiple isolated graphs within a single instance, ensuring security and performance across tenants. It also provides high availability with live replication, ensuring data is always accessible.
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