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It is an open-source RAG framework optimized for large-scale and real-time data. Use Neum AI to bring up-to-date context into your AI applications. | It is the interface between your app and hosted LLMs. It streamlines API requests to OpenAI, Anthropic, Mistral, LLama2, Anyscale, Google Gemini, and more with a unified API. |
High throughput distributed architecture;
Built-in data connectors;
Real-time synchronization;
Customizable data pre-processing;
Cohesive data management | Blazing fast (9.9x faster) with a tiny footprint (~45kb installed);
Load balance across multiple models, providers, and keys;
Fallbacks make sure your app stays resilient;
Automatic Retries with exponential fallbacks come by default;
Plug-in middleware as needed;
Battle-tested over 100B tokens |
Statistics | |
GitHub Stars 864 | GitHub Stars 9.8K |
GitHub Forks 50 | GitHub Forks 775 |
Stacks 0 | Stacks 2 |
Followers 0 | Followers 4 |
Votes 0 | Votes 0 |
Integrations | |

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It is a framework built around LLMs. It can be used for chatbots, generative question-answering, summarization, and much more. The core idea of the library is that we can “chain” together different components to create more advanced use cases around LLMs.

It allows you to run open-source large language models, such as Llama 2, locally.

It is a project that provides a central interface to connect your LLMs with external data. It offers you a comprehensive toolset trading off cost and performance.