Question: Is there a tool that offers a library of building blocks for creating large language models, including document loaders and embedding models?

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LangChain

If you're looking for a tool that comes with a library of building blocks for large language models, including document loaders and embedding models, LangChain is a good option. The platform covers the full spectrum of LLM applications, from development to deployment, and comes with a wide range of RAG building blocks. It can consume many APIs and private sources, so it's a good fit for financial services and technology companies. LangChain also offers a free plan and several paid plans for different business needs.

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SciPhi

Another good option is SciPhi, an information retrieval system that makes it easier to build, deploy and scale RAG systems. It has flexible document ingestion, powerful document management and dynamic scaling. SciPhi also has flexible provider connections and the ability to deploy state-of-the-art methods like HyDE and RAG-Fusion. It has multiple pricing tiers, including a free plan, so it's good for small projects and large-scale enterprise deployments.

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Abacus.AI

For a platform that's geared for building and running AI agents and systems at large scale, Abacus.AI is a good option. It has a range of products and features, including ChatLLM for RAG systems and AI Agents for automating complex workflows. Abacus.AI has predictive and analytical capabilities like forecasting and anomaly detection, and it has tools for model monitoring and explainable ML. The platform is designed to improve customer service and optimize business operations.

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ThirdAI

Last, ThirdAI is a user-friendly platform that makes large language models and other AI technology available without requiring special hardware. It includes features like document intelligence for extracting specific answers and generative AI for summarizing long documents. ThirdAI is designed to integrate with existing workflows and has tiered pricing plans for different business needs.

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