LangSmith: How to Improve LLM Apps in Production Our friends at @AIMakerspace are doing a deep dive on all things LangSmith With tracing, monitoring, testing, annotating, and collaborating – LangSmith a the full collection of tools
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Empowering LLMs with External Tools and Functions
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Building An LLM-Powered Analyst This great article deep dives on how to empower LLMs with external tools using OpenAI functions At a **19 minute** minute, it's pretty comprehensive It examines two use cases: extraction to get structured output and routing to use external
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Proposition-Based Retrieval: New Indexing Method for AI
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Proposition-Based Retrieval This new paper by @tomchen0 introduces a new retrieval method by changing what is indexed in the first place This can easily use our multi-vector retriever, and we've added a template to get started with it easily! How does it work?
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RAG Strategies for Semi-Structured Data in Documents
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overview: Strategies for RAG on semi-structured data We've seen great interest in RAG apps on docs w/ a mixture of tables and text (financial docs, whitepapers, technical manuals). But, this brings up a few tricky questions:
1/ Can I just stuff semi-structured docs -
Docugami KG-RAG Template Outperforms OpenAI Assistant API
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Docugami KG-RAG Template We worked with @docugami to publish a RAG template that uses their technology to create XML knowledge graphs They also benchmarked the RAG performance with LangSmith and found it outperformed OpenAI Assistant API Read more: https://
docugami.com/blog/kg-rag-la
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Gemini Pro Vision vs GPT-4V: Multimodal AI Comparison
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Gemini is natively multimodal, but how does it stack up against GPT-4V? We put gemini-pro-vision head-to-head with the reigning champ to see how well it could answer questions based on a multimodal slide deck. The results? Gemini seems to be a formidable model, matching
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LangChain VertexAI Integration Now Supports Latest Gemini Models
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Want to use Gemini models via GCP? The LangChain x VertexAI integration is now updated to support the recent models! `pip install langchain-community==0.0.3` VertexAI works natively with GCP – great for enterprise use cases!
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LangChain Benchmark for Semi-Structured RAG Systems
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Benchmarking semi-structured RAG We've seen many question about RAG on documents that contain a mixture of text and tables. To test various semi-structured RAG approaches, we built a LangChain public benchmark on a set of whitepapers and financial reports that contain
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LangChain Launches Gemini API Integration Package
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LangChain Gemini Gemini API access is out! Access it through LangChain with our first standalone integration package: `pip install langchain-google-genai` We're also launching an integration guide showing how to: Stream results
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LangChain Splits Into Core and Community Packages
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Towards LangChain 0.1: LangChain-Core and LangChain-Community TL;DR: We've split the old langchain package into three separate packages to improve developer experience `langchain-core` contains simple, core abstractions that have emerged as a standard, as well as