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LangChain Expression Language, or LCEL, is a declarative way to easily compose chains together. LCEL was designed from day 1 to support putting prototypes in production, with no code changes, from the simplest “prompt + LLM” chain to the most complex chains (we’ve seen folks successfully run LCEL chains with 100s of steps in production). To highlight a few of the reasons you might want to use LCEL
Use caseSuppose you have a set of documents (PDFs, Notion pages, customer questions, etc.) and you want to summarize the content. LLMs are a great tool for this given their proficiency in understanding and synthesizing text. In this walkthrough we'll go over how to perform document summarization using LLMs. OverviewA central question for building a summarizer is how to pass your documents into t
All functionality related to Google Cloud Platform and other Google products. LLMsGoogle Generative AIAccess GoogleAI Gemini models such as gemini-pro and gemini-pro-vision through the GoogleGenerativeAI class. Install python package.
LangChain is a framework for developing applications powered by large language models (LLMs). LangChain simplifies every stage of the LLM application lifecycle: Development: Build your applications using LangChain's open-source building blocks and components. Hit the ground running using third-party integrations and Templates.Productionization: Use LangSmith to inspect, monitor and evaluate your c
LangChain integrates with many providers. Partner PackagesThese providers have standalone langchain-{provider} packages for improved versioning, dependency management and testing. AI21AirbyteAnthropicAstra DBCohereElasticsearchExa SearchFireworksGoogleGroqIBMMistralAIMongoDBNomicNvidiaOpenAIPineconeRobocorpTogether AIVoyage AIFeatured Community ProvidersAWSHugging FaceMicrosoftAll ProvidersClic
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