Using Tools All tools in LangChain are also easily usable in this syntax Makes it easy to pipe output from an LLM call into a tool
@hwchase17
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Routing Between Downstream Chains for AI Systems
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Router You can route between various downstream chains depending on the output of a previous one
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Retrieval QA Chain: New Syntax for Easy Retrievers
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Retrieval QA One of our more popular chains, you can use retrievers easily with this new syntax
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Function Call Parsing for JSON Response Output
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Function Call Parsing Of course, after calling a function you usually want to parse it into a workable format – either the whole JSON response or a specific key We've got output parsers for both of those!
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OpenAI Function Calling: Structuring Model Output with Bind
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Function Calling @OpenAI Functions are extremely popular for structuring output – you can easily attach them to a model call using `.bind`
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Prompt Templates and LLM Integration Basics
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Prompt Template + LLM Starting with the most basic, a simple combination of a prompt template + a call to an LLM `prompt | llm`
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Transform Chat Model Outputs with Prompt Templates and Parsers
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Prompt Template + LLM + Output Parser Some types of models (chat models) return chat messages It's often desirable to transform that into a string so you can easily use it in downstream tasks – for that we can add in a simple output parser
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LangChain Expression Language Rewrite Popular Chains Examples
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A on examples of using our new LangChain Expression Language to rewrite some of our most popular chains Benefits: it's very clear what's going on under the hood, and (most importantly) how to modify them
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LangChain ConversationalRetrievalChain Documentation and Implementation
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space moves fast 🙂 not sure why its not showing up – any ideas @CalebPeffer ? here's reference docs: https://
api.python.langchain.com/en/latest/chai
ns/langchain.chains.conversational_retrieval.base.ConversationalRetrievalChain.html
… includes list of examples where its used at the end! -
LangChain Expression Language: Resources and Tools Guide
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Blog: https://
blog.langchain.dev/langchain-expr
ession-language/
… Webinar: https://
crowdcast.io/c/ckw1tydg29er Cookbook of examples: https://
python.langchain.com/docs/guides/ex
pression_language/cookbook#code-writing
… Teacher bot: https://
langchain-teacher-lcel.streamlit.app Let us know if any questions!