Lots of applications use the RAG style framework with @langchain and @pinecone But how can you trouble shoot those applications? Enter @arizeai Excited to be doing a LangChain x Pinecone x Arize webinar on all this (feat @RLanceMartin
) Sign up https://
pinecone-io.zoom.us/webinar/regist
er/WN_xAv6ql91SxW01iN9Sy2yLw#/registration
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AGENTS
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RAG Framework Troubleshooting with LangChain Pinecone Arize
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Rebuilding Chatbot Course with Langchain Conversational Agents
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I’m rebuilding my chatbot course and I’m trying to figure out what to do with the Langchain module. I think in my ideal world it’s Langchain conversational agent that uses Function Calling but afaik that’s not built yet
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LangChain Multi-Action Agent Selection Framework Exposure
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Example notebook: https://
python.langchain.com/docs/modules/a
gents/agent_types/openai_multi_functions_agent
… We'll work on exposing this "multi-action" selection more natively as well (so you can use outside of agents) -
Parallel API Calls in AI Agents Multiple Independent Requests
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Some example use cases where this provides value: "what is the weather in sf and la" -> can generate two independent calls to lookup weather in sf and la "who has revenue in Q1, tesla or apple" -> can generate two independent calls to look up revenue
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Multi-Action Agent with OpenAI Functions for LLMs
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Multi-Action Agent w/ @OpenAI Functions OpenAI functions allows the LLM to select a single tool to use… but often times it can be more efficient to have the LLM select MULTIPLE tools to use (if tasks can be done in parallel) Enter… the `openai-multi-functions` agent
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RoboCat: Self-Improving Foundation Agent for Robotic Manipulation
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RoboCat: A Self-Improving Foundation Agent for Robotic Manipulation paper page: https://
huggingface.co/papers/2306.11
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… The ability to leverage heterogeneous robotic experience from different robots and tasks to quickly master novel skills and embodiments has the potential to transform robot -
HomeRobot: Open-Vocabulary Mobile Manipulation for Object Picking
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HomeRobot: Open-Vocabulary Mobile Manipulation
— AK (@_akhaliq) 21 juin 2023
paper page: https://t.co/Bg5DY8snQ8
Open-Vocabulary Mobile Manipulation (OVMM) is the problem of picking any object in any unseen environment, and placing it in a commanded location. This is a foundational challenge for robots to… pic.twitter.com/J4atienxw2HomeRobot: Open-Vocabulary Mobile Manipulation paper page: https://
huggingface.co/papers/2306.11
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… Open-Vocabulary Mobile Manipulation (OVMM) is the problem of picking any object in any unseen environment, and placing it in a commanded location. This is a foundational challenge for robots to -
RoboCat: DeepMind’s Self-Improving Robotic Agent
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RoboCat: A self-improving robotic agent – DeepMind
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Custom Return Schema in RetrievalQAChain Documentation
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Updated documentation to show how to easily define your own custom return schema and use in the RetrievalQAChain Docs: https://
python.langchain.com/docs/modules/c
hains/additional/openai_functions_retrieval_qa#using-your-own-output-schema
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Document Comparison with LangChain Agents and Retrieval
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Document Comparison There are lots of ways to ask questions about a single document, but what about when you want to compare multiple? @pelaseyed added a great cookbook showing how to do that. Uses an agent and multiple retrieval qa chains! Docs: https://
python.langchain.com/docs/modules/a
gents/toolkits/document_comparison_toolkit
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