Don't let all the OpenAI `functions` distract you from the fact we've got an amazing webinar starting in an hour focused on open source models with @nomic_ai (GPT4ALL) and @MosaicML Can we finetune those models for tool use? Let's find out!
@hwchase17
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LangChain SQL chains versus agents: comparative analysis
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we have both in langchain, often for the same purpose! eg SQL chain vs SQL agent pros and cons to each
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Chains vs Agents: Deterministic vs Nondeterministic AI Systems
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assuming im understanding you correctly, this is me is the difference between "chains" and "agents" (at least as far as how I think about them) chains = deterministic sequence of steps = code shell
agents = nondeterministic sequence of steps = llm shell -
New AI Functionality Unlocked: Day Zero Launch
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you can tell from the lack of proper grammar that its been a long day Big s/o to @veryboldbagel and @nfcampos but its only day zero! Looking forward to seeing what new functionality this unlocks
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OpenAI Functions Release: LangChain Support for Chat Models
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Emergency OpenAI Functions Release `pip install langchain==0.0.199` Support for functions in chat model wrapper Convert @langchain tools to functions Docs: https://
github.com/hwchase17/lang
chain/blob/master/docs/modules/agents/tools/tools_as_openai_functions.ipynb
… Next up… I think its time for a new type of agent -
Open Source LLMs Webinar with Nomic AI and MosaicML
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Open source LLMs have been on lately We're excited to do a webinar focused on them with two of the companies leading the charge: @nomic_ai (creators of GPT4all) @MosaicML (creators of MPT-7B and others) This Wednesday, 9-10am PST
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Semantic Search Edge Cases and LangChain Mitigation Methods
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I participated in a fun webinar with @zilliz_universe on Thursday where I talked about retrieval We did a deep dive on edge cases that arise with semantic search, and methods in LangChain to mitigate those Here are the slides: https://
docs.google.com/presentation/d
/1NHWOLnaA6qhwus3JbluBk7aN1HeKrobZuaRNEdEZSkU/edit?usp=sharing
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Building Quivr: AI-Powered Document Question Answering System
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"Have fun and build" – @_StanGirard An awesome deep-dive on what it takes to build @quivr_brain – a service that can answer questions about any documents you upload Some fun viewing for a Friday afternoon 🙂
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LangChain Release Overview: Key Components for AI
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releases like these are always fun cause you get a full overview of all the langchain components… vectordb, llms, embeddings, document loaders, tools, databases
