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Co-authored-by: jacoblee93 <jacoblee93@gmail.com> Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>
24 lines
1.4 KiB
Plaintext
24 lines
1.4 KiB
Plaintext
# Autonomous (long-running) agents
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Autonomous Agents are agents that designed to be more long running.
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You give them one or multiple long term goals, and they independently execute towards those goals.
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The applications combine tool usage and long term memory.
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At the moment, Autonomous Agents are fairly experimental and based off of other open-source projects.
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By implementing these open source projects in LangChain primitives we can get the benefits of LangChain -
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easy switching and experimenting with multiple LLMs, usage of different vectorstores as memory,
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usage of LangChain's collection of tools.
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## Baby AGI ([Original Repo](https://github.com/yoheinakajima/babyagi))
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- [Baby AGI](./baby_agi.html): a notebook implementing BabyAGI as LLM Chains
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- [Baby AGI with Tools](./baby_agi_with_agent.html): building off the above notebook, this example substitutes in an agent with tools as the execution tools, allowing it to actually take actions.
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## AutoGPT ([Original Repo](https://github.com/Significant-Gravitas/Auto-GPT))
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- [AutoGPT](./autogpt.html): a notebook implementing AutoGPT in LangChain primitives
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- [WebSearch Research Assistant](./marathon_times.html): a notebook showing how to use AutoGPT plus specific tools to act as research assistant that can use the web.
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## MetaPrompt ([Original Repo](https://github.com/ngoodman/metaprompt))
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- [Meta-Prompt](./meta_prompt.html): a notebook implementing Meta-Prompt in LangChain primitives
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