Do Anything with Local Agents with AnythingLLM

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AI Summary

Summary of Video Transcript: Setting Up and Using Anything LLM

• Introduction to Anything LLM:
  • Anything LLM is an open-source software for interacting with different LLMs (Large Language Models) from various providers.
  • It supports OpenAI LLMs using both Olama and LM Studio.
  • Optimized for RTX GPUs from Nvidia.
  • Allows running powerful local agents privately on a local machine.
• Setting Up Anything LLM:
  • Download the Anything LLM desktop app.
  • Create a new workspace within the app.
  • Access chart settings to choose from different API providers (e.g., Olama, LM Studio, local AI, or provide a Hugging Face ID).
• Using AMA Models with Anything LLM:
  • Select AMA as the model provider.
  • Start a model in the terminal (e.g., Lama 38 billion).
  • Update the workspace and interact with the model.
• Using LM Studio with Anything LLM:
  • Load a model in LM Studio (e.g., Mistral small instruct model in 8bit precision).
  • Start the server for LM Studio to listen for traffic.
  • Create a new workspace and select LM Studio as the LLM provider.
  • Update the workspace and interact with the model.
• Using Custom Built Agents:
  • Go to agent configuration settings.
  • Select the LLM provider for your agent (e.g., LM Studio running the Mistral small model).
  • Configure agent skills, enabling or disabling predefined skills.
  • Custom skills can be enabled, such as archive search, web search, and database interaction.
• Using Agent Skills:
  • Use the @agent command to invoke an agent skill.
  • Examples include web search, web scraping, summarizing content, and generating charts.
• Community Hub Tools:
  • Explore tools on the Community Hub, such as open-source apps and readers.
  • Import trusted skills from the Community Hub into Anything LLM.
• Developer Contributions:
  • Developers can contribute agentic skills to the Anything LLM Community Hub.
• Conclusion:
  • Anything LLM is a versatile project that allows for more than just chatting with an LLM.
  • It is open-source and recommended for those with RTX GPUs for local model running.

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