GitHub - robocorp/llmstatemachine: A Python library for building GPT-powered agents with state machine logic and chat history memory.
github.com
GitHub - robocorp/llmstatemachine: A Python library for building GPT-powered agents with state machine logic and chat history memory.
An agent can be thought of as a logical wrapper around an LLM, allowing us to add several features to our AI systems, primarily:
- Tool usage, such as calling APIs for info, executing code,
- Internal thoughts over multiple generation steps
- Ability to use various tools and reasoning steps to answer more complex queries.
- Parallel agents can go and complete
James Briggs • LLMs Are Not All You Need | Pinecone
Introduction
VT.ai is a multi-modal AI Chatbot Assistant, offering a chat interface to interact with Large Language Models (LLMs) from various providers. Both via remote API or running locally with Ollama.
The application supports multi-modal conversations, seamlessly integrating text, images, and vision processing with LLMs.
[Beta] Multi-modal AI As... See more
VT.ai is a multi-modal AI Chatbot Assistant, offering a chat interface to interact with Large Language Models (LLMs) from various providers. Both via remote API or running locally with Ollama.
The application supports multi-modal conversations, seamlessly integrating text, images, and vision processing with LLMs.
[Beta] Multi-modal AI As... See more
GitHub - vinhnx/VT.ai: VT.ai - Multi-modal AI Chatbot Assistant
LangChainHub is a central repository for sharing artifacts like prompts, chains, and agents used in LangChain. Inspired by the Hugging Face Hub, it aims to be a one-stop resource for discovering high-quality building blocks to compose complex LLM apps.
Ben Auffarth • Generative AI with LangChain: Build large language model (LLM) apps with Python, ChatGPT, and other LLMs
🤖 Create perpetual chatbots with self-editing memory!
🗃️ Chat with your data - talk to your SQL database or your local files!
📄 You can also talk to docs - for example ask about LlamaIndex!
🗃️ Chat with your data - talk to your SQL database or your local files!
📄 You can also talk to docs - for example ask about LlamaIndex!