Sample code that uses data from FAO stats to build a RAG over LLM
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Updated
Apr 26, 2024 - Python
Sample code that uses data from FAO stats to build a RAG over LLM
In this solution accelerator, we demonstrate how generative AI, retrieval augmented generation (RAG) and multi stage reasoning can be used to better navigate through the complexities of regulatory filings, bringing more transparency for companies to disclose their societal and environmental impacts.
A discord bot which can call LLMs using either Hugging Face or vLLM on Windows platform. Combined with function calling.
Search for, compare, and list Forex Data chat (coming soon)
Various OpenAI projects and experiments implemented in Python. Utilizes all OpenAI APIs.
Evaluate hosted OpenAI GPT / Google PaLM2/Gemini or local Ollama models against a task
LLM agents is a python package that contains a small collection of autonomous agents.
Digital Artificial Intelligence Agent
Single eyed robot capable of conversing, tracking, home automating and video streaming to its app. Powered by Raspberry Pi.
Evaluate open-source language models on Agent, formatted output, command following, long text, multilingual, coding, and custom task capabilities. 开源语言模型在Agent,格式化输出,指令追随,长文本,多语言,代码,自定义任务的能力基准测试。
This project implements a travel chatbot powered by the RAG (Retrieve and Generate) chain, providing real-time information retrieval using various tools and the ability to fetch weather reports.
Use a RAG Langchain agent that connects to your supermarket's inventory database and get information about product stocks and locations.
GPT Flow: Simplifying tasks with human-like AI, inspired by autogpt.
🚀✨ DRIVE, the tool for creating and managing autonomous LLM agents; implemented using Apache Kafka, Docker, and LangChain.
AutoTask: a novel LLM framework to execute user commands by exploring and learning from mobile GUI.
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