
bao
Chat Bot with LLM and Fact Reference. RAG(Retrieval Augmented Generation) and LangChain backed
Stars: 123

BaoGPT is an AI project designed to facilitate asking questions about YouTube videos. It features a web UI based on Gradio and Discord integration. The tool utilizes a pipeline that routes input questions to either a greeting-like branch or a query & answer branch. The query analysis is performed by the LLM, which extracts attributes as filters and optimizes and rewrites questions for better vector retrieval in the vector DB. The tool then retrieves top-k candidates for grading and outputs final relative documents after grading. Lastly, the LLM performs summarization based on the reranking output, providing answers and attaching sources to the user.
README:
BaoGPT is an AI project that allows you to ask questions about youtube videos.
In the case, the target youtube video is Let's build the GPT Tokenizer from Andrej Karpathy.
- In the pipeline, a input question will be routed to the proper branch, greeting-like or query & answer(QA).
- When comes to QA, the LLM will do query analysis: extracted attributes as filters and the question will be optimised and rewriten for better vector retrieving in the vector DB.
- The filter conditions and optimised question will be passed to the retriever chain and get some top-k candidates for grading.
- The grader chain will take the question and documents as the grader input and output the final relative documents
- The LLM will do the summarisation based on the reraking output and provide the answer and attach the sources to the user.
Before running below cmd, make sure you have figured out the settings in settings.yaml based on your real scenarios.
# validated on python 3.11.4
# create vitual env
python3 -m venv .venv
source venv/bin/activate
pip install -Urq requirements.txt
# Note that below steps take Youtube: https://www.youtube.com/watch?v=zduSFxRajkE as example.
python -m bao.components.crawler.youtube_transcript.crawl -v "https://www.youtube.com/watch?v=zduSFxRajkE"
python -m bao.components.injest.injest --injest
python -m bao
For Tasks:
Click tags to check more tools for each tasksFor Jobs:
Alternative AI tools for bao
Similar Open Source Tools

bao
BaoGPT is an AI project designed to facilitate asking questions about YouTube videos. It features a web UI based on Gradio and Discord integration. The tool utilizes a pipeline that routes input questions to either a greeting-like branch or a query & answer branch. The query analysis is performed by the LLM, which extracts attributes as filters and optimizes and rewrites questions for better vector retrieval in the vector DB. The tool then retrieves top-k candidates for grading and outputs final relative documents after grading. Lastly, the LLM performs summarization based on the reranking output, providing answers and attaching sources to the user.

story-flicks
This project enables users to create story videos by inputting a story theme, utilizing a large language model to generate AI-generated images, story content, audio, and subtitles. The backend is built with Python and FastAPI, while the frontend utilizes React, Ant Design, and Vite.

gemma
Gemma is a family of open-weights Large Language Model (LLM) by Google DeepMind, based on Gemini research and technology. This repository contains an inference implementation and examples, based on the Flax and JAX frameworks. Gemma can run on CPU, GPU, and TPU, with model checkpoints available for download. It provides tutorials, reference implementations, and Colab notebooks for tasks like sampling and fine-tuning. Users can contribute to Gemma through bug reports and pull requests. The code is licensed under the Apache License, Version 2.0.

slide-deck-ai
SlideDeck AI is a tool that leverages Generative Artificial Intelligence to co-create slide decks on any topic. Users can describe their topic and let SlideDeck AI generate a PowerPoint slide deck, streamlining the presentation creation process. The tool offers an iterative workflow with a conversational interface for creating and improving presentations. It uses Mistral Nemo Instruct to generate initial slide content, searches and downloads images based on keywords, and allows users to refine content through additional instructions. SlideDeck AI provides pre-defined presentation templates and a history of instructions for users to enhance their presentations.

ScreenAgent
ScreenAgent is a project focused on creating an environment for Visual Language Model agents (VLM Agent) to interact with real computer screens. The project includes designing an automatic control process for agents to interact with the environment and complete multi-step tasks. It also involves building the ScreenAgent dataset, which collects screenshots and action sequences for various daily computer tasks. The project provides a controller client code, configuration files, and model training code to enable users to control a desktop with a large model.

generative-ai-sagemaker-cdk-demo
This repository showcases how to deploy generative AI models from Amazon SageMaker JumpStart using the AWS CDK. Generative AI is a type of AI that can create new content and ideas, such as conversations, stories, images, videos, and music. The repository provides a detailed guide on deploying image and text generative AI models, utilizing pre-trained models from SageMaker JumpStart. The web application is built on Streamlit and hosted on Amazon ECS with Fargate. It interacts with the SageMaker model endpoints through Lambda functions and Amazon API Gateway. The repository also includes instructions on setting up the AWS CDK application, deploying the stacks, using the models, and viewing the deployed resources on the AWS Management Console.

easy-web-summarizer
A Python script leveraging advanced language models to summarize webpages and youtube videos directly from URLs. It integrates with LangChain and ChatOllama for state-of-the-art summarization, providing detailed summaries for quick understanding of web-based documents. The tool offers a command-line interface for easy use and integration into workflows, with plans to add support for translating to different languages and streaming text output on gradio. It can also be used via a web UI using the gradio app. The script is dockerized for easy deployment and is open for contributions to enhance functionality and capabilities.

aisuite
Aisuite is a simple, unified interface to multiple Generative AI providers. It allows developers to easily interact with various Language Model (LLM) providers like OpenAI, Anthropic, Azure, Google, AWS, and more through a standardized interface. The library focuses on chat completions and provides a thin wrapper around python client libraries, enabling creators to test responses from different LLM providers without changing their code. Aisuite maximizes stability by using HTTP endpoints or SDKs for making calls to the providers. Users can install the base package or specific provider packages, set up API keys, and utilize the library to generate chat completion responses from different models.

GhostOS
GhostOS is an AI Agent framework designed to replace JSON Schema with a Turing-complete code interaction interface (Moss Protocol). It aims to create intelligent entities capable of continuous learning and growth through code generation and project management. The framework supports various capabilities such as turning Python files into web agents, real-time voice conversation, body movements control, and emotion expression. GhostOS is still in early experimental development and focuses on out-of-the-box capabilities for AI agents.

BentoDiffusion
BentoDiffusion is a BentoML example project that demonstrates how to serve and deploy diffusion models in the Stable Diffusion (SD) family. These models are specialized in generating and manipulating images based on text prompts. The project provides a guide on using SDXL Turbo as an example, along with instructions on prerequisites, installing dependencies, running the BentoML service, and deploying to BentoCloud. Users can interact with the deployed service using Swagger UI or other methods. Additionally, the project offers the option to choose from various diffusion models available in the repository for deployment.

ersilia
The Ersilia Model Hub is a unified platform of pre-trained AI/ML models dedicated to infectious and neglected disease research. It offers an open-source, low-code solution that provides seamless access to AI/ML models for drug discovery. Models housed in the hub come from two sources: published models from literature (with due third-party acknowledgment) and custom models developed by the Ersilia team or contributors.

CoLLM
CoLLM is a novel method that integrates collaborative information into Large Language Models (LLMs) for recommendation. It converts recommendation data into language prompts, encodes them with both textual and collaborative information, and uses a two-step tuning method to train the model. The method incorporates user/item ID fields in prompts and employs a conventional collaborative model to generate user/item representations. CoLLM is built upon MiniGPT-4 and utilizes pretrained Vicuna weights for training.

LeanAide
LeanAide is a work in progress AI tool designed to assist with development using the Lean Theorem Prover. It currently offers a tool that translates natural language statements to Lean types, including theorem statements. The tool is based on GPT 3.5-turbo/GPT 4 and requires an OpenAI key for usage. Users can include LeanAide as a dependency in their projects to access the translation functionality.

FigStep
FigStep is a black-box jailbreaking algorithm against large vision-language models (VLMs). It feeds harmful instructions through the image channel and uses benign text prompts to induce VLMs to output contents that violate common AI safety policies. The tool highlights the vulnerability of VLMs to jailbreaking attacks, emphasizing the need for safety alignments between visual and textual modalities.

arch
Arch is an intelligent Layer 7 gateway designed to protect, observe, and personalize LLM applications with APIs. It handles tasks like detecting and rejecting jailbreak attempts, calling backend APIs, disaster recovery, and observability. Built on Envoy Proxy, it offers features like function calling, prompt guardrails, traffic management, and standards-based observability. Arch aims to improve the speed, security, and personalization of generative AI applications.

serverless-pdf-chat
The serverless-pdf-chat repository contains a sample application that allows users to ask natural language questions of any PDF document they upload. It leverages serverless services like Amazon Bedrock, AWS Lambda, and Amazon DynamoDB to provide text generation and analysis capabilities. The application architecture involves uploading a PDF document to an S3 bucket, extracting metadata, converting text to vectors, and using a LangChain to search for information related to user prompts. The application is not intended for production use and serves as a demonstration and educational tool.
For similar tasks

serverless-chat-langchainjs
This sample shows how to build a serverless chat experience with Retrieval-Augmented Generation using LangChain.js and Azure. The application is hosted on Azure Static Web Apps and Azure Functions, with Azure Cosmos DB for MongoDB vCore as the vector database. You can use it as a starting point for building more complex AI applications.

ChatGPT-Telegram-Bot
ChatGPT Telegram Bot is a Telegram bot that provides a smooth AI experience. It supports both Azure OpenAI and native OpenAI, and offers real-time (streaming) response to AI, with a faster and smoother experience. The bot also has 15 preset bot identities that can be quickly switched, and supports custom bot identities to meet personalized needs. Additionally, it supports clearing the contents of the chat with a single click, and restarting the conversation at any time. The bot also supports native Telegram bot button support, making it easy and intuitive to implement required functions. User level division is also supported, with different levels enjoying different single session token numbers, context numbers, and session frequencies. The bot supports English and Chinese on UI, and is containerized for easy deployment.

supersonic
SuperSonic is a next-generation BI platform that integrates Chat BI (powered by LLM) and Headless BI (powered by semantic layer) paradigms. This integration ensures that Chat BI has access to the same curated and governed semantic data models as traditional BI. Furthermore, the implementation of both paradigms benefits from the integration: * Chat BI's Text2SQL gets augmented with context-retrieval from semantic models. * Headless BI's query interface gets extended with natural language API. SuperSonic provides a Chat BI interface that empowers users to query data using natural language and visualize the results with suitable charts. To enable such experience, the only thing necessary is to build logical semantic models (definition of metric/dimension/tag, along with their meaning and relationships) through a Headless BI interface. Meanwhile, SuperSonic is designed to be extensible and composable, allowing custom implementations to be added and configured with Java SPI. The integration of Chat BI and Headless BI has the potential to enhance the Text2SQL generation in two dimensions: 1. Incorporate data semantics (such as business terms, column values, etc.) into the prompt, enabling LLM to better understand the semantics and reduce hallucination. 2. Offload the generation of advanced SQL syntax (such as join, formula, etc.) from LLM to the semantic layer to reduce complexity. With these ideas in mind, we develop SuperSonic as a practical reference implementation and use it to power our real-world products. Additionally, to facilitate further development we decide to open source SuperSonic as an extensible framework.

chat-ollama
ChatOllama is an open-source chatbot based on LLMs (Large Language Models). It supports a wide range of language models, including Ollama served models, OpenAI, Azure OpenAI, and Anthropic. ChatOllama supports multiple types of chat, including free chat with LLMs and chat with LLMs based on a knowledge base. Key features of ChatOllama include Ollama models management, knowledge bases management, chat, and commercial LLMs API keys management.

ChatIDE
ChatIDE is an AI assistant that integrates with your IDE, allowing you to converse with OpenAI's ChatGPT or Anthropic's Claude within your development environment. It provides a seamless way to access AI-powered assistance while coding, enabling you to get real-time help, generate code snippets, debug errors, and brainstorm ideas without leaving your IDE.

azure-search-openai-javascript
This sample demonstrates a few approaches for creating ChatGPT-like experiences over your own data using the Retrieval Augmented Generation pattern. It uses Azure OpenAI Service to access the ChatGPT model (gpt-35-turbo), and Azure AI Search for data indexing and retrieval.

xiaogpt
xiaogpt is a tool that allows you to play ChatGPT and other LLMs with Xiaomi AI Speaker. It supports ChatGPT, New Bing, ChatGLM, Gemini, Doubao, and Tongyi Qianwen. You can use it to ask questions, get answers, and have conversations with AI assistants. xiaogpt is easy to use and can be set up in a few minutes. It is a great way to experience the power of AI and have fun with your Xiaomi AI Speaker.

googlegpt
GoogleGPT is a browser extension that brings the power of ChatGPT to Google Search. With GoogleGPT, you can ask ChatGPT questions and get answers directly in your search results. You can also use GoogleGPT to generate text, translate languages, and more. GoogleGPT is compatible with all major browsers, including Chrome, Firefox, Edge, and Safari.
For similar jobs

sweep
Sweep is an AI junior developer that turns bugs and feature requests into code changes. It automatically handles developer experience improvements like adding type hints and improving test coverage.

teams-ai
The Teams AI Library is a software development kit (SDK) that helps developers create bots that can interact with Teams and Microsoft 365 applications. It is built on top of the Bot Framework SDK and simplifies the process of developing bots that interact with Teams' artificial intelligence capabilities. The SDK is available for JavaScript/TypeScript, .NET, and Python.

ai-guide
This guide is dedicated to Large Language Models (LLMs) that you can run on your home computer. It assumes your PC is a lower-end, non-gaming setup.

classifai
Supercharge WordPress Content Workflows and Engagement with Artificial Intelligence. Tap into leading cloud-based services like OpenAI, Microsoft Azure AI, Google Gemini and IBM Watson to augment your WordPress-powered websites. Publish content faster while improving SEO performance and increasing audience engagement. ClassifAI integrates Artificial Intelligence and Machine Learning technologies to lighten your workload and eliminate tedious tasks, giving you more time to create original content that matters.

chatbot-ui
Chatbot UI is an open-source AI chat app that allows users to create and deploy their own AI chatbots. It is easy to use and can be customized to fit any need. Chatbot UI is perfect for businesses, developers, and anyone who wants to create a chatbot.

BricksLLM
BricksLLM is a cloud native AI gateway written in Go. Currently, it provides native support for OpenAI, Anthropic, Azure OpenAI and vLLM. BricksLLM aims to provide enterprise level infrastructure that can power any LLM production use cases. Here are some use cases for BricksLLM: * Set LLM usage limits for users on different pricing tiers * Track LLM usage on a per user and per organization basis * Block or redact requests containing PIIs * Improve LLM reliability with failovers, retries and caching * Distribute API keys with rate limits and cost limits for internal development/production use cases * Distribute API keys with rate limits and cost limits for students

uAgents
uAgents is a Python library developed by Fetch.ai that allows for the creation of autonomous AI agents. These agents can perform various tasks on a schedule or take action on various events. uAgents are easy to create and manage, and they are connected to a fast-growing network of other uAgents. They are also secure, with cryptographically secured messages and wallets.

griptape
Griptape is a modular Python framework for building AI-powered applications that securely connect to your enterprise data and APIs. It offers developers the ability to maintain control and flexibility at every step. Griptape's core components include Structures (Agents, Pipelines, and Workflows), Tasks, Tools, Memory (Conversation Memory, Task Memory, and Meta Memory), Drivers (Prompt and Embedding Drivers, Vector Store Drivers, Image Generation Drivers, Image Query Drivers, SQL Drivers, Web Scraper Drivers, and Conversation Memory Drivers), Engines (Query Engines, Extraction Engines, Summary Engines, Image Generation Engines, and Image Query Engines), and additional components (Rulesets, Loaders, Artifacts, Chunkers, and Tokenizers). Griptape enables developers to create AI-powered applications with ease and efficiency.