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Top 23 gpt-4 Open-Source Projects
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AutoGPT
AutoGPT is the vision of accessible AI for everyone, to use and to build on. Our mission is to provide the tools, so that you can focus on what matters.
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InfluxDB
Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
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gpt_academic
为GPT/GLM等LLM大语言模型提供实用化交互接口，特别优化论文阅读/润色/写作体验，模块化设计，支持自定义快捷按钮&函数插件，支持Python和C++等项目剖析&自译解功能，PDF/LaTex论文翻译&总结功能，支持并行问询多种LLM模型，支持chatglm3等本地模型。接入通义千问, deepseekcoder, 讯飞星火, 文心一言, llama2, rwkv, claude2, moss等。
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Lobe Chat
LobeChat is a open-source, extensible (Function Calling), high-performance chatbot framework.It supports one-click free deployment of your private ChatGPT/LLM web application.
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autogen
A programming framework for agentic AI. Discord: https://aka.ms/autogen-dc. Roadmap: https://aka.ms/autogen-roadmap
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SaaSHub
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chatgpt-on-wechat
基于大模型搭建的聊天机器人，同时支持 企业微信、微信 公众号、飞书、钉钉 等接入，可选择GPT3.5/GPT4.0/Claude/文心一言/讯飞星火/通义千问/Gemini/GLM-4/Claude/Kimi/LinkAI，能处理文本、语音和图片，访问操作系统和互联网，支持基于自有知识库进行定制企业智能客服。
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Hello-Python
Curso para aprender el lenguaje de programación Python desde cero y para principiantes. 100 clases, 44 horas en vídeo, código, proyectos y grupo de chat. Fundamentos, frontend, backend, testing, IA...
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chatbox
Chatbox is a desktop client for ChatGPT, Claude and other LLMs, available on Windows, Mac, Linux
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LLaVA
[NeurIPS'23 Oral] Visual Instruction Tuning (LLaVA) built towards GPT-4V level capabilities and beyond.
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FastGPT
FastGPT is a knowledge-based platform built on the LLMs, offers a comprehensive suite of out-of-the-box capabilities such as data processing, RAG retrieval, and visual AI workflow orchestration, letting you easily develop and deploy complex question-answering systems without the need for extensive setup or configuration.
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DB-GPT
AI Native Data App Development framework with AWEL(Agentic Workflow Expression Language) and Agents
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shell_gpt
A command-line productivity tool powered by AI large language models like GPT-4, will help you accomplish your tasks faster and more efficiently.
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SaaSHub
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Project mention: gpt4-openai-api VS gpt4free - a user suggested alternative | libhunt.com/r/gpt4-openai-api | 2024-01-04I cant install
A pretrained LLM is a closed-book system: It can only access information that it was trained on. With domain fine-tuning, the system manifests additional material. An early prototype of this technique was shown in this OpenAi cookbook: For the target domain, text was embedded using an API, and then when using the LLM, embeddings were retrieved using semantic similarity search to formulate an answer. Although this approach evolved to retrieval-augmented generation, its still a technique to adapt a Gen2 (2020) or Gen3 (2022) LLM into a question-answering system.
I recently managed to manually install the AnkiBrain addon, utilizing my personal ChatGPT API key. I'd like to extend my appreciation for creating such a useful tool. However, I've noticed a significant difference in speed compared to a local GUI, similar to what's offered by GPT Academic.
Project mention: OpenInterpreter – Natural language interface to your computer | news.ycombinator.com | 2024-04-23
Project mention: The AI Revolution Is Crushing Thousands of Languages | news.ycombinator.com | 2024-04-25Get your OpenAI API key and then use it on one of the hundreds of open source frontends available, such as: https://github.com/lobehub/lobe-chat
Project mention: Pake – Turn any webpage into a desktop app with Rust | news.ycombinator.com | 2023-11-29
Project mention: Chatbox (latest versions) is not open source; AskHN: anything similar? | news.ycombinator.com | 2024-02-08
Project mention: Show HN: I Remade the Fake Google Gemini Demo, Except Using GPT-4 and It's Real | news.ycombinator.com | 2023-12-10Update: For anyone else facing the commercial use question on LLaVA - it is licensed under Apache 2.0. Can be used commercially with attribution: https://github.com/haotian-liu/LLaVA/blob/main/LICENSE
Interact your data and environment using the local GPT (https://github.com/csunny/DB-GPT)
Project mention: Launch HN: Nango (YC W23) – Open-Source Unified API | news.ycombinator.com | 2024-04-25Do you leverage https://gorilla.cs.berkeley.edu/ at all? If not, perhaps consider if it would solve some pain for you.
Link [Github]
Project mention: How do people create those sleek looking demos for startups? | news.ycombinator.com | 2024-05-01I built the demo video for https://plandex.ai myself using CleanShot X (https://cleanshot.com/), Adobe Premiere Pro, an effect I bought in Adobe's marketplace, some AppleScript automation, and music from SoundStripe (https://soundstripe.com/).
It was my first time using all these tools. It took me a couple days to make the video. Premier is a bit of a beast, but by just asking ChatGPT how to do everything, I was able to get up to speed with it pretty fast.
https://github.com/TheR1D/shell_gpt?tab=readme-ov-file#shell...
Unfortunately, you're using sashabaranov/go-openai, which has different api behavior than the official langchain python package [0].
I was hoping this would be a drop in replacement for langchain (so DS ppl can code in python and gophers can port it to production).
[0] - https://github.com/sashabaranov/go-openai#why-dont-we-get-th...
# TODO: Get your Groq AI API key from https://console.groq.com/ GROQ_API_KEY = "" # TODO: Get your E2B API key from https://e2b.dev/docs E2B_API_KEY = "" # Or use 8b version # MODEL_NAME = "llama3-8b-8192" MODEL_NAME = "llama3-70b-8192" SYSTEM_PROMPT = """you are a python data scientist. you are given tasks to complete and you run python code to solve them. - the python code runs in jupyter notebook. - every time you call `execute_python` tool, the python code is executed in a separate cell. it's okay to multiple calls to `execute_python`. - display visualizations using matplotlib or any other visualization library directly in the notebook. don't worry about saving the visualizations to a file. - you have access to the internet and can make api requests. - you also have access to the filesystem and can read/write files. - you can install any pip package (if it exists) if you need to but the usual packages for data analysis are already preinstalled. - you can run any python code you want, everything is running in a secure sandbox environment""" tools = [ { "type": "function", "function": { "name": "execute_python", "description": "Execute python code in a Jupyter notebook cell and returns any result, stdout, stderr, display_data, and error.", "parameters": { "type": "object", "properties": { "code": { "type": "string", "description": "The python code to execute in a single cell.", } }, "required": ["code"], }, }, } ]
NOTE:
The open source projects on this list are ordered by number of github stars.
The number of mentions indicates repo mentiontions in the last 12 Months or
since we started tracking (Dec 2020).
gpt-4 related posts
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How do people create those sleek looking demos for startups?
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GitHub Copilot Workspace: Welcome to the Copilot-native developer environment
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Question-Answer System Architectures using LLMs
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Large language models (e.g., ChatGPT) as research assistants
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OpenInterpreter – Natural language interface to your computer
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Improve Download Speeds with Concurrency
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Concluding OSD700
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A note from our sponsor - InfluxDB
www.influxdata.com | 2 May 2024
Index
What are some of the best open-source gpt-4 projects? This list will help you:
| Project | Stars | |
|---|---|---|
| 1 | AutoGPT | 161,405 |
| 2 | gpt4free | 57,411 |
| 3 | openai-cookbook | 55,954 |
| 4 | gpt_academic | 55,872 |
| 5 | open-interpreter | 48,604 |
| 6 | Lobe Chat | 29,259 |
| 7 | autogen | 25,255 |
| 8 | chatgpt-on-wechat | 24,945 |
| 9 | Pake | 22,876 |
| 10 | Hello-Python | 22,215 |
| 11 | chatbox | 18,573 |
| 12 | LLaVA | 16,333 |
| 13 | FastGPT | 12,961 |
| 14 | botpress | 11,954 |
| 15 | DB-GPT | 11,055 |
| 16 | gorilla | 10,026 |
| 17 | awesome-chatgpt-zh | 9,924 |
| 18 | BingGPT | 9,360 |
| 19 | plandex | 8,826 |
| 20 | shell_gpt | 8,303 |
| 21 | go-openai | 8,177 |
| 22 | BetterChatGPT | 7,490 |
| 23 | awesome-ai-agents | 6,596 |
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