chainlit
private-gpt
chainlit | private-gpt | |
---|---|---|
7 | 131 | |
5,535 | 52,027 | |
7.8% | 2.9% | |
9.7 | 9.2 | |
3 days ago | 5 days ago | |
TypeScript | Python | |
Apache License 2.0 | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
chainlit
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Chat with your Github Repo using llama_index and chainlit
chainlit is open source project that makes it very easy to build frontend interfaces like chatgpt and other features that are required for conversational ai app, so we can focus on the core part and don't need to worry about basic things, and it is dead simple to work with
- Show HN: I made an app to use local AI as daily driver
- Help with conversational_qa_chain - Streamlit Messages
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AI Chatbot powered by Amazon Bedrock 🚀🤖
I have created a sample chatbot application that uses Chainlit and LangChain to showcase Amazon Bedrock.
- Chainlit: Create ChatGPT-like UIs on top of Python code
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Personal movie recommendation agent with GPT4 + Neo4J
For the interface, I'm using chainlit, a new UI library for building LLM apps, with an integration with Langchain.
- Chainlit/chainlit: Build Python LLM apps in minutes ⚡️
private-gpt
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Ask HN: Has Anyone Trained a personal LLM using their personal notes?
PrivateGPT is a nice tool for this. It's not exactly what you're asking for, but it gets part of the way there.
https://github.com/zylon-ai/private-gpt
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PrivateGPT exploring the Documentation
Further details available at: https://docs.privategpt.dev/api-reference/api-reference/ingestion
- Show HN: I made an app to use local AI as daily driver
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privateGPT VS quivr - a user suggested alternative
2 projects | 12 Jan 2024
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Ask HN: How do I train a custom LLM/ChatGPT on my own documents in Dec 2023?
Run https://github.com/imartinez/privateGPT
Then
make ingest /path/to/folder/with/files
Then chat to the LLM.
Done.
Docs: https://docs.privategpt.dev/overview/welcome/quickstart
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Mozilla "MemoryCache" Local AI
PrivateGPT repository in case anyone's interested: https://github.com/imartinez/privateGPT . It doesn't seem to be linked from their official website.
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What Is Retrieval-Augmented Generation a.k.a. RAG
I’m preparing a small internal tool for my work to search documents and provide answers (with references), I’m thinking of using GPT4All [0], Danswer [1] and/or privateGPT [2].
The RAG technique is very close to what I have in mind, but I don’t want the LLM to “hallucinate” and generate answers on its own by synthesizing the source documents. As stated by many others, we’re living in interesting times.
[0] https://gpt4all.io/index.html
[1] https://www.danswer.ai/
[2] https://github.com/imartinez/privateGPT
- LM Studio – Discover, download, and run local LLMs
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Ask HN: Local LLM Recommendation?
https://www.reddit.com/r/LocalLLaMA/comments/14niv66/using_a...
https://github.com/imartinez/privateGPT
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Run ChatGPT-like LLMs on your laptop in 3 lines of code
I've been playing around with https://github.com/imartinez/privateGPT and https://github.com/simonw/llm and wanted to create a simple Python package that made it easier to run ChatGPT-like LLMs on your own machine, use them with non-public data, and integrate them into practical applications.
This resulted in Python package I call OnPrem.LLM.
In the documentation, there are examples for how to use it for information extraction, text generation, retrieval-augmented generation (i.e., chatting with documents on your computer), and text-to-code generation: https://amaiya.github.io/onprem/
Enjoy!
What are some alternatives?
langchain - 🦜🔗 Build context-aware reasoning applications
localGPT - Chat with your documents on your local device using GPT models. No data leaves your device and 100% private.
nitro - Create apps 10x quicker, without Javascript/HTML/CSS.
gpt4all - gpt4all: run open-source LLMs anywhere
web-llm - Bringing large-language models and chat to web browsers. Everything runs inside the browser with no server support.
h2ogpt - Private chat with local GPT with document, images, video, etc. 100% private, Apache 2.0. Supports oLLaMa, Mixtral, llama.cpp, and more. Demo: https://gpt.h2o.ai/ https://codellama.h2o.ai/
dify - Dify is an open-source LLM app development platform. Dify's intuitive interface combines AI workflow, RAG pipeline, agent capabilities, model management, observability features and more, letting you quickly go from prototype to production.
ollama - Get up and running with Llama 3, Mistral, Gemma, and other large language models.
open-webui - User-friendly WebUI for LLMs (Formerly Ollama WebUI)
text-generation-webui - A Gradio web UI for Large Language Models. Supports transformers, GPTQ, AWQ, EXL2, llama.cpp (GGUF), Llama models.
react-llm - Easy-to-use headless React Hooks to run LLMs in the browser with WebGPU. Just useLLM().
llama.cpp - LLM inference in C/C++