Python llms

Open-source Python projects categorized as llms

Top 23 Python llm Projects

  • LLaMA-Factory

    Unify Efficient Fine-Tuning of 100+ LLMs

  • Project mention: Show HN: GPU Prices on eBay | news.ycombinator.com | 2024-02-23

    Depends what model you want to train, and how well you want your computer to keep working while you're doing it.

    If you're interested in large language models there's a table of vram requirements for fine-tuning at [1] which says you could do the most basic type of fine-tuning on a 7B parameter model with 8GB VRAM.

    You'll find that training takes quite a long time, and as a lot of the GPU power is going on training, your computer's responsiveness will suffer - even basic things like scrolling in your web browser or changing tabs uses the GPU, after all.

    Spend a bit more and you'll probably have a better time.

    [1] https://github.com/hiyouga/LLaMA-Factory?tab=readme-ov-file#...

  • chroma

    the AI-native open-source embedding database

  • Project mention: Let’s build AI-tools with the help of AI and Typescript! | dev.to | 2024-04-23

    Package installer for Python (pip), we use this for installing the Python-based packages, such as Jupyter Lab, and we're going to use this for installing other Python-based tools like the Chroma DB vector database

  • 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.

    InfluxDB logo
  • LLMSurvey

    The official GitHub page for the survey paper "A Survey of Large Language Models".

  • Project mention: Ask HN: Textbook Regarding LLMs | news.ycombinator.com | 2024-03-23

    Here’s another one - it’s older but has some interesting charts and graphs.

    https://arxiv.org/abs/2303.18223

  • AutoGPTQ

    An easy-to-use LLMs quantization package with user-friendly apis, based on GPTQ algorithm.

  • Project mention: Setting up LLAMA2 70B Chat locally | /r/developersIndia | 2023-08-18
  • gpt-code-ui

    An open source implementation of OpenAI's ChatGPT Code interpreter

  • Project mention: Should I tell my employer about a product that makes my job irrelevant? | /r/cscareerquestions | 2023-07-11

    Is this of any help?

  • api-for-open-llm

    Openai style api for open large language models, using LLMs just as chatgpt! Support for LLaMA, LLaMA-2, BLOOM, Falcon, Baichuan, Qwen, Xverse, SqlCoder, CodeLLaMA, ChatGLM, ChatGLM2, ChatGLM3 etc. 开源大模型的统一后端接口

  • Project mention: FLaNK Stack Weekly for 14 Aug 2023 | dev.to | 2023-08-14
  • DemoGPT

    Create 🦜️🔗 LangChain apps by just using prompts🌟 Star to support our work! | 只需使用句子即可创建 LangChain 应用程序。 给个star支持我们的工作吧!

  • Project mention: Llama 2 Code Interpreter | news.ycombinator.com | 2023-07-23
  • WorkOS

    The modern identity platform for B2B SaaS. The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning.

    WorkOS logo
  • Project mention: GitHub - swirlai/swirl-search: Swirl is an open-source search platform that uses AI to search multiple content and data sources simultaneously, finds the best results using a reader LLM, then prompts Generative AI, enabling you to get answers based on your data. | /r/programming | 2023-12-05
  • langroid

    Harness LLMs with Multi-Agent Programming

  • Project mention: OpenAI: Streaming is now available in the Assistants API | news.ycombinator.com | 2024-03-14

    This was indeed true in the beginning, and I don’t know if this has changed. Inserting messages with Assistant role is crucial for many reasons, such as if you want to implement caching, or otherwise edit/compress a previous assistant response for cost or other reason.

    At the time I implemented a work-around in Langroid[1]: since you can only insert a “user” role message, prepend the content with ASSISTANT: whenever you want it to be treated as an assistant role. This actually works as expected and I was able to do caching. I explained it in this forum:

    https://community.openai.com/t/add-custom-roles-to-messages-...

    [1] the Langroid code that adds a message with a given role, using this above “assistant spoofing trick”:

    https://github.com/langroid/langroid/blob/main/langroid/agen...

  • loopgpt

    Modular Auto-GPT Framework

  • Project mention: [P] LoopGPT Update - Finally something useful? | /r/MachineLearning | 2023-07-20

    So we thought it would be a good idea to create a framework that makes use of LoopGPT agent's memory and custom tooling capabilities. Let's jump right into the new features of this framework.

  • coffee

    Build and iterate on your UI 10x faster with AI - right from your own IDE ☕️

  • Project mention: AI Grant Traction in OSS Startups | dev.to | 2024-02-01

    Coframe

  • safe-rlhf

    Safe RLHF: Constrained Value Alignment via Safe Reinforcement Learning from Human Feedback

  • Project mention: [R] Meet Beaver-7B: a Constrained Value-Aligned LLM via Safe RLHF Technique | /r/MachineLearning | 2023-05-16
  • LLMStack

    No-code platform to build LLM Agents, workflows and applications with your data

  • Project mention: Vanna.ai: Chat with your SQL database | news.ycombinator.com | 2024-01-14

    We have recently added support to query data from SingleStore to our agent framework, LLMStack (https://github.com/trypromptly/LLMStack). Out of the box performance performance when prompting with just the table schemas is pretty good with GPT-4.

    The more domain specific knowledge needed for queries, the harder it has gotten in general. We've had good success `teaching` the model different concepts in relation to the dataset and giving it example questions and queries greatly improved performance.

  • dstack

    dstack is an open-source orchestration engine for running AI workloads at scale in any cloud or data center. https://discord.gg/u8SmfwPpMd

  • Project mention: Ask HN: How does deploying a fine-tuned model work | news.ycombinator.com | 2024-04-23

    You can use https://github.com/dstackai/dstack to deploy your model to the most affordable GPU clouds. It supports auto-scaling and other features.

    Disclaimer: I’m the creator of dstack.

  • LLMCompiler

    LLMCompiler: An LLM Compiler for Parallel Function Calling

  • Project mention: FLaNK Weekly 18 Dec 2023 | dev.to | 2023-12-18
  • llm_agents

    Build agents which are controlled by LLMs

  • agenta

    The all-in-one LLM developer platform: prompt management, evaluation, human feedback, and deployment all in one place.

  • Project mention: Ask HN: How are you testing your LLM applications? | news.ycombinator.com | 2024-02-06

    I am biased, but I would use a platform and not roll your own solution. You will tend to underestimate the depth of capabilities needed for an eval framework.

    Now for solutions, shameless plug here, we are building an open-source platform for experimenting and evaluating complex LLM apps (https://github.com/agenta-ai/agenta). We offer automatic evaluators as well as human annotation capabilities. Currently, we only provide testing before deployment, but we have plans to include post-production evaluations as well.

    Other tools I would look at in the space are promptfoo (also open-source, more dev oriented), humanloop (one of the most feature complete tools in the space, enterprise oriented), however more enterprise oriented / costly) and vellum (YC company, more focused towards product teams)

  • distilabel

    ⚗️ distilabel is a framework for synthetic data and AI feedback for AI engineers that require high-quality outputs, full data ownership, and overall efficiency.

  • Project mention: Open-source AI Feedback framework for scalable LLM Alignment | news.ycombinator.com | 2023-11-23
  • agent-protocol

    Common interface for interacting with AI agents. The protocol is tech stack agnostic - you can use it with any framework for building agents.

  • Project mention: Show HN: Common protocol for communication with (and between) AI Agents | news.ycombinator.com | 2023-08-09
  • DataDreamer

    DataDreamer: Prompt. Generate Synthetic Data. Train & Align Models.   🤖💤

  • Project mention: FLaNK AI - 01 April 2024 | dev.to | 2024-04-01
  • llmflows

    LLMFlows - Simple, Explicit and Transparent LLM Apps

  • Project mention: Show HN: LLMFlows – LangChain alternative for explicit and transparent apps | news.ycombinator.com | 2023-07-29
  • oterm

    a text-based terminal client for Ollama

  • Project mention: term | /r/LocalLLaMA | 2023-10-17

    Check it out here

  • vectordb

    A minimal Python package for storing and retrieving text using chunking, embeddings, and vector search. (by kagisearch)

  • Project mention: VectorDB: Vector Database Built by Kagi Search | news.ycombinator.com | 2023-11-26

    We needed a low latency, on premise solution that we can run on edge nodes (so lightweight) with sane defaults that anyone in the team can whim in a sec.

    Result is this and we constantly benchmark performance of different embeddings to ensure best defaults.

    [1] https://github.com/kagisearch/vectordb#embeddings-performanc...

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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).

Python llms related posts

Index

What are some of the best open-source llm projects in Python? This list will help you:

Project Stars
1 LLaMA-Factory 17,050
2 chroma 12,189
3 LLMSurvey 8,716
4 AutoGPTQ 3,744
5 gpt-code-ui 3,482
6 api-for-open-llm 1,952
7 DemoGPT 1,566
8 swirl-search 1,509
9 langroid 1,509
10 loopgpt 1,390
11 coffee 1,341
12 safe-rlhf 1,149
13 LLMStack 1,089
14 dstack 1,087
15 LLMCompiler 1,056
16 llm_agents 877
17 agenta 823
18 distilabel 825
19 agent-protocol 754
20 DataDreamer 632
21 llmflows 615
22 oterm 554
23 vectordb 543

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