llm.md

Framework

• link frameworks for LLM apps.

• https://github.com/joaomdmoura/crewAI framework for orchestrating role-playing, autonomous AI agents.

• https://github.com/microsoft/autogen framework for multiple agents.

• https://github.com/run-llama/llama_index framework for your LLM application.

• https://github.com/langchain-ai/langchain framework for LLM apps.

• https://github.com/agenta-ai/agenta

• Enhances:

  • https://github.com/stanfordnlp/dspy framework for algorithmically optimizing LM prompts and weights.
  • https://github.com/kyegomez/tree-of-thoughts Tree of Thoughts (ToT) is a powerful and flexible algorithm that significantly advances model reasoning by up to 70%.
  • https://github.com/togethercomputer/MoA Get multiple LLMs to collaborate

• https://github.com/BerriAI/litellm Call all LLM APIs using the OpenAI format [Bedrock, Huggingface, VertexAI, TogetherAI, Azure, OpenAI, etc.].

  • Or, use Perplexity, TogetherAI, You etc.

• https://github.com/eth-sri/lmql programming language for large language models (LLMs) based on a superset of Python

• https://github.com/embedchain/embedchain` Embedchain is an Open Source Framework for personalizing LLM responses`.

Apps

• https://github.com/vanna-ai/vanna Auto SQL.

• https://github.com/OpenDevin/OpenDevin Auto software engineer

• https://github.com/wandb/openui auto UI.

• https://github.com/princeton-nlp/SWE-agent Auto bug fix on git repo.

• https://github.com/ShishirPatil/gorilla Auto API call

• https://github.com/VinciGit00/Scrapegraph-ai Auto webscrape. See parsera as well.

• https://github.com/Pythagora-io/gpt-pilot A coding Copilot

• https://github.com/microsoft/graphrag Auto graph rag

• https://github.com/infiniflow/ragflow Auto graph rag

• https://github.com/hacksider/Deep-Live-Cam

• https://github.com/black-forest-labs/flux

Parsing

• https://github.com/outlines-dev/outlines unstructured -> structured
• https://github.com/PrefectHQ/marvin unstructured -> structured
• https://github.com/guardrails-ai/guardrails unstructured -> structured
• https://github.com/jackmpcollins/magentic unstructured -> structured

Web

• https://github.com/mendableai/firecrawl Website html -> markdown.
• https://github.com/apify/crawlee-python Website html -> markdown.
• https://github.com/McGill-NLP/webllama Browse internet with agents
• https://github.com/nilsherzig/LLocalSearch locally running search aggregator using LLM Agents.

CLI

• https://github.com/llm-workflow-engine/llm-workflow-engine LLM Workflow Engine (LWE) is a Power CLI and Workflow manager for LLMs.

• https://github.com/iyaja/llama-fs self-organizing file manager. It automatically renames and organizes your files based on their contents and well-known conventions (e.g., time).

• https://github.com/BasedHardware/OpenGlass convert glasses to ai glasses

• https://github.com/microsoft/PubSec-Info-Assistant Information Assistant Accelerator

• https://github.com/goldmansachs/gs-quant

Viz

• chainlit: https://github.com/Chainlit/cookbook
• https://github.com/wandb/openui aims to make the process fun, fast, and flexible. It's also a tool we're using at W&B to test and prototype our next generation tooling for building powerful applications on top of LLM's.
• https://github.com/oobabooga/text-generation-webui A Gradio web UI for Large Language Models..
• https://github.com/google/mesop Next streamlit

Deployment

• https://github.com/bigscience-workshop/petals LLM on private swarm
• https://github.com/h2oai/h2o-llmstudio framework and no-code GUI designed for fine-tuning state-of-the-art large language models (LLMs).
• https://github.com/hiyouga/LLaMA-Factory Finetune
• https://github.com/microsoft/DeepSpeed training with a single click, offering 15x speedup over SOTA RLHF systems with unprecedented cost reduction at all scales.
• https://github.com/TensorOpsAI/LLMstudio Prompt Engineering at your fingertips
• https://lmstudio.ai/ Discover, download, and run local LLMs
• https://github.com/janhq/cortex.cpp Cortex is a Local AI API Platform that is used to run and customize LLMs.
• https://github.com/zylon-ai/private-gpt local llm
• https://github.com/ggerganov/llama.cpp Inference of Meta's LLaMA model (and others) in pure C/C++
• https://github.com/ollama/ollama Get up and running with large language models locally.
• https://github.com/Mozilla-Ocho/llamafile reduce LLM to one file (focuses on CPU, uses llamacpp backed)
• https://github.com/vllm-project/vllm host on gpu
• https://github.com/SJTU-IPADS/PowerInfer Fast Large Language Model Serving with a Consumer-grade GPU.
• https://github.com/bentoml/OpenLLM Self-Hosting Large Language Models Made Easy.
• https://github.com/mudler/LocalAI Open Source OpenAI alternative
• https://github.com/nomic-ai/gpt4all Open-source large language models that run locally on your CPU and nearly any GPU.

Models

• https://github.com/google/gemma.cpp lightweight, standalone C++ inference engine for the Gemma foundation models from Google.
• https://github.com/OpenBMB/MiniCPM-V A GPT-4V Level MLLM for Single Image

Sources

• https://github.com/xai-org/grok-1
• https://github.com/Hannibal046/Awesome-LLM curated list of papers about large language models, especially relating to ChatGPT. It also contains frameworks for LLM training, tools to deploy LLM, courses and tutorials about LLM and all publicly available LLM checkpoints and APIs.
• https://github.com/openai/openai-cookbook Example code and guides for accomplishing common tasks with the OpenAI API.
• https://ai.azure.com/explore/
• https://github.com/f/awesome-chatgpt-prompts
• https://github.com/erikbern/ann-benchmarks

Deprecated

• https://github.com/chenfei-wu/TaskMatrix
• https://github.com/tg12/gpt_jailbreak_status