Bing’s contexts: https://twitter.com/StudentInfosec/status/1640360234882310145
Inner Monologues https://twitter.com/BBacktesting/status/1644509440949755904
Commands… #context #search #message #system #search #browse #calendar #mail
ChatGPT Plugins: https://www.gptplugins.app/
TODO
https://fullstackdeeplearning.com/llm-bootcamp/spring-2023/ https://twitter.com/pwang_szn/status/1656237690843709442 https://twitter.com/pwang_szn/status/1655150503905595394
Langchain
Chat docs: https://www.supportguy.co/chatbot/UMFDPPIGugxNPhSXj1KR
Examples https://colab.research.google.com/drive/1jpI88u06OjuLHsmCQExJoTUKSUP3Lry4?usp=sharing https://gist.github.com/bryanhpchiang/ce16c910b60621dbc6d2c107e1ec6140
Tutorial https://www.youtube.com/watch?v=5-fc4Tlgmro https://www.youtube.com/watch?v=s5LhRdh5fu4
Implementations https://github.com/muellerberndt/micro-gpt
LLamaIndex https://github.com/jerryjliu/llama_index
Streaming Tokens API
LLM API Layer
OpenLM
https://github.com/r2d4/openlm Drop-in OpenAI-compatible library that can call LLMs from other providers (e.g., HuggingFace, Cohere, and more).
LocalAI
https://github.com/go-skynet/LocalAI
- OpenAI compatible API
- LocalAI uses C++ bindings for optimizing speed. It is based on llama.cpp, gpt4all, rwkv.cpp, ggml, whisper.cpp for audio transcriptions, and bert.cpp for embedding.
PhaseLLM
https://github.com/wgryc/phasellm “PhaseLLM makes it incredibly easy to plug and play LLMs and evaluate them, in some cases with other LLMs. Suppose you’re building a travel chatbot, and you want to test Claude and Cohere against each other, using GPT-3.5.”
Basaran
Basaran is an open-source alternative to the OpenAI text completion API. It provides a compatible streaming API for your Hugging Face Transformers-based text generation models.
https://github.com/dcSpark-AI/open-LLM-server https://github.com/nuance1979/llama-server https://github.com/serge-chat/serge
https://abetlen.github.io/llama-cpp-python/ https://github.com/abetlen/llama-cpp-python
https://github.com/iaalm/llama-api-server https://github.com/turboderp/exllama/issues/37 https://github.com/abetlen/llama-cpp-python https://github.com/wgryc/phasellm https://github.com/go-skynet/LocalAI https://github.com/r2d4/openlm https://github.com/iaalm/llama-api-server/tree/main/llama_api_server https://localai.io/model-compatibility/index.html#model-compatibility-table https://github.com/go-skynet/LocalAI
https://github.com/jtsang4/claude-to-chatgpt https://www.anthropic.com/index/100k-context-windows https://console.anthropic.com/docs https://technomancers.ai/eu-ai-act-to-target-us-open-source-software/ https://news.ycombinator.com/item?id=35948742
Production Notes
https://huyenchip.com/2023/04/11/llm-engineering.html
Search: https://www.reddit.com/r/MachineLearning/comments/12tn34b/p_fullstack_llamaindex_app_to_build_and_query/ https://github.com/JSv4/Delphic
Vector DBs
Chroma https://www.trychroma.com/ https://github.com/chroma-core/chroma
Weaviate (BSD) https://weaviate.io/ https://github.com/weaviate/weaviate
Vespa (Apache 2.0) https://vespa.ai/ https://github.com/vespa-engine/vespa https://docs.vespa.ai/en/getting-started.html
Qdrant (Apache 2.0) https://qdrant.tech/ https://github.com/qdrant/qdrant
Milvus https://milvus.io/ (Apache 2.0) https://github.com/milvus-io/milvus
pgvector https://github.com/pgvector/pgvector https://supabase.com/blog/openai-embeddings-postgres-vector
FAISS (MIT) https://github.com/facebookresearch/faiss
mamba install faiss-cpu
mamba install faiss-gpu
LLM as Recommendation Systems https://towardsdatascience.com/using-large-language-models-as-recommendation-systems-49e8aeeff29b
Markdown table converter https://www.tablesgenerator.com/markdown_tables
https://github.com/e-johnstonn/docsummarizer https://gptdoc-summarizer.streamlit.app/ https://app.heptabase.com/w/12484a51f631edbddd6415dafbad56d8ae119058ece8bcb3e8d9a5a3ba80a45b?id=7d359c3d-b443-4547-a852-d384457cd23b https://github.com/fanahova https://twitter.com/FanaHOVA
https://www.reddit.com/r/LocalLLaMA/comments/138lxrp/llama4bit_inference_speed_for_various_context/
Eval https://github.com/aigoopy/llm-jeopardy https://www.reddit.com/r/MachineLearning/comments/13d2vos/r_lmflow_benchmark_an_automatic_evaluation/ https://www.reddit.com/r/LocalLLaMA/comments/13zz8y5/what_questions_do_you_ask_llms_to_check_their/