tedcheng / ai-hackers-field-manual

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AI Hackers' Field Manual

πŸ“š Collections of common [application patterns], [tools], [models], and [research papers] for building AI applications. πŸ”

πŸ”₯ New applications and content updated every week! πŸ“…

Application Patterns and Examples

Have ideas for other patterns? Open an PR and create a new folder under examples. Or simply open an issue and we can discuss it.

Name Example Description Community Projects
LLM Agent Thought, Action, Observation Agent built from scratch Microsoft's Jarvis, Google's Palm, AutoGPT
ChatGPT Plugin A plugin looking up real time Bart schedule
Deploy Self-Hosted LLM Running your own LLM on Replicate
Semantic Search and Q&A Bots 🚧 Under Construction

Tools

Common tools you will come across as you explore projects built in the community.

Name Category Description
Flask Framework A lightweight web framework for Python. Since Python is the language of AI, you might as well use a web framework in Python. Another common option is FastAPI.
Next.js Framework A popular Javascript framework, often used with Vercel.
Vercel Infra & Hosting A cloud platform specialized in hosting Next.js apps.
Tailwindcss Framework A utility-first CSS framework, which means you will define styling directly with pre-built css classes.
Pinecone Infra & Hosting A vector database for AI applications. This is commonly used to store embeddings of data and enable similarity based search (More on this in Q&A bots). Alternatively, you can also use Milvus, Faiss, Chroma and Weaviate and others.
Supabase Infra & Hosting A popular PostgresQL as a service vendor. Works well with NextJS and offers Authentication and storage APIs out of the box. Also has support for storing embeddings (using a Postgres plugin - pgvector) and files.
LlamaIndex Framework A library that provides an interface between LLMs and external data by handling data connectors, building indices and querying (e.g., including managing prompt token size, etc.).
LangChain Framework A library that helps you build LLM based complex action chains and agents.
OpenAI API API Currently the state of the art models. Commonly used APIs include:
  • Whisper - Audio to text. This is also open-sourced, so you can run your own service.
  • Embedding - Generate high dimensional representation based on text and can be used for semantic search.
  • Text completions and chat completions - The API behind ChatGPT. Multiple models exist. gpt-4 is the state of art, but general use cases can be done on gpt-3.5-turbo (cheaper and faster).
  • DALLE - Text to image.
HuggingFace Infra & Hosting The GitHub for AI models, a platform to build, deploy, and share models across the community. An alternative to OpenAI models.
ElevenLabs API AI text to speech API. Voice cloning.
Replicate API Run open-source machine learning models with a cloud API.

Models

A list of the more "hackable" open source models and how to work with them.

Name Description Size Data OSS & License How to work with it
LLaMA Foundational 65B LLM from Meta AI 65B Yes (Research only) Hosting
Dolly 2.0 Open source, instruction-following LLM 12B 15,000 high-quality human-generated prompt / response pairs Yes (Commercial use friendly)

Key research papers

🚧 Under Construction

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