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fabric

Appears in 6 awesome lists

fabric is an open-source framework for augmenting humans using AI. It provides a modular framework for solving specific problems using a crowdsourced set of AI prompts that can be used anywhere.

Open github.comdanielmiessler/fabric

Found in these lists

AI Game DevTools (AI-GDT)

Section: Game (World Model & Agent) · fabric is an open-source framework for augmenting humans using AI.

ActiveScore 77

Awesome AI Tools

Section: Productivity · Apply AI to everyday challenges in the comfort of your terminal. Help’s to get better results with tried and tested library of prompt pattern’s.

SlowScore 67

Awesome Command Line (CLI/TUI) Programs

Section: AI / LLM integration · An open-source framework for augmenting humans using AI, providing a modular framework for solving specific problems using a crowdsourced set of AI prompts that can be used anywhere.

FreshScore 83

Awesome Data Analysis

Section: Tools · Framework for augmenting humans using AI.

FreshScore 80

Awesome Generative AI

Section: Large Language Models (LLMs) · fabric is an open-source framework for augmenting humans using AI. It provides a modular framework for solving specific problems using a crowdsourced set of AI prompts that can be used anywhere.

SlowScore 62

awesome-go

Section: Other · Fabric is an open-source framework for augmenting humans using AI. It provides a modular system for solving specific problems using a crowdsourced set of AI prompts that can be used anywhere.

FreshScore 81

Taskade

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Langchain integrates various providers like Anthropic, AWS, and OpenAI, and offers tools for components such as LLMs, chat models, and data analysis, supporting functionalities from Alpha Vantage to YouTube github | docs

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LlamaIndex

(MIT) provides modules for structured outputs at different levels of abstraction, including output parsers for text completion endpoints, Pydantic programs for mapping prompts to structured outputs using function calling or output parsing, and pre-defined Pydantic programs for specific output types.

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Ollama

Get up and running with Llama 3.3, DeepSeek-R1, Phi-4, Gemma 3, and other large language models. (Source Code) MIT Docker/Python

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Pipecat

Handles frame management, streaming media coordination, and pipeline orchestration between ASR/LLM/TTS services for sub-800ms Total Turn-Around Time voice interactions. The missing harness primitive for voice agents: manages backpressure, handles frame queueing, and exposes a simple async…

In 7 listsDetails