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Top 23 Python Prompt Projects
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powerline
Powerline is a statusline plugin for vim, and provides statuslines and prompts for several other applications, including zsh, bash, tmux, IPython, Awesome and Qtile.
Project mention: How I manage multiple kubernetes clusters w/ kubectx & kubens | dev.to | 2024-10-01I love powerline over traditional PS1 (aka command prompt). It's beautiful and highly customizable.
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Stream
Stream - Scalable APIs for Chat, Feeds, Moderation, & Video. Stream helps developers build engaging apps that scale to millions with performant and flexible Chat, Feeds, Moderation, and Video APIs and SDKs powered by a global edge network and enterprise-grade infrastructure.
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promptflow
Build high-quality LLM apps - from prototyping, testing to production deployment and monitoring.
Project mention: Harnessing OpenAI Assistant 2.0 for Named Entity Recognition in PHP/Symfony 7 | dev.to | 2024-12-19OpenAI Fine-Tuning Documentation Symfony Messenger Documentation OpenAI PHP Client Library PromptFlow Extension for VS Code
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Awesome-Prompt-Engineering
This repository contains a hand-curated resources for Prompt Engineering with a focus on Generative Pre-trained Transformer (GPT), ChatGPT, PaLM etc
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tree-of-thoughts
Plug in and Play Implementation of Tree of Thoughts: Deliberate Problem Solving with Large Language Models that Elevates Model Reasoning by atleast 70%
Just gonna leave this here: https://github.com/kyegomez/tree-of-thoughts/issues/78#issue...
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InfluxDB
InfluxDB – Built for High-Performance Time Series Workloads. InfluxDB 3 OSS is now GA. Transform, enrich, and act on time series data directly in the database. Automate critical tasks and eliminate the need to move data externally. Download now.
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Kiln
The easiest tool for fine-tuning LLM models, synthetic data generation, and collaborating on datasets.
This is a bit confusing, I sort of expected it to be a bit like Kiln https://github.com/Kiln-AI/Kiln to generate datasets for AI, but it looks like the outputs are more just data / files than datasets?
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OFA
Official repository of OFA (ICML 2022). Paper: OFA: Unifying Architectures, Tasks, and Modalities Through a Simple Sequence-to-Sequence Learning Framework
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#!/usr/bin/env -S uv run --script # /// script # requires-python = ">=3.10" # dependencies = [ # "fire", # "magentic", # "pydantic", # ] # /// from fire import Fire from magentic import chatprompt, AssistantMessage, SystemMessage, UserMessage from pydantic import BaseModel # this is a modified version of magentic's example chatprompt code # https://magentic.dev/#chatprompt class Quote(BaseModel): quote: str character: str @chatprompt( SystemMessage("You are a movie buff."), UserMessage("What is your favorite quote from Harry Potter?"), AssistantMessage( Quote( quote="It does not do to dwell on dreams and forget to live.", character="Albus Dumbledore", ) ), UserMessage("What is your favorite quote from {movie}?"), ) def get_movie_quote(movie: str) -> Quote: ... if __name__=="__main__": Fire(get_movie_quote)
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DemoGPT
🤖 Everything you need to create an LLM Agent—tools, prompts, frameworks, and models—all in one place.
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Project mention: Ask HN: Is synthetic data generation practical outside academia? | news.ycombinator.com | 2025-06-06
https://github.com/bespokelabsai/curator
But it still feels very research-oriented. I haven’t found many examples of these pipelines running in real-world products.
I’m curious:
1. Who is using synthetic-data pipelines in production today?
2. What tasks does it actually improve. E.g. fine-tuning smaller models for specific tasks?
Any real-world stories, pointers, or further reading would be hugely appreciated. Thanks!
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awesome-gpt-prompt-engineering
A curated list of awesome resources, tools, and other shiny things for LLM prompt engineering.
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docker-prompt-generator
Using a Model to generate prompts for Model applications. / 使用模型来生成作图咒语的偷懒工具，支持 MidJourney、Stable Diffusion 等。
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prompt-poet
Streamlines and simplifies prompt design for both developers and non-technical users with a low code approach.
Project mention: PromptPoet: Revolutionizing LLM Prompt Design at Character.ai | news.ycombinator.com | 2024-08-07We are thrilled by the community's response to our new open-source project, PromptPoet, which has garnered nearly 400 GitHub stars in less than a week!
Check it out here: https://github.com/character-ai/prompt-poet
At Character.AI, we developed PromptPoet to make LLM prompt design accessible to both technical and non-technical users. We're excited to continue to invest in development of PromptPoet alongside the developer community.
Our immediate next step is to bring these syntax to the community of Character creators on our platform, enabling them to tailor interactions based on runtime attributes—like adjusting prompts according to the user's age or the length of the current conversation.
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InquirerPy
:snake: Python port of Inquirer.js (A collection of common interactive command-line user interfaces)
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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).
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Index
What are some of the best open-source Prompt projects in Python? This list will help you:
| # | Project | Stars |
|---|---|---|
| 1 | powerline | 14,563 |
| 2 | awesome-chatgpt-zh | 11,234 |
| 3 | promptflow | 10,559 |
| 4 | EmotiVoice | 8,083 |
| 5 | OpenPrompt | 4,666 |
| 6 | Awesome-Prompt-Engineering | 4,650 |
| 7 | tree-of-thoughts | 4,513 |
| 8 | myGPTReader | 4,441 |
| 9 | LMOps | 4,065 |
| 10 | DeepKE | 4,033 |
| 11 | Kiln | 3,957 |
| 12 | promptbench | 2,661 |
| 13 | OFA | 2,498 |
| 14 | magentic | 2,338 |
| 15 | YiVal | 2,099 |
| 16 | DemoGPT | 1,845 |
| 17 | curator | 1,446 |
| 18 | awesome-gpt-prompt-engineering | 1,339 |
| 19 | docker-prompt-generator | 1,173 |
| 20 | prompt-poet | 1,087 |
| 21 | riposte | 615 |
| 22 | InquirerPy | 408 |
| 23 | funcchain | 338 |
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