curiousily / tweetcrafter

Write tweets with AI Agents (CrewAI) and LLMs (Llama 3, GPT-4o)

Home Page:https://www.mlexpert.io/bootcamp/ai-agents-in-action

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TweetCrafter

Write tweets with AI Agents (CrewAI)

Installation

Clone the repo

git clone git@github.com:curiousily/tweetcrafter.git
cd tweetcrafter
poetry install

Install iPython kernel:

poetry run python -m ipykernel install --user --name tweetcrafter --display-name "Python (tweetcrafter)"

Add API keys

Create a .env file in the root of the project and add your Groq and/or OpenAI API keys:

GROQ_API_KEY=<GROQ_API_KEY>
OPENAI_API_KEY=<OPENAI_API_KEY>

Usage

Go to app.py and change the inputs:

inputs = {
    "topic": "Summary of the key new features of Phi-3",
    "urls": [
        "https://huggingface.co/microsoft/Phi-3-vision-128k-instruct",
    ],
    "suggestion": "Focus on the performance and how-to use the model.",
}

Add tweets to analyze their writing style in data/tweets.md:

# Tweet

Ever wondered how to reproduce GPT-2 (124M) efficiently?
@karpathy with llm.c has the answer!

- 90 mins, $20 on 8X A100 80GB SXM
- FineWeb dataset: 10B tokens
- MFU: 49-60%, 178K tokens/sec

https://github.com/karpathy/llm.c/discussions/481

Run the app:

poetry run python app.py
{
   "total_tokens":12334,
   "prompt_tokens":10260,
   "completion_tokens":2074,
   "successful_requests":8
}

Result

The tweets I got from the crew (saved to output/tweet.md):

Original Tweet:
"Meet Phi-3, the cutting-edge AI model revolutionizing NLP! πŸš€πŸ’»
β€’ Processes human language efficiently and accurately
β€’ Ideal for NLP, text gen, conversational AI, sentiment analysis, and language translation
β€’ Transparent, accountable, and fair decision-making
β€’ Trained on diverse datasets and compatible with TensorFlow and PyTorch
#Phi3 #AI #NLP #LanguageModel #ResponsibleAI

Version 1:
"Unlock the power of Phi-3, the AI model that's changing the NLP game! πŸš€πŸ’»
β€’ Efficient and accurate language processing
β€’ Perfect for text gen, conversational AI, sentiment analysis, and language translation
β€’ Transparency, accountability, and fairness in decision-making
β€’ Compatible with TensorFlow and PyTorch
#Phi3 #AI #NLP #LanguageModel #ResponsibleAI

Version 2:
"Take your NLP projects to the next level with Phi-3! πŸš€πŸ’»
β€’ Fast and accurate language processing
β€’ Ideal for conversational AI, sentiment analysis, and language translation
β€’ Built with transparency, accountability, and fairness in mind
β€’ Compatible with TensorFlow and PyTorch
#Phi3 #AI #NLP #LanguageModel #ResponsibleAI

Version 3:
"Discover the future of NLP with Phi-3! πŸš€πŸ’»
β€’ Efficient language processing for text gen, conversational AI, and more
β€’ Transparent, accountable, and fair decision-making
β€’ Trained on diverse datasets and compatible with TensorFlow and PyTorch
β€’ Revolutionize your NLP projects with Phi-3
#Phi3 #AI #NLP #LanguageModel #ResponsibleAI

Observability

TweetCrafter stores logs of prompts and individual agent logs in the logs directory.

Have a look at the notebooks/explore-logs.ipynb notebook to explore the logs.

About

Write tweets with AI Agents (CrewAI) and LLMs (Llama 3, GPT-4o)

https://www.mlexpert.io/bootcamp/ai-agents-in-action

License:MIT License


Languages

Language:Jupyter Notebook 81.0%Language:Python 19.0%