zunnoai 0.1.0

Flexible LLM interface for Ollama and more

ZunnoAI

A flexible, modular Python package for using Ollama LLMs (and more in future).
Easily run, batch, and manage local LLMs with a simple interface.
PyPI-ready, extensible, and professional.

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🚀 Features

• Supports all Ollama models (e.g. gemma, llama, mistral, etc.)
• Easy Python API: Just import and use
• Batch inference: Run multiple prompts at once
• History logging: Track your prompt/response history
• Auto model selection: Use any local Ollama model by name
• Ready for future: HuggingFace/OpenAI support coming soon
• PyPI installable: Clean, modular, and production-ready

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📦 Installation

Clone the repo and install locally:

git clone <your-repo-url>
cd zunnoai
pip install .

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🧑‍💻 Usage Examples

List available models

from zunnoai import Zunno

llm = Zunno("gemma:2b")
print("Available models:", llm.list_models())

Run a prompt

from zunnoai import Zunno

llm = Zunno("gemma:2b")
response = llm.run("Tell me a joke about AI.")
print("AI:", response)

Batch prompts

from zunnoai import Zunno

llm = Zunno("gemma:2b")
prompts = ["What is Python?", "What is machine learning?"]
results = llm.run_batch(prompts)
for i, res in enumerate(results):
    print(f"Prompt {i+1}: {prompts[i]}\nAI: {res}\n")

Show history

from zunnoai import Zunno

llm = Zunno("gemma:2b")
llm.run("Say hello!")
llm.show_history()

CLI Usage

python -m zunnoai list
python -m zunnoai pull llama3
python -m zunnoai run gemma:2b "What is AI?"
python -m zunnoai --help

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### 2. **examples/example_usage.py** (Update karo)

```python
from zunnoai import Zunno

# List available models
llm = Zunno("gemma:2b")
print("Available models:", llm.list_models())

# Run a prompt
response = llm.run("Tell me a joke about AI.")
print("AI:", response)

# Batch prompts
prompts = ["What is Python?", "What is machine learning?"]
results = llm.run_batch(prompts)
for i, res in enumerate(results):
    print(f"Prompt {i+1}: {prompts[i]}\nAI: {res}\n")

# Show history
llm.show_history()

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3. Docstrings (Optional but Professional)

Aap chahein toh Zunno class aur public methods mein docstrings bhi add kar sakte hain, jaise:

class Zunno:
    """
    Main interface for using Ollama LLMs via Python or CLI.
    """
    def list_models(self):
        """
        List all available Ollama models on the local server.
        Returns: list of model names (str)
        """
        ...

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4. README.md — Features, Requirements, Contributing, License (Already Provided)

Aapka README.md already kaafi strong hai, bas usage section ko polish kar lo.

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Aap yeh changes kar lo.
Jab ho jaaye, toh batao — agla step (PyPI publish ya koi aur feature) shuru karenge!

⚙️ API Reference

• Zunno(model_name, ollama_url=..., output_format=..., log_to_file=..., log_file=...)
• run(prompt, stream=False, **kwargs)
• run_batch(prompts, **kwargs)
• show_history()
• help()

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🏗️ Project Structure

zunnoai/ ├── zunnoai/ │ ├── core/ │ ├── models/ │ ├── api/ │ ├── utils/ │ └── config.py ├── tests/ ├── examples/ ├── setup.py ├── README.md └── LICENSE

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📝 Requirements

• Python 3.7+
• Ollama running locally
• requests Python package

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🛠️ Extending

• Add new models in zunnoai/models/
• Add new APIs in zunnoai/api/
• Utilities in zunnoai/utils/

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🤝 Contributing

1. Fork this repo
2. Create a feature branch
3. Make your changes
4. Submit a pull request

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📄 License

MIT License

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🙋‍♂️ Contact

For issues or suggestions, open an issue or contact the maintainer.