pydantic-ai-jupyter 0.1.2

Experiment with Pydantic AI Agents in your notebooks.

pydantic-ai-jupyter

Experiment with Pydantic AI Agents interactively in Jupyter notebooks.

Installation

pip install pydantic-ai-jupyter

Or with uv:

uv add pydantic-ai-jupyter

Usage

from pydantic_ai import Agent
from pydantic_ai_jupyter import run_in_jupyter

agent = Agent("openai:gpt-4o-mini")

@agent.tool_plain
def get_weather(city: str) -> str:
    return f"Sunny, 22°C in {city}"

# Run with rich display
result = await run_in_jupyter(agent, "What's the weather in Tokyo?")

Features

• Streaming text - See the model's response as it generates
• Streaming tool calls - Watch tool arguments stream in (with providers that support it, like OpenAI)
• Tool results - Styled success and retry results
• Thinking/reasoning - Collapsible display of model thinking
• Error handling - Graceful display of exceptions with tracebacks

Multi-turn conversations

# First turn
result = await run_in_jupyter(agent, "What's the weather in Tokyo?")

# Continue the conversation
result = await run_in_jupyter(
    agent,
    "What about London?",
    message_history=result.all_messages(),
)

Debug mode

Enable debug mode to see all events:

result = await run_in_jupyter(agent, "Hello!", debug=True)

Supported providers

Tool call argument streaming works best with OpenAI, which streams arguments token-by-token. Other providers like Groq and Ollama (via OpenAI-compat) buffer tool calls and send them all at once.

Provider	Text streaming	Tool call streaming
OpenAI	✅	✅
Groq	✅	❌ (buffered)
Ollama	✅	❌ (buffered)

Development

See TESTING.md for testing guidelines and PUBLISHING.md for release instructions.

# Install dependencies
uv sync --extra dev

# Run tests
uv run pytest tests/ -v

# Run linting
uv run ruff check .
uv run ruff format .

# Type checking
uv run mypy pydantic_ai_jupyter/

License

BSD 3-Clause