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datapizza-ai

Build reliable Gen AI solutions without overhead

datapizza-ai provides clear interfaces and predictable behavior for agents and RAG. End-to-end visibility and reliable orchestration keep engineers in control from PoC to scale

Installation

Install the library using pip:

pip install datapizza-ai

Key Features

  • Integration with AI Providers: Seamlessly connect with AI services like OpenAI and Google VertexAI.
  • Complex workflows, minimal code.: Design, automate, and scale powerful agent workflows without the overhead of boilerplate.
  • Retrieval-Augmented Generation (RAG): Enhance AI responses with document retrieval.
  • Faster delivery, easier onboarding for new engineers: Rebuild a RAG + tools agent without multi-class plumbing; parity with simpler, typed interfaces.
  • Up to 40% less debugging time: Trace and log every LLM/tool call with inputs/outputs

Quick Start

To get started with datapizza-ai, ensure you have Python >=3.10.0,<3.13.0 installed.

Here's a basic example demonstrating how to use agents in datapizza-ai:

from datapizza.agents import Agent
from datapizza.clients.openai import OpenAIClient
from datapizza.tools import tool

@tool
def get_weather(city: str) -> str:
    return f"The weather in {city} is sunny"

client = OpenAIClient(api_key="YOUR_API_KEY")
agent = Agent(name="assistant", client=client, tools = [get_weather])

response = agent.run("What is the weather in Rome?")
# output: The weather in Rome is sunny