GenAI Processors is a lightweight Python library that enables efficient, parallel content processing.

GenAI Processors Library 📚

Build Modular, Asynchronous, and Composable AI Pipelines for Generative AI.

GenAI Processors is a lightweight Python library that enables efficient, parallel content processing. It addresses the fragmentation of LLM APIs through three core pillars:

1. Unified Content Model: A single, consistent representation for inputs and outputs across models, agents, and tools.
2. Processors: Simple, composable Python classes that transform content streams using native asyncio.
3. Streaming: Asynchronous streaming capabilities built-in by default, without added plumbing complexity.

At the ecosystem's core lies the Processor, which encapsulates a unit of work. Through a "dual-interface" pattern, it handles the complexity of asynchronous, multimodal data streaming while exposing a simple API to developers:

from typing import AsyncIterable
from genai_processors import content_api
from genai_processors import processor

class EchoProcessor(processor.Processor):
  # The PRODUCER interface (for the processor author):
  # Takes a robust ProcessorStream as input, and yields part types.
  async def call(
      self, content: content_api.ProcessorStream
  ) -> AsyncIterable[content_api.ProcessorPartTypes]:
      # Process content as it streams in!
      async for part in content:
          yield part

Applying a Processor is just as straightforward. The CONSUMER interface accepts wide, forgiving input types and returns a powerful stream that can be awaited entirely or streamed chunk-by-chunk:

# The CONSUMER interface (for the caller):
# Provide input effortless