pollux-ai 1.4.0

Multimodal orchestration for LLM analysis

Pollux

Multimodal orchestration for LLM APIs.

You describe what to analyze. Pollux handles source patterns, context caching, and multimodal content, so you don't.

Documentation · Getting Started

Quick Start

import asyncio
from pollux import Config, Source, run

result = asyncio.run(
    run(
        "What are the key findings and their implications?",
        source=Source.from_file("earnings-report.pdf"),
        config=Config(provider="gemini", model="gemini-2.5-flash-lite"),
    )
)
print(result["answers"][0])
# Revenue grew 18% YoY to $4.2B, driven by cloud services. Operating
# margins improved from 29% to 34%. Management's $2B buyback and raised
# guidance signal confidence in sustained growth.

run() returns a ResultEnvelope: answers holds one entry per prompt.

To use OpenAI instead: Config(provider="openai", model="gpt-5-nano"). For Anthropic: Config(provider="anthropic", model="claude-haiku-4-5"). For OpenRouter: Config(provider="openrouter", model="google/gemma-3-27b-it:free").

For a full walkthrough (install, key setup, first result), see Getting Started.

What Problems Does Pollux Solve?

Say you have a document and ten questions about it. Each API call re-uploads the file, and you're left managing caching, retries, and concurrency yourself. Pollux uploads once, caches the content, fans out your prompts concurrently, and hands back results.

The same Source interface handles PDFs, images, video, YouTube URLs, and arXiv papers. No per-format upload code.

Need structured output? Pass a Pydantic model as response_schema and get a validated instance alongside the raw text. Switching providers is a one-line change: provider="gemini" to provider="openai".

One Upload, Many Prompts

Got three questions about the same paper? run_many() fans them out concurrently:

import asyncio
from pollux import Config, Source, run_many

envelope = asyncio.run(
    run_many(
        ["Summarize the methodology.", "List key findings.", "Identify limitations."],
        sources=[Source.from_file("paper.pdf")],
        config=Config(provider="gemini", model="gemini-2.5-flash-lite"),
    )
)
for answer in envelope["answers"]:
    print(answer)

Add more sources and Pollux broadcasts every prompt across every source, uploading each once regardless of how many prompts reference it.

Where Pollux Ends

Pollux owns content delivery, context caching, and provider translation. Prompt design, workflow orchestration, and what you do with results are yours. See Core Concepts for the full boundary model.

Installation

pip install pollux-ai

Set your provider's API key:

export GEMINI_API_KEY="your-key-here"     # or
export OPENAI_API_KEY="your-key-here"     # or
export ANTHROPIC_API_KEY="your-key-here"  # or
export OPENROUTER_API_KEY="your-key-here"

Keys from: Google AI Studio · OpenAI · Anthropic · OpenRouter

Documentation

• Getting Started: first result in 2 minutes
• Core Concepts: mental model and vocabulary
• API Reference: entry points and types
• Cookbook: runnable end-to-end recipes

Full docs at polluxlib.dev.

Contributing

See CONTRIBUTING and TESTING.md for guidelines.

Built during Google Summer of Code 2025 with Google DeepMind. Learn more

License

MIT