{#- Landing page: hero (logo + text) → example → features → install. Selected via `template: home.html` in index.md front matter. Extends main.html so the header/nav bar is preserved. -#} {% extends "main.html" %} {% block tabs %} {{ super() }} {# Page-scoped resets: only active when this template is rendered. #} {# ── Hero ─────────────────────────────────────────────────────── #}

Multimodal orchestration for LLM APIs

You describe what to analyze. Pollux handles source patterns, context caching, and multimodal complexity — so you don’t.

{# ── Example ──────────────────────────────────────────────────── #}
from pollux import run, Config, Source

result = await run(
    "Summarize the key findings",
    source=Source.from_file("paper.pdf"),
    config=Config(
        provider="gemini",
        model="gemini-2.5-flash-lite",
    ),
)
print(result["answers"][0])
{# ── Features ─────────────────────────────────────────────────── #}

Multimodal-first

PDFs, images, video, YouTube, arXiv. One interface, any source type.

Source patterns

Fan-out, fan-in, and broadcast execution over your content — no boilerplate.

Context caching

Upload once, reuse across prompts. Automatic TTL management saves tokens and money.

Built for reliability

Async pipeline, retries with backoff, structured output, usage tracking.

{# ── Install ──────────────────────────────────────────────────── #}
pip install pollux-ai
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