pipecat-primd 0.1.0

Sub-millisecond predictive retrieval plugin for Pipecat. Open-source VoiceAgentRAG.

pipecat-primd

Sub-millisecond predictive retrieval for Pipecat. Open-source VoiceAgentRAG.

pipecat-primd is a Pipecat FrameProcessor that connects a voice pipeline to primd — a Rust retrieval runtime that speculates on partial transcripts during STT and pre-warms next-turn answers during TTS.

End-of-utterance retrieval drops from ~157 µs (naive SIMD scan) to ~1.6 µs when speculation matches — 98× faster, deterministically, on a 100k-doc corpus.

Install

pip install pipecat-primd

You also need primd running locally:

cargo install primd-cli
primd index --input examples/faq.jsonl --out /tmp/primd-faq --embedder hashed
primd serve --index /tmp/primd-faq --bind 127.0.0.1:8080

Use

from pipecat.pipeline.pipeline import Pipeline
from pipecat_primd import PrimdRetriever

retriever = PrimdRetriever(
    primd_url="http://127.0.0.1:8080",
    top_k=5,
    corpus_text={"faq-001": "We offer a 14-day free trial...", ...},
)

pipeline = Pipeline([
    transport.input(),
    stt,
    retriever,                # ← interim → /observe, final → /finalize, bot speak → /warm
    context_aggregator.user(),
    llm,
    tts,
    transport.output(),
    context_aggregator.assistant(),
])

That's it. The retriever:

• feeds InterimTranscriptionFrame into primd's /session/{id}/observe so primd starts retrieving while the user is still speaking,
• hits /session/{id}/finalize on TranscriptionFrame — if the partial converged on the final, returns from a sub-microsecond cache,
• calls /session/{id}/warm on BotStartedSpeakingFrame so the next turn is already pre-scoped before STT lands.

Standalone Client

If you want primd retrieval without Pipecat (CLI tools, batch jobs, custom pipelines):

import asyncio
from pipecat_primd import PrimdClient

async def main() -> None:
    async with PrimdClient("http://127.0.0.1:8080") as primd:
        result = await primd.query("is there a free trial", top_k=3)
        for hit in result.hits:
            print(f"{hit.rank}: {hit.id} ({hit.event}) dist={hit.distance}")

asyncio.run(main())

The client also exposes the session methods directly: observe, finalize, warm, reset.

Why session calls?

/query is convenient but doesn't unlock the latency win — primd has no idea what's coming until you call it. The session API lets primd:

1. Speculate on partial transcripts during STT (no critical-path cost).
2. Short-circuit /finalize if the partial converged on the final — cache hit, microseconds.
3. Pre-warm the predictor's scope during TTS so the next turn's /observe is already constrained.

This is the dual-agent fast-talker / slow-thinker pattern from Salesforce VoiceAgentRAG, wired up.

Compatibility

Tested against Pipecat 0.0.49+. Frame names occasionally shift between Pipecat releases — if your version renames InterimTranscriptionFrame, TranscriptionFrame, or BotStartedSpeakingFrame, update the imports in pipecat_primd/retriever.py.

License

Apache-2.0