Pipecat is an open-source Python framework for building real-time conversational agents that work with voice, video, images, and other media. It is for creating voice assistants, companions, business agents, and multi-agent systems from modular conversation pipelines.
Borrowing it
Nothing to install: this file belongs to pipecat-ai/pipecat. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/pipecat-ai/pipecat/main/AGENTS.mdgit clone --depth 1 https://github.com/pipecat-ai/pipecatWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/instructions/pipecat-ai/pipecat/agents-md)<a href="https://agentmods.dev/instructions/pipecat-ai/pipecat/agents-md"><img src="https://agentmods.dev/badge/instructions/pipecat-ai/pipecat/agents-md/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/instructions/pipecat-ai/pipecat/agents-md"><img src="https://agentmods.dev/badge/instructions/pipecat-ai/pipecat/agents-md.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.05362 | $0.05362 |
| Opus 5.5 | $0.02145 | $0.02145 |
| Sonnet 5.5 | $0.01072 | $0.01072 |
| Haiku 4.5 | $0.00536 | $0.00536 |
Grade A, and why
pipecat AGENTS.md scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 242 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AGENTS.md
This file provides guidance to AI coding agents when working with code in this repository.
Project Overview
Pipecat is an open-source Python framework for building real-time voice and multimodal conversational AI agents. It orchestrates audio/video, AI services, transports, and conversation pipelines using a frame-based architecture.
Common Commands
# Setup development environment
uv sync --group dev --all-extras --no-extra gstreamer --no-extra local
# Install pre-commit hooks
uv run pre-commit install
# Run all tests
uv run pytest
# Run a single test file
uv run pytest tests/test_name.py
# Run a specific test
uv run pytest tests/test_name.py::test_function_name
# Preview changelog
uv run towncrier build --draft --version Unreleased
# Run a behavioral eval scenario against a running bot (started with `python bot.py`)
pipecat eval run scenarios/<name>.yaml --bot-url ws://localhost:7860/ws
# Run the full release-eval suite (spawns bots from a manifest, runs scenarios in parallel)
pipecat eval suite evals/release/manifest.yaml -p <bot-pattern> -s <scenario>
# Judge saved simulation conversations (<stem>.conversation.json) again, without the bot
pipecat eval judge scenarios/<name>.yaml -s <scenario> logs/*.conversation.json -o judged.jsonl
# Lint and format check
uv run ruff check
uv run ruff format --check
# Update dependencies (after editing pyproject.toml)
uv lock && uv sync
# Refresh the Pipecat UI component snapshot vendored into the CLI's React client templates
node scripts/cli/sync-pipecat-ui.mjs
Architecture
Frame-Based Pipeline Processing
All data flows as Frame objects through a pipeline of FrameProcessors:
[Processor1] → [Processor2] → ... → [ProcessorN]
Key components:
-
Frames (
src/pipecat/frames/frames.py): Data units (audio, text, video) and control signals. Flow DOWNSTREAM (input→output) or UPSTREAM (acknowledgments/errors). -
FrameProcessor (
src/pipecat/processors/frame_processor.py): Base processing unit. Each processor receives frames, processes them, and pushes results downstream.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2d ago Changed · +5 lines · +211 tokens per session 86487967c6ea
- 7d ago Changed · -2 tokens per session 5835bb3f3448
- 11d ago Changed · +39 tokens per session 8e9deb7c9a3b
- 20d ago Changed e4bbe45162d7
- 23d ago Changed · +24 tokens per session ae0a051f1f65
- 1mo ago Changed · +54 tokens per session 9902956b57e0
- 1mo ago Changed · +25 tokens per session fc584e4ee5bd
- 1mo ago Changed · +4 lines · +268 tokens per session d76816c0fab0
- 1mo ago Changed · +2 lines · +127 tokens per session 5bb5deff1aac
- 1mo ago First seen · 231 lines · 4,616 tokens per session scan A b0d657e3e785
pipecat AGENTS.md is an instructions file published in the GitHub repository pipecat-ai/pipecat (16,618 stars, last pushed today), licensed BSD-2-Clause. It adds 5,362 tokens to every session, about $0.0214 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other instructions, from other repositories
vscode buildNext.instructions.md
Working notes and architecture documentation for the new esbuild-based build system in build/next. Use when making changes to the new build pipeline (transpile/bundle commands, NLS plugin, source-map handling, resource copying, or self-hosting watch tasks).
next.js AGENTS.md
AGENTS.md instructions for vercel/next.js, covering next.js development guide, codebase structure, monorepo overview, core package: packages/next and other important packages.
vscode oss-third-party-notices.instructions.md
Instructions for microsoft/vscode, covering vs code oss third-party-notices pipeline, architecture, pipeline flow in ci, cache eligibility and rollout and applying the notice (cutover).
langchain AGENTS.md
AGENTS.md instructions for langchain-ai/langchain, covering global development guidelines for the langchain monorepo, corridor security analysis, project architecture and context, monorepo structure and development tools & commands.
vscode copilot-instructions.md
Copilot instructions for microsoft/vscode, covering vs code copilot instructions, project overview, root folders, core architecture (src/ folder) and built-in extensions (extensions/ folder).
deepseek-harness AGENTS.md
AGENTS.md instructions for deepseek-ai/deepseek-harness, covering agents.md, pre-stable apis and released session data, repository layout, commands and host sandbox failures.