Skip to content

Add multi-worker handoff example combining Flows with the worker framework #280

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
markbackman merged 2 commits into from
Jun 5, 2026
Merged

Add multi-worker handoff example combining Flows with the worker framework #280

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
2 commits
Select commit Hold shift + click to select a range
b2e1119
Add multi-worker handoff example combining Flows with the worker fram…
aconchillo Jun 4, 2026
6e55c84
Rename changelog fragment to PR #280
aconchillo Jun 4, 2026
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
1 change: 1 addition & 0 deletions changelog/280.added.md
View file
Open in desktop
Original file line number Diff line number Diff line change
@@ -0,0 +1 @@
- Added `multi_worker_handoff.py` example showing how to compose Pipecat Flows with Pipecat's multi-worker framework. A structured Flows reservation worker (built as a plain `PipelineWorker` with a `FlowManager` wired onto it) hands off to and from a free-form `LLMWorker` router over the bus, sharing a single conversation context.
1 change: 1 addition & 0 deletions examples/README.md
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -26,6 +26,7 @@ See [quickstart/README.md](./quickstart/README.md) for a beginner-friendly intro
#### Advanced Features

- `warm_transfer.py` - Transferring calls between different flows (DailyTransport only)
- `multi_worker_handoff.py` - Composing Flows with Pipecat's multi-worker framework: a structured Flows reservation worker hands off to and from a free-form `LLMWorker` router over the bus, sharing a single conversation context

**Note:** All examples support multiple LLM providers (OpenAI, Anthropic, Google, AWS Bedrock) and transport options unless otherwise specified. Pipecat Flows handles the different function calling formats internally while maintaining a consistent API for developers.

Expand Down
Loading
Loading