Skip to content
Merged
Changes from all commits
Commits
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
2 changes: 1 addition & 1 deletion docs/multi_agent.md
Original file line number Diff line number Diff line change
Expand Up @@ -34,4 +34,4 @@ While orchestrating via LLM is powerful, orchestrating via LLM makes tasks more
- Running the agent that performs the task in a `while` loop with an agent that evaluates and provides feedback, until the evaluator says the output passes certain criteria.
- Running multiple agents in parallel, e.g. via Python primitives like `asyncio.gather`. This is useful for speed when you have multiple tasks that don't depend on each other.

We have a number of examples in [`examples/agent_patterns`](https://github.com/openai/openai-agents-python/examples/agent_patterns).
We have a number of examples in [`examples/agent_patterns`](https://github.com/openai/openai-agents-python/tree/main/examples/agent_patterns).