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Document streamed tool call arguments

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lorenzejay
2026-07-02 11:33:26 -07:00
parent 559a9c65c4
commit b6a4af584d
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docs/edge/en/concepts/streaming.mdx
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@@ -61,6 +61,35 @@ Frames are grouped into high-level channels:
The stream itself remains one ordered timeline. Channel projections let consumers focus on only part of that timeline.
### Tool Call Streaming
Tool calls appear in two places because there are two distinct phases:
| Phase | Channel | Event type | Meaning |
|-------|---------|------------|---------|
| Tool-call construction | `llm` | `llm_stream_chunk` | The model is streaming the tool name or arguments it intends to call |
| Tool execution | `tools` | `tool_usage_started`, `tool_usage_finished`, `tool_usage_error` | CrewAI is executing the tool and reporting the result |
For streamed tool-call arguments, the latest provider delta is available as `frame.data["chunk"]`. The accumulated argument string is available at `frame.data["tool_call"]["function"]["arguments"]`.
```python
with llm.stream_events("Check the weather in Paris.", tools=[weather_tool]) as stream:
for frame in stream.llm:
if frame.type != "llm_stream_chunk":
continue
tool_call = frame.data.get("tool_call")
if tool_call:
function = tool_call["function"]
print("Tool:", function["name"])
print("Latest argument delta:", frame.data["chunk"])
print("Arguments so far:", function["arguments"])
elif frame.content:
print(frame.content, end="", flush=True)
```
Use the `tools` channel when you want to display that a tool actually started, completed, or failed. Use the `llm` channel when you want to observe the model constructing the tool call before execution.
```mermaid
flowchart LR
A["flow<br/>flow_started"] --> B["llm<br/>llm_call_started"]