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docs: add missing pre flag (#1130)

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Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com>
This commit is contained in:
Vincent Koc
2025-10-02 11:50:47 -07:00
committed by GitHub
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parent d5fe617285
commit 2696de7428
14 changed files with 22 additions and 24 deletions
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python/samples/getting_started/workflows/README.md
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@@ -7,7 +7,7 @@ Microsoft Agent Framework Workflows support ships with the core `agent-framework
To install with visualization support:
```bash
pip install agent-framework[viz]
pip install agent-framework[viz] --pre
```
To export visualization images you also need to [install GraphViz](https://graphviz.org/download/).
python/samples/getting_started/workflows/parallelism/map_reduce_and_visualization.py
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@@ -296,7 +296,7 @@ async def main():
svg_file = viz.export(format="svg")
print(f"SVG file saved to: {svg_file}")
except ImportError:
print("Tip: Install 'viz' extra to export workflow visualization: pip install agent-framework[viz]")
print("Tip: Install 'viz' extra to export workflow visualization: pip install agent-framework[viz] --pre")
# Step 3: Open the text file and read its content.
async with aiofiles.open(os.path.join(DIR, "../resources", "long_text.txt"), "r") as f:
python/samples/getting_started/workflows/visualization/concurrent_with_visualization.py
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@@ -32,7 +32,7 @@ What it does:
Prerequisites:
- Azure AI/ Azure OpenAI for `AzureOpenAIChatClient` agents.
- Authentication via `azure-identity` — uses `AzureCliCredential()` (run `az login`).
- For visualization export: `pip install agent-framework[viz]` and install GraphViz binaries.
- For visualization export: `pip install agent-framework[viz] --pre` and install GraphViz binaries.
"""
@@ -162,7 +162,7 @@ async def main() -> None:
svg_file = viz.export(format="svg")
print(f"SVG file saved to: {svg_file}")
except ImportError:
print("Tip: Install 'viz' extra to export workflow visualization: pip install agent-framework[viz]")
print("Tip: Install 'viz' extra to export workflow visualization: pip install agent-framework[viz] --pre")
# 3) Run with a single prompt
async for event in workflow.run_stream("We are launching a new budget-friendly electric bike for urban commuters."):