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Python: Fix samples (#4980)

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* First samples 1st batch

* Fix sample paths

* Fix workflow samples

* Fix workflow dependency

* Correct env vars

* Increase idle timeout

* Fix workflows HIL sample

* Fix more workflow samples
This commit is contained in:
Tao Chen
2026-03-31 08:20:35 -07:00
committed by GitHub
Unverified
parent 0f81c277d9
commit 016daf3b98
69 changed files with 234 additions and 306 deletions
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python/samples/03-workflows/checkpoint/checkpoint_with_human_in_the_loop.py
+1 -1
View File
@@ -182,7 +182,7 @@ def create_workflow(checkpoint_storage: FileCheckpointStorage) -> Workflow:
writer_agent = Agent(
client=FoundryChatClient(
project_endpoint=os.environ["FOUNDRY_PROJECT_ENDPOINT"],
model=os.environ["AZURE_AI_MODEL_DEPLOYMENT_NAME"],
model=os.environ["FOUNDRY_MODEL"],
credential=AzureCliCredential(),
),
instructions="Write concise, warm release notes that sound human and helpful.",
python/samples/03-workflows/checkpoint/workflow_as_agent_checkpoint.py
+7 -7
View File
@@ -21,7 +21,7 @@ Key concepts:
Prerequisites:
- FOUNDRY_PROJECT_ENDPOINT must be your Azure AI Foundry Agent Service (V2) project endpoint.
- Environment variables configured for FoundryChatClient
- FOUNDRY_MODEL must be set to your Azure OpenAI model deployment name.
"""
import asyncio
@@ -50,7 +50,7 @@ async def basic_checkpointing() -> None:
client = FoundryChatClient(
project_endpoint=os.environ["FOUNDRY_PROJECT_ENDPOINT"],
model=os.environ["AZURE_AI_MODEL_DEPLOYMENT_NAME"],
model=os.environ["FOUNDRY_MODEL"],
credential=AzureCliCredential(),
)
@@ -67,7 +67,7 @@ async def basic_checkpointing() -> None:
)
workflow = SequentialBuilder(participants=[assistant, reviewer]).build()
agent = Agent(client=workflow, name="CheckpointedAgent")
agent = workflow.as_agent()
# Create checkpoint storage
checkpoint_storage = InMemoryCheckpointStorage()
@@ -97,7 +97,7 @@ async def checkpointing_with_thread() -> None:
client = FoundryChatClient(
project_endpoint=os.environ["FOUNDRY_PROJECT_ENDPOINT"],
model=os.environ["AZURE_AI_MODEL_DEPLOYMENT_NAME"],
model=os.environ["FOUNDRY_MODEL"],
credential=AzureCliCredential(),
)
@@ -108,7 +108,7 @@ async def checkpointing_with_thread() -> None:
)
workflow = SequentialBuilder(participants=[assistant]).build()
agent = Agent(client=workflow, name="MemoryAgent")
agent = workflow.as_agent()
# Create both session (for conversation) and checkpoint storage (for workflow state)
session = agent.create_session()
@@ -145,7 +145,7 @@ async def streaming_with_checkpoints() -> None:
client = FoundryChatClient(
project_endpoint=os.environ["FOUNDRY_PROJECT_ENDPOINT"],
model=os.environ["AZURE_AI_MODEL_DEPLOYMENT_NAME"],
model=os.environ["FOUNDRY_MODEL"],
credential=AzureCliCredential(),
)
@@ -156,7 +156,7 @@ async def streaming_with_checkpoints() -> None:
)
workflow = SequentialBuilder(participants=[assistant]).build()
agent = Agent(client=workflow, name="StreamingCheckpointAgent")
agent = workflow.as_agent()
checkpoint_storage = InMemoryCheckpointStorage()