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Merge pull request #95 from ks6088ts-labs/feature/issue-94_azure-ai-foundry
add Azure AI Foundry operator
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‎.env.template‎

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@@ -20,6 +20,11 @@ AZURE_OPENAI_MODEL_CHAT="gpt-5"
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AZURE_OPENAI_MODEL_EMBEDDING="text-embedding-3-small"
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AZURE_OPENAI_MODEL_REASONING="o4-mini"
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## Azure AI Foundry
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AZURE_AI_FOUNDRY_INFERENCE_ENDPOINT="https://xxx.services.ai.azure.com/api/projects/xxx"
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AZURE_AI_FOUNDRY_INFERENCE_API_VERSION="2025-04-01-preview"
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AZURE_AI_FOUNDRY_INFERENCE_MODEL_CHAT="gpt-5"
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## Ollama Settings
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OLLAMA_MODEL_CHAT="gemma3:270m"
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‎docs/references.md‎

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- [Azure Cosmos DB No SQL](https://python.langchain.com/docs/integrations/vectorstores/azure_cosmos_db_no_sql/)
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- [Azure AI Search](https://python.langchain.com/docs/integrations/vectorstores/azuresearch/)
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### Azure AI Foundry
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- [Quickstart: Get started with Azure AI Foundry](https://learn.microsoft.com/azure/ai-foundry/quickstarts/get-started-code?tabs=python&pivots=fdp-project)
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- [azure-rest-api-specs/specification/ai/data-plane/Azure.AI.Agents](https://github.com/Azure/azure-rest-api-specs/tree/main/specification/ai/data-plane/Azure.AI.Agents)
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### Services
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- [FastAPI](https://fastapi.tiangolo.com/)

‎pyproject.toml‎

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@@ -5,6 +5,7 @@ description = "A GitHub template repository for Python"
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readme = "README.md"
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requires-python = ">=3.10"
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dependencies = [
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"azure-ai-projects>=1.0.0",
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"azure-cosmos>=4.9.0",
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"azure-identity>=1.23.1",
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"azure-search-documents>=11.5.3",

‎scripts/azure_ai_foundry_operator.py‎

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import logging
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import typer
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from dotenv import load_dotenv
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from template_langgraph.llms.azure_ai_foundrys import AzureAiFoundryWrapper
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from template_langgraph.loggers import get_logger
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# Initialize the Typer application
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app = typer.Typer(
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add_completion=False,
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help="Azure AI Foundry operator CLI",
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)
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# Set up logging
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logger = get_logger(__name__)
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@app.command()
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def chat(
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query: str = typer.Option(
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"Hello",
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"--query",
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"-q",
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help="The query to send to the AI",
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),
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verbose: bool = typer.Option(
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False,
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"--verbose",
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"-v",
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help="Enable verbose output",
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),
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):
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# Set up logging
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if verbose:
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logger.setLevel(logging.DEBUG)
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logger.info("Running Azure AI Foundry chat...")
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wrapper = AzureAiFoundryWrapper()
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openai_client = wrapper.get_openai_client()
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response = openai_client.chat.completions.create(
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model=wrapper.settings.azure_ai_foundry_inference_model_chat,
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messages=[
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{"role": "user", "content": query},
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],
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)
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logger.info(response.choices[0].message.content)
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@app.command()
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def create_agent(
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name: str = typer.Option(
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"MyAgent",
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"--name",
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"-n",
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help="The name of the agent",
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),
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instructions: str = typer.Option(
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"This is my agent",
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"--instructions",
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"-i",
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help="The instructions for the agent",
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),
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verbose: bool = typer.Option(
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False,
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"--verbose",
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"-v",
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help="Enable verbose output",
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),
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):
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# Set up logging
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if verbose:
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logger.setLevel(logging.DEBUG)
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logger.info("Creating agent...")
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project_client = AzureAiFoundryWrapper().get_ai_project_client()
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with project_client.agents as agents_client:
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# Create a new agent
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agent = agents_client.create_agent(
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name=name,
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instructions=instructions,
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model=AzureAiFoundryWrapper().settings.azure_ai_foundry_inference_model_chat,
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)
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logger.info(f"Created agent: {agent.as_dict()}")
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@app.command()
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def delete_agent(
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agent_id: str = typer.Option(
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"asst_xxx",
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"--agent-id",
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"-a",
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help="The ID of the agent to delete",
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),
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verbose: bool = typer.Option(
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False,
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"--verbose",
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"-v",
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help="Enable verbose output",
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),
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):
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# Set up logging
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if verbose:
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logger.setLevel(logging.DEBUG)
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logger.info("Deleting agent...")
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project_client = AzureAiFoundryWrapper().get_ai_project_client()
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with project_client.agents as agents_client:
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agents_client.delete_agent(agent_id=agent_id)
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@app.command()
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def list_agents(
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verbose: bool = typer.Option(
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False,
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"--verbose",
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"-v",
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help="Enable verbose output",
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),
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):
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# Set up logging
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if verbose:
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logger.setLevel(logging.DEBUG)
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logger.info("Listing agents...")
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project_client = AzureAiFoundryWrapper().get_ai_project_client()
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with project_client.agents as agents_client:
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agents = agents_client.list_agents()
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for agent in agents:
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logger.info(f"Agent ID: {agent.id}, Name: {agent.name}")
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@app.command()
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def create_thread(
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verbose: bool = typer.Option(
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False,
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"--verbose",
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"-v",
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help="Enable verbose output",
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),
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):
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# Set up logging
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if verbose:
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logger.setLevel(logging.DEBUG)
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logger.info("Creating thread...")
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project_client = AzureAiFoundryWrapper().get_ai_project_client()
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thread = project_client.agents.threads.create()
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logger.info(thread.as_dict())
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@app.command()
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def delete_thread(
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thread_id: str = typer.Option(
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"thread_xxx",
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"--thread-id",
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"-t",
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help="The ID of the thread to delete",
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),
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verbose: bool = typer.Option(
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False,
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"--verbose",
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"-v",
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help="Enable verbose output",
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),
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):
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# Set up logging
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if verbose:
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logger.setLevel(logging.DEBUG)
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logger.info("Deleting thread...")
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project_client = AzureAiFoundryWrapper().get_ai_project_client()
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project_client.agents.threads.delete(thread_id=thread_id)
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@app.command()
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def list_threads(
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verbose: bool = typer.Option(
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False,
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"--verbose",
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"-v",
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help="Enable verbose output",
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),
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):
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# Set up logging
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if verbose:
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logger.setLevel(logging.DEBUG)
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logger.info("Listing threads...")
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project_client = AzureAiFoundryWrapper().get_ai_project_client()
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threads = project_client.agents.threads.list()
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for thread in threads:
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logger.info(thread.as_dict())
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@app.command()
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def create_message(
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role: str = typer.Option(
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"user",
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"--role",
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"-r",
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help="The role of the message sender",
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),
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content: str = typer.Option(
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"Hello, world!",
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"--content",
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"-c",
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help="The content of the message",
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),
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thread_id: str = typer.Option(
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"thread_xxx",
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"--thread-id",
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"-t",
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help="The ID of the thread to list messages from",
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),
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verbose: bool = typer.Option(
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False,
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"--verbose",
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"-v",
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help="Enable verbose output",
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),
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):
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# Set up logging
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if verbose:
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logger.setLevel(logging.DEBUG)
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logger.info("Creating message...")
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project_client = AzureAiFoundryWrapper().get_ai_project_client()
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message = project_client.agents.messages.create(
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thread_id=thread_id,
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role=role,
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content=content,
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)
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logger.info(message.as_dict())
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@app.command()
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def list_messages(
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thread_id: str = typer.Option(
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"thread_xxx",
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"--thread-id",
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"-t",
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help="The ID of the thread to list messages from",
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),
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verbose: bool = typer.Option(
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False,
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"--verbose",
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"-v",
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help="Enable verbose output",
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),
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):
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# Set up logging
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if verbose:
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logger.setLevel(logging.DEBUG)
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logger.info("Listing messages...")
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project_client = AzureAiFoundryWrapper().get_ai_project_client()
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messages = project_client.agents.messages.list(thread_id=thread_id)
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for message in messages:
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logger.info(message.as_dict())
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@app.command()
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def run_thread(
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agent_id: str = typer.Option(
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"agent_xxx",
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"--agent-id",
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"-a",
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help="The ID of the agent to run",
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),
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thread_id: str = typer.Option(
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"thread_xxx",
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"--thread-id",
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"-t",
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help="The ID of the thread to run",
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),
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verbose: bool = typer.Option(
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False,
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"--verbose",
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"-v",
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help="Enable verbose output",
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),
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):
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# Set up logging
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if verbose:
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logger.setLevel(logging.DEBUG)
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logger.info("Running thread...")
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project_client = AzureAiFoundryWrapper().get_ai_project_client()
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run = project_client.agents.runs.create(
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thread_id=thread_id,
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agent_id=agent_id,
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)
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logger.info(f"Run created: {run.as_dict()}")
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@app.command()
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def get_run(
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thread_id: str = typer.Option(
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"thread_xxx",
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"--thread-id",
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"-t",
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help="The ID of the thread to run",
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),
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run_id: str = typer.Option(
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"run_xxx",
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"--run-id",
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"-r",
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help="The ID of the run to retrieve",
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),
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verbose: bool = typer.Option(
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False,
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"--verbose",
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"-v",
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help="Enable verbose output",
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),
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):
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# Set up logging
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if verbose:
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logger.setLevel(logging.DEBUG)
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logger.info("Getting run...")
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project_client = AzureAiFoundryWrapper().get_ai_project_client()
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run = project_client.agents.runs.get(
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thread_id=thread_id,
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run_id=run_id,
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)
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logger.info(run.as_dict())
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if __name__ == "__main__":
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load_dotenv(
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override=True,
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verbose=True,
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)
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app()

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