mirror of
https://github.com/microsoft/agent-framework.git
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Eduard van Valkenburg
95fd5ec658
* renamed AzureAIINferenceEmbeddings and lazy load azure-cosmos and env var rename * updated coverage * fix readme
99 lines
3.3 KiB
Python
99 lines
3.3 KiB
Python
# Copyright (c) Microsoft. All rights reserved.
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import asyncio
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import os
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from agent_framework import Agent
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from agent_framework.azure import CosmosHistoryProvider
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from agent_framework.foundry import FoundryChatClient
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from azure.identity.aio import AzureCliCredential
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from dotenv import load_dotenv
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# Load environment variables from .env file.
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load_dotenv()
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"""
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This sample demonstrates CosmosHistoryProvider as an agent history provider.
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Key components:
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- FoundryChatClient configured with an Azure AI project endpoint
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- CosmosHistoryProvider configured for Cosmos DB-backed message history
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- Provider-configured container name with session_id as partition key
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Environment variables:
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FOUNDRY_PROJECT_ENDPOINT
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FOUNDRY_MODEL
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AZURE_COSMOS_ENDPOINT
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AZURE_COSMOS_DATABASE_NAME
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AZURE_COSMOS_CONTAINER_NAME
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Optional:
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AZURE_COSMOS_KEY
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"""
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async def main() -> None:
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"""Run the Cosmos history provider sample with an Agent."""
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project_endpoint = os.getenv("FOUNDRY_PROJECT_ENDPOINT")
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model = os.getenv("FOUNDRY_MODEL")
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cosmos_endpoint = os.getenv("AZURE_COSMOS_ENDPOINT")
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cosmos_database_name = os.getenv("AZURE_COSMOS_DATABASE_NAME")
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cosmos_container_name = os.getenv("AZURE_COSMOS_CONTAINER_NAME")
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cosmos_key = os.getenv("AZURE_COSMOS_KEY")
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if (
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not project_endpoint
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or not model
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or not cosmos_endpoint
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or not cosmos_database_name
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or not cosmos_container_name
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):
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print(
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"Please set FOUNDRY_PROJECT_ENDPOINT, FOUNDRY_MODEL, "
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"AZURE_COSMOS_ENDPOINT, AZURE_COSMOS_DATABASE_NAME, and AZURE_COSMOS_CONTAINER_NAME."
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)
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return
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# 1. Create an Azure credential and a CosmosHistoryProvider for agent context
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async with (
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AzureCliCredential() as credential,
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CosmosHistoryProvider(
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endpoint=cosmos_endpoint,
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database_name=cosmos_database_name,
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container_name=cosmos_container_name,
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credential=cosmos_key or credential,
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) as history_provider,
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# 2. Create an agent that uses Cosmos for persisted conversation history.
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Agent(
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client=FoundryChatClient(
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project_endpoint=project_endpoint,
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model=model,
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credential=credential,
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),
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name="CosmosHistoryAgent",
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instructions="You are a helpful assistant that remembers prior turns.",
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context_providers=[history_provider],
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default_options={"store": False},
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) as agent,
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):
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# 3. Create a session (session_id is used as the partition key).
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session = agent.create_session()
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# 4. Run a multi-turn conversation; history is persisted by CosmosHistoryProvider.
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response1 = await agent.run("My name is Ada and I enjoy distributed systems.", session=session)
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print(f"Assistant: {response1.text}")
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response2 = await agent.run("What do you remember about me?", session=session)
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print(f"Assistant: {response2.text}")
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print(f"Container: {history_provider.container_name}")
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if __name__ == "__main__":
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asyncio.run(main())
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"""
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Sample output:
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Assistant: Nice to meet you, Ada! Distributed systems are a fascinating area.
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Assistant: You told me your name is Ada and that you enjoy distributed systems.
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Container: <AZURE_COSMOS_CONTAINER_NAME>
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"""
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