mirror of
https://github.com/microsoft/agent-framework.git
synced 2026-06-16 21:04:09 +08:00
5e056b672e
* Python: Provider-leading client design & OpenAI package extraction Major refactoring of the Python Agent Framework client architecture: - Extract OpenAI clients into new `agent-framework-openai` package - Core package no longer depends on openai, azure-identity, azure-ai-projects - Rename clients for discoverability: OpenAIResponsesClient → OpenAIChatClient, OpenAIChatClient → OpenAIChatCompletionClient - Unify `model_id`/`deployment_name`/`model_deployment_name` → `model` param - New FoundryChatClient for Azure AI Foundry Responses API - New FoundryAgent/FoundryAgentClient for connecting to pre-configured Foundry agents - Remove OpenAIBase/OpenAIConfigMixin from non-deprecated client MRO - Deprecate AzureOpenAI* clients, AzureAIClient, OpenAIAssistantsClient - Reorganize samples: azure_openai+azure_ai+azure_ai_agent → azure/ - ADR-0020: Provider-Leading Client Design Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fix: missing Agent imports in samples, .model_id → .model in foundry_local sample Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fix: CI failures — mypy errors, coverage targets, sample imports - azure-ai mypy: add type ignores for TypedDict total=, model arg, forward ref - Coverage: replace core.azure/openai targets with openai package target - project_provider: add type annotation for opts dict Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fix: populate openai .pyi stub, fix broken README links, coverage targets Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fixes * updated observabilitty * reset azure init.pyi * fix errors * updated adr number * fix foundry local * fixed not renamed docstrings and comments, and added deprecated markers to old classes * fix tests and pyprojects * fix test vars * updated function tests * update durable * updated test setup for functions * Fix Foundry auth in workflow samples Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Stabilize Python integration workflows Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Update hosting samples for Foundry Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Trigger full CI rerun Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Trigger CI rerun again Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * trigger rerun * trigger rerun * fix for litellm * undo durabletask changes * Move Foundry APIs into foundry namespace Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Fix Foundry pyproject formatting Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Split provider samples by Foundry surface Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Restore hosting sample requirements Also fix the Foundry Local sample link after the provider sample move. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * updated tests * udpated foundry integration tests * removed dist from azurefunctions tests * Use separate Foundry clients for concurrent agents Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fix client setup in azfunc and durable * disabled two tests * updated setup for some function and durable tests * improved azure openai setup with new clients * ignore deprecated * fixes * skip 11 * remove openai assistants int tests --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
129 lines
4.3 KiB
Python
129 lines
4.3 KiB
Python
# Copyright (c) Microsoft. All rights reserved.
|
|
"""Sample agent using Azure OpenAI Responses API for Agent Framework DevUI.
|
|
|
|
This agent uses the Responses API which supports:
|
|
- PDF file uploads
|
|
- Image uploads
|
|
- Audio inputs
|
|
- And other multimodal content
|
|
|
|
The Chat Completions API (FoundryChatClient) does NOT support PDF uploads.
|
|
Use this agent when you need to process documents or other file types.
|
|
|
|
Required environment variables:
|
|
- AZURE_OPENAI_ENDPOINT: Your Azure OpenAI endpoint
|
|
- FOUNDRY_MODEL: Deployment name for Responses API
|
|
(falls back to FOUNDRY_MODEL if not set)
|
|
- AZURE_OPENAI_API_KEY: Your API key (or use Azure CLI auth)
|
|
"""
|
|
|
|
import logging
|
|
import os
|
|
from typing import Annotated
|
|
|
|
from agent_framework import Agent, tool
|
|
from agent_framework.foundry import FoundryChatClient
|
|
from dotenv import load_dotenv
|
|
|
|
# Load environment variables from .env file
|
|
load_dotenv()
|
|
|
|
logger = logging.getLogger(__name__)
|
|
|
|
# Get deployment name - try responses-specific env var first, fall back to chat deployment
|
|
_deployment_name = os.environ.get(
|
|
"FOUNDRY_MODEL",
|
|
os.environ.get("FOUNDRY_MODEL", ""),
|
|
)
|
|
|
|
# Get endpoint - try responses-specific env var first, fall back to default
|
|
_endpoint = os.environ.get(
|
|
"AZURE_OPENAI_RESPONSES_ENDPOINT",
|
|
os.environ.get("AZURE_OPENAI_ENDPOINT", ""),
|
|
)
|
|
|
|
|
|
def analyze_content(
|
|
query: Annotated[str, "What to analyze or extract from the uploaded content"],
|
|
) -> str:
|
|
"""Analyze uploaded content based on the user's query.
|
|
|
|
This is a placeholder - the actual analysis is done by the model
|
|
when processing the uploaded files.
|
|
"""
|
|
return f"Analyzing content for: {query}"
|
|
|
|
|
|
# NOTE: approval_mode="never_require" is for sample brevity. Use "always_require" in production; see samples/02-agents/tools/function_tool_with_approval.py and samples/02-agents/tools/function_tool_with_approval_and_sessions.py.
|
|
@tool(approval_mode="never_require")
|
|
def summarize_document(
|
|
length: Annotated[str, "Desired summary length: 'brief', 'medium', or 'detailed'"] = "medium",
|
|
) -> str:
|
|
"""Generate a summary of the uploaded document."""
|
|
return f"Generating {length} summary of the document..."
|
|
|
|
|
|
@tool(approval_mode="never_require")
|
|
def extract_key_points(
|
|
max_points: Annotated[int, "Maximum number of key points to extract"] = 5,
|
|
) -> str:
|
|
"""Extract key points from the uploaded document."""
|
|
return f"Extracting up to {max_points} key points..."
|
|
|
|
|
|
# Agent using Azure OpenAI Responses API (supports PDF uploads!)
|
|
agent = Agent(
|
|
name="AzureResponsesAgent",
|
|
description="An agent that can analyze PDFs, images, and other documents using Azure OpenAI Responses API",
|
|
instructions="""
|
|
You are a helpful document analysis assistant. You can:
|
|
|
|
1. Analyze uploaded PDF documents and extract information
|
|
2. Summarize document contents
|
|
3. Answer questions about uploaded files
|
|
4. Extract key points and insights
|
|
|
|
When a user uploads a file, carefully analyze its contents and provide
|
|
helpful, accurate information based on what you find.
|
|
|
|
For PDFs, you can read and understand the text, tables, and structure.
|
|
For images, you can describe what you see and extract any text.
|
|
""",
|
|
client=FoundryChatClient(
|
|
model=_deployment_name,
|
|
endpoint=_endpoint,
|
|
api_version="2025-03-01-preview", # Required for Responses API
|
|
),
|
|
tools=[summarize_document, extract_key_points],
|
|
)
|
|
|
|
|
|
def main():
|
|
"""Launch the Azure Responses agent in DevUI."""
|
|
from agent_framework_devui import serve
|
|
|
|
logging.basicConfig(level=logging.INFO, format="%(message)s")
|
|
|
|
logger.info("=" * 60)
|
|
logger.info("Starting Azure Responses Agent")
|
|
logger.info("=" * 60)
|
|
logger.info("")
|
|
logger.info("This agent uses the Azure OpenAI Responses API which supports:")
|
|
logger.info(" - PDF file uploads")
|
|
logger.info(" - Image uploads")
|
|
logger.info(" - Audio inputs")
|
|
logger.info("")
|
|
logger.info("Try uploading a PDF and asking questions about it!")
|
|
logger.info("")
|
|
logger.info("Required environment variables:")
|
|
logger.info(" - AZURE_OPENAI_ENDPOINT")
|
|
logger.info(" - FOUNDRY_MODEL")
|
|
logger.info(" - AZURE_OPENAI_API_KEY (or use Azure CLI auth)")
|
|
logger.info("")
|
|
|
|
serve(entities=[agent], port=8090, auto_open=True)
|
|
|
|
|
|
if __name__ == "__main__":
|
|
main()
|