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* restructure: Python samples into progressive 01-05 layout - 01-get-started/: 6 numbered steps (hello agent → hosting) - 02-agents/: all agent concept samples (tools, middleware, providers, etc.) - 03-workflows/: ALL existing workflow samples preserved as-is - 04-hosting/: azure-functions, durabletask, a2a - 05-end-to-end/: demos, evaluation, hosted agents - Old files moved to _to_delete/ for review - Added AGENTS.md with structure documentation - autogen-migration/ and semantic-kernel-migration/ preserved at root * fix: switch to AzureOpenAI Foundry, fix CI failures - Switch all 01-get-started samples to AzureOpenAIResponsesClient with Azure AI Foundry project endpoint (AZURE_AI_PROJECT_ENDPOINT + AZURE_OPENAI_RESPONSES_DEPLOYMENT_NAME + AzureCliCredential) - Add _to_delete/ and 05-end-to-end/ to pyrightconfig.samples.json excludes - Fix test paths in packages/ that referenced old getting_started/ dirs: durabletask conftest + streaming test, azurefunctions conftest, devui conftest + capture_messages + openai_sdk_integration - Fix workflow_as_agent_human_in_the_loop.py import (sibling import) - Update hosting READMEs and tool comment paths - Replace root README.md with new structure overview - Update AGENTS.md to document Azure OpenAI Foundry as default provider * cleanup: remove _to_delete folder, copy resource files to active dirs All files in _to_delete/ were either: - Exact duplicates of files in the new structure (240 files) - Same file with only comment path updates (100 files) - One import-fix diff (workflow_as_agent_human_in_the_loop.py) - One superseded minimal_sample.py Resource files (sample.pdf, countries.json, employees.pdf, weather.json) copied to 02-agents/sample_assets/ and 02-agents/resources/ since active samples reference them. * fix: address PR review comments, centralize resources, remove root duplicates - Fix type annotation in 04_memory.py (string union -> proper types) - Fix old sample paths in observability files - Fix grammar/spelling in observability samples - Move sample_assets/ and resources/ to shared/ folder - Remove 8 duplicate observability files from 02-agents root - Update resource path references in multimodal_input and provider samples * fix: update broken links from old getting_started paths to new structure - Update relative paths in READMEs: getting_started/ → 01-get-started/, 02-agents/, 03-workflows/, 04-hosting/, 05-end-to-end/ - Fix absolute GitHub URLs in package READMEs - Fix broken link in ollama package README * fix: convert absolute GitHub URLs to relative paths for link checker Absolute URLs to python/samples/ on main branch 404 until PR merges. Converted to relative paths that linkspector can verify locally. * fix: update link for handoff sample moved to orchestrations/ * fix: update chatkit-integration README path from demos/ to 05-end-to-end/ * fix: update broken links in orchestrations README to match flat directory structure
125 lines
4.3 KiB
Python
125 lines
4.3 KiB
Python
# Copyright (c) Microsoft. All rights reserved.
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"""Sample agent using Azure OpenAI Responses API for Agent Framework DevUI.
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This agent uses the Responses API which supports:
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- PDF file uploads
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- Image uploads
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- Audio inputs
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- And other multimodal content
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The Chat Completions API (AzureOpenAIChatClient) does NOT support PDF uploads.
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Use this agent when you need to process documents or other file types.
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Required environment variables:
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- AZURE_OPENAI_ENDPOINT: Your Azure OpenAI endpoint
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- AZURE_OPENAI_RESPONSES_DEPLOYMENT_NAME: Deployment name for Responses API
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(falls back to AZURE_OPENAI_CHAT_DEPLOYMENT_NAME if not set)
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- AZURE_OPENAI_API_KEY: Your API key (or use Azure CLI auth)
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"""
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import logging
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import os
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from typing import Annotated
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from agent_framework import Agent, tool
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from agent_framework.azure import AzureOpenAIResponsesClient
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logger = logging.getLogger(__name__)
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# Get deployment name - try responses-specific env var first, fall back to chat deployment
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_deployment_name = os.environ.get(
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"AZURE_OPENAI_RESPONSES_DEPLOYMENT_NAME",
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os.environ.get("AZURE_OPENAI_CHAT_DEPLOYMENT_NAME", ""),
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)
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# Get endpoint - try responses-specific env var first, fall back to default
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_endpoint = os.environ.get(
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"AZURE_OPENAI_RESPONSES_ENDPOINT",
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os.environ.get("AZURE_OPENAI_ENDPOINT", ""),
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)
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def analyze_content(
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query: Annotated[str, "What to analyze or extract from the uploaded content"],
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) -> str:
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"""Analyze uploaded content based on the user's query.
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This is a placeholder - the actual analysis is done by the model
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when processing the uploaded files.
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"""
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return f"Analyzing content for: {query}"
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# 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_threads.py.
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@tool(approval_mode="never_require")
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def summarize_document(
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length: Annotated[str, "Desired summary length: 'brief', 'medium', or 'detailed'"] = "medium",
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) -> str:
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"""Generate a summary of the uploaded document."""
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return f"Generating {length} summary of the document..."
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@tool(approval_mode="never_require")
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def extract_key_points(
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max_points: Annotated[int, "Maximum number of key points to extract"] = 5,
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) -> str:
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"""Extract key points from the uploaded document."""
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return f"Extracting up to {max_points} key points..."
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# Agent using Azure OpenAI Responses API (supports PDF uploads!)
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agent = Agent(
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name="AzureResponsesAgent",
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description="An agent that can analyze PDFs, images, and other documents using Azure OpenAI Responses API",
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instructions="""
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You are a helpful document analysis assistant. You can:
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1. Analyze uploaded PDF documents and extract information
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2. Summarize document contents
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3. Answer questions about uploaded files
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4. Extract key points and insights
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When a user uploads a file, carefully analyze its contents and provide
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helpful, accurate information based on what you find.
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For PDFs, you can read and understand the text, tables, and structure.
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For images, you can describe what you see and extract any text.
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""",
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client=AzureOpenAIResponsesClient(
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deployment_name=_deployment_name,
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endpoint=_endpoint,
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api_version="2025-03-01-preview", # Required for Responses API
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),
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tools=[summarize_document, extract_key_points],
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)
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def main():
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"""Launch the Azure Responses agent in DevUI."""
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from agent_framework_devui import serve
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logging.basicConfig(level=logging.INFO, format="%(message)s")
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logger.info("=" * 60)
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logger.info("Starting Azure Responses Agent")
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logger.info("=" * 60)
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logger.info("")
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logger.info("This agent uses the Azure OpenAI Responses API which supports:")
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logger.info(" - PDF file uploads")
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logger.info(" - Image uploads")
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logger.info(" - Audio inputs")
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logger.info("")
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logger.info("Try uploading a PDF and asking questions about it!")
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logger.info("")
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logger.info("Required environment variables:")
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logger.info(" - AZURE_OPENAI_ENDPOINT")
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logger.info(" - AZURE_OPENAI_RESPONSES_DEPLOYMENT_NAME")
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logger.info(" - AZURE_OPENAI_API_KEY (or use Azure CLI auth)")
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logger.info("")
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serve(entities=[agent], port=8090, auto_open=True)
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if __name__ == "__main__":
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main()
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