Files
Eduard van Valkenburg a2856d3b92 Python: restructure: Python samples into progressive 01-05 layout (#3862)
* 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- One superseded minimal_sample.py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
2026-02-12 17:36:36 +00:00

125 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 (AzureOpenAIChatClient) 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
- AZURE_OPENAI_RESPONSES_DEPLOYMENT_NAME: Deployment name for Responses API
(falls back to AZURE_OPENAI_CHAT_DEPLOYMENT_NAME 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.azure import AzureOpenAIResponsesClient
logger = logging.getLogger(__name__)
# Get deployment name - try responses-specific env var first, fall back to chat deployment
_deployment_name = os.environ.get(
"AZURE_OPENAI_RESPONSES_DEPLOYMENT_NAME",
os.environ.get("AZURE_OPENAI_CHAT_DEPLOYMENT_NAME", ""),
)
# 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_threads.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=AzureOpenAIResponsesClient(
deployment_name=_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(" - AZURE_OPENAI_RESPONSES_DEPLOYMENT_NAME")
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()