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@SAMK-online SAMK-online commented Oct 27, 2025

This example showcases advanced ADK capabilities:

  • Multi-agent orchestration with specialized agent roles
  • Gmail API integration for newsletter extraction
  • Financial data enrichment with yfinance
  • TLDR-specific parsing for complex newsletter formats
  • Intelligent content validation using List-ID headers
  • Error handling with retry logic and exponential backoff

Features:

  • newsletter_podcast_producer: Main orchestrator agent
  • podcaster_agent: Specialized audio generation agent
  • Real-time stock price lookup integration
  • Support for 25+ newsletter sources
  • 95% newsletter identification accuracy

Includes:

  • README with setup instructions and architecture diagrams
  • main.py for testing with runner
  • test_agent.py with unit tests
  • requirements.txt with dependencies

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This example showcases advanced ADK capabilities:
- Multi-agent orchestration with specialized agent roles
- Gmail API integration for newsletter extraction
- Financial data enrichment with yfinance
- TLDR-specific parsing for complex newsletter formats
- Intelligent content validation using List-ID headers
- Error handling with retry logic and exponential backoff

Features:
- newsletter_podcast_producer: Main orchestrator agent
- podcaster_agent: Specialized audio generation agent
- Real-time stock price lookup integration
- Support for 25+ newsletter sources
- 95% newsletter identification accuracy

Includes:
- README with setup instructions and architecture diagrams
- main.py for testing with runner
- test_agent.py with unit tests
- requirements.txt with dependencies
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Summary of Changes

Hello @SAMK-online, I'm Gemini Code Assist1! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed!

This pull request introduces a new, comprehensive example within the ADK framework, showcasing a multi-agent system designed to transform daily newsletters into engaging podcasts. The system orchestrates several tasks, from fetching and parsing email content to enriching data with financial context and generating multi-speaker audio. It highlights advanced features like robust API integrations, intelligent content processing, and resilient error handling, providing a practical demonstration of complex agent interactions.

Highlights

  • Multi-Agent Orchestration: Introduces a sophisticated multi-agent system demonstrating advanced ADK capabilities, featuring a main orchestrator agent (newsletter_podcast_producer) and a specialized audio generation agent (podcaster_agent).
  • Newsletter Processing & Enrichment: Integrates with the Gmail API to extract newsletters, performs intelligent content validation using List-ID headers, and enriches stories with real-time financial data via yfinance.
  • Podcast Generation Workflow: Automates the creation of multi-speaker podcasts from newsletter content, including script generation with strict length and dialogue requirements, and audio production with retry logic and exponential backoff.
  • Robustness and Features: Showcases error handling with retry logic, supports over 25 newsletter sources, and achieves 95% newsletter identification accuracy, alongside deep research capabilities for article content and web searches.
  • Comprehensive Example: Provides a complete example with detailed setup instructions, usage examples for direct agent interaction and API server, unit tests, and an architecture diagram.
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Code Review

This pull request introduces a new example showcasing multi-agent orchestration for processing Gmail newsletters and generating podcasts. The code includes several new files with agent definitions, utility functions for interacting with the Gmail API, and unit tests. The review focuses on correctness and potential improvements in error handling and code clarity, particularly in the agent.py file.

Then return the COMPLETE script text so it can be passed to the audio generation agent.
""",
tools=[save_news_to_markdown],
)

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critical

There is a syntax error here. A closing parenthesis is missing, which will cause the code to not compile.

Suggested change
)
tools=[save_news_to_markdown],
)

wf.writeframes(pcm)


async def generate_podcast_audio(podcast_script: str, tool_context: ToolContext, filename: str = "'ai_today_podcast") -> Dict[str, str]:

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high

The default filename includes a leading quote, which is likely a typo and will cause the file to be named "ai_today_podcast.wav".

It's also recommended to remove the single quotes around the default filename to avoid confusion and ensure the file is named as intended.

Suggested change
async def generate_podcast_audio(podcast_script: str, tool_context: ToolContext, filename: str = "'ai_today_podcast") -> Dict[str, str]:
async def generate_podcast_audio(podcast_script: str, tool_context: ToolContext, filename: str = "ai_today_podcast") -> Dict[str, str]:

Comment on lines +103 to +104
if not pathlib.Path(credentials_file).exists():
return {"status": "error", "message": "credentials.json file not found. Please download it from Google Cloud Console."}

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medium

It's good to check if the credentials file exists, but it would be more helpful to provide a more specific error message guiding the user on where to find or how to create this file, especially since this is part of the setup process. Consider including a link to the Google Cloud Console.

Also, consider logging this error to the process_log so that the user can see this error in the report.

Comment on lines +666 to +669
# ** BUG FIX **: This logic now runs for all cases, not just when the extension is added.
current_directory = pathlib.Path.cwd()
file_path = current_directory / filename
wave_file(str(file_path), data)

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medium

The comment ** BUG FIX **: This logic now runs for all cases, not just when the extension is added. is useful, but it would be even better to explain why this change was necessary. What bug was being fixed, and how does this change address it? This helps future maintainers understand the intent and avoid accidentally reintroducing the bug.

@ryanaiagent ryanaiagent self-assigned this Nov 3, 2025
@wuliang229 wuliang229 self-requested a review November 4, 2025 07:38
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2 participants