Slides Content Reader
Reads and summarizes content from existing Google Slides presentations.
"""
Slides Content Reader
=====================
Reads and summarizes content from existing Google Slides presentations.
The agent extracts text, metadata, and thumbnails from presentations,
providing structured summaries of slide content.
Key concepts:
- read_all_text: extracts text from every slide (handles shapes, tables, groups)
- get_slide_text: targeted text extraction from a single slide
- get_presentation_metadata: lightweight metadata (title, slide count, IDs)
- get_slide_thumbnail: retrieves slide thumbnail image URLs
Setup:
1. Create OAuth credentials at https://console.cloud.google.com (enable Slides API + Drive API)
2. Export GOOGLE_CLIENT_ID, GOOGLE_CLIENT_SECRET, GOOGLE_PROJECT_ID env vars
3. pip install openai google-api-python-client google-auth-httplib2 google-auth-oauthlib
4. First run opens browser for OAuth consent, saves token.json for reuse
"""
from typing import List
from agno.agent import Agent
from agno.models.openai import OpenAIResponses
from agno.tools.google.slides import GoogleSlidesTools
from pydantic import BaseModel, Field
class SlideSummary(BaseModel):
slide_id: str = Field(..., description="The slide object ID")
slide_number: int = Field(..., description="1-based slide position")
title: str = Field(..., description="Inferred slide title or first text element")
key_points: List[str] = Field(
default_factory=list, description="Key points from the slide"
)
class PresentationSummary(BaseModel):
title: str = Field(..., description="Presentation title")
slide_count: int = Field(..., description="Total number of slides")
slides: List[SlideSummary] = Field(..., description="Summary of each slide")
overall_summary: str = Field(
..., description="One-paragraph summary of the entire presentation"
)
agent = Agent(
name="Slides Reader",
model=OpenAIResponses(id="gpt-5.5"),
tools=[GoogleSlidesTools()],
instructions=[
"Use get_presentation_metadata first to understand structure.",
"Use read_all_text to extract all content at once.",
"Identify the main topic of each slide from its text content.",
"Provide a concise overall summary of the presentation.",
],
output_schema=PresentationSummary,
markdown=True,
)
if __name__ == "__main__":
agent.print_response(
"Summarize this presentation: https://docs.google.com/presentation/d/"
"1nJAZYHrAe-K0OOqZ3HA1-YrY6aNO5yOIV5MosOkaIOU "
"Extract the presentation ID from the URL and read all content.",
stream=True,
)
# Summarize a specific slide
# agent.print_response(
# "Get the metadata for presentation ID <your_presentation_id>, "
# "then extract and summarize the text from the third slide.",
# stream=True,
# )
# List and pick a presentation
# agent.print_response(
# "List all my presentations, then read and summarize the most recently modified one.",
# stream=True,
# )Replace the sample URL with a presentation that your authenticated account can read. The default toolkit also enables creation and editing. For a reader, use:
GoogleSlidesTools(
include_tools=[
"get_presentation_metadata", "read_all_text", "get_slide_text",
"get_slide_thumbnail", "list_presentations",
],
scopes=[
"https://www.googleapis.com/auth/presentations.readonly",
"https://www.googleapis.com/auth/drive.readonly",
],
)The explicit Drive read scope lets the optional list operation discover accessible presentations beyond the default app-authorized files. Follow nextPageToken when listing. Text extraction covers text objects and tables; it does not OCR images or interpret charts. Thumbnail URLs are returned as text, not automatically submitted to a vision model.
Run the Example
Set up your virtual environment
uv venv --python 3.12
source .venv/bin/activateInstall dependencies
uv pip install -U agno google-api-python-client google-auth google-auth-httplib2 google-auth-oauthlib openaiConfigure Google OAuth
Enable the Google API used by this example, configure the consent screen, and create a Desktop OAuth client in your Cloud project. Export its GOOGLE_CLIENT_ID, GOOGLE_CLIENT_SECRET, and GOOGLE_PROJECT_ID, or place the downloaded client JSON at credentials.json in the directory where you run Python. Google's Python quickstart shows the Desktop client setup.
The first tool call opens a browser for consent and caches credentials in token.json. Use a separate token_path when switching accounts. Passing an Agno user_id does not switch the authenticated Google account.
Export environment variables
export GOOGLE_CLIENT_ID="your_google_client_id_here"
export GOOGLE_CLIENT_SECRET="your_google_client_secret_here"
export GOOGLE_PROJECT_ID="your_google_project_id_here"
export OPENAI_API_KEY="your_openai_api_key_here"Run the example
Save the code above as content_reader.py, then run:
python content_reader.pyFull source: cookbook/91_tools/google/slides/content_reader.py