Audio Sentiment Analysis

Analyze speaker sentiment in a recorded conversation with Gemini, then ask a follow-up question answered from SQLite-backed session history.

Audio Sentiment Analysis.

audio_sentiment_analysis.py

"""
Audio Sentiment Analysis
=============================

Audio Sentiment Analysis.
"""

import requests
from agno.agent import Agent
from agno.db.sqlite import SqliteDb
from agno.media import Audio
from agno.models.google import Gemini

# ---------------------------------------------------------------------------
# Create Agent
# ---------------------------------------------------------------------------
agent = Agent(
    model=Gemini(id="gemini-3.5-flash"),
    add_history_to_context=True,
    markdown=True,
    db=SqliteDb(
        session_table="audio_sentiment_analysis_sessions",
        db_file="tmp/audio_sentiment_analysis.db",
    ),
)

url = "https://agno-public.s3.amazonaws.com/demo_data/sample_conversation.wav"

response = requests.get(url)
audio_content = response.content

# ---------------------------------------------------------------------------
# Run Agent
# ---------------------------------------------------------------------------
if __name__ == "__main__":
    # Give a sentiment analysis of this audio conversation. Use speaker A, speaker B to identify speakers.
    agent.print_response(
        "Give a sentiment analysis of this audio conversation. Use speaker A, speaker B to identify speakers.",
        audio=[Audio(content=audio_content)],
        stream=True,
    )

    agent.print_response(
        "What else can you tell me about this audio conversation?",
        stream=True,
    )

Run the Example

1. Set up your virtual environment

   Mac

   uv venv --python 3.12
   source .venv/bin/activate
   

   uv venv --python 3.12
   .venv\Scripts\activate
   
2. Install dependencies

   uv pip install -U agno google-genai requests sqlalchemy
   
3. Export your Google API key

   Mac/Linux

   export GOOGLE_API_KEY="your_google_api_key_here"
   

   $Env:GOOGLE_API_KEY="your_google_api_key_here"
   
4. Run the example

   Save the code above as audio_sentiment_analysis.py, then run:

   python audio_sentiment_analysis.py
   

Full source: cookbook/02_agents/12_multimodal/audio_sentiment_analysis.py