Audio Sentiment Analysis Team

This example demonstrates how an Agno Agent Team can collaborate to perform sentiment analysis on audio conversations using transcription and sentiment analysis agents working together.

Code

cookbook/02_examples/teams/multimodal/audio_sentiment_analysis.py

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

transcription_agent = Agent(
    name="Audio Transcriber",
    role="Transcribe audio conversations accurately",
    model=Gemini(id="gemini-2.0-flash-exp"),
    instructions=[
        "Transcribe audio with speaker identification",
        "Maintain conversation structure and flow",
    ],
)

sentiment_analyst = Agent(
    name="Sentiment Analyst",
    role="Analyze emotional tone and sentiment in conversations",
    model=Gemini(id="gemini-2.0-flash-exp"),
    instructions=[
        "Analyze sentiment for each speaker separately",
        "Identify emotional patterns and conversation dynamics",
        "Provide detailed sentiment insights",
    ],
)

# Create a team for collaborative audio sentiment analysis
sentiment_team = Team(
    name="Audio Sentiment Team",
    members=[transcription_agent, sentiment_analyst],
    model=Gemini(id="gemini-2.0-flash-exp"),
    instructions=[
        "Analyze audio sentiment with conversation memory.",
        "Audio Transcriber: First transcribe audio with speaker identification.",
        "Sentiment Analyst: Analyze emotional tone and conversation dynamics.",
    ],
    add_history_to_context=True,
    markdown=True,
    db=SqliteDb(
        session_table="audio_sentiment_team_sessions",
        db_file="tmp/audio_sentiment_team.db",
    ),
)

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

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

sentiment_team.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,
)

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

Usage

1. Set up your virtual environment

   Mac

   uv venv --python 3.12
   source .venv/bin/activate
   
2. Install required libraries

   uv pip install agno requests google-generativeai
   
3. Set environment variables

   export GOOGLE_API_KEY=****
   
4. Run the agent

   python cookbook/02_examples/teams/multimodal/audio_sentiment_analysis.py