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"""
Advanced Compression
=============================

This example shows how to set a context token based limit for tool call compression.
"""

from agno.agent import Agent
from agno.compression.manager import CompressionManager
from agno.db.sqlite import SqliteDb
from agno.models.openai import OpenAIResponses
from agno.tools.websearch import WebSearchTools

compression_prompt = """
    You are a compression expert. Your goal is to compress web search results for a competitive intelligence analyst.
    
    YOUR GOAL: Extract only actionable competitive insights while being extremely concise.
    
    MUST PRESERVE:
    - Competitor names and specific actions (product launches, partnerships, acquisitions, pricing changes)
    - Exact numbers (revenue, market share, growth rates, pricing, headcount)
    - Precise dates (announcement dates, launch dates, deal dates)
    - Direct quotes from executives or official statements
    - Funding rounds and valuations
    
    MUST REMOVE:
    - Company history and background information
    - General industry trends (unless competitor-specific)
    - Analyst opinions and speculation (keep only facts)
    - Detailed product descriptions (keep only key differentiators and pricing)
    - Marketing fluff and promotional language
    
    OUTPUT FORMAT:
    Return a bullet-point list where each line follows this format:
    "[Company Name] - [Date]: [Action/Event] ([Key Numbers/Details])"
    
    Keep it under 200 words total. Be ruthlessly concise. Facts only.
    
    Example:
    - Acme Corp - Mar 15, 2024: Launched AcmeGPT at $99/user/month, targeting enterprise market
    - TechCo - Feb 10, 2024: Acquired DataStart for $150M, gaining 500 enterprise customers
"""

compression_manager = CompressionManager(
    model=OpenAIResponses(id="gpt-5-mini"),
    compress_token_limit=5000,
    compress_tool_call_instructions=compression_prompt,
)

# ---------------------------------------------------------------------------
# Create Agent
# ---------------------------------------------------------------------------
agent = Agent(
    model=OpenAIResponses(id="gpt-5-mini"),
    tools=[WebSearchTools()],
    description="Specialized in tracking competitor activities",
    instructions="Use the search tools and always use the latest information and data.",
    db=SqliteDb(db_file="tmp/token_based_tool_call_compression.db"),
    compression_manager=compression_manager,
    add_history_to_context=True,  # Add history to context
    num_history_runs=3,
    session_id="token_based_tool_call_compression",
)

# ---------------------------------------------------------------------------
# Run Agent
# ---------------------------------------------------------------------------
if __name__ == "__main__":
    agent.print_response(
        """
        Use the search tools and always use the latest information and data.
        Research recent activities (last 3 months) for these AI companies:
        
        1. OpenAI - product launches, partnerships, pricing
        2. Anthropic - new features, enterprise deals, funding
        3. Google DeepMind - research breakthroughs, product releases
        4. Meta AI - open source releases, research papers
       
        For each, find specific actions with dates and numbers.""",
        stream=True,
    )

​
Run the Example

# Clone and setup repo
git clone https://github.com/agno-agi/agno.git
cd agno/cookbook/02_agents/14_advanced

# Create and activate virtual environment
./scripts/demo_setup.sh
source .venvs/demo/bin/activate

python advanced_compression.py