competitor_tracker.py
"""
Monitor API — Competitive Intelligence
=======================================
Track competitors for product launches, news, and strategic moves.
USE CASES:
- Product launches and feature announcements
- Executive changes and key hires
- Partnership announcements
- Pricing changes
- Press coverage and sentiment
Monitors detect NEW information and alert you to changes.
Two-phase usage:
python competitor_tracker.py # Phase 1: create monitors
python competitor_tracker.py check # Phase 2: pull events (re-run later)
Wait at least one monitor cycle (default_monitor_frequency) between phases so
the monitors have time to run and detect changes.
Prerequisites:
- pip install parallel-web
- export PARALLEL_API_KEY=<your-api-key>
"""
import sys
from agno.agent import Agent
from agno.models.openai import OpenAIResponses
from agno.tools.parallel import ParallelTools
# =============================================================================
# COMPETITOR TRACKING CONFIGURATION
# =============================================================================
# Hourly tracking for fast-moving markets
competitor_monitor = ParallelTools(
enable_search=False,
enable_extract=False,
enable_monitor=True,
default_monitor_frequency="1h",
default_monitor_processor="lite",
)
# Daily tracking for general competitive intel
daily_monitor = ParallelTools(
enable_search=False,
enable_extract=False,
enable_monitor=True,
default_monitor_frequency="1d",
default_monitor_processor="base",
)
# =============================================================================
# COMPETITIVE INTELLIGENCE AGENT
# =============================================================================
competitive_intel_agent = Agent(
model=OpenAIResponses(id="gpt-5.4"),
tools=[competitor_monitor],
markdown=True,
instructions="""You track competitors and market activity.
Tips for effective monitoring:
- Be specific: "OpenAI product launches and API updates" not "OpenAI news"
- Include company context: "Anthropic (Claude AI) funding and partnerships"
- Focus on actionable signals: "competitor pricing changes" not "competitor mentions"
Available tools:
- create_monitor(query): Start tracking
- list_monitors(): See active monitors
- get_monitor_events(monitor_id): Get recent events
- cancel_monitor(monitor_id): Stop tracking
""",
)
# =============================================================================
# RUN
# =============================================================================
if __name__ == "__main__":
if len(sys.argv) > 1 and sys.argv[1] == "check":
# Phase 2: read what monitors have detected so far
competitive_intel_agent.print_response(
"List my active monitors. For each one, fetch the latest events with "
"get_monitor_events and summarize any new competitive activity. "
"Flag anything that looks strategically significant.",
stream=True,
)
else:
# Phase 1: stand up the monitors
competitive_intel_agent.print_response(
"Create monitors to track OpenAI and Anthropic for product launches, "
"API updates, and major announcements.",
stream=True,
)
print(
"\nMonitors created. Wait at least one cycle "
"(see default_monitor_frequency), then run:\n"
" python competitor_tracker.py check"
)
Parallel monitors continue running after the script exits and may consume usage. Save every
monitor_id returned by the creation response. When you finish, create a ParallelTools(enable_search=False, enable_extract=False, enable_monitor=True) instance and call cancel_monitor(monitor_id) for each saved ID. Leave unrelated account monitors active.Run the Example
1
Set up your virtual environment
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 openai parallel-web
3
Export your API keys
export OPENAI_API_KEY="your_openai_api_key_here"
export PARALLEL_API_KEY="your_parallel_api_key_here"
$Env:OPENAI_API_KEY="your_openai_api_key_here"
$Env:PARALLEL_API_KEY="your_parallel_api_key_here"
4
Run the example
Save the code above as
competitor_tracker.py, then run:python competitor_tracker.py