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- Python 83.8%
- JavaScript 6.8%
- HTML 5.9%
- CSS 3.4%
Chris Arseno
973317ed92
Produce the public community edition from the private source: strip proprietary/internal surfaces and de-pin the telemetry dependency. - De-pin gozerai-telemetry: drop the commit pin and the private-org git URL, leaving a plain, unpinned dependency name (pyproject + CI) - Remove a smuggled base64-encoded Enterprise source blob left at repo root - Remove the Enterprise autonomy package that the exporter failed to strip (kept the license-required stub in its place) - Remove monetization modules and their tests from the public surface - Replace the service and HTTP API layer with clean community implementations that gate advanced analytics behind a license (no internal integrations) - Genericize identity-provider and licensing references in code, frontend, env example, and docs - Drop internal build tooling and internal-integration tests Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> |
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| .github/workflows | ||
| frontend | ||
| src/trendscope | ||
| tests | ||
| .env.example | ||
| .gitignore | ||
| Dockerfile | ||
| LICENSE | ||
| LICENSING.md | ||
| pyproject.toml | ||
| README.md | ||
| run.bat | ||
Trendscope
AI-powered trend analysis and market intelligence — Part of the GozerAI ecosystem.
Overview
Trendscope is a Python library for collecting, analyzing, and scoring market trends across multiple platforms. It identifies niche opportunities, detects trend drift, finds cross-platform correlations, and generates actionable buy/sell signals.
Features (Community Tier)
- Multi-source collection — Pluggable collectors for Google Trends, Reddit, Hacker News, and Product Hunt
- Trend analysis — Velocity, momentum, and composite scoring with lifecycle classification
- Niche identification — Automatic detection of market opportunities
- Drift detection — Alerts when trends surge, decline, or exhibit unusual volatility
- SQLite persistence — Built-in trend database with history tracking
Pro Features (requires license)
- Advanced anomaly detection
- Forecasting and predictive models
- Trend intelligence and correlation engine
- Narrative extraction
- Credibility scoring
- Real-time feed
Enterprise Features (requires license)
- Autonomous analysis pipelines
- Scheduled analysis
- Trend snapshots and time-travel comparison
- Lifecycle tracking and coverage analysis
Visit gozerai.com/pricing for Pro and Enterprise tier details.
Installation
pip install trendscope
For development:
pip install -e ".[dev]"
Quick Start
import asyncio
from trendscope import TrendService
async def main():
service = TrendService()
await service.initialize()
# Collect trends from all sources
result = await service.refresh_trends()
# Find niche market opportunities
opportunities = await service.find_opportunities(min_score=50)
# Detect significant trend changes
drifts = await service.detect_drifts(lookback_days=7)
# Get buy/sell signals
signals = await service.get_signals()
asyncio.run(main())
Running Tests
pytest tests/ -v
Requirements
- Python >= 3.10
- No external dependencies (stdlib only)
License
This project is dual-licensed:
- AGPL-3.0 — For open-source use (see LICENSE)
- Commercial — For proprietary integration
Contact chris@gozerai.com for commercial licensing.