Files

Alejandro Gutiérrez c797470421 fix(synthesis): Calculate analysis_period from actual data range

Previously hardcoded "Last 12 months" which was misleading when data
spanned multiple years. Now calculates the actual period from the
earliest to latest review dates in the dataset.

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>

2026-01-30 15:49:51 +00:00

src/reviewiq_pipeline

fix(synthesis): Calculate analysis_period from actual data range

2026-01-30 15:49:51 +00:00

tests

feat: Add reviewiq-pipeline package for LLM-powered review classification

2026-01-24 18:07:11 +00:00

pyproject.toml

feat: Add extensible multi-pipeline integration system

2026-01-24 19:05:38 +00:00

README.md

feat: Add reviewiq-pipeline package for LLM-powered review classification

2026-01-24 18:07:11 +00:00

README.md

ReviewIQ Pipeline

LLM-powered review classification and analysis pipeline using URT (Universal Review Taxonomy) v5.1.

Features

Stage 1: Normalization - Text cleaning, language detection, deduplication
Stage 2: LLM Classification - Span extraction with URT codes using OpenAI/Anthropic
Stage 3: Issue Routing - Route negative spans to issues for tracking
Stage 4: Fact Aggregation - Pre-aggregate metrics for dashboard queries

Installation

pip install reviewiq-pipeline

Or install from source:

pip install -e packages/reviewiq-pipeline

Quick Start

Python API

from reviewiq_pipeline import Pipeline, Config

# Initialize
config = Config(
    database_url="postgresql://...",
    llm_provider="openai",
    llm_api_key="sk-...",
    taxonomy_version="v5.1"
)
pipeline = Pipeline(config)

# Run full pipeline
result = await pipeline.process(scraper_output)

# Or run individual stages
stage1_result = await pipeline.normalize(scraper_output)
stage2_result = await pipeline.classify(stage1_result)
stage3_result = await pipeline.route(stage2_result)
stage4_result = await pipeline.aggregate(business_id, date)

# Validate
validation = await pipeline.validate(job_id)

CLI

# Run migrations
reviewiq-pipeline migrate --database-url $DATABASE_URL

# Process a job
reviewiq-pipeline run --job-id <UUID> --stages 1,2,3,4

# Validate pipeline output
reviewiq-pipeline validate --job-id <UUID>

Configuration

Environment variables:

DATABASE_URL - PostgreSQL connection string
LLM_PROVIDER - openai or anthropic
OPENAI_API_KEY - OpenAI API key (if using OpenAI)
ANTHROPIC_API_KEY - Anthropic API key (if using Anthropic)
TAXONOMY_VERSION - URT taxonomy version (default: v5.1)

Development

# Install with dev dependencies
pip install -e "packages/reviewiq-pipeline[dev]"

# Run tests
pytest

# Run with coverage
pytest --cov=reviewiq_pipeline

# Type checking
mypy src/reviewiq_pipeline

# Linting
ruff check src/reviewiq_pipeline

License

MIT