Python FastAPI ChromaDB Agent Architecture PDF Reports

ARIA: AI-Powered Research Intelligence Assistant

Research Intelligence Assistant is a web-based tool with intelligent agents that transforms a research topic into a structured benchmark report by collecting, ranking, and comparing scientific papers and patents across custom metrics with PDF export and analytics.

View GitHub Repository → See Workflow
🔎 Research Topic Analysis
🤖 LLM Relevance Ranking
📊 Benchmark Report Generated

Core Features

A web-based research platform with intelligent agents for adaptive metric learning, source comparison, PDF export, and LLM analytics tracking.

🌐

Web-Based Research Workflow

Interactive browser interface for entering topics, selecting metrics, generating reports, and exporting results.

📚

Paper and Patent Retrieval

Searches Semantic Scholar for papers and SerpAPI for patents, with intelligent caching using ChromaDB.

🧠

Adaptive Metric Bank Agent

Suggests topic-relevant comparison metrics using ChromaDB and improves over time by learning from selected, custom-added, and ignored metrics.

✅

Comparison Agent

Validates comparison matrix cells with rule-based and LLM checks to ensure accurate YES/PART/NO evaluations.

📊

Source Comparison Matrix

Compares papers and patents across selected metrics with clear YES, PART, or NO coverage indicators.

📈

LangSmith Execution Analytics

Tracks LLM calls, token usage, cost, and duration by workflow stage with optional LangSmith integration.

📄

PDF Report Export

Generates professional PDF reports with executive summary, comparison matrix, sources, and analytics dashboard.

🧪

Tested Python Pipeline

Comprehensive Pytest test suite covering adapters, ranking, analytics, PDF export, and agent validation.

Workflow

A streamlined web interface from research topic to PDF report with intelligent agent assistance.

1
Topic Enter research topic in web interface
2
Settings Choose max results and cache mode
3
Metrics Get topic-aware metric suggestions
4
Select Review and customize metrics
5
Search Retrieve papers and patents
6
Matrix Generate comparison matrix
7
Analytics Review LLM usage and costs
8
Export Download PDF report

System Architecture

A FastAPI web application with intelligent agents, ChromaDB caching, and comprehensive analytics tracking throughout the research pipeline.

FastAPI Web UI Browser interface for research workflow
→
Metric Bank Agent ChromaDB-powered adaptive metric suggestions
Research Pipeline Search, cache, deduplicate, rank sources
→
Comparison Agent Matrix validation and improvement
Report + Analytics PDF export with execution analytics
→
ChromaDB Storage Metrics bank and research cache

Technology Stack

Built with modern Python web frameworks, vector databases, and intelligent agent architecture.

Python
FastAPI
ChromaDB
LangSmith
Semantic Scholar
SerpAPI
ReportLab
Chart.js
Pytest
GitHub Pages

Project Status

The core platform is feature-complete with intelligent agents, web UI, and PDF export. Future enhancements focus on advanced analysis capabilities.

✓
Web UI workflow with intelligent agents
FastAPI interface with Metric Bank Agent and Comparison Agent for adaptive learning.
✓
Interactive dashboard and PDF export
Visual analytics, comparison matrix heatmaps, and professional PDF reports.
○
RAG-based document analysis
Analyze uploaded papers, patents, and internal documents with vector search.
○
Multi-language support
Extend research capabilities to non-English papers and patents.