vectorless-qv 0.2.0

Reasoning-based RAG for Excel financial models — no vectors, no chunking. Supports all major LLM providers.

Vectorless-QV

Reasoning-based RAG for Excel financial models — no vectors, no chunking.

Inspired by the PageIndex architecture, Vectorless builds a hierarchical tree index of an Excel workbook and uses an LLM reasoning loop (via AWS Bedrock) to navigate it — just like a financial analyst would.

Features

• No vector database — no embeddings, no similarity search
• No chunking — formulas and cell relationships stay intact
• Hierarchical tree index — sheets → tables → formulas → cells
• LLM-driven reasoning — parallel tool calls, search, drill-down
• Formula tracing — follows =+PL!X118 across sheets
• What-if analysis — override cells and recalculate formulas
• 100% traceable — every answer cites exact sheet, cell, and formula

Installation

pip install -e .

Or from a built wheel:

pip install vectorless-qv

Quick Start

1. Index a workbook

vectorless-qv index --file financials.xlsx

This creates two files:

• financials.tree.json — the hierarchical tree index
• financials.parsed.json — raw cell data for query-time lookups

2. Ask questions

# Single question
vectorless-qv query --file financials.xlsx -q "What is the gross margin?"

# Interactive mode
vectorless-qv query --file financials.xlsx

# With reasoning trace
vectorless-qv query --file financials.xlsx -q "How is EBITDA calculated?" -v

3. Inspect the tree

# Full overview
vectorless-qv inspect --file financials.xlsx

# Specific node
vectorless-qv inspect --file financials.xlsx --node s1_t0

Python API

from vectorless_qv import parse_workbook, build_tree, BedrockAgent
import json

# Parse and index
data = parse_workbook("financials.xlsx")
tree = build_tree(data)

# Query
agent = BedrockAgent(tree=tree, workbook_data=data, excel_path="financials.xlsx")
result = agent.query("What drives net income?")
print(result["answer"])
print(result["citations"])

Configuration

Env Variable	Default	Description
AWS_DEFAULT_REGION	us-east-1	AWS region for Bedrock
AWS_ACCESS_KEY_ID	—	AWS credentials
AWS_SECRET_ACCESS_KEY	—	AWS credentials

Override the model via CLI:

vectorless-qv query --file f.xlsx --model us.anthropic.claude-sonnet-4-5-20250929-v1:0 -q "..."

Architecture

Excel File
    │
    ▼
┌──────────┐     ┌──────────┐     ┌──────────┐
│  Parser  │────▶│ Indexer   │────▶│ Tree JSON│
│(openpyxl)│     │(hierarchy)│     │  (ToC)   │
└──────────┘     └──────────┘     └──────────┘
                                       │
                                       ▼
                               ┌──────────────┐
                               │ Bedrock Agent │◀── User Question
                               │ (Claude LLM)  │
                               └──────┬───────┘
                                      │
                          ┌───────────┼───────────┐
                          ▼           ▼           ▼
                    drill_down   get_cells    search_rows
                    get_row      what_if      answer

License

MIT