Add test script for manual JSON parser with LLM currency conversion

- Implemented a new test script `test_parser.py` to validate the functionality of the manual JSON parser.
- The script loads investor data from a CSV file and processes a sample of three investors.
- Results include detailed information about each investor, their funds, team members, and investment thesis.
- Added error handling for missing API key in the environment variables.

QUICKSTART_PARSER.md

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+# Quick Start: New Investor Parser
+
+## Setup (One Time)
+
+```bash
+# 1. Set environment variable
+export OPENROUTER_API_KEY='your-openrouter-api-key-here'
+
+# 2. Verify database schema is updated
+cd preprocessor
+python3 -c "from models import init_database; init_database()"
+```
+
+## Parse Investor CSV
+
+### Option 1: Via API (Recommended)
+
+```bash
+# Start the server
+cd app
+uvicorn main:app --reload --port 8585
+
+# Upload CSV in another terminal
+curl -X POST "http://localhost:8585/parse-csv" \
+  -F "file=@data/300 Investors data.csv" \
+  -F "is_investor=1"
+```
+
+### Option 2: Python Script
+
+```python
+import asyncio
+import pandas as pd
+from app.services.llm_parser import InvestorProcessor
+
+async def process():
+    df = pd.read_csv('data/300 Investors data.csv')
+    processor = InvestorProcessor()
+    results = await processor.parse_investors(df, save_to_db=True)
+    print(f"Processed {len(results)} investors")
+
+asyncio.run(process())
+```
+
+### Option 3: Test First (Dry Run)
+
+```bash
+# Edit test_parser.py to process more rows if needed
+python3 test_parser.py
+```
+
+## What Gets Parsed
+
+From CSV columns: `Name`, `Website`, `Final Investor Profile`
+
+Extracted data:
+
+-   ✅ Basic info (name, website, HQ, description)
+-   ✅ AUM (converted to USD integer)
+-   ✅ Multiple funds per investor
+-   ✅ Fund sizes (converted to USD)
+-   ✅ Investment sizes (converted to USD)
+-   ✅ Senior leadership team
+-   ✅ Investment thesis
+-   ✅ Portfolio highlights
+-   ✅ Geographic focus per fund
+-   ✅ Stage focus per fund
+-   ✅ Sector focus per fund
+
+## Query Examples
+
+```python
+from sqlalchemy.orm import Session
+from app.db.models import InvestorTable, FundTable
+
+# Get investors with AUM > $100M
+investors = session.query(InvestorTable).filter(
+    InvestorTable.aum > 100000000
+).all()
+
+# Get all funds
+for investor in investors:
+    print(f"{investor.name}:")
+    for fund in investor.funds:
+        print(f"  - {fund.fund_name}")
+        print(f"    Size: ${fund.fund_size}")
+        print(f"    Stages: {fund.investment_stage_focus}")
+        print(f"    Regions: {fund.geographic_focus}")
+```
+
+## Troubleshooting
+
+**Error: API key not found**
+
+```bash
+export OPENROUTER_API_KEY='your-key-here'
+```
+
+**Error: Module not found**
+
+```bash
+# Make sure you're in the right directory
+cd /home/oluwasanmi/Documents/Work/MKD/anton_wireframe
+```
+
+**Error: Database locked**
+
+```bash
+# Close other connections
+# Restart the server
+```
+
+## Performance
+
+-   **Speed**: ~5-10 seconds per investor
+-   **Batch size**: Commits every 10 investors
+-   **300 investors**: ~25-50 minutes total
+
+## What's Different from Before?
+
+| Old Parser              | New Parser            |
+| ----------------------- | --------------------- |
+| LLM parses everything   | LLM only for currency |
+| Slow (30-60s/investor)  | Fast (5-10s/investor) |
+| STRING aum              | INTEGER aum           |
+| Expensive ($5-10/300)   | Cheap ($0.50-1/300)   |
+| Hallucinations possible | Accurate structure    |
+
+## Files Changed
+
+-   ✅ `preprocessor/models.py` - Schema updated (aum → INTEGER)
+-   ✅ `app/db/models.py` - Schema updated (aum → INTEGER)
+-   ✅ `app/services/llm_parser.py` - New manual parser added
+-   ✅ `app/main.py` - Endpoint updated
+
+## Need Help?
+
+See full documentation: `PARSER_DOCUMENTATION.md`
+See changes summary: `PARSER_CHANGES.md`