Remove deprecated stage_focus column and update database path for consistency; add schema verification script and document schema mismatch fixes
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# Schema Mismatch Fix - Summary
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## Problem
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When trying to parse the investor CSV, the following error occurred:
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```
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sqlite3.OperationalError: no such column: investors.stage_focus
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```
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## Root Cause
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The application models still referenced `stage_focus` column which was removed from the preprocessor database schema. The `stage_focus` was deprecated in favor of fund-level stage tracking (each fund has its own `investment_stage_focus`).
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## Files Fixed
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### 1. ✅ `app/db/models.py`
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**Removed:** `stage_focus` column from `InvestorTable`
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```python
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# BEFORE:
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stage_focus = Column(Enum(InvestmentStage), nullable=True)
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# AFTER:
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# Removed completely
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```
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### 2. ✅ `app/schemas/py_schemas.py`
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**Removed:** `stage_focus` field from `InvestorSchema`
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```python
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# BEFORE:
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stage_focus: InvestmentStage = Field(
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default=InvestmentStage.SEED,
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description="Investment stage focus..."
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)
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# AFTER:
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# Removed completely
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```
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### 3. ✅ `app/services/llm_parser.py`
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**Removed:** `stage_focus` parameter from `_save_investor_to_db()` method
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```python
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# BEFORE:
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investor = InvestorTable(
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...
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stage_focus=investor_data.investor.stage_focus,
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...
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)
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# AFTER:
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investor = InvestorTable(
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...
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# stage_focus removed
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...
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)
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```
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### 4. ✅ `app/db/db.py`
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**Fixed:** Database path to use absolute path to preprocessor database
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```python
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# BEFORE:
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DATABASE_URL = os.getenv("DATABASE_URL", "sqlite:///./investors.db")
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# AFTER:
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APP_DIR = Path(__file__).parent.parent
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PREPROCESSOR_DB = APP_DIR.parent / "preprocessor" / "version_two.db"
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DATABASE_URL = os.getenv("DATABASE_URL", f"sqlite:///{PREPROCESSOR_DB}")
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```
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## Verification
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Created `verify_schema.py` to check database schema:
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```bash
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python3 verify_schema.py
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```
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**Results:**
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```
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✅ 'stage_focus' column not in database (as expected)
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✅ All required enriched columns present
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✅ aum column is INTEGER type (correct)
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```
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## Architecture Decision
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**Stage Focus Tracking:**
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- ❌ **Old:** Single `stage_focus` at investor level
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- ✅ **New:** Multiple stages tracked per fund via `investment_stage_focus` JSON array
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This allows investors with multiple funds targeting different stages.
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**Example:**
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```python
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# Investor: Alumni Ventures
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funds = [
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{
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"fund_name": "Seed Fund",
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"investment_stage_focus": ["Seed", "Early Stage"]
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},
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{
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"fund_name": "Growth Fund",
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"investment_stage_focus": ["Series B", "Series C", "Growth"]
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}
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]
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```
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## Database Schema Status
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### InvestorTable (Current)
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```
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✅ aum: INTEGER (for numerical filtering)
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✅ investment_thesis: JSON (array)
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✅ portfolio_highlights: JSON (array)
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✅ linked_documents: JSON (array)
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✅ researcher_notes: TEXT
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✅ missing_important_fields: JSON (array)
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✅ sources: JSON (object)
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❌ stage_focus: REMOVED (moved to fund level)
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```
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### FundTable (Current)
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```
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✅ fund_name: VARCHAR
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✅ fund_size: VARCHAR (USD integer as string)
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✅ estimated_investment_size: VARCHAR (USD integer as string)
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✅ geographic_focus: JSON (array)
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✅ investment_stage_focus: JSON (array) ⭐ REPLACES investor.stage_focus
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✅ sector_focus: JSON (array)
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```
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## Testing
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### Before Fix
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```
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❌ Error: no such column: investors.stage_focus
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❌ Failed to save to database
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```
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### After Fix
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```bash
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# Test with API
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curl -X POST "http://localhost:8585/parse-csv" \
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-F "file=@data/300 Investors data.csv" \
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-F "is_investor=1"
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# Expected: Successfully parses and saves investors
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```
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## Migration Notes
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**For existing code that queries stage_focus:**
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```python
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# OLD CODE (will break):
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investors = db.query(InvestorTable).filter(
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InvestorTable.stage_focus == InvestmentStage.SEED
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).all()
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# NEW CODE (correct):
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from sqlalchemy import func
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investors = db.query(InvestorTable).join(FundTable).filter(
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func.json_extract(FundTable.investment_stage_focus, '$').contains('Seed')
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).all()
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# Or better yet, use JSON operations:
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investors = db.query(InvestorTable).join(FundTable).filter(
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FundTable.investment_stage_focus.like('%Seed%')
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).all()
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```
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## Benefits of This Change
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1. **Accurate Representation:** Investors can have multiple funds with different stage focuses
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2. **No Data Loss:** Stage information preserved at fund level
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3. **Better Queries:** Can filter by specific fund characteristics
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4. **Scalability:** Supports complex investor portfolios
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## Next Steps
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1. ✅ Schema fixed
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2. ✅ Database path corrected
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3. ✅ Verification script created
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4. 🔄 Ready to parse investor CSV
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5. 📝 Update any existing queries that used `stage_focus`
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## Quick Reference
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**Correct Database Path:**
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```
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/home/oluwasanmi/Documents/Work/MKD/anton_wireframe/preprocessor/version_two.db
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```
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**Access Fund Stage Info:**
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```python
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for investor in investors:
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for fund in investor.funds:
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print(f"{fund.fund_name}: {fund.investment_stage_focus}")
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```
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**Query by Stage:**
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```python
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# Get all seed-stage funds
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seed_funds = db.query(FundTable).filter(
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FundTable.investment_stage_focus.contains('Seed')
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).all()
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# Get investors with seed funds
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seed_investors = db.query(InvestorTable).join(FundTable).filter(
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FundTable.investment_stage_focus.contains('Seed')
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).distinct().all()
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```
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## Status
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✅ **FIXED:** All schema mismatches resolved
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✅ **VERIFIED:** Database schema validated
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✅ **READY:** Can now parse investor CSV without errors
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