forked from 0xWheatyz/SPARC
Compare commits
1 Commits
| Author | SHA1 | Date | |
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 agent-company
|
1bd9dccdb8 |
+56
-58
@@ -9,7 +9,7 @@ from typing import Annotated, List
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from fastapi import BackgroundTasks, Depends, FastAPI, HTTPException, Query, Request
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from fastapi.middleware.cors import CORSMiddleware
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from fastapi.responses import JSONResponse
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from fastapi.responses import JSONResponse, StreamingResponse
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from pydantic import BaseModel, EmailStr, Field
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from slowapi import Limiter
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from slowapi.errors import RateLimitExceeded
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@@ -169,9 +169,6 @@ async def lifespan(app: FastAPI):
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import logging
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logging.getLogger(__name__).warning("Marked %d stale jobs as failed on startup", stale)
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_db.close()
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# Start scheduled analysis if tracked companies are configured
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from SPARC.scheduler import start_scheduler
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start_scheduler()
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yield
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# Cleanup
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_analyzer = None
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@@ -372,60 +369,6 @@ async def delete_user(
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return {"message": "User deleted"}
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# ============== Tracked Companies Endpoints ==============
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class TrackCompanyRequest(BaseModel):
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"""Request to add a company to tracking."""
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company_name: str = Field(..., min_length=1, max_length=255)
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@app.get("/admin/tracked", tags=["Admin"])
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async def list_tracked_companies(
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_: UserResponse = Depends(get_current_admin),
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):
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"""List all tracked companies (admin only)."""
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db = get_db_client()
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return db.list_tracked_companies()
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@app.post("/admin/tracked", tags=["Admin"])
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async def add_tracked_company(
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request: TrackCompanyRequest,
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_: UserResponse = Depends(get_current_admin),
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):
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"""Add a company to the tracked list (admin only)."""
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db = get_db_client()
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result = db.add_tracked_company(request.company_name)
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if not result:
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raise HTTPException(status_code=409, detail="Company already tracked")
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return result
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@app.delete("/admin/tracked/{company_name}", tags=["Admin"])
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async def remove_tracked_company(
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company_name: str,
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_: UserResponse = Depends(get_current_admin),
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):
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"""Remove a company from the tracked list (admin only)."""
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db = get_db_client()
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removed = db.remove_tracked_company(company_name)
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if not removed:
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raise HTTPException(status_code=404, detail="Company not found in tracking list")
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return {"message": f"Stopped tracking {company_name}"}
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@app.get("/admin/alerts", tags=["Admin"])
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async def list_alerts(
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limit: int = Query(default=50, ge=1, le=200),
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_: UserResponse = Depends(get_current_admin),
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):
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"""List recent alerts from scheduled analysis (admin only)."""
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db = get_db_client()
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return db.list_alerts(limit=limit)
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# ============== Analytics Endpoint ==============
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@@ -446,6 +389,61 @@ async def get_analytics(
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)
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# ============== Export Endpoints ==============
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@app.get("/export/{company_name}", tags=["Export"])
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async def export_company_csv(
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company_name: str,
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_: UserResponse = Depends(get_current_user),
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):
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"""Export analysis results for a company as a CSV file.
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Returns all stored analysis records for the given company, including
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analysis type, model used, response text, and timestamp.
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Args:
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company_name: Company name to export results for
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Returns:
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CSV file download
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"""
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import csv
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import io
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db = get_db_client()
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# Query all non-cached analysis results for this company
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with db.get_conn() as conn:
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with conn.cursor() as cur:
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cur.execute(
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"""
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SELECT company_name, analysis_type, model, response, timestamp
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FROM llm_messages
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WHERE LOWER(company_name) = LOWER(%s) AND is_cached = FALSE
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ORDER BY timestamp DESC
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""",
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(company_name,),
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)
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rows = cur.fetchall()
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if not rows:
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raise HTTPException(status_code=404, detail=f"No analysis results found for '{company_name}'")
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output = io.StringIO()
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writer = csv.writer(output)
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writer.writerow(["company_name", "analysis_type", "model", "analysis", "timestamp"])
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for row in rows:
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writer.writerow(row)
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output.seek(0)
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safe_name = company_name.replace(" ", "_").lower()
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return StreamingResponse(
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iter([output.getvalue()]),
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media_type="text/csv",
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headers={"Content-Disposition": f'attachment; filename="sparc_{safe_name}_export.csv"'},
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)
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# ============== System Endpoints ==============
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@@ -192,35 +192,6 @@ class DatabaseClient:
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ON jobs(status)
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""")
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# Create tracked companies table for scheduled analysis
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cursor.execute("""
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CREATE TABLE IF NOT EXISTS tracked_companies (
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id SERIAL PRIMARY KEY,
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company_name VARCHAR(255) UNIQUE NOT NULL,
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last_patent_count INTEGER DEFAULT 0,
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last_analysis_at TIMESTAMP,
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created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP
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)
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""")
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# Create alerts table for significant changes
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cursor.execute("""
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CREATE TABLE IF NOT EXISTS alerts (
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id SERIAL PRIMARY KEY,
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company_name VARCHAR(255) NOT NULL,
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alert_type VARCHAR(50) NOT NULL,
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message TEXT NOT NULL,
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old_value NUMERIC,
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new_value NUMERIC,
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created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP
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)
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""")
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cursor.execute("""
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CREATE INDEX IF NOT EXISTS idx_alerts_company
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ON alerts(company_name)
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""")
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self.conn.commit()
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@staticmethod
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@@ -832,81 +803,3 @@ class DatabaseClient:
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with conn.cursor() as cursor:
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cursor.execute("SELECT COUNT(*) FROM users")
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return cursor.fetchone()[0]
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# Tracked Companies Methods
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def add_tracked_company(self, company_name: str) -> Optional[Dict]:
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"""Add a company to the tracking list."""
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with self.get_conn() as conn:
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with conn.cursor(cursor_factory=RealDictCursor) as cursor:
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try:
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cursor.execute(
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"INSERT INTO tracked_companies (company_name) VALUES (%s) RETURNING *",
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(company_name,),
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)
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row = cursor.fetchone()
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conn.commit()
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return dict(row) if row else None
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except Exception:
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conn.rollback()
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return None
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def remove_tracked_company(self, company_name: str) -> bool:
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"""Remove a company from the tracking list."""
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with self.get_conn() as conn:
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with conn.cursor() as cursor:
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cursor.execute(
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"DELETE FROM tracked_companies WHERE LOWER(company_name) = LOWER(%s)",
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(company_name,),
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)
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conn.commit()
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return cursor.rowcount > 0
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def list_tracked_companies(self) -> List[Dict]:
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"""List all tracked companies."""
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with self.get_conn() as conn:
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with conn.cursor(cursor_factory=RealDictCursor) as cursor:
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cursor.execute("SELECT * FROM tracked_companies ORDER BY company_name")
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return [dict(row) for row in cursor.fetchall()]
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def update_tracked_company(
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self, company_name: str, patent_count: int
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) -> None:
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"""Update the last analysis stats for a tracked company."""
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with self.get_conn() as conn:
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with conn.cursor() as cursor:
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cursor.execute(
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"""UPDATE tracked_companies
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SET last_patent_count = %s, last_analysis_at = CURRENT_TIMESTAMP
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WHERE LOWER(company_name) = LOWER(%s)""",
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(patent_count, company_name),
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)
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conn.commit()
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def store_alert(
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self,
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company_name: str,
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alert_type: str,
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message: str,
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old_value: float | None = None,
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new_value: float | None = None,
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) -> None:
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"""Record an alert for a significant change."""
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with self.get_conn() as conn:
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with conn.cursor() as cursor:
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cursor.execute(
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"""INSERT INTO alerts (company_name, alert_type, message, old_value, new_value)
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VALUES (%s, %s, %s, %s, %s)""",
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(company_name, alert_type, message, old_value, new_value),
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)
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conn.commit()
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def list_alerts(self, limit: int = 50) -> List[Dict]:
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"""List recent alerts."""
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with self.get_conn() as conn:
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with conn.cursor(cursor_factory=RealDictCursor) as cursor:
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cursor.execute(
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"SELECT * FROM alerts ORDER BY created_at DESC LIMIT %s",
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(limit,),
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)
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return [dict(row) for row in cursor.fetchall()]
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@@ -1,109 +0,0 @@
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"""Scheduled patent analysis for tracked companies.
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Uses APScheduler to periodically re-analyze tracked companies and
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detect significant changes in patent counts.
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"""
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import logging
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import os
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from SPARC import config
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from SPARC.analyzer import CompanyAnalyzer
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from SPARC.database import DatabaseClient
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logger = logging.getLogger(__name__)
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# Configurable via environment variable (in hours, default 24)
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SCHEDULE_INTERVAL_HOURS = int(os.getenv("SCHEDULE_INTERVAL_HOURS", "24"))
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# Patent count change threshold (percentage) to trigger an alert
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CHANGE_THRESHOLD_PERCENT = int(os.getenv("CHANGE_THRESHOLD_PERCENT", "20"))
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def run_scheduled_analysis() -> None:
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"""Re-analyze all tracked companies and check for significant changes."""
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db = DatabaseClient(config.database_url)
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db.connect()
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db.initialize_schema()
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tracked = db.list_tracked_companies()
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if not tracked:
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logger.info("No tracked companies configured; skipping scheduled analysis")
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return
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logger.info("Running scheduled analysis for %d tracked companies", len(tracked))
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analyzer = CompanyAnalyzer(db_client=db)
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for company_row in tracked:
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name = company_row["company_name"]
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old_count = company_row.get("last_patent_count", 0) or 0
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try:
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result = analyzer._analyze_company_safe(name)
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if result.success:
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new_count = result.patent_count
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# Update tracking record
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db.update_tracked_company(name, new_count)
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# Check for significant change
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if old_count > 0:
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delta_pct = abs(new_count - old_count) / old_count * 100
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if delta_pct >= CHANGE_THRESHOLD_PERCENT:
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direction = "increased" if new_count > old_count else "decreased"
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message = (
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f"Patent count for {name} {direction} by {delta_pct:.0f}% "
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f"({old_count} -> {new_count})"
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)
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logger.warning("ALERT: %s", message)
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db.store_alert(
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company_name=name,
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alert_type="patent_count_change",
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message=message,
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old_value=old_count,
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new_value=new_count,
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)
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elif new_count > 0:
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# First analysis -- record baseline
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logger.info("Baseline for %s: %d patents", name, new_count)
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else:
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logger.warning("Scheduled analysis failed for %s: %s", name, result.error)
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except Exception as e:
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logger.error("Error analyzing tracked company %s: %s", name, e)
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db.close()
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logger.info("Scheduled analysis complete")
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def start_scheduler() -> None:
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"""Start the APScheduler background scheduler.
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Safe to call at application startup. If apscheduler is not installed,
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the function logs a warning and returns without starting anything.
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"""
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try:
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from apscheduler.schedulers.background import BackgroundScheduler
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except ImportError:
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logger.warning(
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"apscheduler not installed; scheduled analysis disabled. "
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"Install with: pip install apscheduler"
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)
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return
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scheduler = BackgroundScheduler()
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scheduler.add_job(
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run_scheduled_analysis,
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"interval",
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hours=SCHEDULE_INTERVAL_HOURS,
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id="scheduled_patent_analysis",
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replace_existing=True,
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)
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scheduler.start()
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logger.info(
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"Scheduled patent analysis started (every %d hours, threshold %d%%)",
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SCHEDULE_INTERVAL_HOURS,
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CHANGE_THRESHOLD_PERCENT,
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)
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@@ -126,6 +126,23 @@ export const analysisApi = {
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},
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};
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// Export API
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export const exportApi = {
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exportCsv: async (companyName: string): Promise<void> => {
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const response = await api.get(`/export/${encodeURIComponent(companyName)}`, {
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responseType: 'blob',
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});
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const url = window.URL.createObjectURL(new Blob([response.data]));
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const link = document.createElement('a');
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link.href = url;
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link.setAttribute('download', `sparc_${companyName.toLowerCase().replace(/\s+/g, '_')}_export.csv`);
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document.body.appendChild(link);
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link.click();
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link.remove();
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window.URL.revokeObjectURL(url);
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},
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};
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// Analytics API
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export const analyticsApi = {
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getAnalytics: async (days = 30): Promise<Analytics> => {
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@@ -1,7 +1,7 @@
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import { useState } from 'react';
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import { useMutation } from '@tanstack/react-query';
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import { analysisApi } from '../api/client';
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import { Search, CheckCircle, AlertCircle, Clock, FileText } from 'lucide-react';
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import { analysisApi, exportApi } from '../api/client';
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import { Search, CheckCircle, AlertCircle, Clock, FileText, Download } from 'lucide-react';
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import type { CompanyAnalysis } from '../types';
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export function Analysis() {
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@@ -106,9 +106,18 @@ export function Analysis() {
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{/* Analysis Content */}
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{result.success && result.analysis && (
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<div className="bg-bg-card/60 backdrop-blur-lg border border-primary/15 rounded-2xl p-6">
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<h3 className="text-lg font-semibold text-text-primary border-b-2 border-primary/30 pb-2 mb-4">
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<div className="flex items-center justify-between border-b-2 border-primary/30 pb-2 mb-4">
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<h3 className="text-lg font-semibold text-text-primary">
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AI Analysis Results
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</h3>
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<button
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onClick={() => exportApi.exportCsv(result.company_name)}
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className="flex items-center gap-2 text-sm bg-primary/20 hover:bg-primary/30 text-primary font-medium px-3 py-1.5 rounded-lg transition-colors"
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>
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<Download size={14} />
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Export CSV
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</button>
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</div>
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<div className="prose prose-invert max-w-none">
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<div className="text-text-primary whitespace-pre-wrap leading-relaxed">
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{result.analysis}
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@@ -15,4 +15,3 @@ pandas
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bcrypt
|
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PyJWT
|
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slowapi
|
||||
apscheduler
|
||||
|
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Reference in New Issue
Block a user