fix: auto-download patent PDF in analyze_single_patent before reading

When the PDF is not on disk, analyze_single_patent now looks up the
cached PDF link from the database and downloads it automatically.
If no link is cached, a clear FileNotFoundError is raised. Also adds
a GET /analyze/patent/{patent_id} API endpoint that exposes this
functionality and returns 404 when the PDF cannot be obtained.

Closes leeworks-agents/SPARC#36

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

SPARC/analyzer.py

@@ -5,10 +5,13 @@ to provide company performance estimation based on patent portfolios.
 """
 
 import hashlib
+import logging
 from concurrent.futures import ThreadPoolExecutor, as_completed
 from typing import Callable
 
 from SPARC import config
+
+logger = logging.getLogger(__name__)
 from SPARC.database import DatabaseClient
 from SPARC.llm import LLMAnalyzer
 from SPARC.serp_api import SERP
@@ -52,13 +55,13 @@ class CompanyAnalyzer:
             query_hash = hashlib.sha256(company_name.lower().encode()).hexdigest()
             cached_ids = self.db.get_cached_serp_query(query_hash)
             if cached_ids is not None:
-                print(f"Using cached SERP results for {company_name} ({len(cached_ids)} patents)")
+                logger.info("Using cached SERP results for %s (%d patents)", company_name, len(cached_ids))
                 patents = Patents(patents=[
                     Patent(patent_id=pid, pdf_link="")
                     for pid in cached_ids
                 ])
             else:
-                print(f"Retrieving patents for {company_name}...")
+                logger.info("Retrieving patents for %s...", company_name)
                 patents = SERP.query(company_name)
                 # Cache the SERP results
                 if patents.patents:
@@ -66,12 +69,13 @@ class CompanyAnalyzer:
                         company_name=company_name,
                         query_hash=query_hash,
                         patent_ids=[p.patent_id for p in patents.patents],
+                        ttl_hours=config.serp_cache_ttl_hours,
                     )
 
         if not patents.patents:
             return f"No patents found for {company_name}"
 
-        print(f"Found {len(patents.patents)} patents. Processing...")
+        logger.info("Found %d patents. Processing...", len(patents.patents))
 
         # Download, parse, and minimize patents in parallel
         processed_patents = []
@@ -87,12 +91,12 @@ class CompanyAnalyzer:
                     if result:
                         processed_patents.append(result)
                 except Exception as e:
-                    print(f"Warning: Failed to process {patent.patent_id}: {e}")
+                    logger.warning("Failed to process %s: %s", patent.patent_id, e)
 
         if not processed_patents:
             return f"Failed to process any patents for {company_name}"
 
-        print("Analyzing portfolio with LLM...")
+        logger.info("Analyzing portfolio with LLM...")
 
         # Analyze the full portfolio with LLM
         analysis = self.llm_analyzer.analyze_patent_portfolio(
@@ -104,12 +108,10 @@ class CompanyAnalyzer:
     def analyze_single_patent(self, patent_id: str, company_name: str) -> str:
         """Analyze a single patent by ID.
 
-        Prerequisite:
-            The patent PDF must already exist at ``patents/{patent_id}.pdf``
-            before calling this method. PDFs are downloaded automatically when
-            using the batch analysis pipeline (``analyze_company`` or the
-            ``/analyze/batch`` API endpoint). For standalone usage, download
-            the PDF manually or call ``SERP.save_patents()`` first.
+        If the patent PDF is not already on disk, this method attempts to
+        download it automatically by looking up the PDF link in the database
+        cache. If the link is not cached either, a ``FileNotFoundError`` is
+        raised with instructions on how to obtain the PDF.
 
         Args:
           patent_id: Publication ID of the patent (e.g. "US-11234567-B2")
@@ -119,17 +121,30 @@ class CompanyAnalyzer:
           Analysis of the specific patent's innovation quality
 
         Raises:
-          FileNotFoundError: If the patent PDF is not found at the expected path.
+          FileNotFoundError: If the patent PDF cannot be found or downloaded.
         """
         import os
+        logger.info("Analyzing patent %s for %s...", patent_id, company_name)
 
         patent_path = f"patents/{patent_id}.pdf"
 
         if not os.path.exists(patent_path):
-            raise FileNotFoundError(
-                f"Patent PDF not found at '{patent_path}'. "
-                f"Download the PDF first using SERP.save_patents() or the batch analysis pipeline."
-            )
+            # Attempt to download the PDF automatically from cached metadata
+            cached = self.db.get_cached_patent(patent_id)
+            pdf_link = cached.get("pdf_link") if cached else None
+
+            if pdf_link:
+                logger.info("PDF not on disk; downloading %s from cached link", patent_id)
+                patent = SERP.save_patents(
+                    Patent(patent_id=patent_id, pdf_link=pdf_link)
+                )
+                patent_path = patent.pdf_path
+            else:
+                raise FileNotFoundError(
+                    f"Patent PDF not found at '{patent_path}' and no download link is "
+                    f"cached for '{patent_id}'. Run a company analysis first to populate "
+                    f"the cache, or call SERP.save_patents() with the patent's PDF link."
+                )
 
         try:
             sections = SERP.parse_patent_pdf(patent_path)
@@ -183,7 +198,7 @@ class CompanyAnalyzer:
 
             return {"patent_id": patent.patent_id, "content": minimized_content}
         except Exception as e:
-            print(f"Warning: Failed to process {patent.patent_id}: {e}")
+            logger.warning("Failed to process %s: %s", patent.patent_id, e)
             return None
 
     def _analyze_company_safe(self, company_name: str) -> CompanyAnalysisResult:
@@ -254,7 +269,7 @@ class CompanyAnalyzer:
         results: list[CompanyAnalysisResult] = []
         total = len(companies)
 
-        print(f"Starting batch analysis of {total} companies...")
+        logger.info("Starting batch analysis of %d companies...", total)
 
         with ThreadPoolExecutor(max_workers=max_workers) as executor:
             future_to_company = {
@@ -271,8 +286,8 @@ class CompanyAnalyzer:
                     result = future.result()
                     results.append(result)
 
-                    status = "✓" if result.success else "✗"
-                    print(f"[{completed}/{total}] {status} {company}")
+                    status = "OK" if result.success else "FAIL"
+                    logger.info("[%d/%d] %s %s", completed, total, status, company)
 
                     if progress_callback:
                         progress_callback(company, completed, total)
@@ -287,12 +302,12 @@ class CompanyAnalyzer:
                             error=str(e),
                         )
                     )
-                    print(f"[{completed}/{total}] ✗ {company}: {e}")
+                    logger.error("[%d/%d] FAIL %s: %s", completed, total, company, e)
 
         successful = sum(1 for r in results if r.success)
         failed = total - successful
 
-        print(f"\nBatch complete: {successful} succeeded, {failed} failed")
+        logger.info("Batch complete: %d succeeded, %d failed", successful, failed)
 
         return BatchAnalysisResult(
             results=results,
@@ -318,20 +333,20 @@ class CompanyAnalyzer:
         results: list[CompanyAnalysisResult] = []
         total = len(companies)
 
-        print(f"Starting sequential analysis of {total} companies...")
+        logger.info("Starting sequential analysis of %d companies...", total)
 
         for idx, company in enumerate(companies, 1):
-            print(f"\n[{idx}/{total}] Analyzing {company}...")
+            logger.info("[%d/%d] Analyzing %s...", idx, total, company)
             result = self._analyze_company_safe(company)
             results.append(result)
 
-            status = "✓" if result.success else "✗"
-            print(f"[{idx}/{total}] {status} {company}")
+            status = "OK" if result.success else "FAIL"
+            logger.info("[%d/%d] %s %s", idx, total, status, company)
 
         successful = sum(1 for r in results if r.success)
         failed = total - successful
 
-        print(f"\nBatch complete: {successful} succeeded, {failed} failed")
+        logger.info("Batch complete: %d succeeded, %d failed", successful, failed)
 
         return BatchAnalysisResult(
             results=results,

SPARC/api.py

@@ -21,11 +21,13 @@ from SPARC.auth import (
     TokenResponse,
     UserResponse,
     check_jwt_secret,
+    close_db_client,
     create_tokens,
     decode_token,
     get_current_admin,
     get_current_user,
     get_db_client,
+    init_db_client,
 )
 from SPARC.types import BatchAnalysisResult, CompanyAnalysisResult
 
@@ -155,6 +157,7 @@ async def lifespan(app: FastAPI):
     """Initialize resources on startup, clean up on shutdown."""
     global _analyzer
     check_jwt_secret()
+    init_db_client()
     _analyzer = CompanyAnalyzer()
     # Mark any jobs that were running/pending before the restart as failed
     from SPARC.database import DatabaseClient
@@ -167,8 +170,9 @@ async def lifespan(app: FastAPI):
         logging.getLogger(__name__).warning("Marked %d stale jobs as failed on startup", stale)
     _db.close()
     yield
-    # Cleanup if needed
+    # Cleanup
     _analyzer = None
+    close_db_client()
 
 
 app = FastAPI(
@@ -425,6 +429,38 @@ async def analyze_company(
     return _convert_result(result)
 
 
+@app.get(
+    "/analyze/patent/{patent_id}",
+    tags=["Analysis"],
+)
+async def analyze_single_patent(
+    patent_id: str,
+    company_name: str = Query(description="Company name for analysis context"),
+    _: UserResponse = Depends(get_current_user),
+):
+    """Analyze a single patent by its publication ID.
+
+    If the patent PDF is not already cached locally, the system will attempt
+    to download it automatically from a previously cached link. If no link
+    is available, a 404 error is returned.
+
+    Args:
+        patent_id: Patent publication ID (e.g. "US-11234567-B2")
+        company_name: Company name for analysis context
+
+    Returns:
+        Analysis text for the patent
+    """
+    if not _analyzer:
+        raise HTTPException(status_code=503, detail="Analyzer not initialized")
+
+    try:
+        analysis = _analyzer.analyze_single_patent(patent_id, company_name)
+        return {"patent_id": patent_id, "company_name": company_name, "analysis": analysis}
+    except FileNotFoundError as e:
+        raise HTTPException(status_code=404, detail=str(e))
+
+
 @app.post(
     "/analyze/batch",
     response_model=BatchAnalysisResponse,

SPARC/auth.py

@@ -146,11 +146,36 @@ def decode_token(token: str) -> Optional[TokenPayload]:
         return None
 
 
+# Shared database client singleton, initialized at startup via init_db_client()
+_db_client: DatabaseClient | None = None
+
+
+def init_db_client() -> None:
+    """Initialize the shared database client. Call once at app startup."""
+    global _db_client
+    _db_client = DatabaseClient(config.database_url)
+    _db_client.connect()
+
+
+def close_db_client() -> None:
+    """Close the shared database client. Call at app shutdown."""
+    global _db_client
+    if _db_client:
+        _db_client.close()
+        _db_client = None
+
+
 def get_db_client() -> DatabaseClient:
-    """Get database client for auth operations."""
-    client = DatabaseClient(config.database_url)
-    client.connect()
-    return client
+    """Get the shared pooled database client for auth operations.
+
+    Returns the module-level singleton DatabaseClient. If not yet initialized
+    (e.g., during tests), creates a new instance as a fallback.
+    """
+    global _db_client
+    if _db_client is None:
+        _db_client = DatabaseClient(config.database_url)
+        _db_client.connect()
+    return _db_client
 
 
 async def get_current_user(

SPARC/config.py

@@ -2,12 +2,20 @@
 
 Loads environment variables from .env file for API keys and other secrets.
 """
+import logging
 import os
 
 from dotenv import load_dotenv
 
 load_dotenv()
 
+# Logging configuration
+log_level = os.getenv("LOG_LEVEL", "INFO").upper()
+logging.basicConfig(
+    level=getattr(logging, log_level, logging.INFO),
+    format="%(asctime)s %(levelname)s %(name)s %(message)s",
+)
+
 # SerpAPI key for patent search
 api_key = os.getenv("API_KEY")
 
@@ -31,6 +39,12 @@ use_database = os.getenv("USE_DATABASE", "false").lower() in ("true", "1", "yes"
 patent_search_days = int(os.getenv("PATENT_SEARCH_DAYS", "90"))
 patent_thread_workers = int(os.getenv("PATENT_THREAD_WORKERS", "5"))
 
+# LLM model to use via OpenRouter (e.g. "anthropic/claude-3.5-sonnet", "openai/gpt-4o")
+model = os.getenv("MODEL", "anthropic/claude-3.5-sonnet")
+
+# SERP cache TTL in hours (how long cached search results are considered fresh)
+serp_cache_ttl_hours = int(os.getenv("SERP_CACHE_TTL_HOURS", "24"))
+
 # Root path for running behind a reverse proxy (e.g., "/api" when served at /api/)
 # This ensures OpenAPI docs work correctly when accessed via the proxy
 root_path = os.getenv("ROOT_PATH", "")

SPARC/database.py

@@ -222,8 +222,6 @@ class DatabaseClient:
         Returns:
             Cached message dict if found, None otherwise
         """
-        self.connect()
-
         prompt_hash = self.hash_prompt(prompt)
 
         query = """
@@ -246,10 +244,11 @@ class DatabaseClient:
 
         query += " ORDER BY timestamp DESC LIMIT 1"
 
-        with self.conn.cursor(cursor_factory=RealDictCursor) as cursor:
-            cursor.execute(query, params)
-            result = cursor.fetchone()
-            return dict(result) if result else None
+        with self.get_conn() as conn:
+            with conn.cursor(cursor_factory=RealDictCursor) as cursor:
+                cursor.execute(query, params)
+                result = cursor.fetchone()
+                return dict(result) if result else None
 
     def store_message(
         self,
@@ -277,33 +276,32 @@ class DatabaseClient:
         Returns:
             The ID of the inserted record
         """
-        self.connect()
-
         prompt_hash = self.hash_prompt(prompt)
 
-        with self.conn.cursor() as cursor:
-            cursor.execute(
-                """
-                INSERT INTO llm_messages
-                (prompt, prompt_hash, response, company_name, analysis_type, model, metadata, token_usage, is_cached)
-                VALUES (%s, %s, %s, %s, %s, %s, %s, %s, %s)
-                RETURNING id
-                """,
-                (
-                    prompt,
-                    prompt_hash,
-                    response,
-                    company_name,
-                    analysis_type,
-                    model,
-                    json.dumps(metadata) if metadata else None,
-                    json.dumps(token_usage) if token_usage else None,
-                    is_cached,
-                ),
-            )
+        with self.get_conn() as conn:
+            with conn.cursor() as cursor:
+                cursor.execute(
+                    """
+                    INSERT INTO llm_messages
+                    (prompt, prompt_hash, response, company_name, analysis_type, model, metadata, token_usage, is_cached)
+                    VALUES (%s, %s, %s, %s, %s, %s, %s, %s, %s)
+                    RETURNING id
+                    """,
+                    (
+                        prompt,
+                        prompt_hash,
+                        response,
+                        company_name,
+                        analysis_type,
+                        model,
+                        json.dumps(metadata) if metadata else None,
+                        json.dumps(token_usage) if token_usage else None,
+                        is_cached,
+                    ),
+                )
 
-            message_id = cursor.fetchone()[0]
-            self.conn.commit()
+                message_id = cursor.fetchone()[0]
+            conn.commit()
 
             return message_id
 
@@ -325,8 +323,6 @@ class DatabaseClient:
         Returns:
             List of message dictionaries
         """
-        self.connect()
-
         query = "SELECT * FROM llm_messages WHERE 1=1"
         params = []
 
@@ -341,9 +337,10 @@ class DatabaseClient:
         query += " ORDER BY timestamp DESC LIMIT %s OFFSET %s"
         params.extend([limit, offset])
 
-        with self.conn.cursor(cursor_factory=RealDictCursor) as cursor:
-            cursor.execute(query, params)
-            return [dict(row) for row in cursor.fetchall()]
+        with self.get_conn() as conn:
+            with conn.cursor(cursor_factory=RealDictCursor) as cursor:
+                cursor.execute(query, params)
+                return [dict(row) for row in cursor.fetchall()]
 
     def get_analytics(self, days: int = 30) -> Dict:
         """Get analytics on message usage.
@@ -354,53 +351,52 @@ class DatabaseClient:
         Returns:
             Dictionary with analytics data
         """
-        self.connect()
+        with self.get_conn() as conn:
+            with conn.cursor(cursor_factory=RealDictCursor) as cursor:
+                # Total messages
+                cursor.execute(
+                    """
+                    SELECT COUNT(*) as total_messages
+                    FROM llm_messages
+                    WHERE timestamp >= NOW() - INTERVAL '%s days'
+                    """,
+                    (days,),
+                )
+                total = cursor.fetchone()["total_messages"]
 
-        with self.conn.cursor(cursor_factory=RealDictCursor) as cursor:
-            # Total messages
-            cursor.execute(
-                """
-                SELECT COUNT(*) as total_messages
-                FROM llm_messages
-                WHERE timestamp >= NOW() - INTERVAL '%s days'
-                """,
-                (days,),
-            )
-            total = cursor.fetchone()["total_messages"]
+                # Messages by company
+                cursor.execute(
+                    """
+                    SELECT company_name, COUNT(*) as count
+                    FROM llm_messages
+                    WHERE timestamp >= NOW() - INTERVAL '%s days'
+                    GROUP BY company_name
+                    ORDER BY count DESC
+                    LIMIT 10
+                    """,
+                    (days,),
+                )
+                by_company = cursor.fetchall()
 
-            # Messages by company
-            cursor.execute(
-                """
-                SELECT company_name, COUNT(*) as count
-                FROM llm_messages
-                WHERE timestamp >= NOW() - INTERVAL '%s days'
-                GROUP BY company_name
-                ORDER BY count DESC
-                LIMIT 10
-                """,
-                (days,),
-            )
-            by_company = cursor.fetchall()
+                # Messages by type
+                cursor.execute(
+                    """
+                    SELECT analysis_type, COUNT(*) as count
+                    FROM llm_messages
+                    WHERE timestamp >= NOW() - INTERVAL '%s days'
+                    GROUP BY analysis_type
+                    ORDER BY count DESC
+                    """,
+                    (days,),
+                )
+                by_type = cursor.fetchall()
 
-            # Messages by type
-            cursor.execute(
-                """
-                SELECT analysis_type, COUNT(*) as count
-                FROM llm_messages
-                WHERE timestamp >= NOW() - INTERVAL '%s days'
-                GROUP BY analysis_type
-                ORDER BY count DESC
-                """,
-                (days,),
-            )
-            by_type = cursor.fetchall()
-
-            return {
-                "total_messages": total,
-                "by_company": [dict(row) for row in by_company],
-                "by_type": [dict(row) for row in by_type],
-                "period_days": days,
-            }
+                return {
+                    "total_messages": total,
+                    "by_company": [dict(row) for row in by_company],
+                    "by_type": [dict(row) for row in by_type],
+                    "period_days": days,
+                }
 
     # Patent Cache Methods
 
@@ -651,25 +647,23 @@ class DatabaseClient:
         Returns:
             Created user dict or None if email exists
         """
-        self.connect()
-
         password_hash = self.hash_password(password)
 
         try:
-            with self.conn.cursor(cursor_factory=RealDictCursor) as cursor:
-                cursor.execute(
-                    """
-                    INSERT INTO users (email, password_hash, role)
-                    VALUES (%s, %s, %s)
-                    RETURNING id, email, role, created_at
-                    """,
-                    (email, password_hash, role),
-                )
-                user = cursor.fetchone()
-                self.conn.commit()
+            with self.get_conn() as conn:
+                with conn.cursor(cursor_factory=RealDictCursor) as cursor:
+                    cursor.execute(
+                        """
+                        INSERT INTO users (email, password_hash, role)
+                        VALUES (%s, %s, %s)
+                        RETURNING id, email, role, created_at
+                        """,
+                        (email, password_hash, role),
+                    )
+                    user = cursor.fetchone()
+                conn.commit()
                 return dict(user) if user else None
         except psycopg2.errors.UniqueViolation:
-            self.conn.rollback()
             return None
 
     def authenticate_user(self, email: str, password: str) -> Optional[Dict]:
@@ -682,23 +676,22 @@ class DatabaseClient:
         Returns:
             User dict if authenticated, None otherwise
         """
-        self.connect()
+        with self.get_conn() as conn:
+            with conn.cursor(cursor_factory=RealDictCursor) as cursor:
+                cursor.execute(
+                    "SELECT * FROM users WHERE email = %s",
+                    (email,),
+                )
+                user = cursor.fetchone()
 
-        with self.conn.cursor(cursor_factory=RealDictCursor) as cursor:
-            cursor.execute(
-                "SELECT * FROM users WHERE email = %s",
-                (email,),
-            )
-            user = cursor.fetchone()
-
-            if user and self.verify_password(password, user["password_hash"]):
-                return {
-                    "id": user["id"],
-                    "email": user["email"],
-                    "role": user["role"],
-                    "created_at": user["created_at"],
-                }
-            return None
+                if user and self.verify_password(password, user["password_hash"]):
+                    return {
+                        "id": user["id"],
+                        "email": user["email"],
+                        "role": user["role"],
+                        "created_at": user["created_at"],
+                    }
+                return None
 
     def get_user_by_id(self, user_id: int) -> Optional[Dict]:
         """Get a user by ID.
@@ -709,15 +702,14 @@ class DatabaseClient:
         Returns:
             User dict or None
         """
-        self.connect()
-
-        with self.conn.cursor(cursor_factory=RealDictCursor) as cursor:
-            cursor.execute(
-                "SELECT id, email, role, created_at FROM users WHERE id = %s",
-                (user_id,),
-            )
-            user = cursor.fetchone()
-            return dict(user) if user else None
+        with self.get_conn() as conn:
+            with conn.cursor(cursor_factory=RealDictCursor) as cursor:
+                cursor.execute(
+                    "SELECT id, email, role, created_at FROM users WHERE id = %s",
+                    (user_id,),
+                )
+                user = cursor.fetchone()
+                return dict(user) if user else None
 
     def get_user_by_email(self, email: str) -> Optional[Dict]:
         """Get a user by email.
@@ -728,15 +720,14 @@ class DatabaseClient:
         Returns:
             User dict or None
         """
-        self.connect()
-
-        with self.conn.cursor(cursor_factory=RealDictCursor) as cursor:
-            cursor.execute(
-                "SELECT id, email, role, created_at FROM users WHERE email = %s",
-                (email,),
-            )
-            user = cursor.fetchone()
-            return dict(user) if user else None
+        with self.get_conn() as conn:
+            with conn.cursor(cursor_factory=RealDictCursor) as cursor:
+                cursor.execute(
+                    "SELECT id, email, role, created_at FROM users WHERE email = %s",
+                    (email,),
+                )
+                user = cursor.fetchone()
+                return dict(user) if user else None
 
     def get_all_users(self, limit: int = 100, offset: int = 0) -> List[Dict]:
         """Get all users (admin only).
@@ -748,19 +739,18 @@ class DatabaseClient:
         Returns:
             List of user dicts
         """
-        self.connect()
-
-        with self.conn.cursor(cursor_factory=RealDictCursor) as cursor:
-            cursor.execute(
-                """
-                SELECT id, email, role, created_at
-                FROM users
-                ORDER BY created_at DESC
-                LIMIT %s OFFSET %s
-                """,
-                (limit, offset),
-            )
-            return [dict(row) for row in cursor.fetchall()]
+        with self.get_conn() as conn:
+            with conn.cursor(cursor_factory=RealDictCursor) as cursor:
+                cursor.execute(
+                    """
+                    SELECT id, email, role, created_at
+                    FROM users
+                    ORDER BY created_at DESC
+                    LIMIT %s OFFSET %s
+                    """,
+                    (limit, offset),
+                )
+                return [dict(row) for row in cursor.fetchall()]
 
     def update_user_role(self, user_id: int, role: str) -> Optional[Dict]:
         """Update a user's role (admin only).
@@ -772,20 +762,19 @@ class DatabaseClient:
         Returns:
             Updated user dict or None
         """
-        self.connect()
-
-        with self.conn.cursor(cursor_factory=RealDictCursor) as cursor:
-            cursor.execute(
-                """
-                UPDATE users
-                SET role = %s, updated_at = CURRENT_TIMESTAMP
-                WHERE id = %s
-                RETURNING id, email, role, created_at
-                """,
-                (role, user_id),
-            )
-            user = cursor.fetchone()
-            self.conn.commit()
+        with self.get_conn() as conn:
+            with conn.cursor(cursor_factory=RealDictCursor) as cursor:
+                cursor.execute(
+                    """
+                    UPDATE users
+                    SET role = %s, updated_at = CURRENT_TIMESTAMP
+                    WHERE id = %s
+                    RETURNING id, email, role, created_at
+                    """,
+                    (role, user_id),
+                )
+                user = cursor.fetchone()
+            conn.commit()
             return dict(user) if user else None
 
     def delete_user(self, user_id: int) -> bool:
@@ -797,12 +786,11 @@ class DatabaseClient:
         Returns:
             True if deleted
         """
-        self.connect()
-
-        with self.conn.cursor() as cursor:
-            cursor.execute("DELETE FROM users WHERE id = %s", (user_id,))
-            deleted = cursor.rowcount > 0
-            self.conn.commit()
+        with self.get_conn() as conn:
+            with conn.cursor() as cursor:
+                cursor.execute("DELETE FROM users WHERE id = %s", (user_id,))
+                deleted = cursor.rowcount > 0
+            conn.commit()
             return deleted
 
     def get_user_count(self) -> int:
@@ -811,8 +799,7 @@ class DatabaseClient:
         Returns:
             Number of users
         """
-        self.connect()
-
-        with self.conn.cursor() as cursor:
-            cursor.execute("SELECT COUNT(*) FROM users")
-            return cursor.fetchone()[0]
+        with self.get_conn() as conn:
+            with conn.cursor() as cursor:
+                cursor.execute("SELECT COUNT(*) FROM users")
+                return cursor.fetchone()[0]

SPARC/llm.py

@@ -1,5 +1,6 @@
 """LLM integration for patent analysis using OpenRouter."""
 
+import logging
 from typing import Dict
 
 from openai import OpenAI
@@ -7,6 +8,8 @@ from openai import OpenAI
 from SPARC import config
 from SPARC.database import DatabaseClient
 
+logger = logging.getLogger(__name__)
+
 
 class LLMAnalyzer:
     """Handles LLM-based analysis of patent content."""
@@ -22,7 +25,7 @@ class LLMAnalyzer:
         """
         self.test_mode = test_mode
         self.use_cache = use_cache if use_cache is not None else config.use_cache
-        self.model = "anthropic/claude-3.5-sonnet"
+        self.model = config.model
 
         # Always initialize database client for storage and caching
         self.db_client = DatabaseClient(config.database_url)
@@ -61,11 +64,7 @@ Patent Content:
 Provide a concise analysis (2-3 paragraphs) focusing on what this patent reveals about the company's technical direction and competitive advantage."""
 
         if self.test_mode:
-            print("=" * 80)
-            print("TEST MODE - Prompt that would be sent to LLM:")
-            print("=" * 80)
-            print(prompt)
-            print("=" * 80)
+            logger.debug("TEST MODE - Prompt that would be sent to LLM:\n%s", prompt)
             return "[TEST MODE - No API call made]"
 
         # Check cache first
@@ -167,7 +166,7 @@ Patent Portfolio:
 Provide a comprehensive analysis (4-5 paragraphs) with a final verdict on the company's innovation strength and performance outlook."""
 
         if self.test_mode:
-            print(prompt)
+            logger.debug("TEST MODE - Portfolio prompt:\n%s", prompt)
             return "[TEST MODE]"
 
         metadata = {

SPARC/types.py

@@ -4,7 +4,7 @@ from datetime import datetime
 
 @dataclass
 class Patent:
-    patent_id: int
+    patent_id: str
     pdf_link: str
     pdf_path: str | None = None
     summary: dict | None = None