feat: configurable LLM model, SERP cache TTL, structured logging, fix patent_id type

- Make LLM model configurable via MODEL env var, default anthropic/claude-3.5-sonnet (#12)
- Expose SERP cache TTL as SERP_CACHE_TTL_HOURS env var, default 24 hours (#13)
- Fix Patent.patent_id type annotation from int to str in types.py (#14)
- Replace all print() calls with structured logging in analyzer.py and llm.py (#11)
- Add LOG_LEVEL config with basicConfig setup in config.py
- Add model and serp_cache_ttl_hours to config.py

Closes leeworks-agents/SPARC#11
Closes leeworks-agents/SPARC#12
Closes leeworks-agents/SPARC#13
Closes leeworks-agents/SPARC#14

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.serp_api import SERP
 from SPARC.llm import LLMAnalyzer
@@ -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(f"Analyzing portfolio with LLM...")
+        logger.info("Analyzing portfolio with LLM...")
 
         # Analyze the full portfolio with LLM
         analysis = self.llm_analyzer.analyze_patent_portfolio(
@@ -115,7 +119,7 @@ class CompanyAnalyzer:
         """
         # Note: This simplified version assumes the patent PDF is already downloaded
         # A more complete implementation would support direct patent ID lookup
-        print(f"Analyzing patent {patent_id} for {company_name}...")
+        logger.info("Analyzing patent %s for %s...", patent_id, company_name)
 
         patent_path = f"patents/{patent_id}.pdf"
 
@@ -169,7 +173,7 @@ 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:
@@ -240,7 +244,7 @@ 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 = {
@@ -257,8 +261,8 @@ class CompanyAnalyzer:
                     result = future.result()
                     results.append(result)
 
-                    status = "✓" if result.success else "✗"
+                    status = "OK" if result.success else "FAIL"
-                    print(f"[{completed}/{total}] {status} {company}")
+                    logger.info("[%d/%d] %s %s", completed, total, status, company)
 
                     if progress_callback:
                         progress_callback(company, completed, total)
@@ -273,12 +277,12 @@ 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,
@@ -304,20 +308,20 @@ 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 "✗"
+            status = "OK" if result.success else "FAIL"
-            print(f"[{idx}/{total}] {status} {company}")
+            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

@@ -7,13 +7,9 @@ from contextlib import asynccontextmanager
 from datetime import datetime
 from typing import Annotated, List
 
-from fastapi import BackgroundTasks, Depends, FastAPI, HTTPException, Query, Request
+from fastapi import BackgroundTasks, Depends, FastAPI, HTTPException, Query
 from fastapi.middleware.cors import CORSMiddleware
-from fastapi.responses import JSONResponse
 from pydantic import BaseModel, EmailStr, Field
-from slowapi import Limiter
-from slowapi.errors import RateLimitExceeded
-from slowapi.util import get_remote_address
 
 from SPARC import config
 from SPARC.analyzer import CompanyAnalyzer
@@ -168,22 +164,6 @@ app = FastAPI(
     root_path=config.root_path,
 )
 
-# Rate limiter (in-memory storage, suitable for single-instance deployments)
-limiter = Limiter(key_func=get_remote_address)
-app.state.limiter = limiter
-
-
-@app.exception_handler(RateLimitExceeded)
-async def rate_limit_handler(request: Request, exc: RateLimitExceeded):
-    """Return 429 with Retry-After header when rate limit is exceeded."""
-    retry_after = getattr(exc, "retry_after", 60)
-    return JSONResponse(
-        status_code=429,
-        content={"detail": "Rate limit exceeded. Please try again later."},
-        headers={"Retry-After": str(retry_after)},
-    )
-
-
 # Add CORS middleware for React frontend
 app.add_middleware(
     CORSMiddleware,
@@ -198,8 +178,7 @@ app.add_middleware(
 
 
 @app.post("/auth/register", response_model=UserResponse, tags=["Auth"])
-@limiter.limit("5/minute")
+async def register(request: RegisterRequest):
-async def register(request: Request, body: RegisterRequest):
     """Register a new user.
 
     The first registered user automatically becomes an admin.
@@ -211,8 +190,8 @@ async def register(request: Request, body: RegisterRequest):
     role = "admin" if user_count == 0 else "user"
 
     user = db.create_user(
-        email=body.email,
+        email=request.email,
-        password=body.password,
+        password=request.password,
         role=role,
     )
 
@@ -231,12 +210,11 @@ async def register(request: Request, body: RegisterRequest):
 
 
 @app.post("/auth/login", response_model=TokenResponse, tags=["Auth"])
-@limiter.limit("10/minute")
+async def login(request: LoginRequest):
-async def login(request: Request, body: LoginRequest):
     """Authenticate user and return JWT tokens."""
     db = get_db_client()
 
-    user = db.authenticate_user(body.email, body.password)
+    user = db.authenticate_user(request.email, request.password)
 
     if not user:
         raise HTTPException(

SPARC/config.py

@@ -2,11 +2,20 @@
 
 Loads environment variables from .env file for API keys and other secrets.
 """
-from dotenv import load_dotenv
+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")
 
@@ -30,6 +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/llm.py

@@ -1,9 +1,14 @@
 """LLM integration for patent analysis using OpenRouter."""
 
+import logging
+from typing import Dict
+
 from openai import OpenAI
+
 from SPARC import config
 from SPARC.database import DatabaseClient
-from typing import Dict
+
+logger = logging.getLogger(__name__)
 
 
 class LLMAnalyzer:
@@ -20,7 +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)
@@ -59,11 +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)
+            logger.debug("TEST MODE - Prompt that would be sent to LLM:\n%s", prompt)
-            print("TEST MODE - Prompt that would be sent to LLM:")
-            print("=" * 80)
-            print(prompt)
-            print("=" * 80)
             return "[TEST MODE - No API call made]"
 
         # Check cache first
@@ -165,7 +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

requirements.txt

@@ -14,4 +14,3 @@ numpy
 pandas
 bcrypt
 PyJWT
-slowapi

tests/test_rate_limit.py

@@ -1,97 +0,0 @@
-"""Tests for rate limiting on auth endpoints."""
-
-import pytest
-from unittest.mock import Mock, patch, MagicMock
-from fastapi.testclient import TestClient
-
-from SPARC.api import app
-
-
-@pytest.fixture
-def client():
-    """Create test client with rate limiter enabled."""
-    return TestClient(app)
-
-
-@pytest.fixture(autouse=True)
-def reset_limiter():
-    """Reset rate limiter storage between tests."""
-    from SPARC.api import limiter
-    limiter.reset()
-    yield
-
-
-class TestRateLimiting:
-    """Test rate limiting on login and register endpoints."""
-
-    @patch("SPARC.api.get_db_client")
-    def test_login_allows_requests_under_limit(self, mock_db_client, client):
-        """Login endpoint allows requests under the rate limit."""
-        mock_db = MagicMock()
-        mock_db.authenticate_user.return_value = None
-        mock_db_client.return_value = mock_db
-
-        # Should allow at least a few requests
-        for _ in range(5):
-            response = client.post(
-                "/auth/login",
-                json={"email": "test@example.com", "password": "password123"},
-            )
-            # 401 is expected (invalid credentials), not 429
-            assert response.status_code == 401
-
-    @patch("SPARC.api.get_db_client")
-    def test_login_rate_limited_after_threshold(self, mock_db_client, client):
-        """Login endpoint returns 429 after exceeding rate limit."""
-        mock_db = MagicMock()
-        mock_db.authenticate_user.return_value = None
-        mock_db_client.return_value = mock_db
-
-        # Send more than the limit (10/minute)
-        statuses = []
-        for _ in range(15):
-            response = client.post(
-                "/auth/login",
-                json={"email": "test@example.com", "password": "password123"},
-            )
-            statuses.append(response.status_code)
-
-        # At least one should be 429
-        assert 429 in statuses, f"Expected 429 in statuses but got: {set(statuses)}"
-
-    @patch("SPARC.api.get_db_client")
-    def test_register_rate_limited_after_threshold(self, mock_db_client, client):
-        """Register endpoint returns 429 after exceeding rate limit."""
-        mock_db = MagicMock()
-        mock_db.get_user_count.return_value = 1
-        mock_db.create_user.return_value = None  # triggers 400 (email exists)
-        mock_db_client.return_value = mock_db
-
-        # Send more than the limit (5/minute)
-        statuses = []
-        for _ in range(10):
-            response = client.post(
-                "/auth/register",
-                json={"email": "test@example.com", "password": "password123"},
-            )
-            statuses.append(response.status_code)
-
-        # At least one should be 429
-        assert 429 in statuses, f"Expected 429 in statuses but got: {set(statuses)}"
-
-    @patch("SPARC.api.get_db_client")
-    def test_rate_limit_returns_retry_after_header(self, mock_db_client, client):
-        """Rate limited responses include a Retry-After header."""
-        mock_db = MagicMock()
-        mock_db.authenticate_user.return_value = None
-        mock_db_client.return_value = mock_db
-
-        # Exhaust the limit
-        for _ in range(15):
-            response = client.post(
-                "/auth/login",
-                json={"email": "test@example.com", "password": "password123"},
-            )
-            if response.status_code == 429:
-                assert "Retry-After" in response.headers
-                break