tests: testing modes have been added in an attempt to tune without wasting tokens.

SPARC/llm.py

@@ -8,14 +8,20 @@ from typing import Dict
 class LLMAnalyzer:
     """Handles LLM-based analysis of patent content."""
 
-    def __init__(self, api_key: str | None = None):
+    def __init__(self, api_key: str | None = None, test_mode: bool = False):
         """Initialize the LLM analyzer.
 
         Args:
           api_key: Anthropic API key. If None, will attempt to load from config.
+          test_mode: If True, print prompts instead of making API calls
         """
-        self.client = Anthropic(api_key=api_key or config.anthropic_api_key)
-        self.model = "claude-3-5-sonnet-20241022"
+        self.test_mode = test_mode
+
+        if config.anthropic_api_key and not test_mode:
+            self.client = Anthropic(api_key=api_key or config.anthropic_api_key)
+            self.model = "claude-3-5-sonnet-20241022"
+        else:
+            self.client = None
 
     def analyze_patent_content(self, patent_content: str, company_name: str) -> str:
         """Analyze patent content to estimate company innovation and performance.
@@ -40,14 +46,22 @@ Patent Content:
 
 Provide a concise analysis (2-3 paragraphs) focusing on what this patent reveals about the company's technical direction and competitive advantage."""
 
-        message = self.client.messages.create(
-            model=self.model,
-            max_tokens=1024,
-            messages=[{"role": "user", "content": prompt}],
-        )
-
-        return message.content[0].text
+        if self.test_mode:
+            print("=" * 80)
+            print("TEST MODE - Prompt that would be sent to LLM:")
+            print("=" * 80)
+            print(prompt)
+            print("=" * 80)
+            return "[TEST MODE - No API call made]"
 
+        if self.client:
+            message = self.client.messages.create(
+                model=self.model,
+                max_tokens=1024,
+                messages=[{"role": "user", "content": prompt}],
+            )
+            return message.content[0].text
+       
     def analyze_patent_portfolio(
         self, patents_data: list[Dict[str, str]], company_name: str
     ) -> str:
@@ -84,10 +98,18 @@ Patent Portfolio:
 
 Provide a comprehensive analysis (4-5 paragraphs) with a final verdict on the company's innovation strength and performance outlook."""
 
-        message = self.client.messages.create(
-            model=self.model,
-            max_tokens=2048,
-            messages=[{"role": "user", "content": prompt}],
-        )
+        if self.test_mode:
+            print(prompt)
+            return "[TEST MODE]"
 
-        return message.content[0].text
+        try:
+            message = self.client.messages.create(
+                model=self.model,
+                max_tokens=2048,
+                messages=[{"role": "user", "content": prompt}],
+            )
+
+            return message.content[0].text
+        except AttributeError:
+            return prompt
+