Update gemini_agent.py

gemini_agent.py

@@ -19,7 +19,7 @@ class GeminiAgent:
         api_key = os.getenv('GOOGLE_API_KEY')
         genai.configure(api_key=api_key)
         
-        self.model = genai.GenerativeModel('gemini-2.0-flash')
+        self.model = genai.GenerativeModel('gemini-2.5-flash')
         self.last_request_time = 0
         self.min_request_interval = 8.0  # 7 seconds between requests (10 per minute limit, with margin)
         
@@ -163,27 +163,43 @@ Provide only the direct answer. If it's a quote, give just the quoted text. If i
     async def _handle_text_question(self, question: str) -> str:
         """Handle regular text-based questions"""
         prompt = ""
-        # Only use retrieval for explicit web/Wikipedia questions
+        # Use retrieval for explicit web/Wikipedia questions and factual queries
         def is_explicit_retrieval_question(question):
             q = question.lower()
-            return (
-                "according to wikipedia" in q or
-                "from wikipedia" in q or
-                "search the web" in q or
-                "duckduckgo" in q or
-                "web search" in q
-            )
+            # Explicit retrieval requests
+            explicit_triggers = [
+                "according to wikipedia", "from wikipedia", "search the web", 
+                "duckduckgo", "web search"
+            ]
+            # Factual question patterns that benefit from Wikipedia
+            factual_triggers = [
+                "who played", "actor who", "actress who", "cast of", "starred in",
+                "tv show", "television", "movie", "film", "character in",
+                "version of", "adaptation of", "remake of",
+                # New triggers for entity-relationship/role questions
+                "who did the actor", "who did the actress", "role in", "portrayed in", "played in", "give only the first name"
+            ]
+            # Also trigger if question starts with 'who' and mentions 'actor', 'actress', 'role', or 'character'
+            if q.startswith('who') and any(x in q for x in ["actor", "actress", "role", "character"]):
+                return True
+            return any(trigger in q for trigger in explicit_triggers + factual_triggers)
         wiki_context = ""
         ddg_context = ""
         if is_explicit_retrieval_question(question):
-            if "wikipedia" in question.lower():
-                try:
-                    wiki_context = self.wiki_tool.run(question)
-                except Exception as e:
-                    print(f"Wikipedia tool failed: {e}")
-            if "duckduckgo" in question.lower() or "web search" in question.lower():
+            try:
+                wiki_context = self.wiki_tool.run(question)
+                print(f"Wiki context: {wiki_context[:200]}...")  # Debug
+            except Exception as e:
+                print(f"Wikipedia tool failed: {e}")
+            
+            # Use DuckDuckGo as fallback if Wikipedia context is poor or for web search requests
+            def is_poor_context(context):
+                return not context or any(x in context.lower() for x in ["not found", "no results", "does not contain", "disambiguation"])
+            
+            if "duckduckgo" in question.lower() or "web search" in question.lower() or is_poor_context(wiki_context):
                 try:
                     ddg_context = self.ddg_tool.run(question)
+                    print(f"DDG context: {ddg_context[:200]}...")  # Debug
                 except Exception as e:
                     print(f"DuckDuckGo tool failed: {e}")
         # Handle attached file questions with enhanced prompts
@@ -225,9 +241,12 @@ Provide only the direct answer. If it's a quote, give just the quoted text. If i
         
         # Prepend context to the prompt if available and likely relevant
         def is_good_context(context):
-            return context and not any(x in context.lower() for x in ["not found", "no results", "does not contain information"])
+            return context and not any(x in context.lower() for x in ["not found", "no results", "does not contain", "disambiguation"])
         if wiki_context and is_good_context(wiki_context):
-            prompt = f"Use the following Wikipedia context to answer the question:\n{wiki_context}\n\n{prompt}"
+            if "first name" in question.lower() or "give only the first name" in question.lower():
+                prompt = f"Based on this Wikipedia information, answer the question and give only the first name as the answer.\n{wiki_context}\n\n{question}\n\nAnswer:"
+            else:
+                prompt = f"Use the following Wikipedia context to answer the question:\n{wiki_context}\n\n{prompt}"
         elif ddg_context and is_good_context(ddg_context):
             prompt = f"Use the following web search context to answer the question:\n{ddg_context}\n\n{prompt}"
         
@@ -260,11 +279,13 @@ Provide only the direct answer. If it's a quote, give just the quoted text. If i
             answer = sentences[0] + '.'
         
         # If the question expects a single value, extract it
-        if any(kw in question.lower() for kw in ["how many", "what is the", "who", "where", "give only", "provide only"]):
-            # Extract the first number, word, or phrase (tweak regex as needed)
-            match = re.search(r'^[A-Za-z0-9 ,+-]+', answer)
-            if match:
-                answer = match.group(0).strip()
+        if any(kw in question.lower() for kw in ["how many", "what is the", "who", "where", "give only", "provide only", "first name"]):
+            # Special handling for "give only the first name"
+            if "give only the first name" in question.lower() or "first name" in question.lower():
+                # Extract first name from full name (robust: first capitalized word, allow Polish chars)
+                name_match = re.search(r'\b([A-ZĄĆĘŁŃÓŚŹŻ][a-ząćęłńóśźż]+)', answer)
+                if name_match:
+                    answer = name_match.group(1)
         
         # Post-processing for chess move extraction
         if 'chess position' in question.lower() and 'image' in question.lower():