fix(backend): replace decommissioned gemma2-9b-it with llama-3.3-70b-versatile

backend/app/modules/bias_detection/check_bias.py

@@ -61,7 +61,7 @@ def check_bias(text):
                     "content": (f"Give bias score to the following article \n\n{text}"),
                 },
             ],
-            model="gemma2-9b-it",
+            model="llama-3.3-70b-versatile",
             temperature=0.3,
             max_tokens=512,
         )

backend/app/modules/chat/llm_processing.py

@@ -55,7 +55,7 @@ def ask_llm(question, docs):
 """
 
     response = client.chat.completions.create(
-        model="gemma2-9b-it",
+        model="llama-3.3-70b-versatile",
         messages=[
             {"role": "system", "content": "Use only the context to answer."},
             {"role": "user", "content": prompt},

backend/app/modules/facts_check/llm_processing.py

@@ -63,7 +63,7 @@ def run_claim_extractor_sdk(state):
                     ),
                 },
             ],
-            model="gemma2-9b-it",
+            model="llama-3.3-70b-versatile",
             temperature=0.3,
             max_tokens=512,
         )
@@ -128,7 +128,7 @@ def run_fact_verifier_sdk(search_results):
                         ),
                     },
                 ],
-                model="gemma2-9b-it",
+                model="llama-3.3-70b-versatile",
                 temperature=0.3,
                 max_tokens=256,
             )
@@ -144,7 +144,13 @@ def run_fact_verifier_sdk(search_results):
                 parsed = json.loads(content)
             except Exception as parse_err:
                 logger.error(f"LLM JSON parse error: {parse_err}")
-
+             parsed = {
+                    "verdict": "Unknown",
+                    "explanation": f"Parse error: {parse_err}",
+                    "original_claim": claim,
+                    "source_link": source,
+                }
+
             results_list.append(parsed)
 
         return {

backend/app/modules/langgraph_nodes/judge.py

@@ -24,7 +24,7 @@
 
 # Init once
 groq_llm = ChatGroq(
-    model="gemma2-9b-it",
+    model="llama-3.3-70b-versatile",
     temperature=0.0,
     max_tokens=10,
 )

backend/app/modules/langgraph_nodes/sentiment.py

@@ -49,7 +49,7 @@ def run_sentiment_sdk(state):
                     ),
                 },
             ],
-            model="gemma2-9b-it",
+            model="llama-3.3-70b-versatile",
             temperature=0.2,
             max_tokens=3,
         )