removed gemini llm

pipeline.py

@@ -164,14 +164,14 @@ RATE_LIMIT_REQUESTS = 60
 CACHE_SIZE_LIMIT = 1000
 
 # Google Gemini (primary)
-GOOGLE_API_KEY = os.environ.get("GOOGLE_API_KEY")
-gemini_llm = ChatGoogleGenerativeAI(
-    model="gemini-2.0-flash",
-    temperature=0.5,
-    max_tokens=None,
-    timeout=None,
-    max_retries=2,
-)
+# GOOGLE_API_KEY = os.environ.get("GOOGLE_API_KEY")
+# gemini_llm = ChatGoogleGenerativeAI(
+#     model="gemini-2.0-flash",
+#     temperature=0.5,
+#     max_tokens=None,
+#     timeout=None,
+#     max_retries=2,
+# )
 
 # Fallback
 fallback_groq_api_key = os.environ.get("GROQ_API_KEY_FALLBACK", "GROQ_API_KEY")
@@ -450,15 +450,21 @@ class PipelineState:
 
         # Specialized chain for self-harm
         from prompts import selfharm_prompt
-        self.self_harm_chain = LLMChain(llm=gemini_llm, prompt=selfharm_prompt, verbose=False)
+        # self.self_harm_chain = LLMChain(llm=gemini_llm, prompt=selfharm_prompt, verbose=False)
+        
+        self.self_harm_chain = LLMChain(llm=groq_fallback_llm, prompt=selfharm_prompt, verbose=False)
+        
         
         # NEW: chain for frustration/harsh queries
         from prompts import frustration_prompt
-        self.frustration_chain = LLMChain(llm=gemini_llm, prompt=frustration_prompt, verbose=False)
+        # self.frustration_chain = LLMChain(llm=gemini_llm, prompt=frustration_prompt, verbose=False)
+        self.frustration_chain = LLMChain(llm=groq_fallback_llm, prompt=frustration_prompt, verbose=False)
+        
         
         # NEW: chain for ethical conflict queries
         from prompts import ethical_conflict_prompt
-        self.ethical_conflict_chain = LLMChain(llm=gemini_llm, prompt=ethical_conflict_prompt, verbose=False)
+        # self.ethical_conflict_chain = LLMChain(llm=gemini_llm, prompt=ethical_conflict_prompt, verbose=False)
+        self.ethical_conflict_chain = LLMChain(llm=groq_fallback_llm, prompt=ethical_conflict_prompt, verbose=False)
 
         # Build brand & wellness vectorstores
         brand_csv    = "BrandAI.csv"
@@ -473,8 +479,8 @@ class PipelineState:
         self.gemini_llm = gemini_llm
         self.groq_fallback_llm = groq_fallback_llm
 
-        self.brand_rag_chain    = build_rag_chain2(brand_vs,    self.gemini_llm)
-        self.wellness_rag_chain = build_rag_chain(wellness_vs, self.gemini_llm)
+        # self.brand_rag_chain    = build_rag_chain2(brand_vs,    self.gemini_llm)
+        # self.wellness_rag_chain = build_rag_chain(wellness_vs, self.gemini_llm)
 
         self.brand_rag_chain_fallback    = build_rag_chain2(brand_vs,    self.groq_fallback_llm)
         self.wellness_rag_chain_fallback = build_rag_chain(wellness_vs, self.groq_fallback_llm)