Update app.py

app.py

@@ -162,16 +162,16 @@ def chat_query_IS(question, chat_history_IS):
     """
     Handles queries about Indian/International Standards using OpenAI model.
     """
-    #llm = ChatOpenAI(model = llm_name, temperature = 0.1, api_key = OPENAI_API_KEY)
+    llm = ChatOpenAI(model = llm_name, temperature = 0.1, api_key = OPENAI_API_KEY)
     #llm = ChatGoogleGenerativeAI(model="gemini-pro", google_api_key=GEMINI_API_KEY)                                   ###
     #llm = OllamaLLM(model="unsloth/Llama-3.2-3B")
 
-    llm = HuggingFacePipeline.from_model_id(
-        model_id=llm_name,  # Replace with a valid Hugging Face model ID
-        task="text-generation",  # Specify the appropriate task for your model
-        device=0,  # Use -1 for CPU or 0 for GPU
-        model_kwargs={"temperature": 0.1}
-    )
+    # llm = HuggingFacePipeline.from_model_id(
+    #     model_id=llm_name,  # Replace with a valid Hugging Face model ID
+    #     task="text-generation",  # Specify the appropriate task for your model
+    #     device=0,  # Use -1 for CPU or 0 for GPU
+    #     model_kwargs={"temperature": 0.1}
+    # )
     
     system_prompt = f"""
         Provide an elaborate, detailed and point-wise reply about the topic as per relevant IS/IEEE/BIS standards:
@@ -181,10 +181,10 @@ def chat_query_IS(question, chat_history_IS):
 
     system = f""" Provide a reply poetically precise as william shakespeare for the Topic : {question}"""
 
-    result = llm(system_prompt)
-    chat_history_IS.append((system_prompt, result))
+    result = llm.invoke(system_prompt)
+    chat_history_IS.append((system_prompt, result.content))
     
-    return result    
+    return result.content
 
 
 iface_doc = gr.ChatInterface(