Update chain_app.py

chain_app.py

@@ -1907,634 +1907,646 @@ async def on_chat_start():
 @cl.on_message  
 async def main(message: cl.Message):
     chat_profile = cl.user_session.get("chat_profile")
-    if chat_profile == 'neural-brain-AI':
-        completion = openai_client.chat.completions.create(
-            model="ft:gpt-3.5-turbo-1106:nb:aria1:9UWDrLJK",
-            messages=[
-                {"role": "system", "content": "You are neural nexus official chatbot, you are made by Artin Daneshvar and Sadra Noadoust"},
-                {"role": "user", "content": message.content}
-            ]
-        )
-        model_response = completion.choices[0].message.content
+    res = await cl.AskActionMessage(
+        content="Pick an action!",
+        actions=[
+            cl.Action(name="continue", value="continue", label="✅ Continue"),
+            cl.Action(name="cancel", value="cancel", label="❌ Cancel"),
+        ],
+    ).send()
+
+    if res and res.get("value") == "continue":
         await cl.Message(
-            content=model_response
+            content="Continue!",
         ).send()
-
-    elif chat_profile == "Dorna-AI":
-        result = hf_text_client.predict(
-            message=message.content,
-            request="your name is Dorna,An AI Assistant designed by neural nexus team. i was made by Artin Daneshvar and Sadra Noadoust, 2 iranian students!",
-            param_3=512,
-            param_4=0.7,
-            param_5=0.95,
-            api_name="/chat"
-        )
-        model_response = result.strip("</s>") 
-        await cl.Message(
-            content=model_response
-        ).send()
-    elif chat_profile == "gpt4-o-mini":
-        completion = openai_client.chat.completions.create(
-            model="gpt-4o-mini",
-            messages=[
-                {"role": "system", "content": "You are neural nexus official chatbot, you are made by Artin Daneshvar and Sadra Noadoust"},
-                {"role": "user", "content": message.content}
-            ]
-        )
-        model_response = completion.choices[0].message.content
-        await cl.Message(
-            content=model_response
-        ).send()
-  #   elif chat_profile == 'Image-Generation':
-  #       result = hf_image_client.predict(
-		# prompt=message.content,
-		# negative_prompt="",
-		# seed=0,
-		# randomize_seed=True,
-		# width=512,
-		# height=512,
-		# guidance_scale=0,
-		# num_inference_steps=2,
-		# api_name="/infer"
-  #       )
-  #       image = cl.Image(path=result, name="result", display="inline")
-  #       await cl.Message(
-  #           content="This message has an image!",
-  #           elements=[image],
-  #       ).send()
-    elif chat_profile == 'GPT-4':
-        completion = openai_client.chat.completions.create(
-            model="gpt-4",
-            messages=[
-                {"role": "system", "content": "You are neural nexus official chatbot, you are made by Artin Daneshvar and Sadra Noadoust"},
-                {"role": "user", "content": message.content}
-            ]
-        )
-        model_response = completion.choices[0].message.content
-        await cl.Message(
-            content=model_response
-        ).send()
-
-    elif chat_profile == 'gpt-3.5-turbo':
-        completion = openai_client.chat.completions.create(
-            model="gpt-3.5-turbo",
-            messages=[
-                {"role": "system", "content": "You are neural nexus official chatbot, you are made by Artin Daneshvar and Sadra Noadoust"},
-                {"role": "user", "content": message.content}
-            ]
-        )
-        model_response = completion.choices[0].message.content
-        await cl.Message(
-            content=model_response
-        ).send()
-    elif chat_profile == 'GPT-3.5-turbo-0125':
-        completion = openai_client.chat.completions.create(
-            model="GPT-3.5-turbo-0125",
-            messages=[
-                {"role": "system", "content": "You are neural nexus official chatbot, you are made by Artin Daneshvar and Sadra Noadoust"},
-                {"role": "user", "content": message.content}
-            ]
-        )
-        model_response = completion.choices[0].message.content
-        await cl.Message(
-            content=model_response
-        ).send()
-    elif chat_profile == 'gpt-3.5-turbo-1106':
-        completion = openai_client.chat.completions.create(
-            model="gpt-3.5-turbo-1106",
-            messages=[
-                {"role": "system", "content": "You are neural nexus official chatbot, you are made by Artin Daneshvar and Sadra Noadoust"},
-                {"role": "user", "content": message.content}
+        if chat_profile == 'neural-brain-AI':
+            completion = openai_client.chat.completions.create(
+                model="ft:gpt-3.5-turbo-1106:nb:aria1:9UWDrLJK",
+                messages=[
+                    {"role": "system", "content": "You are neural nexus official chatbot, you are made by Artin Daneshvar and Sadra Noadoust"},
+                    {"role": "user", "content": message.content}
+                ]
+            )
+            model_response = completion.choices[0].message.content
+            await cl.Message(
+                content=model_response
+            ).send()
+    
+        elif chat_profile == "Dorna-AI":
+            result = hf_text_client.predict(
+                message=message.content,
+                request="your name is Dorna,An AI Assistant designed by neural nexus team. i was made by Artin Daneshvar and Sadra Noadoust, 2 iranian students!",
+                param_3=512,
+                param_4=0.7,
+                param_5=0.95,
+                api_name="/chat"
+            )
+            model_response = result.strip("</s>") 
+            await cl.Message(
+                content=model_response
+            ).send()
+        elif chat_profile == "gpt4-o-mini":
+            completion = openai_client.chat.completions.create(
+                model="gpt-4o-mini",
+                messages=[
+                    {"role": "system", "content": "You are neural nexus official chatbot, you are made by Artin Daneshvar and Sadra Noadoust"},
+                    {"role": "user", "content": message.content}
+                ]
+            )
+            model_response = completion.choices[0].message.content
+            await cl.Message(
+                content=model_response
+            ).send()
+      #   elif chat_profile == 'Image-Generation':
+      #       result = hf_image_client.predict(
+    		# prompt=message.content,
+    		# negative_prompt="",
+    		# seed=0,
+    		# randomize_seed=True,
+    		# width=512,
+    		# height=512,
+    		# guidance_scale=0,
+    		# num_inference_steps=2,
+    		# api_name="/infer"
+      #       )
+      #       image = cl.Image(path=result, name="result", display="inline")
+      #       await cl.Message(
+      #           content="This message has an image!",
+      #           elements=[image],
+      #       ).send()
+        elif chat_profile == 'GPT-4':
+            completion = openai_client.chat.completions.create(
+                model="gpt-4",
+                messages=[
+                    {"role": "system", "content": "You are neural nexus official chatbot, you are made by Artin Daneshvar and Sadra Noadoust"},
+                    {"role": "user", "content": message.content}
+                ]
+            )
+            model_response = completion.choices[0].message.content
+            await cl.Message(
+                content=model_response
+            ).send()
+    
+        elif chat_profile == 'gpt-3.5-turbo':
+            completion = openai_client.chat.completions.create(
+                model="gpt-3.5-turbo",
+                messages=[
+                    {"role": "system", "content": "You are neural nexus official chatbot, you are made by Artin Daneshvar and Sadra Noadoust"},
+                    {"role": "user", "content": message.content}
+                ]
+            )
+            model_response = completion.choices[0].message.content
+            await cl.Message(
+                content=model_response
+            ).send()
+        elif chat_profile == 'GPT-3.5-turbo-0125':
+            completion = openai_client.chat.completions.create(
+                model="GPT-3.5-turbo-0125",
+                messages=[
+                    {"role": "system", "content": "You are neural nexus official chatbot, you are made by Artin Daneshvar and Sadra Noadoust"},
+                    {"role": "user", "content": message.content}
+                ]
+            )
+            model_response = completion.choices[0].message.content
+            await cl.Message(
+                content=model_response
+            ).send()
+        elif chat_profile == 'gpt-3.5-turbo-1106':
+            completion = openai_client.chat.completions.create(
+                model="gpt-3.5-turbo-1106",
+                messages=[
+                    {"role": "system", "content": "You are neural nexus official chatbot, you are made by Artin Daneshvar and Sadra Noadoust"},
+                    {"role": "user", "content": message.content}
+                ]
+            )
+            model_response = completion.choices[0].message.content
+            await cl.Message(
+                content=model_response
+            ).send()
+        # elif chat_profile == 'davinci-002':
+        #     completion = openai_client.chat.completions.create(
+        #         model="davinci-002",
+        #         messages=[
+        #             {"role": "system", "content": "You are neural nexus official chatbot, you are made by Artin Daneshvar and Sadra Noadoust"},
+        #             {"role": "user", "content": message.content}
+        #         ]
+        #     )
+        #     model_response = completion.choices[0].message.content
+        #     await cl.Message(
+        #         content=model_response
+        #     ).send()
+    
+        elif chat_profile == 'TTS':
+            response = openai_client.audio.speech.create(
+                model="tts-1",
+                voice="alloy",
+                input=message.content,
+            )
+    
+            response.stream_to_file("output.mp3")
+    
+            elements = [
+                cl.Audio(name="output.mp3", path="./output.mp3", display="inline"),
             ]
-        )
-        model_response = completion.choices[0].message.content
-        await cl.Message(
-            content=model_response
-        ).send()
-    # elif chat_profile == 'davinci-002':
-    #     completion = openai_client.chat.completions.create(
-    #         model="davinci-002",
-    #         messages=[
-    #             {"role": "system", "content": "You are neural nexus official chatbot, you are made by Artin Daneshvar and Sadra Noadoust"},
-    #             {"role": "user", "content": message.content}
-    #         ]
-    #     )
-    #     model_response = completion.choices[0].message.content
-    #     await cl.Message(
-    #         content=model_response
-    #     ).send()
-
-    elif chat_profile == 'TTS':
-        response = openai_client.audio.speech.create(
-            model="tts-1",
-            voice="alloy",
-            input=message.content,
-        )
-
-        response.stream_to_file("output.mp3")
-
-        elements = [
-            cl.Audio(name="output.mp3", path="./output.mp3", display="inline"),
-        ]
-        await cl.Message(
-            content="Here it is the response!",
-            elements=elements,
-        ).send()
-
-    elif chat_profile == 'Qwen2-57B':
-        client = Client("Qwen/Qwen2-57b-a14b-instruct-demo", hf_token=hf_token)
-        result = client.predict(
-    		query=message.content,
-    		system="You are a helpful AI chatbot made by two iranian boys named Artin Daneshvar and Sadra Noadoust",
-    		api_name="/model_chat"
-        )
-        await cl.Message(
-            content=result[1][0][1]
-        ).send()
+            await cl.Message(
+                content="Here it is the response!",
+                elements=elements,
+            ).send()
+    
+        elif chat_profile == 'Qwen2-57B':
+            client = Client("Qwen/Qwen2-57b-a14b-instruct-demo", hf_token=hf_token)
+            result = client.predict(
+        		query=message.content,
+        		system="You are a helpful AI chatbot made by two iranian boys named Artin Daneshvar and Sadra Noadoust",
+        		api_name="/model_chat"
+            )
+            await cl.Message(
+                content=result[1][0][1]
+            ).send()
+            
+        elif chat_profile == 'Qwen2-7B':
+            client = Client("Qwen/Qwen2-7b-instruct-demo", hf_token=hf_token)
+            result = client.predict(
+        		query=message.content,
+        		system="You are a helpful AI chatbot made by two iranian boys named Artin Daneshvar and Sadra Noadoust",
+        		api_name="/model_chat"
+            )
+            await cl.Message(
+                content=result[1][0][1]
+    
+            ).send()
+    
+        elif chat_profile == 'Qwen2-1.5B':
+            client = Client("Qwen/Qwen2-1.5b-instruct-demo", hf_token=hf_token)
+            result = client.predict(
+        		query=message.content,
+        		system="You are a helpful AI chatbot made by two iranian boys named Artin Daneshvar and Sadra Noadoust",
+        		api_name="/model_chat"
+            )
+            await cl.Message(
+                content=result[1][0][1]
+    
+            ).send()
+    
+        elif chat_profile == 'Qwen2-0.5B':
+            client = Client("Qwen/Qwen2-0.5B-Instruct", hf_token=hf_token)
+            result = client.predict(
+        		query=message.content,
+        		system="You are a helpful AI chatbot made by two iranian boys named Artin Daneshvar and Sadra Noadoust",
+        		api_name="/model_chat"
+            )
+            await cl.Message(
+                content=result[1][0][1]
+    
+            ).send()
+        elif chat_profile == 'Qwen1.5-110B':
+            client = Client("Qwen/Qwen1.5-110B-Chat-demo", hf_token=hf_token)
+            result = client.predict(
+        		query=message.content,
+        		system="You are a helpful AI chatbot made by two iranian boys named Artin Daneshvar and Sadra Noadoust",
+        		api_name="/model_chat"
+            )
+            await cl.Message(
+                content=result[1][0][1]
+    
+            ).send()
+    
+        elif chat_profile == 'Qwen1.5-32B':
+            client = Client("Qwen/Qwen1.5-32B-Chat-demo", hf_token=hf_token)
+            result = client.predict(
+        		query=message.content,
+        		system="You are a helpful AI chatbot made by two iranian boys named Artin Daneshvar and Sadra Noadoust",
+        		api_name="/model_chat"
+            )
+            await cl.Message(
+                content=result[1][0][1]
+    
+            ).send()
+    
+        elif chat_profile == 'Qwen1.5-2.7B':
+            client = Client("Qwen/qwen1.5-MoE-A2.7B-Chat-demo", hf_token=hf_token)
+            result = client.predict(
+        		query=message.content,
+        		system="You are a helpful AI chatbot made by two iranian boys named Artin Daneshvar and Sadra Noadoust",
+        		api_name="/model_chat"
+            )
+            await cl.Message(
+                content=result[1][0][1]
+    
+            ).send()
+    
+        # elif chat_profile == 'Qwen-14B':
+        #     client = Client("Qwen/qwen1.5-MoE-A2.7B-Chat-demo", hf_token=hf_token)
+        #     result = client.predict(
+        # 		query=message.content,
+        # 		system="You are a helpful AI chatbot made by two iranian boys named Artin Daneshvar and Sadra Noadoust",
+        # 		api_name="/model_chat"
+        #     )
+        #     await cl.Message(
+        #         content=result[1][0][1]
+    
+        #     ).send()
+    
+        # elif chat_profile == 'Qwen-7B':
+        #     client = Client("Qwen/qwen1.5-MoE-A2.7B-Chat-demo", hf_token=hf_token)
+        #     result = client.predict(
+        # 		query=message.content,
+        # 		system="You are a helpful AI chatbot made by two iranian boys named Artin Daneshvar and Sadra Noadoust",
+        # 		api_name="/model_chat"
+        #     )
+        #     await cl.Message(
+        #         content=result[1][0][1]
+    
+        #     ).send()
+            
+        elif chat_profile == 'Llama-3.1-405B':        
+            completion = groq_client.chat.completions.create(
+                model="llama-3.1-405b-reasoning",
+                messages=[
+                    {
+                        "role": "user",
+                        "content": message.content
+                    }
+                ],
+                temperature=1,
+                max_tokens=1024,
+                top_p=1,
+                stream=True,
+                stop=None,
+            )
         
-    elif chat_profile == 'Qwen2-7B':
-        client = Client("Qwen/Qwen2-7b-instruct-demo", hf_token=hf_token)
-        result = client.predict(
-    		query=message.content,
-    		system="You are a helpful AI chatbot made by two iranian boys named Artin Daneshvar and Sadra Noadoust",
-    		api_name="/model_chat"
-        )
-        await cl.Message(
-            content=result[1][0][1]
-
-        ).send()
-
-    elif chat_profile == 'Qwen2-1.5B':
-        client = Client("Qwen/Qwen2-1.5b-instruct-demo", hf_token=hf_token)
-        result = client.predict(
-    		query=message.content,
-    		system="You are a helpful AI chatbot made by two iranian boys named Artin Daneshvar and Sadra Noadoust",
-    		api_name="/model_chat"
-        )
-        await cl.Message(
-            content=result[1][0][1]
-
-        ).send()
-
-    elif chat_profile == 'Qwen2-0.5B':
-        client = Client("Qwen/Qwen2-0.5B-Instruct", hf_token=hf_token)
-        result = client.predict(
-    		query=message.content,
-    		system="You are a helpful AI chatbot made by two iranian boys named Artin Daneshvar and Sadra Noadoust",
-    		api_name="/model_chat"
-        )
-        await cl.Message(
-            content=result[1][0][1]
-
-        ).send()
-    elif chat_profile == 'Qwen1.5-110B':
-        client = Client("Qwen/Qwen1.5-110B-Chat-demo", hf_token=hf_token)
-        result = client.predict(
-    		query=message.content,
-    		system="You are a helpful AI chatbot made by two iranian boys named Artin Daneshvar and Sadra Noadoust",
-    		api_name="/model_chat"
-        )
-        await cl.Message(
-            content=result[1][0][1]
-
-        ).send()
-
-    elif chat_profile == 'Qwen1.5-32B':
-        client = Client("Qwen/Qwen1.5-32B-Chat-demo", hf_token=hf_token)
-        result = client.predict(
-    		query=message.content,
-    		system="You are a helpful AI chatbot made by two iranian boys named Artin Daneshvar and Sadra Noadoust",
-    		api_name="/model_chat"
-        )
-        await cl.Message(
-            content=result[1][0][1]
-
-        ).send()
-
-    elif chat_profile == 'Qwen1.5-2.7B':
-        client = Client("Qwen/qwen1.5-MoE-A2.7B-Chat-demo", hf_token=hf_token)
-        result = client.predict(
-    		query=message.content,
-    		system="You are a helpful AI chatbot made by two iranian boys named Artin Daneshvar and Sadra Noadoust",
-    		api_name="/model_chat"
-        )
-        await cl.Message(
-            content=result[1][0][1]
-
-        ).send()
-
-    # elif chat_profile == 'Qwen-14B':
-    #     client = Client("Qwen/qwen1.5-MoE-A2.7B-Chat-demo", hf_token=hf_token)
-    #     result = client.predict(
-    # 		query=message.content,
-    # 		system="You are a helpful AI chatbot made by two iranian boys named Artin Daneshvar and Sadra Noadoust",
-    # 		api_name="/model_chat"
-    #     )
-    #     await cl.Message(
-    #         content=result[1][0][1]
-
-    #     ).send()
-
-    # elif chat_profile == 'Qwen-7B':
-    #     client = Client("Qwen/qwen1.5-MoE-A2.7B-Chat-demo", hf_token=hf_token)
-    #     result = client.predict(
-    # 		query=message.content,
-    # 		system="You are a helpful AI chatbot made by two iranian boys named Artin Daneshvar and Sadra Noadoust",
-    # 		api_name="/model_chat"
-    #     )
-    #     await cl.Message(
-    #         content=result[1][0][1]
-
-    #     ).send()
+            complete_content = ""
+        
+            # Iterate over each chunk
+            for chunk in completion:
+                # Retrieve the content from the current chunk
+                content = chunk.choices[0].delta.content
+                
+                # Check if the content is not None before concatenating it
+                if content is not None:
+                    complete_content += content
         
-    elif chat_profile == 'Llama-3.1-405B':        
-        completion = groq_client.chat.completions.create(
-            model="llama-3.1-405b-reasoning",
-            messages=[
-                {
-                    "role": "user",
-                    "content": message.content
-                }
-            ],
-            temperature=1,
-            max_tokens=1024,
-            top_p=1,
-            stream=True,
-            stop=None,
-        )
+            # Send the concatenated content as a message
+            await cl.Message(content=complete_content).send()
     
-        complete_content = ""
+        
+        elif chat_profile == 'Llama-3.1-70B':
+            completion = groq_client.chat.completions.create(
+                model="llama-3.1-70b-versatile",
+                messages=[
+                    {
+                        "role": "user",
+                        "content": message.content
+                    }
+                ],
+                temperature=1,
+                max_tokens=1024,
+                top_p=1,
+                stream=True,
+                stop=None,
+            )
+        
+            complete_content = ""
+        
+            # Iterate over each chunk
+            for chunk in completion:
+                # Retrieve the content from the current chunk
+                content = chunk.choices[0].delta.content
+                
+                # Check if the content is not None before concatenating it
+                if content is not None:
+                    complete_content += content
+        
+            # Send the concatenated content as a message
+            await cl.Message(content=complete_content).send()
     
-        # Iterate over each chunk
-        for chunk in completion:
-            # Retrieve the content from the current chunk
-            content = chunk.choices[0].delta.content
-            
-            # Check if the content is not None before concatenating it
-            if content is not None:
-                complete_content += content
+        elif chat_profile == 'Llama-3.1-8B':
+            completion = groq_client.chat.completions.create(
+                model="llama-3.1-8b-instant",
+                messages=[
+                    {
+                        "role": "user",
+                        "content": message.content
+                    }
+                ],
+                temperature=1,
+                max_tokens=1024,
+                top_p=1,
+                stream=True,
+                stop=None,
+            )
+        
+            complete_content = ""
+        
+            # Iterate over each chunk
+            for chunk in completion:
+                # Retrieve the content from the current chunk
+                content = chunk.choices[0].delta.content
+                
+                # Check if the content is not None before concatenating it
+                if content is not None:
+                    complete_content += content
+        
+            # Send the concatenated content as a message
+            await cl.Message(content=complete_content).send()
     
-        # Send the concatenated content as a message
-        await cl.Message(content=complete_content).send()
-
+        elif chat_profile == 'Llama-3-70B':
+            completion = groq_client.chat.completions.create(
+                model="llama3-70b-8192",
+                messages=[
+                    {
+                        "role": "user",
+                        "content": message.content
+                    }
+                ],
+                temperature=1,
+                max_tokens=1024,
+                top_p=1,
+                stream=True,
+                stop=None,
+            )
     
-    elif chat_profile == 'Llama-3.1-70B':
-        completion = groq_client.chat.completions.create(
-            model="llama-3.1-70b-versatile",
-            messages=[
-                {
-                    "role": "user",
-                    "content": message.content
-                }
-            ],
-            temperature=1,
-            max_tokens=1024,
-            top_p=1,
-            stream=True,
-            stop=None,
-        )
+            complete_content = ""
     
-        complete_content = ""
+            # Iterate over each chunk
+            for chunk in completion:
+                # Retrieve the content from the current chunk
+                content = chunk.choices[0].delta.content
+                
+                # Check if the content is not None before concatenating it
+                if content is not None:
+                    complete_content += content
     
-        # Iterate over each chunk
-        for chunk in completion:
-            # Retrieve the content from the current chunk
-            content = chunk.choices[0].delta.content
-            
-            # Check if the content is not None before concatenating it
-            if content is not None:
-                complete_content += content
+            # Send the concatenated content as a message
+            await cl.Message(content=complete_content).send()
     
-        # Send the concatenated content as a message
-        await cl.Message(content=complete_content).send()
-
-    elif chat_profile == 'Llama-3.1-8B':
-        completion = groq_client.chat.completions.create(
-            model="llama-3.1-8b-instant",
-            messages=[
-                {
-                    "role": "user",
-                    "content": message.content
-                }
-            ],
-            temperature=1,
-            max_tokens=1024,
-            top_p=1,
-            stream=True,
-            stop=None,
-        )
+        elif chat_profile == 'Llama-3-8B':
+            completion = groq_client.chat.completions.create(
+                model="llama3-8b-8192",
+                messages=[
+                    {
+                        "role": "user",
+                        "content": message.content
+                    }
+                ],
+                temperature=1,
+                max_tokens=1024,
+                top_p=1,
+                stream=True,
+                stop=None,
+            )
     
-        complete_content = ""
+            complete_content = ""
     
-        # Iterate over each chunk
-        for chunk in completion:
-            # Retrieve the content from the current chunk
-            content = chunk.choices[0].delta.content
-            
-            # Check if the content is not None before concatenating it
-            if content is not None:
-                complete_content += content
+            # Iterate over each chunk
+            for chunk in completion:
+                # Retrieve the content from the current chunk
+                content = chunk.choices[0].delta.content
+                
+                # Check if the content is not None before concatenating it
+                if content is not None:
+                    complete_content += content
     
-        # Send the concatenated content as a message
-        await cl.Message(content=complete_content).send()
-
-    elif chat_profile == 'Llama-3-70B':
-        completion = groq_client.chat.completions.create(
-            model="llama3-70b-8192",
-            messages=[
-                {
-                    "role": "user",
-                    "content": message.content
-                }
-            ],
-            temperature=1,
-            max_tokens=1024,
-            top_p=1,
-            stream=True,
-            stop=None,
-        )
-
-        complete_content = ""
-
-        # Iterate over each chunk
-        for chunk in completion:
-            # Retrieve the content from the current chunk
-            content = chunk.choices[0].delta.content
-            
-            # Check if the content is not None before concatenating it
-            if content is not None:
-                complete_content += content
-
-        # Send the concatenated content as a message
-        await cl.Message(content=complete_content).send()
-
-    elif chat_profile == 'Llama-3-8B':
-        completion = groq_client.chat.completions.create(
-            model="llama3-8b-8192",
-            messages=[
-                {
-                    "role": "user",
-                    "content": message.content
-                }
-            ],
-            temperature=1,
-            max_tokens=1024,
-            top_p=1,
-            stream=True,
-            stop=None,
-        )
-
-        complete_content = ""
-
-        # Iterate over each chunk
-        for chunk in completion:
-            # Retrieve the content from the current chunk
-            content = chunk.choices[0].delta.content
-            
-            # Check if the content is not None before concatenating it
-            if content is not None:
-                complete_content += content
-
-        # Send the concatenated content as a message
-        await cl.Message(content=complete_content).send()
-
-    elif chat_profile == 'gemma2-9B':
-        completion = groq_client.chat.completions.create(
-            model="gemma2-9b-it",
-            messages=[
-                {
-                    "role": "user",
-                    "content": message.content
-                }
-            ],
-            temperature=1,
-            max_tokens=1024,
-            top_p=1,
-            stream=True,
-            stop=None,
-        )
-
-        complete_content = ""
-
-        # Iterate over each chunk
-        for chunk in completion:
-            # Retrieve the content from the current chunk
-            content = chunk.choices[0].delta.content
-            
-            # Check if the content is not None before concatenating it
-            if content is not None:
-                complete_content += content
-
-        # Send the concatenated content as a message
-        await cl.Message(content=complete_content).send()
-
-    elif chat_profile == 'gemma-7B':
-        completion = groq_client.chat.completions.create(
-            model="gemma-7b-it",
-            messages=[
-                {
-                    "role": "user",
-                    "content": message.content
-                }
-            ],
-            temperature=1,
-            max_tokens=1024,
-            top_p=1,
-            stream=True,
-            stop=None,
-        )
-
-        complete_content = ""
-
-        # Iterate over each chunk
-        for chunk in completion:
-            # Retrieve the content from the current chunk
-            content = chunk.choices[0].delta.content
-            
-            # Check if the content is not None before concatenating it
-            if content is not None:
-                complete_content += content
-
-        # Send the concatenated content as a message
-        await cl.Message(content=complete_content).send()
+            # Send the concatenated content as a message
+            await cl.Message(content=complete_content).send()
+    
+        elif chat_profile == 'gemma2-9B':
+            completion = groq_client.chat.completions.create(
+                model="gemma2-9b-it",
+                messages=[
+                    {
+                        "role": "user",
+                        "content": message.content
+                    }
+                ],
+                temperature=1,
+                max_tokens=1024,
+                top_p=1,
+                stream=True,
+                stop=None,
+            )
+    
+            complete_content = ""
+    
+            # Iterate over each chunk
+            for chunk in completion:
+                # Retrieve the content from the current chunk
+                content = chunk.choices[0].delta.content
+                
+                # Check if the content is not None before concatenating it
+                if content is not None:
+                    complete_content += content
+    
+            # Send the concatenated content as a message
+            await cl.Message(content=complete_content).send()
     
-    elif chat_profile == "zephyr-7B":
-        result = hf_text_client.predict(
+        elif chat_profile == 'gemma-7B':
+            completion = groq_client.chat.completions.create(
+                model="gemma-7b-it",
+                messages=[
+                    {
+                        "role": "user",
+                        "content": message.content
+                    }
+                ],
+                temperature=1,
+                max_tokens=1024,
+                top_p=1,
+                stream=True,
+                stop=None,
+            )
+    
+            complete_content = ""
+    
+            # Iterate over each chunk
+            for chunk in completion:
+                # Retrieve the content from the current chunk
+                content = chunk.choices[0].delta.content
+                
+                # Check if the content is not None before concatenating it
+                if content is not None:
+                    complete_content += content
+    
+            # Send the concatenated content as a message
+            await cl.Message(content=complete_content).send()
+        
+        elif chat_profile == "zephyr-7B":
+            result = hf_text_client.predict(
+                message=message.content,
+                request="your name is zephyr,An AI Assistant designed by neural nexus team. i was made by Artin Daneshvar and Sadra Noadoust, 2 iranian students!",
+                param_3=512,
+                param_4=0.7,
+                param_5=0.95,
+                api_name="/chat"
+            )
+            model_response = result.strip("</s>") 
+            await cl.Message(
+                content=model_response
+            ).send()
+    
+        elif chat_profile == 'mixtral-8x7B':
+            completion = groq_client.chat.completions.create(
+                model="mixtral-8x7b-32768",
+                messages=[
+                    {
+                        "role": "user",
+                        "content": message.content
+                    }
+                ],
+                temperature=1,
+                max_tokens=1024,
+                top_p=1,
+                stream=True,
+                stop=None,
+            )
+    
+            complete_content = ""
+    
+            for chunk in completion:
+                content = chunk.choices[0].delta.content
+                
+                if content is not None:
+                    complete_content += content
+    
+            await cl.Message(content=complete_content).send() 
+    
+        elif chat_profile == 'mistral-nemo-12B':
+            client = Client("0x7o/Mistral-Nemo-Instruct", hf_token=hf_token)
+            result = client.predict(
+            		message=message.content,
+            		max_new_tokens=512,
+            		temperature=0.7,
+            		top_p=0.95,
+            		api_name="/chat"
+            )
+            await cl.Message(
+                content=result[1][0][1]
+    
+            ).send()
+    
+        # elif chat_profile == 'Toka-353M':
+        #     output = query({
+        #     "inputs": message.content,
+        # })
+        #     await cl.Message(
+        #         content=output[0]['sequence']
+        #     ).send()
+    
+        elif chat_profile == 'Aya-23B':
+            stream = co.chat_stream( 
+            model='c4ai-aya-23',
             message=message.content,
-            request="your name is zephyr,An AI Assistant designed by neural nexus team. i was made by Artin Daneshvar and Sadra Noadoust, 2 iranian students!",
-            param_3=512,
-            param_4=0.7,
-            param_5=0.95,
-            api_name="/chat"
-        )
-        model_response = result.strip("</s>") 
-        await cl.Message(
-            content=model_response
-        ).send()
-
-    elif chat_profile == 'mixtral-8x7B':
-        completion = groq_client.chat.completions.create(
-            model="mixtral-8x7b-32768",
-            messages=[
-                {
-                    "role": "user",
-                    "content": message.content
-                }
-            ],
-            temperature=1,
-            max_tokens=1024,
-            top_p=1,
-            stream=True,
-            stop=None,
-        )
-
-        complete_content = ""
-
-        for chunk in completion:
-            content = chunk.choices[0].delta.content
+            temperature=0.3,
+            # chat_history=[{"role": "User", "message": "Hello"}, {"role": "Chatbot", "message": "Hello! How can I help you today?"}, {"role": "User", "message": "Hi"}, {"role": "User", "message": "hello"}],
+            prompt_truncation='OFF',
+            connectors=[],
+            ) 
+    
+            complete_content = ''
+            for event in stream:
+                if event.event_type == 'text-generation':
+                    complete_content += event.text
+            await cl.Message(content=complete_content).send()
+    
+        elif chat_profile == 'Aya-35B':
+            stream = co.chat_stream( 
+            model='c4ai-aya-23',
+            message=message.content,
+            temperature=0.3,
+            # chat_history=[{"role": "User", "message": "Hello"}, {"role": "Chatbot", "message": "Hello! How can I help you today?"}, {"role": "User", "message": "Hi"}, {"role": "User", "message": "hello"}],
+            prompt_truncation='OFF',
+            connectors=[],
+            ) 
+    
+            complete_content = ''
+            for event in stream:
+                if event.event_type == 'text-generation':
+                    complete_content += event.text
+            await cl.Message(content=complete_content).send()
+    
+        elif chat_profile == 'Command-R-Plus':
+            stream = co.chat_stream( 
+              model='command-r-plus',
+              message=message.content,
+              temperature=0.3,
+              chat_history=[],
+              prompt_truncation='AUTO',
+            ) 
+            complete_content = ''
+            for event in stream:
+                if event.event_type == 'text-generation':
+                    complete_content += event.text
+            await cl.Message(content=complete_content).send()
+    
+        elif chat_profile == 'Command-R':
+            stream = co.chat_stream( 
+              model='command-r',
+              message=message.content,
+              temperature=0.3,
+              chat_history=[],
+              prompt_truncation='AUTO',
+            ) 
+            complete_content = ''
+            for event in stream:
+                if event.event_type == 'text-generation':
+                    complete_content += event.text
+            await cl.Message(content=complete_content).send()
+    
+        elif chat_profile == 'Command':
+            stream = co.chat_stream( 
+              model='command',
+              message=message.content,
+              temperature=0.3,
+              chat_history=[],
+              prompt_truncation='AUTO',
+            ) 
+            complete_content = ''
+            for event in stream:
+                if event.event_type == 'text-generation':
+                    complete_content += event.text
+            await cl.Message(content=complete_content).send()
             
-            if content is not None:
-                complete_content += content
-
-        await cl.Message(content=complete_content).send() 
-
-    elif chat_profile == 'mistral-nemo-12B':
-        client = Client("0x7o/Mistral-Nemo-Instruct", hf_token=hf_token)
-        result = client.predict(
-        		message=message.content,
-        		max_new_tokens=512,
-        		temperature=0.7,
-        		top_p=0.95,
-        		api_name="/chat"
-        )
-        await cl.Message(
-            content=result[1][0][1]
-
-        ).send()
-
-    # elif chat_profile == 'Toka-353M':
-    #     output = query({
-    #     "inputs": message.content,
-    # })
-    #     await cl.Message(
-    #         content=output[0]['sequence']
-    #     ).send()
-
-    elif chat_profile == 'Aya-23B':
-        stream = co.chat_stream( 
-        model='c4ai-aya-23',
-        message=message.content,
-        temperature=0.3,
-        # chat_history=[{"role": "User", "message": "Hello"}, {"role": "Chatbot", "message": "Hello! How can I help you today?"}, {"role": "User", "message": "Hi"}, {"role": "User", "message": "hello"}],
-        prompt_truncation='OFF',
-        connectors=[],
-        ) 
-
-        complete_content = ''
-        for event in stream:
-            if event.event_type == 'text-generation':
-                complete_content += event.text
-        await cl.Message(content=complete_content).send()
-
-    elif chat_profile == 'Aya-35B':
-        stream = co.chat_stream( 
-        model='c4ai-aya-23',
-        message=message.content,
-        temperature=0.3,
-        # chat_history=[{"role": "User", "message": "Hello"}, {"role": "Chatbot", "message": "Hello! How can I help you today?"}, {"role": "User", "message": "Hi"}, {"role": "User", "message": "hello"}],
-        prompt_truncation='OFF',
-        connectors=[],
-        ) 
-
-        complete_content = ''
-        for event in stream:
-            if event.event_type == 'text-generation':
-                complete_content += event.text
-        await cl.Message(content=complete_content).send()
-
-    elif chat_profile == 'Command-R-Plus':
-        stream = co.chat_stream( 
-          model='command-r-plus',
-          message=message.content,
-          temperature=0.3,
-          chat_history=[],
-          prompt_truncation='AUTO',
-        ) 
-        complete_content = ''
-        for event in stream:
-            if event.event_type == 'text-generation':
-                complete_content += event.text
-        await cl.Message(content=complete_content).send()
-
-    elif chat_profile == 'Command-R':
-        stream = co.chat_stream( 
-          model='command-r',
-          message=message.content,
-          temperature=0.3,
-          chat_history=[],
-          prompt_truncation='AUTO',
-        ) 
-        complete_content = ''
-        for event in stream:
-            if event.event_type == 'text-generation':
-                complete_content += event.text
-        await cl.Message(content=complete_content).send()
-
-    elif chat_profile == 'Command':
-        stream = co.chat_stream( 
-          model='command',
-          message=message.content,
-          temperature=0.3,
-          chat_history=[],
-          prompt_truncation='AUTO',
-        ) 
-        complete_content = ''
-        for event in stream:
-            if event.event_type == 'text-generation':
-                complete_content += event.text
-        await cl.Message(content=complete_content).send()
-        
-    elif chat_profile == 'Command-Light':
-        stream = co.chat_stream( 
-          model='command-light',
-          message=message.content,
-          temperature=0.3,
-          chat_history=[],
-          prompt_truncation='AUTO',
-        ) 
-        complete_content = ''
-        for event in stream:
-            if event.event_type == 'text-generation':
-                complete_content += event.text
-        await cl.Message(content=complete_content).send()
-
-    elif chat_profile == 'Command-Light-Nightly':
-        stream = co.chat_stream( 
-          model='command-light-nightly',
-          message=message.content,
-          temperature=0.3,
-          chat_history=[],
-          prompt_truncation='AUTO',
-        ) 
-        complete_content = ''
-        for event in stream:
-            if event.event_type == 'text-generation':
-                complete_content += event.text
-        await cl.Message(content=complete_content).send()
-
-    elif chat_profile == 'Command-Nightly':
-        stream = co.chat_stream( 
-          model='command-light-nightly',
-          message=message.content,
-          temperature=0.3,
-          chat_history=[],
-          prompt_truncation='AUTO',
-        ) 
-        complete_content = ''
-        for event in stream:
-            if event.event_type == 'text-generation':
-                complete_content += event.text
-        await cl.Message(content=complete_content).send()
+        elif chat_profile == 'Command-Light':
+            stream = co.chat_stream( 
+              model='command-light',
+              message=message.content,
+              temperature=0.3,
+              chat_history=[],
+              prompt_truncation='AUTO',
+            ) 
+            complete_content = ''
+            for event in stream:
+                if event.event_type == 'text-generation':
+                    complete_content += event.text
+            await cl.Message(content=complete_content).send()
+    
+        elif chat_profile == 'Command-Light-Nightly':
+            stream = co.chat_stream( 
+              model='command-light-nightly',
+              message=message.content,
+              temperature=0.3,
+              chat_history=[],
+              prompt_truncation='AUTO',
+            ) 
+            complete_content = ''
+            for event in stream:
+                if event.event_type == 'text-generation':
+                    complete_content += event.text
+            await cl.Message(content=complete_content).send()
+    
+        elif chat_profile == 'Command-Nightly':
+            stream = co.chat_stream( 
+              model='command-light-nightly',
+              message=message.content,
+              temperature=0.3,
+              chat_history=[],
+              prompt_truncation='AUTO',
+            ) 
+            complete_content = ''
+            for event in stream:
+                if event.event_type == 'text-generation':
+                    complete_content += event.text
+            await cl.Message(content=complete_content).send()
 
 @cl.on_settings_update
 async def setup_agent(settings):