Update chain_app.py

chain_app.py

@@ -104,9 +104,13 @@ async def chat_profile():
             name="Llama-3-8B",
             markdown_description="Meta Open Source model Llama-2 with 7B parameters",
         ),
+        cl.ChatProfile(
+            name = "gemma2-9B",
+            markdown_description = 'Google Generation 2 Open Source LLM with 9B parameters'
+        ),
         cl.ChatProfile(
             name = "gemma-7B",
-            markdown_description = 'Google Open Source LLM'
+            markdown_description = 'Google Generation 1 Open Source LLM with 7B parameters'
         ),
         cl.ChatProfile(
             name="zephyr-7B",
@@ -187,7 +191,7 @@ async def on_chat_start():
                 Select(
                     id="OpenAI-Model",
                     label="OpenAI - Model",
-                    values=["gpt-4"],
+                    values=["gpt4-o-mini"],
                     initial_index=0,
                 ),
                 Slider(
@@ -334,7 +338,7 @@ async def on_chat_start():
                 Select(
                     id="Meta-Model",
                     label="Meta - Model",
-                    values=["Llama-3-70B"],
+                    values=["Llama-3.1-405B"],
                     initial_index=0,
                 ),
                 Slider(
@@ -357,7 +361,7 @@ async def on_chat_start():
                 Select(
                     id="Meta-Model",
                     label="Meta - Model",
-                    values=["Llama-3-70B"],
+                    values=["Llama-3.1-70B"],
                     initial_index=0,
                 ),
                 Slider(
@@ -379,7 +383,7 @@ async def on_chat_start():
                 Select(
                     id="Meta-Model",
                     label="Meta - Model",
-                    values=["Llama-3-70B"],
+                    values=["Llama-3.1-8B"],
                     initial_index=0,
                 ),
                 Slider(
@@ -440,6 +444,29 @@ async def on_chat_start():
         await cl.Message(
             content="Im The small Llama!. one of the best open source models released by Meta! i am the small version of meta's open source LLMs. i was configured by Artin Daneshvar and Sadra Noadoust, 2 iranian students to help you, how can i assist you today ? "
         ).send()
+    if chat_profile == 'gemma-9B':
+        await cl.ChatSettings(
+            [
+                Select(
+                    id="Google-Model",
+                    label="Google - Model",
+                    values=["Gemma-9B"],
+                    initial_index=0,
+                ),
+                Slider(
+                    id="Temperature",
+                    label="Model Temperature",
+                    initial=0.7,
+                    min=0,
+                    max=1,
+                    step=0.1,
+                ),
+            ]
+        ).send()
+        await cl.Message(
+            content="Im Gemma2. the 9B version of google second generation open source LLMs. i was configured by Artin Daneshvar and Sadra Noadoust, 2 iranian students to help you, how can i assist you today ? "
+        ).send()
+        
     if chat_profile == 'gemma-7B':
         await cl.ChatSettings(
             [
@@ -807,6 +834,36 @@ async def main(message: cl.Message):
         # Send the concatenated content as a message
         await cl.Message(content=complete_content).send()
 
+    elif chat_profile == 'gemma-9B':
+        completion = groq_client.chat.completions.create(
+            model="gemma-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",
@@ -836,7 +893,7 @@ async def main(message: cl.Message):
 
         # 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,