Update app.py

app.py

@@ -4,6 +4,16 @@ from llama_index.llms.base import ChatMessage
 from llama_index.llms import Perplexity
 from openai import OpenAI
 
+
+MODEL_CHOICES_LLM1 = [
+    "pplx-7b-online", "pplx-70b-online", "codellama-34b-instruct", "llama-2-70b-chat", "mistral-7b-instruct",
+    "mixtral-8x7b-instruct", "pplx-7b-chat", "pplx-70b-chat"  # Add actual model names here
+]
+
+MODEL_CHOICES_LLM2 = [
+    "gpt-4", "gpt-4-1106-preview", "gpt-3.5-turbo", "gpt-3.5-turbo-1106", " gpt-3.5-turbo-0613", "dall-e-3"   # Add actual model names here
+]
+
 # Initialize default variables and models for both LLMs
 DEFAULT_LLM1_MODEL = "pplx-70b-online"
 DEFAULT_LLM2_MODEL = "gpt-4"
@@ -87,12 +97,14 @@ def chat_with_llms(message):
 def chat_with_llms(message):
     if not message.strip():
         return "No input provided. Please enter a message."
+
     # First LLM Chain
     messages_1 = []
     if SYSTEM_MESSAGE_1:  # Add system message only if it's not empty
         messages_1.append(ChatMessage(role="system", content=SYSTEM_MESSAGE_1))
     messages_1.append(ChatMessage(role="user", content=(PREP_PROMPT_1 if PREP_PROMPT_1 else "") + message + (AFTER_PROMPT_1 if AFTER_PROMPT_1 else "")))
     response_1 = llm1.chat(messages_1).message.content
+
     # Second LLM Chain
     messages_2 = []
     if SYSTEM_MESSAGE_2:  # Add system message only if it's not empty
@@ -100,22 +112,27 @@ def chat_with_llms(message):
     messages_2.append({"role": "user", "content": (PREP_PROMPT_2 if PREP_PROMPT_2 else "") + response_1})
     completion = client.chat.completions.create(model="gpt-4", temperature=OpenAItemp, messages=messages_2)
     response_2 = completion.choices[0].message.content
+
     return response_2  # Return only the response from LLM 2
+
 ##SHOW FULL INPUTS and OUTPUTS FOR LLM1 AND 2 and exclude any empty values from inputs##
 def chat_with_llms(message):
     if not message.strip():
         return "No input provided. Please enter a message."
+
     # First LLM Chain
     messages_1 = []
     if SYSTEM_MESSAGE_1:  # Add system message only if it's not empty
         messages_1.append(ChatMessage(role="system", content=SYSTEM_MESSAGE_1))
     messages_1.append(ChatMessage(role="user", content=(PREP_PROMPT_1 if PREP_PROMPT_1 else "") + message + (AFTER_PROMPT_1 if AFTER_PROMPT_1 else "")))
     response_1 = llm1.chat(messages_1).message.content
+
     # Full message chain for LLM 1
     full_message_chain_llm1 = 'LLM 1 Conversation:\n'
     for msg in messages_1:
         full_message_chain_llm1 += f"{msg.role.title()}: {msg.content}\n"
     full_message_chain_llm1 += f"Assistant: {response_1}\n\n"
+
     # Second LLM Chain
     messages_2 = []
     if SYSTEM_MESSAGE_2:  # Add system message only if it's not empty
@@ -123,25 +140,31 @@ def chat_with_llms(message):
     messages_2.append({"role": "user", "content": (PREP_PROMPT_2 if PREP_PROMPT_2 else "") + response_1})
     completion = client.chat.completions.create(model="gpt-4", temperature=OpenAItemp, messages=messages_2)
     response_2 = completion.choices[0].message.content
+
     # Full message chain for LLM 2
     full_message_chain_llm2 = 'LLM 2 Conversation:\n'
     for msg in messages_2:
         full_message_chain_llm2 += f"{msg['role'].title()}: {msg['content']}\n"
     full_message_chain_llm2 += f"Assistant: {response_2}\n"
+
     return full_message_chain_llm1 + full_message_chain_llm2
+
 ### SHOW FULL LLMS INPUTS ##
 def chat_with_llms(message):
     # Check if the input message is empty or only contains whitespace
     if not message.strip():
         return "No input provided. Please enter a message."
+
     # First LLM Chain
     messages_1 = [ChatMessage(role="system", content=SYSTEM_MESSAGE_1), ChatMessage(role="user", content=PREP_PROMPT_1 + message + AFTER_PROMPT_1)]
     response_1 = llm1.chat(messages_1).message.content
+
     # Build the full message chain for LLM 1
     full_message_chain_llm1 = 'LLM 1 Conversation:\n'
     for msg in messages_1:
         full_message_chain_llm1 += f"{msg.role.title()}: {msg.content}\n"
     full_message_chain_llm1 += f"Assistant: {response_1}\n\n"
+
     # Second LLM Chain
     messages_2 = [
         {"role": "system", "content": SYSTEM_MESSAGE_2},
@@ -149,18 +172,25 @@ def chat_with_llms(message):
     ]
     completion = client.chat.completions.create(model="gpt-4", temperature=OpenAItemp, messages=messages_2)
     response_2 = completion.choices[0].message.content
+
     # Build the full message chain for LLM 2
     full_message_chain_llm2 = 'LLM 2 Conversation:\n'
     for msg in messages_2:
         full_message_chain_llm2 += f"{msg['role'].title()}: {msg['content']}\n"
     full_message_chain_llm2 += f"Assistant: {response_2}\n"
+
     # Return the full conversation histories of both LLMs
     return full_message_chain_llm1 + full_message_chain_llm2
+
 '''
+
 # Gradio interface for updating LLM 1 variables and model
 llm1_interface = gr.Interface(
     fn=update_variables_and_model_llm1,
-    inputs=["text", "text", "text", "text"],  # Added model name input
+    inputs=[
+        gr.Dropdown(choices=MODEL_CHOICES_LLM1, label="LLM 1 - PPX - Models", value=DEFAULT_LLM1_MODEL),  # Dropdown for LLM1
+        "text", "text", "text"
+    ],
     outputs="text",
     title="Update Variables and Model for LLM 1"
 )
@@ -170,10 +200,15 @@ reset_llm1_interface = gr.Interface(
     outputs="text",
     title="Reset Variables for LLM 1"
 )
+
+
 # Gradio interface for updating LLM 2 variables and model
 llm2_interface = gr.Interface(
     fn=update_variables_and_model_llm2,
-    inputs=["text", "text", "text"],  # Added model name input
+    inputs=[
+        gr.Dropdown(choices=MODEL_CHOICES_LLM2, label="LLM 2 - OpenAI - Models", value=DEFAULT_LLM2_MODEL),  # Dropdown for LLM2
+        "text", "text"
+    ],
     outputs="text",
     title="Update Variables and Model for LLM 2"
 )
@@ -184,8 +219,6 @@ reset_llm2_interface = gr.Interface(
     title="Reset Variables for LLM 2"
 )
 
-# Interfaces for resetting variables remain the same
-
 # Update Gradio chat interface
 chat_interface = gr.Interface(
     fn=chat_with_llms, 
@@ -197,5 +230,5 @@ chat_interface = gr.Interface(
 # Tabbed interface
 gr.TabbedInterface(
     [chat_interface, llm1_interface, reset_llm1_interface, llm2_interface, reset_llm2_interface],
-    ["Chat", "Update LLM 1", "Reset LLM 1", "Update LLM 2", "Reset LLM 2"]
-).launch()
+    ["Chat", "LLM 1 - PPX", "Reset LLM 1", "LLM 2 - OpenAI", "Reset LLM 2"]
+).launch()