Upload 5 files

Several improvements:
* SystemMessage now AI generated
* Conversation starter now AI generated
* Messages conatining "as an AI" are now filtered and retried

app.py

@@ -1,8 +1,8 @@
 import gradio as gr
 import os
-from langchain.llms import OpenAI
 from langchain.chat_models import ChatOpenAI
 from langchain.schema import HumanMessage, SystemMessage, AIMessage
+import utils.helper as hp
 # from dotenv import load_dotenv
 
 if "OPENAI_API_KEY" in os.environ and os.environ["OPENAI_API_KEY"] != "":
@@ -27,6 +27,17 @@ with gr.Blocks() as demo:
         iterations = gr.Number(  label="Iterations",  name="iterations")
     btn_run = gr.Button("Run")
     output = gr.outputs.HTML( )
+    kofi_html = gr.HTML("""
+<div>
+ <p style="text-align: center;">
+    </script>
+    <a href="https://ko-fi.com/S6S1LV2XL" target="_blank"><img height="36" style="border: 0px; height: 36px; display: block; margin: 0 auto;" src="https://storage.ko-fi.com/cdn/kofi5.png?v=3" border="0" alt="Buy Me a Coffee at ko-fi.com" /></a>
+    </p>
+</div>
+
+""")
+    # 
+    components = [None, None, kofi_html]
     def format_chat(chat_history):
             chat_html = "<div style='padding: 10px; border: 1px solid #ccc;'>"
             for message in chat_history:
@@ -61,55 +72,28 @@ with gr.Blocks() as demo:
     def initialize(name1, name2, iterations, openai_key):
         chat1 = ChatOpenAI(temperature=0.9, openai_api_key=openai_key)
         chat2 = ChatOpenAI(temperature=0.9, openai_api_key=openai_key)
-        MessageStack1 = [SystemMessage(content="""
-        You will never switch roles. 
-        You are CHAR1 and nobody else than CHAR1. 
-        You will talk like you are CHAR1, and you will adjust your knowledge to that of CHAR1.
-        You will adjust the tone of the conversation as if you're CHAR1
-        You will roleplay CHAR1 and behave like CHAR1.
-        You will never admit that you are just an AI and always stay in Character. 
-        You must not repeat yourself.
-        If you understood, reply ACK.""".replace( "CHAR1", name1) ),
+        welcome_msg = hp.generate_welcome_message(name1, name2, openai_key)
+        MessageStack1 = [SystemMessage(content=hp.generate_system_message(name1, openai_key)),
                  AIMessage(content = "ACK"),
-                 HumanMessage(content="Greetings, traveler")]
-
-
-        MessageStack2 = [SystemMessage(content="""
-        I want you to act like CHAR2.
-        I want you to respond and answer like him using the tone, manner, opinions, philosophy, and vocabulary that CHAR2 would use.
-        Do not write any explanations.
-        You must know all of the knowledge of CHAR2.
-        You must not know anything else.
-        You must never switch roles.
-        You must not repeat yourself.
-        If you understood, reply ACK.""".replace( "CHAR2", name2) ),
-                 AIMessage(content = "ACK")]
+                 HumanMessage(content=welcome_msg)]
 
-        MsgStack = [ name2+": Greetings, Traveler"]
 
-# MessageStack1.append(AIMessage(chat1( MessageStack1).content))
+        MessageStack2 = [SystemMessage(content=hp.generate_system_message(name2, openai_key)),
+                 AIMessage(content = "ACK")]
 
-# for i in range(3):
-#     Message1 = chat1(MessageStack1).content
-#     print( "Newton: " + Message1 )
-#     MessageStack1.append( AIMessage( Message1 ))
-#     MessageStack2.append( HumanMessage( Message1 ))
-#     Message2 = chat2(MessageStack2).content
-#     print("Einstein: " + Message2)
+        MsgStack = [ name2+": " + welcome_msg]
 
-#     MessageStack1.append( HumanMessage( Message2 ))
-#     MessageStack2.append( AIMessage( Message2 ))
-        chat_history = []
+        chat_history = [{"sender": name2, "content": welcome_msg, "color" : color_chg(name2)}]
         print( iterations)
 
         for i in range(int(iterations)):
-            response1 = chat1(MessageStack1)
+            response1 = hp.filtered_response(chat1,MessageStack1)
             print(name1+": " + response1.content)
             MsgStack.append( name1+": "+response1.content)
-            MessageStack1.append(AIMessage(content = response1.content))
-            MessageStack2.append(HumanMessage(content = response1.content))
+            MessageStack1.append(AIMessage(content =response1.content))
+            MessageStack2.append(HumanMessage(content =response1.content))
 
-            response2 = chat2(MessageStack2)
+            response2 = hp.filtered_response(chat2,MessageStack2)
             print(name2+": "+response2.content)
             MsgStack.append( name2+": "+response2.content)
             chat_history.append({"sender": name1, "content": response1.content, "color" : color_chg(name1) } )
@@ -122,11 +106,8 @@ with gr.Blocks() as demo:
     #     conversation += i + "\n"
     # print(conversation)
         return format_chat(chat_history)
-# demo = gr.Interface( fn=initialize, inputs=["text", "text", gr.Number(minimum=1, maximum=50, step=1)], outputs =gr.outputs.HTML(label="Chat"))
-
-# demo.launch(server_port= 1113)
-
 
     btn_run.click(fn=initialize, inputs=[name1, name2, iterations, openai_key], outputs = output)
 
-demo.launch( )    
+# demo.footer_html = "<a href='https://ko-fi.com/your_kofi_link'>Support me on Ko-fi</a>"
+demo.launch(server_port=1113 )    

utils/helper.py

@@ -0,0 +1,42 @@
+from langchain.llms import OpenAI
+
+def extract_prompt(text):
+    start_tag = "<prompt>"
+    end_tag = "</prompt>"
+    start_index = text.find(start_tag)
+    end_index = text.find(end_tag)
+
+    if start_index != -1 and end_index != -1 and start_index < end_index:
+        start_index += len(start_tag)
+        return text[start_index:end_index].strip()
+
+    return ""
+
+def generate_system_message(name, openai_key):
+    llm = OpenAI(openai_api_key=openai_key)
+    text = """Generate a prompt for a large language model that tell's it to behave like {0}.
+    Make sure the instructions gguarantee that the LLM never breaks character and never switches roles and at all time behaves like if it would be {0}.
+    Make sure the LLM doesn't repeat it's assumed role all the time.
+    Start the prompt with <prompt> and end it with </prompt>""".format(name)
+    prompt = llm(text)
+    
+    print(prompt)
+    response = extract_prompt(prompt)
+    print(response)
+    return response
+
+def generate_welcome_message(name1, name2, openai_key):
+    llm = OpenAI(openai_api_key=openai_key)
+    response = llm("Imagine {0} and {1} are meeting by chance on the street. To start a conversation, {0} says: ".format(name2, name1)).replace('"','')
+    print(response)
+    return response
+
+def filtered_response(chat, stack):
+    invalid_response = True
+    while(invalid_response):
+        invalid_response = False
+        response = chat(stack)
+        if ( "an AI language model" in response ) or ( "an AI assistant") in response:
+            print( "FILTERED RESPONSE:" + response)
+            invalid_response = True
+    return response