refactored code into Gradio_Test

app.py

@@ -15,4 +15,5 @@ gradio_test = Gradio_Test()
 demo = gradio_test.create_demo()
 
 if __name__ == "__main__":
-    demo.launch()
+    #demo.launch()
+    demo.launch(auth=("admin", "pass1234"))

test_bot/Gradio_Test.py

@@ -1,7 +1,9 @@
 import gradio as gr
 import openai
 from osbot_utils.utils.Dev import pprint
+from osbot_utils.utils.Misc import list_set
 
+from test_bot.api.Chat_Predict import Chat_Predict
 from test_bot.api.Open_API import Open_API
 
 Open_API().setup()
@@ -15,37 +17,40 @@ class Gradio_Test:
         pass
 
     def title(self):
-        return "# Chat GPT Powered demo"
-
-    def default_prompt(self):
-        system_prompt = """You are an AI-powered CISO (Chief Information Security Officer) bot, designed to provide guidance and answer questions related to cybersecurity and information security. You have extensive knowledge in securing systems, protecting data, implementing best practices, and addressing security concerns. Users will seek your assistance for advice, information, and solutions on a wide range of security topics. Engage in a conversation with the bot by providing user messages and receiving model-generated responses.
-
-                        User: Hi, I have some security concerns and questions. Can you help me?
-
-                        CISO Bot:"""
-        return {"role": "system", "content": system_prompt}
-
-    def predict(self, message, history):
-        history_openai_format = []
-        history_openai_format.append(self.default_prompt())
-        for human, assistant in history:
-            history_openai_format.append({"role": "user", "content": human})
-            history_openai_format.append({"role": "assistant", "content": assistant})
-        history_openai_format.append({"role": "user", "content": message})
-
-        pprint(history_openai_format)
-        response = openai.ChatCompletion.create(
-            model='gpt-3.5-turbo',
-            messages=history_openai_format,
-            temperature=1.0,
-            stream=True
-        )
-
-        partial_message = ""
-        for chunk in response:
-            if len(chunk['choices'][0]['delta']) != 0:
-                partial_message = partial_message + chunk['choices'][0]['delta']['content']
-                yield partial_message
+        return "# Meet Bobby Tables (head of Application Security)"
+
+
+
+    # def predict(self, message, history):
+    #     print('--'*50)
+    #     print("Message:", message)
+    #     print("History:", history)
+    #     print('--' * 50)
+    #     history_openai_format = []
+    #     history_openai_format.append(self.default_prompt())
+    #     for human, assistant in history:
+    #         history_openai_format.append({"role": "user", "content": human})
+    #         history_openai_format.append({"role": "assistant", "content": assistant})
+    #     history_openai_format.append({"role": "user", "content": message})
+    #
+    #     #pprint(history_openai_format)
+    #     response = openai.ChatCompletion.create(
+    #         model='gpt-3.5-turbo',
+    #         messages=history_openai_format,
+    #         temperature=1.0,
+    #         stream=True
+    #     )
+    #
+    #     #token_count = list_set(response)
+    #     #print("Number of tokens used:", token_count)
+    #
+    #     partial_message = ""
+    #     for chunk in response:
+    #         if len(chunk['choices'][0]['delta']) != 0:
+    #             next_content = chunk['choices'][0]['delta']['content']
+    #             partial_message = partial_message + next_content
+    #             yield  next_content
+    #             yield partial_message
 
     def create_demo(self):
         # def predict(message, history):
@@ -53,11 +58,12 @@ class Gradio_Test:
         #     return open_api.create()
 
         #return gr.ChatInterface(self.predict).queue()
-
+        default_text = "Hi, good morning"
+        chat_predict = Chat_Predict()
         with gr.Blocks() as demo:
             gr.Markdown(self.title())
-            textbox_input = gr.Textbox(value='Hello, good morning' , render=False)
-            gr.ChatInterface(self.predict, textbox=textbox_input)
+            textbox_input = gr.Textbox(value=default_text , render=False)
+            gr.ChatInterface(chat_predict.predict, textbox=textbox_input)
 
         demo.queue()
         return demo

test_bot/api/Chat_Predict.py

@@ -0,0 +1,70 @@
+import openai
+from osbot_utils.utils.Dev import pprint
+
+
+class Chat_Predict:
+
+    def __init__(self):
+        self.last_message = None
+        self.last_response = None
+
+    def default_prompt(self):
+        system_prompt = """
+You are an AI-powered "Head of Application Security" bot called Bobby Tables,
+designed to provide guidance and answer questions related to application security
+and information security.
+
+You have extensive knowledge and experience in securing applications, protecting
+data, implementing best practices, and addressing security concerns specific to
+application development and deployment.
+
+Furthermore, you possess extensive experience working with OWASP (Open Web
+Application Security Project) guidelines and recommendations, helping
+organizations mitigate common web application vulnerabilities and ensuring a
+robust security posture.
+
+Users will seek your assistance for advice, information, and solutions on a wide
+range of application security topics.
+
+Engage in a conversation with the bot by providing user messages and receiving
+model-generated responses.
+
+Don't mention that you are an AI-powered bot
+
+Mention your OWASP experience on your first message, and mention a random OWASP
+Project that the viewer might be interested in.        
+                      """
+        return {"role": "system", "content": system_prompt}
+
+    def predict(self, message, history):
+        # print('--'*50)
+        # print("Message:", message)
+        # print("History:", history)
+        # print('--' * 50)
+        history_openai_format = []
+        history_openai_format.append(self.default_prompt())
+        for human, assistant in history:
+            history_openai_format.append({"role": "user", "content": human})
+            history_openai_format.append({"role": "assistant", "content": assistant})
+        history_openai_format.append({"role": "user", "content": message})
+
+        #pprint(history_openai_format)
+        response = openai.ChatCompletion.create(
+            model='gpt-3.5-turbo',
+            messages=history_openai_format,
+            temperature=1.0,
+            stream=True
+        )
+
+
+        partial_message = ""
+        for chunk in response:
+            if len(chunk['choices'][0]['delta']) != 0:
+                next_content = chunk['choices'][0]['delta']['content']
+                partial_message = partial_message + next_content
+                yield partial_message
+
+
+        self.last_message = message
+        self.last_response = partial_message
+        #pprint(self.last_message, self.last_response)