Salary Negotiation

app.py

@@ -1,64 +1,186 @@
 import gradio as gr
 from huggingface_hub import InferenceClient
+import re
+import traceback
 
-"""
-For more information on `huggingface_hub` Inference API support, please check the docs: https://huggingface.co/docs/huggingface_hub/v0.22.2/en/guides/inference
-"""
+# Initialize the Inference Client with your model
 client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
 
+# Regular expression to validate YouTube URLs (modify if needed)
+YOUTUBE_URL_PATTERN = re.compile(
+    r'(https?://)?(www\.)?(youtube\.com|youtu\.?be)/.+'
+)
 
 def respond(
     message,
-    history: list[tuple[str, str]],
-    system_message,
+    history,
     max_tokens,
     temperature,
     top_p,
+    current_salary
 ):
+    """
+    Respond function to handle the conversation and negotiate salary.
+    """
+    # Define the system message internally (hidden from the user)
+    system_message = (
+        "You are a hiring manager negotiating a job offer. "
+        "Your goal is to offer a fair salary based on the candidate's negotiation skills. "
+        "Start the negotiation with an initial offer of $60,000."
+    )
+    
+    # Initialize the messages with the system prompt
     messages = [{"role": "system", "content": system_message}]
-
-    for val in history:
-        if val[0]:
-            messages.append({"role": "user", "content": val[0]})
-        if val[1]:
-            messages.append({"role": "assistant", "content": val[1]})
-
+    
+    # Append the conversation history to messages
+    for user_msg, ai_msg in history:
+        if user_msg:
+            messages.append({"role": "user", "content": user_msg})
+        if ai_msg:
+            messages.append({"role": "assistant", "content": ai_msg})
+    
+    # Append the latest user message
     messages.append({"role": "user", "content": message})
-
+    
     response = ""
+    success = False  # Flag to determine if negotiation was successful
+    
+    try:
+        # Generate the AI response
+        for msg in client.chat_completion(
+            messages,
+            max_tokens=max_tokens,
+            stream=True,
+            temperature=temperature,
+            top_p=top_p,
+        ):
+            token = msg.choices[0].delta.content
+            response += token
+            yield response
+    
+        # Simple logic to determine negotiation success based on AI's response
+        success_keywords = ["agreed", "accepted", "increase", "raised", "enhanced", "approved", "offer"]
+    
+        # Check if any success keywords are in the AI's response (case-insensitive)
+        if any(keyword.lower() in response.lower() for keyword in success_keywords):
+            # Increment the salary by a fixed amount
+            increment = 5000  # Fixed increment; modify as desired
+            current_salary += increment
+            success = True
+            yield f"\n\n🎉 Negotiation successful! Your salary has been increased to ${current_salary:,}."
+    
+    except Exception as e:
+        response = f"An error occurred while communicating with the AI: {e}"
+        yield response
+        traceback.print_exc()
+    
+    # Update the salary display if negotiation was successful
+    if success:
+        yield gr.update(value=current_salary)
 
-    for message in client.chat_completion(
-        messages,
-        max_tokens=max_tokens,
-        stream=True,
-        temperature=temperature,
-        top_p=top_p,
-    ):
-        token = message.choices[0].delta.content
+def reset_game():
+    """
+    Function to reset the game to initial state.
+    """
+    return [], 60000  # Reset history and salary to 60k
 
-        response += token
-        yield response
+# Define the Gradio Blocks layout
+with gr.Blocks() as demo:
+    gr.Markdown("# 💼 Salary Negotiation Game")
+    gr.Markdown(
+        """
+        **Objective:** Negotiate with the employer to increase your salary from \$60,000.
+        
+        **Instructions:**
+        - Use the chat interface to negotiate.
+        - If you negotiate successfully, your salary will increase.
+        - Aim to reach the highest salary possible through effective negotiation.
+        """
+    )
 
+    with gr.Row():
+        with gr.Column(scale=1):
+            # Display the current salary
+            salary_display = gr.Number(
+                value=60000,
+                label="Current Salary (\$)",
+                interactive=False,
+                precision=0
+            )
+            # Reset button to restart the game
+            reset_btn = gr.Button("Reset Game")
+            reset_btn.click(fn=reset_game, inputs=None, outputs=[gr.State(), salary_display])
 
-"""
-For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
-"""
-demo = gr.ChatInterface(
-    respond,
-    additional_inputs=[
-        gr.Textbox(value="You are a friendly Chatbot.", label="System message"),
-        gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
-        gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
-        gr.Slider(
-            minimum=0.1,
-            maximum=1.0,
-            value=0.95,
-            step=0.05,
-            label="Top-p (nucleus sampling)",
-        ),
-    ],
-)
+        with gr.Column(scale=3):
+            # Chat history to keep track of the conversation
+            chat_history = gr.State([])
+
+            # Chat Interface
+            chatbot = gr.Chatbot()
+    
+            # User input
+            user_input = gr.Textbox(
+                label="Your Message",
+                placeholder="Enter your negotiation message here...",
+                lines=2
+            )
+            send_button = gr.Button("Send")
+
+            def handle_message(message, history, max_tokens, temperature, top_p, current_salary):
+                """
+                Handles user messages and updates the conversation history and salary.
+                """
+                generator = respond(message, history, max_tokens, temperature, top_p, current_salary)
+                try:
+                    # Get the initial AI response
+                    response = next(generator)
+                    # Update history
+                    history.append((message, response))
+                    # Process the rest of the generator
+                    try:
+                        while True:
+                            additional_response = next(generator)
+                            response += additional_response
+                            # Check for negotiation success message
+                            if "Negotiation successful" in additional_response:
+                                current_salary = int(re.search(r'\$(\d{1,3}(?:,\d{3})*)', additional_response).group(1).replace(',', ''))
+                            yield (history, current_salary)
+                    except StopIteration:
+                        pass
+                except StopIteration:
+                    pass
+                except Exception as e:
+                    history.append((message, f"An error occurred: {e}"))
+                    yield (history, current_salary)
+    
+            send_button.click(
+                handle_message,
+                inputs=[
+                    user_input,
+                    chat_history,
+                    gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max New Tokens"),
+                    gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
+                    gr.Slider(
+                        minimum=0.1,
+                        maximum=1.0,
+                        value=0.95,
+                        step=0.05,
+                        label="Top-p (nucleus sampling)",
+                    ),
+                    salary_display
+                ],
+                outputs=[
+                    chatbot,
+                    salary_display
+                ]
+            )
 
+    gr.Markdown(
+        """
+        ---
+        *Developed with ❤️ using Gradio and Hugging Face.*
+        """
+    )
 
 if __name__ == "__main__":
     demo.launch()