Update app.py

app.py

@@ -8,14 +8,21 @@ import re
 import os
 
 openai.api_key = os.getenv("OPENAI_API_KEY")
- 
+
+if not openai.api_key:
+    try:
+        openai.api_key = OPENAI_API_KEY
+    except NameError:
+        print("API key is not set in the environment or as a variable.")
+
 class PDFChat:
     def __init__(self):
         self.pdf_text = ""
         self.chat_history = []
-        self.system_prompt = """You are a knowledgeable assistant specializing in microcontrollers from Renesas, TI, and STM. 
+        self.system_prompt = """You are a knowledgeable assistant specializing in microcontrollers from various manufacturers including but not limited to Renesas, Texas Instruments (TI), and STMicroelectronics (STM).
         When comparing microcontrollers, always provide structured data in a JSON format that can be converted to a table.
-        Focus on key specifications like CPU frequency, memory, peripherals, ADC Resolution , Flash Memory ,temperature range, and special features."""
+        Focus on key specifications like CPU frequency, memory, peripherals, ADC Resolution, Flash Memory, temperature range, and special features.
+        Consider all manufacturers' products when making recommendations based on application requirements."""
     
     def extract_text_from_pdf(self, pdf_file):
         if not pdf_file:
@@ -41,12 +48,10 @@ class PDFChat:
 
     def extract_json_from_text(self, text):
         """Extract JSON data from the response text"""
-        # Find JSON pattern between ```json and ```
         json_match = re.search(r'```json\s*(.*?)\s*```', text, re.DOTALL)
         if json_match:
             json_str = json_match.group(1)
         else:
-            # Try to find JSON pattern between { and }
             json_match = re.search(r'({[\s\S]*})', text)
             if json_match:
                 json_str = json_match.group(1)
@@ -63,15 +68,15 @@ class PDFChat:
             return "", None
 
         structured_prompt = """
-        If the question is asking for a comparison or suggestion of microcontrollers, 
+        Based on the application requirements, recommend suitable microcontrollers and 
         provide your response in the following JSON format wrapped in ```json ```:
         {
             "explanation": "Your textual explanation here",
             "comparison_table": [
                 {
                     "Feature": "feature name",
-                    "Controller1_Name": "value",
-                    "Controller2_Name": "value",
+                    "Option1": "value",
+                    "Option2": "value",
                     ...
                 },
                 ...
@@ -100,7 +105,6 @@ class PDFChat:
             )
             response_text = response.choices[0].message['content']
             
-            
             json_data = self.extract_json_from_text(response_text)
             
             if json_data and "comparison_table" in json_data:
@@ -119,7 +123,7 @@ class PDFChat:
 pdf_chat = PDFChat()
 
 with gr.Blocks() as demo:
-    gr.Markdown("# Renasus Chatbot")
+    gr.Markdown("# Renesas Chatbot")
     
     with gr.Row():
         with gr.Column(scale=1):
@@ -139,9 +143,10 @@ with gr.Blocks() as demo:
         with gr.Column(scale=2):
             gr.Markdown("### Microcontroller Selection Interface")
             question_input = gr.Textbox(
-                label="Ask about microcontroller selection",
-                placeholder="Describe your requirements or ask for comparisons...",
-                lines=3
+                label="Briefly describe your target application for controller recommendation",
+                placeholder="Example: Industrial motor control system with precise temperature monitoring...",
+                lines=3,
+                value=""  # This will keep the input persistent
             )
             explanation_text = gr.Textbox(
                 label="Explanation",
@@ -158,19 +163,21 @@ with gr.Blocks() as demo:
                 clear_history_button = gr.Button("Clear Chat History")
             
             with gr.Group():
-                gr.Markdown("### Example Questions")
+                gr.Markdown("### Example Applications")
                 gr.Examples(
                     examples=[
-                        ["Suggest controller suitable for water level monitoring system comparing RA4M1 and STM32L4"],
-                        ["Recommend controller for centralized vehicle lighting and door control systems comparing RA6M3 and STM32F4"],
-                        ["Suggest best suited controller for a Solar Inverter Design comparing RA6T1 and TMS320F28379D"],
-                        ["Compare RA6M5 and STM32G4 series for building automation applications"],
+                        ["Industrial automation system requiring precise motion control and multiple sensor inputs"],
+                        ["Battery-powered IoT device with wireless connectivity and low power requirements"],
+                        ["High-performance motor control application with real-time processing needs"],
+                        ["Smart building management system with multiple environmental sensors"],
                     ],
                     inputs=[question_input],
-                    label="Example Questions"
+                    label="Example Applications"
                 )
     
-   
+    def handle_question(question):
+        explanation, df = pdf_chat.answer_question(question)
+        return explanation, df, question  
     load_button.click(
         pdf_chat.extract_text_from_pdf,
         inputs=[pdf_input],
@@ -187,10 +194,6 @@ with gr.Blocks() as demo:
         outputs=[explanation_text, table_output]
     )
     
-    def handle_question(question):
-        explanation, df = pdf_chat.answer_question(question)
-        return explanation, df, ""
-    
     question_input.submit(
         handle_question,
         inputs=[question_input],