Update app.py

app.py

@@ -1,60 +1,51 @@
 import openai
 import gradio as gr
 import os
-import PyPDF2
+import time
 
 # Load your OpenAI API key from the environment variable
 openai.api_key = os.getenv("OPENAI_API_KEY")
 
-# Function to extract text from an uploaded PDF
-def extract_text_from_pdf(pdf_file):
-    reader = PyPDF2.PdfReader(pdf_file)
-    text = ""
-    for page in reader.pages:
-        text += page.extract_text()
-    return text
-
 # Function to interact with the GPT-4o-mini model via the OpenAI API
-def subsurface_sentinel(user_input, pdf_file=None):
-    context = ""
-    
-    if pdf_file is not None:
-        context = extract_text_from_pdf(pdf_file)
-        # Truncate or summarize context if needed, depending on the length
-        context = context[:2000]  # Truncate to first 2000 characters for example
-    
-    # Combine the context with the user input
-    prompt = f"Context: {context}\n\nUser: {user_input}"
+def subsurface_sentinel(user_input):
+    prompt = f"User: {user_input}"
     
-    response = openai.chat.completions.create(  # Correct method usage
-        model="gpt-4o-mini",  # Use the gpt-4o-mini model
-        messages=[
-            {"role": "system", "content": "You are Subsurface Sentinel, a virtual assistant for professionals in the oil and gas industry, focusing on field development planning."},
-            {"role": "user", "content": prompt}
-        ],
-        max_tokens=150,
-        temperature=0.7,
-    )
+    # Retry mechanism in case of connection errors
+    for _ in range(3):  # Try up to 3 times
+        try:
+            response = openai.chat.completions.create(
+                model="gpt-4o-mini",  # Use the gpt-4o-mini model
+                messages=[
+                    {"role": "system", "content": "You are Subsurface Sentinel, a virtual assistant for professionals in the oil and gas industry, focusing on field development planning."},
+                    {"role": "user", "content": prompt}
+                ],
+                max_tokens=150,
+                temperature=0.7,
+            )
+            # Extract the response text and remove any leading/trailing whitespace
+            return response.choices[0].message.content.strip()
+        except openai.error.APIConnectionError as e:
+            print(f"Connection error: {e}. Retrying...")
+            time.sleep(2)  # Wait for 2 seconds before retrying
     
-    # Extract the response text and remove any leading/trailing whitespace
-    return response.choices[0].message.content.strip()
+    return "Failed to connect to OpenAI API after several attempts."
 
 # Create the Gradio interface
 iface = gr.Interface(
     fn=subsurface_sentinel,  # The function to be called for generating responses
-    inputs=[
-        gr.Textbox(label="Enter your question here"),  # User input
-        gr.File(label="Upload a PDF for context (optional)")  # PDF upload input
-    ],
+    inputs=gr.Textbox(label="Enter your question here"),  # User input
     outputs="text",  # Output type for the bot's response
     title="Subsurface Sentinel",
     description=(
         "A virtual assistant for professionals in the oil and gas industry focusing on field development planning.\n\n"
-        "You can ask a question or upload a PDF to provide additional context for your query."
+        "You can ask questions related to field development, subsurface risks, reservoir management, and more."
     ),
     examples=[
-        ["Analyze the provided Field Development Plan for insights.", None], 
-        ["What are the potential risks in subsurface operations?", None]
+        ["Analyze the provided Field Development Plan for insights."],
+        ["What are the potential risks in subsurface operations?"],
+        ["How can machine learning be applied to improve reservoir management?"],
+        ["Summarize the key details from the latest geological survey report."],
+        ["Evaluate the proposed drilling strategy in terms of cost-effectiveness."]
     ]
 )