import openai
import gradio as gr
import os
import time

# Load your OpenAI API key from the environment variable
api_key = os.getenv("OPENAI_API_KEY")

# Ensure the API key doesn't have any leading/trailing whitespace or newline characters
openai.api_key = api_key.strip()

# Function to interact with the GPT-4o-mini model via the OpenAI API
def subsurface_sentinel(user_input):
    prompt = f"User: {user_input}"

    # 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
        except openai.InvalidRequestError as e:
            return f"Invalid request: {e}"
        except openai.AuthenticationError as e:
            return f"Authentication failed: {e}"
        except openai.RateLimitError as e:
            return f"Rate limit exceeded: {e}"
        except Exception as e:
            return f"An unexpected error occurred: {e}"
    
    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
    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 questions related to field development, subsurface risks, reservoir management, and more."
    ),
    examples=[
        ["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."]
    ]
)

# Launch the Gradio interface
iface.launch()