Prompt
Answer
Pseudo Code for Flask Application with OpenAI Interaction
Overview
The objective is to describe the logic of a Flask web application that generates random data based on user-defined scenarios by leveraging OpenAI's code generation capabilities. The application includes features for handling HTTP requests, executing generated Python code, and returning CSV files.
Main Components
1. Application Initialization
- Import necessary libraries
- Initialize Flask application
- Set up OpenAI API key from environment variables
2. Function: extract_python_code
- Extracts Python code from OpenAI's response which is embedded within markdown code blocks.
3. Function: generate_python_code
- Constructs a prompt to request Python code generation.
- Interacts with OpenAI's API to generate the desired function.
- Handles exceptions and logs errors.
4. Route Handlers
index
: Main entry point for web interactions. Handles both GET and POST requests.- On POST:
- Log the scenario and number of rows/columns.
- Generate code and execute it dynamically.
- Prepare and send CSV for download or preview based on user input.
- On GET:
- Render the index page for user interaction.
- On POST:
scenario_browser
: Renders a different page for browsing scenarios.set_scenario
: Stores selected scenario in the session for later use.
5. Main Execution
- Run the application with specified host and port settings.
Pseudo Code
START Application
IMPORT necessary libraries (Flask, render_template, request, send_file, jsonify, session, csv, io, random, openai, os, logging, traceback)
INITIALIZE Flask application
SET OPENAI API key from environment variable 'OPENAIDEMO'
FUNCTION extract_python_code(response):
INITIALIZE empty list code_lines
SET in_code_block to False
SPLIT response by newline
FOR each line IN lines:
IF line starts with '```python':
SET in_code_block to True
CONTINUE
ELSE IF line is '```' AND in_code_block:
SET in_code_block to False
CONTINUE
IF in_code_block:
APPEND line to code_lines
RETURN joined code_lines with newline
FUNCTION generate_python_code(scenario, num_columns):
CONSTRUCT prompt using scenario and num_columns
TRY:
CALL OpenAI API to get code response
STORE response from OpenAI
RETURN extract_python_code(full_response)
EXCEPT Exception e:
LOG error message
RETURN None
SET logging configuration
DEFINE route '/' with methods GET, POST:
IF method is POST:
LOG received scenario and data
TRY:
GET scenario, num_rows, num_columns from request
LOG received data
generated_code = CALL generate_python_code(scenario, num_columns)
LOG generated code
IF generated_code is valid string:
TRY:
EXECUTE generated_code using exec
IF 'generate_random_data' is not defined:
RAISE NameError
IF 'preview' is present in request:
preview_data = CALL generate_random_data with 5 rows
RETURN preview_data as JSON response
ELSE:
data = CALL generate_random_data with num_rows
LOG data generation
INITIALIZE CSV writer
WRITE header and data to CSV
RETURN CSV file for download
EXCEPT Exception e:
LOG execution error
RETURN error message as JSON response
ELSE:
LOG code generation failure
RETURN failure message as JSON response
EXCEPT Exception e:
LOG unexpected error
RETURN unexpected error message as JSON response
ELSE:
SELECTED_SCENARIO from session or set to empty
RENDER index.html with selected scenario
DEFINE route '/scenario-browser':
RENDER scenario_browser.html
DEFINE route '/set-scenario' with method POST:
GET scenario from request JSON
STORE scenario in session
RETURN success message as JSON response
IF main module:
RUN application on host '0.0.0.0' and port 8080 with debug mode
END Application
Conclusion
The outlined pseudo code serves as a blueprint for implementing a Flask-based application that interacts with the OpenAI API for dynamic code generation and data handling. This structure ensures clarity and ease of understanding for future development and documentation purposes.
Description
This Flask app generates random data based on user scenarios using OpenAI's code generation capabilities. It handles HTTP requests, executes generated Python code, and can return data in CSV format for download.