''' GRADIO APP '''

import os
import gradio as gr
import openai



'''
#########################
    Environment Variables
#########################
'''
# Read OpenAI API key from environment variable
openai.api_key = os.getenv("OPENAI_API_KEY")

if not openai.api_key:
    st.error("No OpenAI API key found in the environment variable OPENAI_API_KEY")


'''
#####################
    Backend Functions
#####################
'''

conversation_tc = [{"role": "system", "content": "You are a technical and a professional QA manager, working in a technological firm. You provide test cases for a scenario. "}]
convo_py = [{"role": "system", "content": "You are a technical and a professional QA manager who specializes in Python Unittest, working in a technological firm. You should provide Python Unittest test scripts in for the test case provided"}]
convo_java = [{"role": "system", "content": "You are a technical and a professional QA manager who specializes in Java JUnit, working in a technological firm. You should provide Java JUnit test scripts in for the test case provided"}]


def generate_test_cases(topic):
    if topic:
        conversation_tc.append({"role": "user", "content": f"Generate a manual test case for the topic: {topic}"})
        response = openai.ChatCompletion.create(
              model="gpt-3.5-turbo",
              messages=conversation_tc
          )

        test_cases = response["choices"][0]["message"]["content"]
        return test_cases
    else:
        return "Please enter a topic/subject."

def generate_test_scripts(framework, test_cases):
    print("TEST SCRIPT", framework)
    if framework == "Python, unittest":
        print("py")
        return generate_python_unittest(test_cases)
    elif framework == "Java, JUnit":
        print("java")
        return generate_java_junit(test_cases)
    else:
        return "Unsupported language or framework."

def generate_python_unittest(test_cases):
    convo_py.append({"role": "user", "content": f"Here is a manual test case. {test_cases}"})
    # prompt = f"Create a Python unittest test script for the following test cases:\n{test_cases}"
    response = openai.ChatCompletion.create(
        model="gpt-3.5-turbo",
        messages=convo_py
    )
    script = response["choices"][0]["message"]["content"]
    return script

def generate_java_junit(test_cases):
    convo_java.append({"role": "user", "content": f"Here is a manual test case. {test_cases}"})
    # prompt = f"Create a Java JUnit test script for the following test cases:\n{test_cases}"
    response = openai.ChatCompletion.create(
        model="gpt-3.5-turbo",
        messages=convo_java
    )
    script = response["choices"][0]["message"]["content"]
    return script



'''
#####################
    Markdown Content
#####################
'''

title = """
# QA Leveraging GenAI
"""

description = '''
This tool leverages OpenAI's GPT-3.5-turbo model to automate two key aspects of quality assurance in software development: generating test cases and writing test scripts.

By inputting a functional use case, you can generate detailed test cases to ensure the quality of your software. 
You can also select your preferred testing framework, and the tool will generate test scripts based on the generated test cases
<hr>
'''

howto = '''
<br>
## How to Use

**Test Case Generation**
Enter Functional usecase: Describe the functional use case for which you want to generate test cases. The more specific you are, the better the generated test cases will be.
Click on Generate Test Case button

**Test Script Generation**
Select a Test Framework: Choose the testing framework that you want the test scripts to be compatible with. Currently, you can select between Python's unittest and Java's JUnit frameworks.
---
## Results

- **Test Case**: This section will display the generated test cases based on the functional use case you provided. 

- **Test Script**: After choosing your preferred language and testing framework, this section will display the test scripts corresponding to the generated test cases.
---
'''

notices = '''
**Notice**
This tool is produced by an LLM and therefore the outputs might not be perfect. Its best to review and edit the generated test cases and scripts as necessary.
'''


'''
#####################
    Gradio Block
#####################
'''
test_case = None

with gr.Blocks() as demo:
    gr.Markdown(title)
    gr.Markdown(description)


    with gr.Row() as text_to_image:

        with gr.Column():
            test_case_topic = gr.Textbox(label='Functional Usecase', value='VR Headset Battery Installation', info="Descriptive usecase to generate Test Cases for")
            tc_button = gr.Button("Generate Test Case")
            test_case = gr.Textbox(label="Test Case")

        with gr.Column():
            fw = gr.Dropdown(["Python, unittest", "Java, JUnit"], label="Framework", info="Framework to generate test scripts on"),
            ts_button = gr.Button("Generate Test Script")
            test_script = gr.Textbox(label="Test Script")


        tc_button.click(fn=generate_test_cases, inputs=test_case_topic, outputs=test_case, show_progress=True)
        ts_button.click(fn=generate_test_scripts, inputs=[fw[0], test_case], outputs=test_script, show_progress=True)

    # gr.Markdown(howto)
    gr.Markdown(notices)

demo.queue(api_open=False, max_size=5).launch()