app.py

import os
import streamlit as st
import openai

# 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")

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, num_cases):
    if topic:
        conversation_tc.append({"role": "user", "content": f"Generate {num_cases} manual test cases 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(language, framework, test_cases):
    if language == "Python" and framework == "unittest":
        return generate_python_unittest(test_cases)
    elif language == "Java" and framework == "JUnit":
        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

# Streamlit interface
st.title("Manual Test Case Generator")

# Columns layout
col1, col2 = st.columns(2)
test_cases = None

with col1:
    topic = st.text_input("Enter a topic or subject:")
    num_cases = st.number_input("Number of test cases:", min_value=1, max_value=10, value=1)

    if st.button("Generate Test Case"):
        test_cases = generate_test_cases(topic, num_cases)
        st.write(test_cases)

with col2:
    if test_cases:
        language = st.selectbox("Select a language:", ["Python", "Java"])
        framework = st.selectbox("Select a test framework:", ["unittest", "JUnit"])
    
        if st.button("Generate Test Script"):
            test_scripts = generate_test_scripts(language, framework, test_cases)
            st.code(test_scripts, language)