allow context setting

app.py

@@ -1,6 +1,6 @@
 ''' GRADIO APP '''
 
-import os
+import os, json
 import gradio as gr
 import openai
 
@@ -12,7 +12,8 @@ import openai
 #########################
 '''
 # Read OpenAI API key from environment variable
-openai.api_key = os.getenv("OPENAI_API_KEY")
+openai.api_key = "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"
+# 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")
@@ -24,25 +25,32 @@ if not 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. "}]
+# 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):
+def generate_test_cases(ctx, topic):
+    if ctx:
+        conversation_tc = json.loads(ctx)
+        print(conversation_tc)
     if topic:
         conversation_tc.append({"role": "user", "content": f"Generate a manual test case for the topic: {topic}"})
+        print("Request to OpenAI", conversation_tc)
         response = openai.ChatCompletion.create(
               model="gpt-3.5-turbo",
               messages=conversation_tc
           )
-
+        print("Response from OpenAI", response["usage"]["total_tokens"])
         test_cases = response["choices"][0]["message"]["content"]
-        return test_cases
+        return test_cases, test_cases
     else:
         return "Please enter a topic/subject."
 
-def generate_test_scripts(framework, test_cases):
+def generate_test_scripts(ctx, framework, test_cases):
+    if ctx:
+        convo_py = json.loads(ctx)
+        convo_java = json.loads(ctx)
     print("TEST SCRIPT", framework)
     if framework == "Python, unittest":
         print("py")
@@ -88,7 +96,7 @@ title = """
 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. 
+By providing 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>
 '''
@@ -123,30 +131,45 @@ This tool is produced by an LLM and therefore the outputs might not be perfect.
     Gradio Block
 #####################
 '''
-test_case = None
+test_case_1 = None
+test_case_2 = 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')
-            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"),
-            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)
+    with gr.Tab("1. Text Generation"):
+        with gr.Accordion("Context"):
+                test_case_context = gr.Textbox(label='Functional Usecase', 
+                    open=False, 
+                    value='[{"role": "system", "content": "You are a technical and a professional QA manager, working in a technological firm. You provide test cases for a scenario. "}]')
+        with gr.Row():
+            with gr.Column():
+                test_case_topic = gr.Textbox(label='Functional Usecase', value='Robotic arm to test payments using card with driver, inspector and billing device')
+                tc_button = gr.Button("Generate Test Case")
+            with gr.Column():
+                test_case_1 = gr.Textbox(label="Test Case")
+
+    with gr.Tab("2. Test Script Generation"):
+        with gr.Accordion("Context"):
+                test_script_context = gr.Textbox(label='Functional Usecase', 
+                    open=False, 
+                    value='[{"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"}]')
+        with gr.Row():
+            with gr.Column():
+                fw = gr.Dropdown(["Python, unittest", "Java, JUnit"], label="Framework")
+                test_case_2 = gr.Textbox(label="Test Case", lines=20, interactive=True)
+                ts_button = gr.Button("Generate Test Script")
+            with gr.Column():
+                test_script = gr.Code(label="Test Script",language="python")
+
+
+        tc_button.click(fn=generate_test_cases, inputs=[test_case_context,test_case_topic], outputs=[test_case_1,test_case_2], show_progress=True)
+        ts_button.click(fn=generate_test_scripts, inputs=[test_script_context, fw, test_case_2], outputs=test_script, show_progress=True)
 
     # gr.Markdown(howto)
     gr.Markdown(notices)
 
-demo.queue(api_open=False, max_size=5).launch()
+demo.queue(api_open=False, max_size=5).launch(debug=True)