Added user defined questions

app.py

@@ -1,79 +1,95 @@
-from Promptless_LLM_Agent import questions
-from Summarization import Summarizer
-from TextToImage_StableDiffusion import generate as image_generator
-
-import gradio as gr
-
-def nextGen():
-    try:
-        x = next(q)
-    except StopIteration:
-        x = None
-    return x
-
-def requirement_string(req, QA):
-    req = "User Requirement: "+req+"\n"
-    for q, a in QA:
-        req = req+'\n'+'Graphic Designer: '+q+'\n'+'User: '+a
-    return req
-
-r = None
-q = None
-qa = None
-summary = None
-
-with gr.Blocks() as demo:
-    
-    title = gr.Label(value="Graphic Designer", show_label=False)
-
-    a = gr.Textbox(label="Enter Requirement")
-    b = gr.Button("Submit")
-    c = gr.Label(visible=False)
-    d = gr.Chatbot(visible=False)
-    g = gr.Textbox(visible=False)
-    e = gr.Textbox(visible=False)
-    f = gr.Button(visible=False)
-    h = gr.Label(visible=False)
-    m = gr.Image(visible=False)
-
-    def fn_req(data):
-        global r
-        global q
-        r = data[a]
-        q = (i for i in questions(data[a])[:3])
-        return {a: gr.Textbox(visible=False), 
-                b: gr.Button(visible=False), 
-                c: gr.Label(value=data[a], label="Customer Requirement", visible=True),
-                d: gr.Chatbot(label="Requirements Gathering", visible=True),
-                g: gr.Textbox(value=nextGen(), label="Question", visible=True),
-                e: gr.Textbox(label="Answer", visible=True),
-                f: gr.Button("Submit Answer", visible=True)}
-    
-    def bot_user_response(question, answer, history):
-        global qa
-        global summary
-        history = history + [[question, answer]]
-        question = nextGen()
-
-        if question:
-            return {g: question, e: '', d: history}
-        else:
-            qa = requirement_string(r, history)
-            summary = Summarizer(qa)
-            # summary = """The user requires a YouTube thumbnail for an educational video. 
-            #              They want a dancer to be featured in the image and 
-            #              the tone or mood they want to convey is joyful."""
-            image = image_generator(summary)
-            text = "Thank you for your response"
-            return {g: gr.Textbox(visible=False), 
-                    e: gr.Textbox(visible=False), 
-                    d: history,
-                    h: gr.Label(value=text, visible=True, show_label=False),
-                    f: gr.Button(visible=False),
-                    m: gr.Image(value=image ,visible=True)}
-
-    b.click(fn=fn_req, inputs={a}, outputs=[a,b,c,d,g,e,f])
-
-    f.click(bot_user_response, [g, e, d], [g, e, d, h, f, m])
-
+from Promptless_LLM_Agent import questions
+from Summarization import Summarizer
+from TextToImage_StableDiffusion import generate as image_generator
+
+import gradio as gr
+
+user_defined_questions = ["What is the title or subject of the video? Please provide a brief description (1-2 sentences) to help me understand the content?", 
+       "What type of video is this (e.g., documentary, informative, sarcastic, comedy, tutorial, review, etc.)?",
+       "Are there any specific keywords or tags you want to include for search optimization? ",
+       "What is the desired mood or atmosphere for the thumbnail (e.g., energetic, calm, inspirational, humorous)?",
+       "What style or tone do you want to convey (e.g., serious, playful, minimalist, detailed)?",
+       "Are there any specific text elements (e.g., titles, subtitles, quotes) you want to include in the thumbnail?",
+       "Who is the target audience for this video?"]
+
+def nextGen():
+    try:
+        x = next(q)
+    except StopIteration:
+        x = None
+    return x
+
+def requirement_string(req, QA):
+    req = "User Requirement: "+req+"\n"
+    for q, a in QA:
+        req = req+'\n'+'Graphic Designer: '+q+'\n'+'User: '+a
+    return req
+
+r = None
+q = None
+qa = None
+summary = None
+
+with gr.Blocks() as demo:
+    
+    title = gr.Label(value="Graphic Designer", show_label=False)
+
+    a = gr.Textbox(label="Enter Requirement")
+    b = gr.Button("Submit")
+    c = gr.Label(visible=False)
+    d = gr.Chatbot(visible=False)
+    g = gr.Textbox(visible=False)
+    e = gr.Textbox(visible=False)
+    f = gr.Button(visible=False)
+    h = gr.Label(visible=False)
+    m = gr.Image(visible=False)
+
+    def fn_req(data):
+        global r
+        global q
+        r = data[a]
+
+        try:
+            llm_q = questions(data[a])
+            llm_q = random.sample(llm_q, 3)
+        except:
+            llm_q = []
+
+        all_q = user_defined_questions + llm_q
+        q = (i for i in all_q)
+        return {a: gr.Textbox(visible=False), 
+                b: gr.Button(visible=False), 
+                c: gr.Label(value=data[a], label="Customer Requirement", visible=True),
+                d: gr.Chatbot(label="Requirements Gathering", visible=True),
+                g: gr.Textbox(value=nextGen(), label="Question", visible=True),
+                e: gr.Textbox(label="Answer", visible=True),
+                f: gr.Button("Submit Answer", visible=True)}
+    
+    def bot_user_response(question, answer, history):
+        global qa
+        global summary
+        history = history + [[question, answer]]
+        question = nextGen()
+
+        if question:
+            return {g: question, e: '', d: history}
+        else:
+            qa = requirement_string(r, history)
+            summary = Summarizer(qa)
+            # summary = """The user requires a YouTube thumbnail for an educational video. 
+            #              They want a dancer to be featured in the image and 
+            #              the tone or mood they want to convey is joyful."""
+            image = image_generator(summary)
+            text = "Thank you for your response"
+            return {g: gr.Textbox(visible=False), 
+                    e: gr.Textbox(visible=False), 
+                    d: history,
+                    h: gr.Label(value=text, visible=True, show_label=False),
+                    f: gr.Button(visible=False),
+                    m: gr.Image(value=image ,visible=True)}
+
+    b.click(fn=fn_req, inputs={a}, outputs=[a,b,c,d,g,e,f])
+
+    f.click(bot_user_response, [g, e, d], [g, e, d, h, f, m])
+
 demo.launch()