update ui

app.py

@@ -12,10 +12,7 @@ def get_feedback(
     experiences: str,
     projects: str,
     skills: str,
-    description: str,
-    max_new_tokens: int,
-    top_p: float,
-    temperature: float
+    description: str
 ):
     headers = {
         'accept': 'application/json',
@@ -31,9 +28,9 @@ def get_feedback(
     }
 
     model_config = {
-        "max_new_tokens": max_new_tokens,
-        "top_p": top_p,
-        "temperature": temperature,
+        "max_new_tokens": 512,
+        "top_p": 0.9,
+        "temperature": 0.4,
         "do_sample": True
     }
 
@@ -64,58 +61,99 @@ with gr.Blocks(theme=gr.themes.Base(font=[gr.themes.GoogleFont("Poppins")])) as
         <div style="text-align: center; font-size: 18px; margin-bottom: 20px;">
             A demo application that provides review on a resume against the job market using the G-Retriever framework, an LLM powered by a Knowledge Graph.
         </div>
+        <div style="text-align: left; font-size: 14px; margin-bottom: 20px;">
+            *Currently, ReviceGraph only supports the English language.
+        </div>
         """
     )
     with gr.Row(equal_height=True):
         with gr.Column():
-            education = gr.Textbox(label="Education", lines=2)
-            experience = gr.Textbox(label="Experiences", lines=2)
-            project = gr.Textbox(label="Projects", lines=2)
-            skill = gr.Textbox(label="Skills", lines=2)
-        with gr.Column():
-            # feedback = gr.Textbox(label="Feedback", interactive=False, lines=18)
-            strengths = gr.Textbox(label="Strengths", lines=3.7, interactive=False)
-            weaknesses = gr.Textbox(label="Weaknesses", lines=3.7, interactive=False)
-            improvements = gr.Textbox(label="Improvements", lines=3.7, interactive=False)
-
-
-    with gr.Row():
-        with gr.Column():
+            gr.Markdown("### Input")
+            education = gr.Textbox(
+                label="Education",
+                lines=2,
+                placeholder="e.g. Bachelor Degree of Mathematics at Institut Teknologi Sepuluh Nopember",
+                info="The candidate's formal education."
+            )
+            experience = gr.Textbox(
+                label="Experiences",
+                lines=2,
+                placeholder="e.g. Data Scientist Intern at Bank Rakyat Indonesia",
+                info="The candidate's work experience and job descriptions. Could be intenship experience or professional experience."
+            )
+            project = gr.Textbox(
+                label="Projects",
+                lines=2,
+                placeholder="e.g. Chatbot for Customer Service using LLM",
+                info="Projects completed by the candidate and their description. Could be college project or internship project"
+            )
+            skill = gr.Textbox(
+                label="Skills",
+                lines=2,
+                placeholder="e.g. Python, Pytorch, Machine Learning, Deep Learning",
+                info="Skills possessed by the candidate. Could be technical skill, concept skill, or soft skill."
+            )
             description = gr.Textbox(
                 label="Description",
-                lines=3,
+                lines=2,
+                placeholder="e.g. I want to pursue my career as machine learning engineer",
+                info="Candidate career orientation"
             )
-            submit = gr.Button("Get Feedback")
 
+            submit = gr.Button("Get Feedback")
         with gr.Column():
-            max_new_tokens = gr.Slider(
-                minimum=256,
-                maximum=512,
-                value=512,
-                step=1.0,
-                label="Maximum Output Length",
-                interactive=True
+            # feedback = gr.Textbox(label="Feedback", interactive=False, lines=18)
+            gr.Markdown("### Output")
+            strengths = gr.Textbox(
+                label="Strengths",
+                lines=7,
+                interactive=False,
+                info="Potential reasons for the candidate to be accepted."
             )
-            top_p = gr.Slider(
-                minimum=0,
-                maximum=1,
-                value=0.9,
-                step=0.01,
-                label="Top P",
-                interactive=True
+            weaknesses = gr.Textbox(
+                label="Weaknesses",
+                lines=7,
+                interactive=False,
+                info="Potential reasons for the candidate to be rejected."
             )
-            temperature = gr.Slider(
-                minimum=0.01,
-                maximum=1,
-                value=0.5,
-                step=0.01,
-                label="Temperature",
-                interactive=True
+            improvements = gr.Textbox(
+                label="Improvements",
+                lines=7,
+                interactive=False,
+                info="Recommendation for improvement on candidate's skills, experiences, or projects based on their weaknesses."
             )
 
+        # with gr.Column():
+        #     max_new_tokens = gr.Slider(
+        #         minimum=256,
+        #         maximum=512,
+        #         value=512,
+        #         step=1.0,
+        #         info="Maximum number of tokens or words",
+        #         label="Maximum Output Length",
+        #         interactive=True
+        #     )
+        #     top_p = gr.Slider(
+        #         minimum=0,
+        #         maximum=1,
+        #         value=0.9,
+        #         step=0.01,
+        #         label="Top P",
+        #         interactive=True
+        #     )
+        #     temperature = gr.Slider(
+        #         minimum=0.01,
+        #         maximum=1,
+        #         value=0.4,
+        #         step=0.01,
+        #         info="Define how creative the model to generates feedback.\nThe optimal value is 0.4.",
+        #         label="Temperature",
+        #         interactive=True
+        #     )
+
     submit.click(
         fn=get_feedback,
-        inputs=[education, experience, project, skill, description, max_new_tokens, temperature, top_p],
+        inputs=[education, experience, project, skill, description], #, max_new_tokens, temperature, top_p],
         outputs=[strengths, weaknesses, improvements],
         # outputs=feedback,
         show_progress=True