Update app.py

app.py

@@ -159,7 +159,7 @@ async def run_function_on_text(top_k,study_obj,study_type,phase,purpose,allocati
       3. Conditions
       4. Intervention/Treatment
 
-      Please follows the pattern of the output(### Pattern of the output).
+      Please follow the pattern of the output(### Pattern of the output).
       --------------------------------------------------
       ### Clinical Trial Information
       {study_information}
@@ -181,13 +181,14 @@ async def run_function_on_text(top_k,study_obj,study_type,phase,purpose,allocati
 
 
       """
+    )
 
-  Combine_response = await llm.acomplete(f"""
-      Based on the provided instructions clinical and criteria information, generate the new eligibility criteria by analyzing Criteria 1 (### Criteria 1) and Criteria 2 (### Criteria 2).
+  combine_response = await llm.acomplete(f"""
+      Based on the provided instructions clinical, clinical trial information, and criteria information, generate the appropriate eligibility criteria for ### Clinical Trial Information by analyze clinical trial information(### Clinical Trial Information), criteria 1 (### Criteria 1) and criteria 2 (### Criteria 2).
       ### Instruction:
       Criteria generation:
-      As a clinical researcher, generate eligibility criteria for given information.
-      Ensure the criteria are clear, specific, and reasonable for a clinical research information().
+      As a clinical researcher, generate appropriate eligibility criteria by analyzing given information.
+      Ensure the criteria are clear, specific, and reasonable for a clinical research information(### Clinical Trial Information).
 
       Prioritize the following topics in clinical trial information.:
       1. Study Objectives
@@ -195,11 +196,22 @@ async def run_function_on_text(top_k,study_obj,study_type,phase,purpose,allocati
       3. Conditions
       4. Intervention/Treatment
 
-      Please follows the pattern of the output(### Pattern of the output).
+      Do not generate redundant inclusion and exclusion criteria. For example, if a criterion is included in one set of inclusion or exclusion criteria, do not include it again.
+
+      Reference Papers generation:
+      Please give us NCT IDs and study names from the references list in ### Criteria 1.
+
+      Please follow the pattern of the output(### Pattern of the output).
       --------------------------------------------------
       ### Clinical Trial Information
       {study_information}
       --------------------------------------------------
+      ### Criteria 1
+      {query_response}
+      --------------------------------------------------
+      ### Criteria 2
+      {complete_response}
+      --------------------------------------------------
       ### Pattern of the output
       Inclusion Criteria
       1.
@@ -215,11 +227,22 @@ async def run_function_on_text(top_k,study_obj,study_type,phase,purpose,allocati
       .
       .
 
-
+      Reference Papers
+      1.NCT ID:
+        Study Name:
+        Condition:
+        Intervention/Treatment:
+      2.NCT ID:
+        Study Name:
+        Condition:
+        Intervention/Treatment:
+      .
+      .
+      .
       """
     )
 
-  return query_response,complete_response
+  return query_response,complete_response,combine_response
 
 # Place holder
 place_holder = f"""Study Objectives
@@ -280,45 +303,45 @@ interventions_place_holder = f"""Example:
 
 prefilled_value = f"""Study Objectives The purpose of this study is to find out if the combination of docetaxel and capecitabine can shrink the size of breast tumors and preserve the breast. Conditions: Breast Cancer Intervention / Treatment: DRUG: Docetaxel, DRUG: Capecitabine Location: United States Study Design and Phases Study Type: INTERVENTIONAL Phase: PHASE2 Primary Purpose: TREATMENT Allocation: RANDOMIZED Interventional Model: PARALLEL Masking: NONE"""
 
-custom_css = """
-.gradio-container {
-    font-family: 'Roboto', sans-serif;
-}
-.main-header {
-    text-align: center;
-    color: #4a4a4a;
-    margin-bottom: 2rem;
-}
-.tab-header {
-    font-size: 1.2rem;
-    font-weight: bold;
-    margin-bottom: 1rem;
-}
-.custom-chatbot {
-    border-radius: 10px;
-    box-shadow: 0 4px 6px rgba(0, 0, 0, 0.1);
-}
-.custom-button {
-    background-color: #3498db;
-    color: white;
-    border: none;
-    padding: 10px 20px;
-    border-radius: 5px;
-    cursor: pointer;
-    transition: background-color 0.3s ease;
-}
-.custom-button:hover {
-    background-color: #2980b9;
-}
-"""
-
-# Define Gradio theme
-theme = gr.themes.Default(
-    primary_hue="zinc",
-    secondary_hue="red",
-    neutral_hue="neutral",
-    font=[gr.themes.GoogleFont('Roboto'), "sans-serif"]
-)
+# custom_css = """
+# .gradio-container {
+#     font-family: 'Roboto', sans-serif;
+# }
+# .main-header {
+#     text-align: center;
+#     color: #4a4a4a;
+#     margin-bottom: 2rem;
+# }
+# .tab-header {
+#     font-size: 1.2rem;
+#     font-weight: bold;
+#     margin-bottom: 1rem;
+# }
+# .custom-chatbot {
+#     border-radius: 10px;
+#     box-shadow: 0 4px 6px rgba(0, 0, 0, 0.1);
+# }
+# .custom-button {
+#     background-color: #3498db;
+#     color: white;
+#     border: none;
+#     padding: 10px 20px;
+#     border-radius: 5px;
+#     cursor: pointer;
+#     transition: background-color 0.3s ease;
+# }
+# .custom-button:hover {
+#     background-color: #2980b9;
+# }
+# """
+
+# # Define Gradio theme
+# theme = gr.themes.Default(
+#     primary_hue="zinc",
+#     secondary_hue="red",
+#     neutral_hue="neutral",
+#     font=[gr.themes.GoogleFont('Roboto'), "sans-serif"]
+# )
 
 with gr.Blocks() as demo:
 
@@ -415,18 +438,24 @@ with gr.Blocks() as demo:
               label="Response 2",
               lines=5,
               interactive=False)
+  with gr.Row():
+      with gr.Column():
+          combine_box = gr.Textbox(
+              label="Response 3",
+              lines=5,
+              interactive=False)
+          
+  inputs_information = [top_k_box, study_obj_box, study_type_box, phase_box, purpose_box, allocation_box, intervention_model_box, masking_box, conditions_box, intervention_box, location_box, removed_location_box]
+  outputs_information = [base_box, rag_box,combine_box]
 
   submit_button.click(
       run_function_on_text,
-      inputs=[top_k_box,study_obj_box,study_type_box,phase_box,purpose_box,allocation_box,intervention_model_box,masking_box,conditions_box,intervention_box,location_box,removed_location_box],
-      outputs=[base_box, rag_box]
-  )
-
-  inputs_information = [top_k_box, study_obj_box, study_type_box, phase_box, purpose_box, allocation_box, intervention_model_box, masking_box, conditions_box, intervention_box, location_box, removed_location_box]
+      inputs=inputs_information,
+      outputs=outputs_information
+      )
 
   clear_button.click(lambda : [None] * len(inputs_information), outputs=inputs_information)
 
-
   with gr.Row():
       selected_response = gr.Radio(
           choices=[
@@ -449,7 +478,7 @@ with gr.Blocks() as demo:
   with gr.Row():
     clear_all_button = gr.Button("Clear All")
 
-  output_information = inputs_information + [base_box, rag_box, selected_response]
+  output_information = inputs_information + outputs_information
   clear_all_button.click(lambda : [None] * len(output_information), outputs=output_information)
 
 if __name__ == "__main__":