Update app.py

app.py

@@ -10,6 +10,57 @@ model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.float
 model.to(device)
 tokenizer = AutoTokenizer.from_pretrained(model_name)
 
+# Default values for system and user input
+test_instruction_string = """
+You're a clinical trial expert. For each trial query, list probable baseline features (each in backticks and comma-separated).
+Baseline features are demographic characteristics used in primary outcome analysis, often shown by group in clinical publications.
+"""
+
+test_input_string = """
+<Title:>Vinorelbine in Treating Patients With Advanced Solid Tumors That Have Not Responded to Treatment and Liver Dysfunction <BriefSummary:>RATIONALE: Drugs used in chemotherapy, such as vinorelbine, work in different ways to stop the growth of tumor cells, either by killing the cells or by stopping them from dividing.
+
+PURPOSE: This pilot trial is studying the side effects and best dose of vinorelbine in treating patients with advanced solid tumors that have not responded to treatment and liver dysfunction. <EligibilityCriteria:>DISEASE CHARACTERISTICS:
+
+* Histologically confirmed advanced solid tumor
+
+  * Any histology allowed
+* Refractory to standard therapy OR no standard therapy exists
+
+  * Previously untreated non-small cell lung cancer allowed, provided abnormal liver function is present, defined as moderate (group 3) or severe (group 4)
+* Measurable disease not required
+
+  * Present measurable disease requires baseline measurements within 4 weeks of study entry
+* Patients with acute hepatitis from viral or drug etiologies should recover to a stable baseline prior to study therapy
+* History of brain metastasis allowed, provided the following criteria are met:
+
+  * Metastasis has been controlled by radiotherapy or surgery
+  * Patient is not currently on corticosteroids
+  * Neurologic status is stable
+
+PATIENT CHARACTERISTICS:
+
+* Karnofsky performance status 70-100%
+* Life expectancy ≥ 2 months
+* ANC = 1,500/mm³
+* Platelet count = 100,000/mm³
+* Hemoglobin = 10 g/dL (transfusion to this level allowed)
+* Creatinine \< 1.5 mg/dL OR creatinine clearance \> 60 mL/ min
+* Patients with EKG evidence of first- or second-degree AV block or left or right bundle branch block are ineligible for the lidocaine bolus, but may otherwise be treated on this protocol
+* Not pregnant or nursing
+* Negative pregnancy test
+* Fertile patients must use effective contraception
+* No concurrent illness (e.g., cardiovascular, pulmonary, or central nervous system) that is poorly controlled or of such severity that the investigator deems unwise to enter the patient on protocol
+* Must have ability to comply with study treatment and required tests
+* Obstructive jaundice requires a drainage procedure prior to study treatment
+
+PRIOR CONCURRENT THERAPY:
+
+* See Disease Characteristics
+* Recovered from prior therapy
+* At least 3 weeks since prior chemotherapy (6 weeks for mitomycin or nitrosourea therapy)
+* No prior radiotherapy to \> 30% of the bone marrow or more than standard adjuvant pelvic radiotherapy for rectal cancer <Conditions:>Lung Cancer, Unspecified Adult Solid Tumor, Protocol Specific,  <Interventions:>indocyanine green, lidocaine, vinorelbine ditartrate, high performance liquid chromatography, intracellular fluorescence polarization analysis, liquid chromatography, mass spectrometry, pharmacological study <StudyType:>INTERVENTIONAL <PrimaryOutcomes:>Area Under the Curve, Number of Participants With Grade 3 and 4 Toxicities <OverallStatus:>COMPLETED
+"""
+
 @spaces.GPU
 def generate_response(system_instruction, user_input):
     # Format the prompt using the messages structure
@@ -35,18 +86,25 @@ with gr.Blocks() as demo:
         # Left sidebar for inputs
         with gr.Column():
             system_instruction = gr.Textbox(
-                placeholder="Enter system instruction here...", label="System Instruction")
+                value=test_instruction_string,
+                placeholder="Enter system instruction here...",
+                label="System Instruction"
+            )
             user_input = gr.Textbox(
-                placeholder="Type your message here...", label="Your Message")
+                value=test_input_string,
+                placeholder="Type your message here...",
+                label="Your Message"
+            )
             submit_btn = gr.Button("Submit")
 
         # Right column for displaying bot response
         with gr.Column():
             response_display = gr.Textbox(
-                label="Bot Response", interactive=False, placeholder="Response will appear here.")
+                label="Bot Response", interactive=False, placeholder="Response will appear here."
+            )
 
     # Link submit button to the generate_response function
     submit_btn.click(generate_response, [system_instruction, user_input], response_display)
 
 # Launch the app
-demo.launch(share=True)
+demo.launch()