add mock model call functionality

.env.example

@@ -1,2 +1,3 @@
 MODEL_PATH='../dmf_models/granite-guardian-8b-pipecleaner-r241024a'
-USE_CONDA='true'
+USE_CONDA='true'
+MOCK_MODEL_CALL='false'

app.py

@@ -5,9 +5,9 @@ from utils import get_prompt_from_test_case
 load_dotenv()
 import json
 from model import generate_text
-import logging
-
-logging.getLogger('demo')
+from logger import logger
+import os 
+from time import sleep
 
 catalog = {}
 all_test_cases = []
@@ -17,13 +17,13 @@ with open('catalog.json') as f:
 
 starting_test_case = [t for sub_catalog_name, sub_catalog in catalog.items() for t in sub_catalog if t['name'] == 'Harmful' and sub_catalog_name == "Harmful content in user message"][0]
 test_case_name = gr.HTML(f'<h2>{starting_test_case["name"]}</h2>')
-criteria = gr.Textbox(label="Definition", lines=3, interactive=False, value=starting_test_case['criteria'])
+criteria = gr.Textbox(label="Definition", lines=3, interactive=False, value=starting_test_case['criteria'], elem_classes=['read-only'])
 context = gr.Textbox(label="Context", lines=3, interactive=True, value=starting_test_case['context'], visible=False)
 user_message = gr.Textbox(label="User Message", lines=3, interactive=True, value=starting_test_case['user_message'])
 assistant_message = gr.Textbox(label="Assistant Message", lines=3, interactive=True, visible=False, value=starting_test_case['assistant_message'])
 catalog_buttons: dict[str,dict[str,gr.Button]] = {}
-result_text = gr.Textbox(label="Result", interactive=False)
-result_certainty = gr.Number(label="Certainty", interactive=False, value='')
+result_text = gr.Textbox(label="Result", interactive=False, elem_classes=['read-only'])
+result_certainty = gr.Number(label="Certainty", interactive=False, value='', elem_classes=['read-only'])
 
 for sub_catalog_name, sub_catalog in catalog.items():
     catalog_buttons[sub_catalog_name] = {}
@@ -43,7 +43,7 @@ def on_test_case_click(link, event: gr.EventData):
         test_case_name: f'<h2>{selected_test_case["name"]}</h2>',
         criteria: selected_test_case['criteria'],
         context: selected_test_case['context'] if selected_test_case['context'] is not None else gr.update(visible=False, value=''),
-        user_message: selected_test_case['user_message'],
+        user_message: gr.update(value=selected_test_case['user_message'], elem_classes=[], interactive=True) if target_sub_catalog_name != 'Harmful content in assistant message' else gr.update(value=selected_test_case['user_message'], interactive=False, elem_classes=['read-only']),
         assistant_message: gr.update(value=selected_test_case['assistant_message'], visible=True) if selected_test_case['assistant_message'] is not None else gr.update(visible=False, value=''),
         result_text: gr.update(value=''),
         result_certainty: gr.update(value='')
@@ -53,16 +53,20 @@ def change_button_color(event: gr.EventData):
     return [gr.update(elem_classes=['catalog-button', 'selected']) if v.elem_id == event.target.elem_id else gr.update(elem_classes=['catalog-button']) for c in catalog_buttons.values() for v in c.values()]
 
 def on_submit(inputs):
-    prompt = get_prompt_from_test_case({
-        'criteria': inputs[criteria],
-        'context': inputs[context],
-        'user_message': inputs[user_message],
-        'assistant_message': inputs[assistant_message],
-    })
-    result = generate_text(prompt)
-    return result['assessment'], result['certainty']
-    # sleep(3)
-    # return 'Yes', 0.97
+    mock_model_call = os.getenv('MOCK_MODEL_CALL') == 'true'
+    if mock_model_call:
+        logger.debug('Returning mocked model result.')
+        sleep(3)
+        return 'Yes', 0.97
+    else:
+        prompt = get_prompt_from_test_case({
+            'criteria': inputs[criteria],
+            'context': inputs[context],
+            'user_message': inputs[user_message],
+            'assistant_message': inputs[assistant_message],
+        })
+        result = generate_text(prompt)
+        return result['assessment'], result['certainty']
 
 with gr.Blocks(
     title='Granite Guardian',

model.py

@@ -17,7 +17,6 @@ model = AutoModelForCausalLM.from_pretrained(
     device_map=device if use_conda else None
 )
 
-
 def generate_text(prompt):
     logger.debug('Starting evaluation...')
     logger.debug(f'Prompts content is: \n{prompt["content"]}')

styles.css

@@ -40,3 +40,8 @@
     text-align: left;
     font-weight: 600 !important;
 }
+
+
+.read-only label textarea,input {
+    cursor: not-allowed !important;
+}