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Runtime error
Runtime error
added more settings to patients
Browse files- data/patients.json +29 -34
- main.py +62 -21
data/patients.json
CHANGED
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@@ -1,50 +1,45 @@
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[
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"presentingComplaint": "Abdominal pain",
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"matchedCondition": "Gastritis",
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"name": "Emma Thompson",
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"age": 28,
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"characterSummary": "Spirited graphic designer, curious, empathetic",
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"levelOfUnderstanding": 2,
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"rangeOfMedicalUnderstanding":
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"communicative": 5,
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"difficulty": "easy",
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"mood": "pain"
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"presentingComplaint": "Chest pain",
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"matchedCondition": "
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"name": "James Wilson",
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"age": 45,
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"characterSummary": "Seasoned entrepreneur, strategic, mentoring spirit",
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"levelOfUnderstanding":
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"rangeOfMedicalUnderstanding":
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"presentingComplaint": "Headache",
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"matchedCondition": "
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"name": "Olivia Patel",
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"age": 52,
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"characterSummary": "Compassionate nurse, nurturing, animal lover",
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"levelOfUnderstanding": 8,
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"rangeOfMedicalUnderstanding":
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"
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"
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"levelOfUnderstanding": 2,
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"rangeOfMedicalUnderstanding": "Limited understanding of medical issues"
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},
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{
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"presentingComplaint": "Fever",
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"matchedCondition": "Influenza",
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"name": "Ava Mitchell",
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"age": 19,
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"characterSummary": "Ambitious computer science student, talented pianist",
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"levelOfUnderstanding": 3,
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"rangeOfMedicalUnderstanding": "Familiar with basic medical concepts"
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}
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]
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[
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{
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"patientId": 1,
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"presentingComplaint": "Abdominal pain",
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"matchedCondition": "Gastritis",
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"name": "Emma Thompson",
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"age": 28,
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"characterSummary": "Spirited graphic designer, curious, empathetic, smoker, takes psychedelics and smokes marijuana, drinks alcohol",
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"levelOfUnderstanding": 2,
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"rangeOfMedicalUnderstanding": 2,
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"communicative": 5,
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"difficulty": "easy",
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"mood": "pain",
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"familyHistory": "none known"
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},
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{
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"patientId": 2,
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"presentingComplaint": "Chest pain",
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"matchedCondition": "myocardial infarction",
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"name": "James Wilson",
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"age": 45,
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"characterSummary": "Seasoned entrepreneur, strategic, mentoring spirit, ultramarathon runner, non smoker, non drinker",
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"levelOfUnderstanding": 8,
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"rangeOfMedicalUnderstanding": 4,
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"communicative": 3,
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"difficulty": "hard",
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"mood": "severe pain",
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"familyHistory": "Father died of heart attack at 48, uncle died of heart attack at 54."
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},
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{
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"patientId": 3,
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"presentingComplaint": "Headache",
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"matchedCondition": "subarachnoid haemorrhage",
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"name": "Olivia Patel",
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"age": 52,
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"characterSummary": "Compassionate nurse, nurturing, animal lover",
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"levelOfUnderstanding": 8,
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"rangeOfMedicalUnderstanding": 9,
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"communicative": 3,
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"difficulty": "hard",
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"mood": "pain but can talk easily",
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"familyHistory": "none known"
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}
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]
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main.py
CHANGED
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@@ -60,6 +60,7 @@ def message_handler(
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if chat is None:
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# in the queue we will store our streamed tokens
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queue = Queue()
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# let's create our default chat
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chat = ChatOpenAI(
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model_name=MODELS_NAMES[0],
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@@ -71,7 +72,6 @@ def message_handler(
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# hacky way to get the queue back
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queue = chat.callbacks[0].queue
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job_done = object()
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-
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logging.info("asking question to GPT")
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# let's add the messages to our stuff
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messages.append(HumanMessage(content=f"Doctor:{message}"))
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@@ -104,8 +104,9 @@ def message_handler(
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return chat, "", chatbot_messages, messages
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def on_clear_click() -> Tuple[str, List, List]:
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def on_done_click(
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@@ -115,10 +116,16 @@ def on_done_click(
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add_chat_by_uid(
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client, Chat(patient=patient, messages=chatbot_messages), user["uid"]
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)
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return on_clear_click()
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-
def on_apply_settings_click(
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logging.info(
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f"Applying settings: model_name={model_name}, temperature={temperature}"
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)
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@@ -130,7 +137,11 @@ def on_apply_settings_click(model_name: str, temperature: float):
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)
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# don't forget to nuke our queue
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chat.callbacks[0].queue.empty()
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def on_drop_down_change(selected_item, messages):
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@@ -138,7 +149,15 @@ def on_drop_down_change(selected_item, messages):
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patient = patiens[index]
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messages = [system_message_prompt.format(patient=patient)]
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print(f"You selected: {selected_item}", index)
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def on_demo_load(url_params, request: gr.Request):
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@@ -192,12 +211,12 @@ with gr.Blocks(
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[chat, message, chatbot, messages],
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[chat, message, chatbot, messages],
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)
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-
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with gr.Row():
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with gr.Column():
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js = "(x) => confirm('Press a button!')"
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done = gr.Button("Done",
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done.click(
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on_done_click,
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[chatbot, patient, user],
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@@ -215,12 +234,22 @@ with gr.Blocks(
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label="temperature",
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interactive=True,
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)
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)
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with gr.Column():
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patients_names = [el["name"] for el in patiens]
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dropdown = gr.Dropdown(
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@@ -229,15 +258,25 @@ with gr.Blocks(
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interactive=True,
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label="Patient",
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)
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-
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patient_card = gr.JSON(patient.value, visible=True, label="Patient card")
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dropdown.change(
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fn=on_drop_down_change,
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inputs=[dropdown, messages],
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outputs=[
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)
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-
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# app = FastAPI()
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# os.makedirs("static", exist_ok=True)
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# app.mount("/static", StaticFiles(directory="static"), name="static")
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# async def home(request: Request):
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# return templates.TemplateResponse(
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# "home.html", {"request": request, "videos": []})
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def auth_handler(username: str, password: str) -> bool:
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if password != os.environ["GRADIO_PASSWORD"]:
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return False
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-
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return True
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demo.queue()
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demo.launch(auth=auth_handler)
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if chat is None:
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# in the queue we will store our streamed tokens
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queue = Queue()
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print("Creating new chat")
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# let's create our default chat
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chat = ChatOpenAI(
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model_name=MODELS_NAMES[0],
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# hacky way to get the queue back
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queue = chat.callbacks[0].queue
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job_done = object()
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logging.info("asking question to GPT")
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# let's add the messages to our stuff
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messages.append(HumanMessage(content=f"Doctor:{message}"))
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return chat, "", chatbot_messages, messages
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def on_clear_click(patient: str) -> Tuple[str, List, List]:
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messages = [system_message_prompt.format(patient=patient)]
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return "", [], messages
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def on_done_click(
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add_chat_by_uid(
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client, Chat(patient=patient, messages=chatbot_messages), user["uid"]
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)
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return on_clear_click(patient)
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def on_apply_settings_click(
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model_name: str,
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temperature: float,
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patient: str,
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difficulty: str,
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communicative: str,
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):
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logging.info(
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f"Applying settings: model_name={model_name}, temperature={temperature}"
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)
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)
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# don't forget to nuke our queue
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chat.callbacks[0].queue.empty()
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patient["difficulty"] = difficulty
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patient["communicative"] = communicative
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print("patient", patient)
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message, chatbot, messages = on_clear_click(patient)
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return chat, message, chatbot, messages, patient
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def on_drop_down_change(selected_item, messages):
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patient = patiens[index]
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messages = [system_message_prompt.format(patient=patient)]
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print(f"You selected: {selected_item}", index)
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print(f"on_drop_down_change {patient}")
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return (
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patient,
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patient,
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[],
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messages,
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patient["difficulty"],
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patient["communicative"],
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)
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def on_demo_load(url_params, request: gr.Request):
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[chat, message, chatbot, messages],
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[chat, message, chatbot, messages],
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)
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with gr.Row():
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with gr.Column():
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js = "(x) => confirm('Press a button!')"
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done = gr.Button("Done", variant="stop")
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done.click(
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on_done_click,
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[chatbot, patient, user],
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label="temperature",
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interactive=True,
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)
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difficulty = gr.Dropdown(
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choices=["easy", "medium", "hard"],
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value=patient.value["difficulty"],
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label="difficulty",
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interactive=True,
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)
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communicative = gr.Slider(
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minimum=0,
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maximum=5,
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value=patient.value["communicative"],
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step=1,
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label="communicative",
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interactive=True,
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)
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apply_settings = gr.Button("Apply")
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with gr.Column():
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patients_names = [el["name"] for el in patiens]
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dropdown = gr.Dropdown(
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interactive=True,
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label="Patient",
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)
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patient_card = gr.JSON(patient.value, visible=True, label="Patient card")
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apply_settings.click(
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on_apply_settings_click,
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[model_name, temperature, patient, difficulty, communicative],
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[chat, message, chatbot, messages, patient_card],
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)
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dropdown.change(
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fn=on_drop_down_change,
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inputs=[dropdown, messages],
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outputs=[
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patient_card,
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patient,
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chatbot,
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messages,
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difficulty,
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communicative,
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],
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)
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# app = FastAPI()
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# os.makedirs("static", exist_ok=True)
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# app.mount("/static", StaticFiles(directory="static"), name="static")
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# async def home(request: Request):
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# return templates.TemplateResponse(
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# "home.html", {"request": request, "videos": []})
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def auth_handler(username: str, password: str) -> bool:
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if password != os.environ["GRADIO_PASSWORD"]:
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return False
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return True
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demo.queue()
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demo.launch(auth=auth_handler)
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# gradio_app = gr.routes.App.create_app(demo)
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# app.mount("/gradio", gradio_app)
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