Create app.py

app.py

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+"""
+P3 Myeloma - AI Follow-up Chatbot
+==================================
+Takes a participant's answers to the 16 Shared Decision Making questions
+and runs an adaptive follow-up conversation using Google's Gemini API.
+
+Deploy on Hugging Face Spaces (SDK: Gradio).
+Set your Gemini key as a Space Secret named GEMINI_API_KEY,
+or paste it in the UI field at runtime.
+"""
+
+import os
+import json
+from google import genai
+from google.genai import types
+import gradio as gr
+
+# ----------------------------------------------------------------------
+# The 16 profile questions (verbatim from the intake form)
+# ----------------------------------------------------------------------
+QUESTIONS = [
+    "I prefer my healthcare team (hematologist, nurse practitioner, or physician assistant), and I collaborate in deciding which treatment for relapsed or refractory myeloma is best for me",
+    "It is important for me to understand my treatment options for relapsed or refractory myeloma",
+    "I trust my healthcare team very much, that's why I leave it up to them to recommend therapy that is right for me",
+    "I live alone with no caregiver",
+    "I have strong social support and a network that can help with my treatment appointments",
+    "I will do whatever it takes to so I can be cured, cancer-free, kill all the myeloma, or at least be in remission and live a long life",
+    "I would like to take an aggressive approach to treat my myeloma",
+    "I am willing to endure as many side effects as possible to control my myeloma",
+    "I prefer to receive treatment in an outpatient setting",
+    "I prefer to take medications at home",
+    "I prefer to take the least possible amount of pills to control my cancer",
+    "Quality of life is more important to me than quantity of life",
+    "Clinical drug trial participation is of interest to me",
+    "My out-of-pocket cost of treatment is important to me",
+    "I prefer to continue an active lifestyle during my myeloma treatment",
+    "I worry about how my treatment will affect future treatment options",
+]
+
+# Short tags used for the summary view
+QUESTION_TAGS = [
+    "Shared decision-making",
+    "Wants to understand options",
+    "Defers to care team",
+    "Lives alone / no caregiver",
+    "Strong social support",
+    "Goal: cure / long life",
+    "Wants aggressive approach",
+    "Tolerant of side effects",
+    "Prefers outpatient",
+    "Prefers meds at home",
+    "Prefers fewer pills",
+    "Quality over quantity",
+    "Interested in clinical trials",
+    "Out-of-pocket cost matters",
+    "Wants active lifestyle",
+    "Worries about future options",
+]
+
+MODEL = "gemini-2.5-flash"
+MAX_FOLLOWUPS = 8  # cap the adaptive conversation
+
+# ----------------------------------------------------------------------
+# Prompt building
+# ----------------------------------------------------------------------
+def build_profile_text(answers):
+    """answers: list of 'Yes'/'No' aligned to QUESTIONS."""
+    lines = []
+    for q, tag, a in zip(QUESTIONS, QUESTION_TAGS, answers):
+        lines.append(f"- [{a.upper()}] ({tag}) {q}")
+    return "\n".join(lines)
+
+
+def detect_tensions(answers):
+    """Flag notable patterns/contradictions worth probing. Pure logic, no API."""
+    a = {i: (answers[i].strip().lower() == "yes") for i in range(len(answers))}
+    flags = []
+
+    # Aggressive cure-seeking vs quality-over-quantity
+    if (a.get(5) or a.get(6) or a.get(7)) and a.get(11):
+        flags.append("Wants an aggressive/curative approach but also values quality of life over quantity. Worth clarifying how they weigh these when they conflict.")
+    # Willing to endure side effects vs wants active lifestyle / quality of life
+    if a.get(7) and (a.get(14) or a.get(11)):
+        flags.append("Willing to endure many side effects, yet wants to stay active / prioritizes quality of life. Probe acceptable side-effect threshold.")
+    # Lives alone AND no strong social support -> logistics risk
+    if a.get(3) and not a.get(4):
+        flags.append("Lives alone with no caregiver and limited social support. Treatment logistics and safety monitoring need exploration.")
+    # Lives alone but prefers home meds -> safety of self-administration
+    if a.get(3) and a.get(9):
+        flags.append("Lives alone but prefers taking medications at home. Explore support for safe self-administration and side-effect monitoring.")
+    # Defers fully to team but also wants to collaborate / understand options
+    if a.get(2) and (a.get(0) or a.get(1)):
+        flags.append("Says they leave decisions to the care team, yet also wants to collaborate / understand options. Clarify how involved they actually want to be.")
+    # Cost matters + trial interest (trials can offset cost) — opportunity, not conflict
+    if a.get(13) and a.get(12):
+        flags.append("Cost matters and they're open to clinical trials — trials may reduce drug cost; worth surfacing.")
+    # Fewer pills preference but aggressive
+    if a.get(10) and (a.get(6) or a.get(7)):
+        flags.append("Prefers the fewest pills possible but wants an aggressive approach. Explore tolerance for treatment intensity vs convenience.")
+    # Outpatient + lives alone
+    if a.get(8) and a.get(3):
+        flags.append("Prefers outpatient treatment but lives alone — explore transport and post-visit support.")
+    return flags
+
+
+def system_instruction():
+    return (
+        "You are a warm, plain-spoken health navigator helping a multiple myeloma patient "
+        "(relapsed or refractory) prepare for a shared decision-making conversation with their "
+        "care team. You are NOT a doctor and you never give medical advice, diagnoses, dosing, or "
+        "treatment recommendations. Your job is ONLY to ask thoughtful follow-up questions that help "
+        "the patient clarify their own values, priorities, constraints, and concerns.\n\n"
+        "RULES:\n"
+        "1. Ask exactly ONE question per turn. Keep it to 1-3 sentences, conversational, jargon-free.\n"
+        "2. Base each question on the patient's profile and their previous answers. Prioritize the "
+        "FLAGGED TENSIONS provided — gently explore apparent contradictions without judgment.\n"
+        "3. Do not repeat questions already asked. Build on what they say.\n"
+        "4. Never recommend or rank treatments. If the patient asks for medical advice, kindly "
+        "redirect them to discuss it with their care team, then continue with a follow-up question.\n"
+        "5. Tone: empathetic, respectful, never alarming.\n"
+        "6. When you judge that you have enough to summarize their priorities (or after several "
+        "exchanges), instead of asking another question, output a final summary. Begin that final "
+        "message with the exact token <<SUMMARY>> on its own line, then 4-7 short bullet points "
+        "capturing the patient's key priorities, constraints, and questions to raise with their care team."
+    )
+
+
+# ----------------------------------------------------------------------
+# Gemini client helpers
+# ----------------------------------------------------------------------
+def get_client(user_key):
+    key = (user_key or "").strip() or os.environ.get("GEMINI_API_KEY", "").strip()
+    if not key:
+        return None, "No API key found. Paste your Gemini API key above, or set GEMINI_API_KEY as a Space secret."
+    try:
+        client = genai.Client(api_key=key)
+        return client, None
+    except Exception as e:
+        return None, f"Could not initialize Gemini client: {e}"
+
+
+def to_gemini_contents(history):
+    """history: list of {'role': 'user'|'assistant', 'content': str}
+    Returns Gemini Content list (assistant -> 'model')."""
+    contents = []
+    for m in history:
+        role = "model" if m["role"] == "assistant" else "user"
+        contents.append(types.Content(role=role, parts=[types.Part(text=m["content"])]))
+    return contents
+
+
+def gemini_reply(client, convo, n_followups):
+    """convo: internal history list. Returns assistant text."""
+    contents = to_gemini_contents(convo)
+    # Nudge toward summarizing as we approach the cap
+    extra = ""
+    if n_followups >= MAX_FOLLOWUPS - 1:
+        extra = "\n\nYou have asked enough questions. Provide the final <<SUMMARY>> now."
+    cfg = types.GenerateContentConfig(
+        system_instruction=system_instruction() + extra,
+        temperature=0.7,
+        max_output_tokens=600,
+    )
+    resp = client.models.generate_content(model=MODEL, contents=contents, config=cfg)
+    return (resp.text or "").strip()
+
+
+# ----------------------------------------------------------------------
+# Gradio app
+# ----------------------------------------------------------------------
+def start_chat(api_key, *radio_values):
+    answers = [v if v in ("Yes", "No") else None for v in radio_values]
+    if any(v is None for v in answers):
+        missing = [i + 1 for i, v in enumerate(answers) if v is None]
+        gr.Warning(f"Please answer all 16 questions. Missing: {missing}")
+        return (gr.update(), [], [], 0, gr.update(visible=True), gr.update(visible=False))
+
+    client, err = get_client(api_key)
+    if err:
+        gr.Warning(err)
+        return (gr.update(), [], [], 0, gr.update(visible=True), gr.update(visible=False))
+
+    profile = build_profile_text(answers)
+    flags = detect_tensions(answers)
+    flag_text = "\n".join(f"- {f}" for f in flags) if flags else "- (No obvious contradictions; explore their highest-stakes priorities.)"
+
+    kickoff = (
+        "Here is the patient's completed profile (16 yes/no answers):\n\n"
+        f"{profile}\n\n"
+        "FLAGGED TENSIONS / PRIORITIES TO EXPLORE:\n"
+        f"{flag_text}\n\n"
+        "Begin the follow-up conversation. Warmly acknowledge in one short sentence, then ask your "
+        "FIRST single follow-up question."
+    )
+
+    convo = [{"role": "user", "content": kickoff}]
+    try:
+        reply = gemini_reply(client, convo, 0)
+    except Exception as e:
+        gr.Warning(f"Gemini error: {e}")
+        return (gr.update(), [], [], 0, gr.update(visible=True), gr.update(visible=False))
+
+    convo.append({"role": "assistant", "content": reply})
+    chat_display = [{"role": "assistant", "content": reply}]
+    return (
+        chat_display,          # chatbot
+        chat_display,          # display_state
+        convo,                 # convo_state
+        1,                     # followup count
+        gr.update(visible=False),  # hide intake
+        gr.update(visible=True),   # show chat
+    )
+
+
+def respond(user_msg, chat_display, convo, n_followups, api_key):
+    user_msg = (user_msg or "").strip()
+    if not user_msg:
+        return chat_display, chat_display, convo, n_followups, ""
+
+    client, err = get_client(api_key)
+    if err:
+        gr.Warning(err)
+        return chat_display, chat_display, convo, n_followups, user_msg
+
+    convo = convo + [{"role": "user", "content": user_msg}]
+    chat_display = chat_display + [{"role": "user", "content": user_msg}]
+
+    try:
+        reply = gemini_reply(client, convo, n_followups)
+    except Exception as e:
+        gr.Warning(f"Gemini error: {e}")
+        return chat_display, chat_display, convo, n_followups, ""
+
+    convo = convo + [{"role": "assistant", "content": reply}]
+
+    display_reply = reply
+    if "<<SUMMARY>>" in reply:
+        display_reply = reply.replace("<<SUMMARY>>", "").strip()
+        display_reply = "**Your Priorities Summary**\n\n" + display_reply + (
+            "\n\n_This summary reflects what you shared. Please bring it to your care team. "
+            "It is not medical advice._"
+        )
+
+    chat_display = chat_display + [{"role": "assistant", "content": display_reply}]
+    return chat_display, chat_display, convo, n_followups + 1, ""
+
+
+def reset_all():
+    radio_resets = [gr.update(value=None) for _ in QUESTIONS]
+    return (
+        [],   # chatbot
+        [],   # display_state
+        [],   # convo_state
+        0,    # followups
+        gr.update(visible=True),   # intake
+        gr.update(visible=False),  # chat
+        *radio_resets,
+    )
+
+
+CSS = """
+.q-card {border:1px solid #e5e5e5; border-radius:12px; padding:14px 16px; margin-bottom:10px; background:#fff;}
+#title {color:#7a0c2e; font-weight:700;}
+footer {visibility:hidden;}
+"""
+
+with gr.Blocks(title="P3 Myeloma Follow-up Chatbot", css=CSS,
+               theme=gr.themes.Soft(primary_hue="red")) as demo:
+    gr.Markdown("# <span id='title'>AI-Enhanced Personalized Patient Profile (P3) Myeloma</span>")
+    gr.Markdown("### Follow-up Questions for Shared Decision Making")
+
+    with gr.Accordion("Gemini API Key (optional if set as Space secret GEMINI_API_KEY)", open=False):
+        api_key = gr.Textbox(label="GEMINI_API_KEY", type="password",
+                             placeholder="Paste your key here, or leave blank to use the Space secret")
+
+    convo_state = gr.State([])
+    display_state = gr.State([])
+    followups = gr.State(0)
+
+    # ---- Intake panel ----
+    with gr.Group(visible=True) as intake_panel:
+        gr.Markdown("**Answer all 16 questions, then click Start Follow-up.**")
+        radios = []
+        for i, q in enumerate(QUESTIONS):
+            with gr.Row(elem_classes="q-card"):
+                r = gr.Radio(["Yes", "No"], label=f"{i+1}. {q}")
+                radios.append(r)
+        start_btn = gr.Button("Start Follow-up", variant="primary")
+
+    # ---- Chat panel ----
+    with gr.Group(visible=False) as chat_panel:
+        chatbot = gr.Chatbot(label="Follow-up Conversation", type="messages", height=460)
+        with gr.Row():
+            msg = gr.Textbox(placeholder="Type your answer...", show_label=False, scale=8)
+            send_btn = gr.Button("Send", variant="primary", scale=1)
+        restart_btn = gr.Button("Start Over")
+
+    start_btn.click(
+        start_chat,
+        inputs=[api_key] + radios,
+        outputs=[chatbot, display_state, convo_state, followups, intake_panel, chat_panel],
+    )
+
+    send_btn.click(
+        respond,
+        inputs=[msg, display_state, convo_state, followups, api_key],
+        outputs=[chatbot, display_state, convo_state, followups, msg],
+    )
+    msg.submit(
+        respond,
+        inputs=[msg, display_state, convo_state, followups, api_key],
+        outputs=[chatbot, display_state, convo_state, followups, msg],
+    )
+
+    restart_btn.click(
+        reset_all,
+        inputs=None,
+        outputs=[chatbot, display_state, convo_state, followups, intake_panel, chat_panel] + radios,
+    )
+
+if __name__ == "__main__":
+    demo.launch()