Update app.py

app.py

@@ -1,126 +1,477 @@
+# app.py
+# ThinkPal – Hugging Face Space (Gradio)
+
+import os, json, uuid, re, unicodedata
+from difflib import get_close_matches, SequenceMatcher
+
 import gradio as gr
-import json
-import os
-import uuid
+
+# Optional Gemini (works if GEMINI_API_KEY set in HF Space secrets)
+try:
+    import google.generativeai as genai
+except Exception:
+    genai = None
 
 # -----------------------------
-# File for student profiles
+# Config
 # -----------------------------
-STUDENTS_FILE = "student_profiles.json"
+DATA_FILE = "student_profiles.json"
+GEMINI_MODEL = os.getenv("GEMINI_MODEL", "gemini-1.5-pro")
+GEMINI_API_KEY = os.getenv("GEMINI_API_KEY")
+
+if GEMINI_API_KEY and genai:
+    genai.configure(api_key=GEMINI_API_KEY)
+    _gemini_model = genai.GenerativeModel(GEMINI_MODEL)
+else:
+    _gemini_model = None  # fallback to local simulated responses
+
 
 # -----------------------------
-# Student data handling
+# Storage helpers (JSON)
 # -----------------------------
-def load_students():
-    """Load all student profiles from JSON file."""
-    if not os.path.exists(STUDENTS_FILE):
+def load_students() -> dict:
+    if not os.path.exists(DATA_FILE):
         return {}
-    with open(STUDENTS_FILE, "r", encoding="utf-8") as f:
+    with open(DATA_FILE, "r", encoding="utf-8") as f:
         return json.load(f)
 
-def save_students(data):
-    """Save all student profiles to JSON file."""
-    with open(STUDENTS_FILE, "w", encoding="utf-8") as f:
+def save_students(data: dict) -> None:
+    with open(DATA_FILE, "w", encoding="utf-8") as f:
         json.dump(data, f, indent=2, ensure_ascii=False)
 
-def get_student_data(student_id):
-    """Retrieve a single student profile by ID."""
+def list_student_ids() -> list:
+    return sorted(load_students().keys())
+
+def get_student(student_id: str) -> dict | None:
+    return load_students().get(student_id)
+
+def add_student(data: dict) -> str:
     students = load_students()
-    return students.get(student_id)
+    # unique random id (short)
+    new_id = f"student_{uuid.uuid4().hex[:8]}"
+    students[new_id] = data
+    save_students(students)
+    return new_id
 
-def add_student_data(data):
-    """Add a new student with unique random ID."""
+def update_student(student_id: str, updates: dict) -> str:
     students = load_students()
-    student_id = "student_" + str(uuid.uuid4())[:8]  # unique random ID
-    students[student_id] = data
+    if student_id not in students:
+        return f"❌ {student_id} not found."
+    # merge shallowly (keep structure)
+    for k, v in updates.items():
+        if v not in [None, "", []]:
+            students[student_id][k] = v
     save_students(students)
-    return student_id
+    return f"✅ {student_id} updated."
+
 
 # -----------------------------
-# Simulated AI responses (replace with Gemini later)
+# FAQs (Arabic + English) + fuzzy match
 # -----------------------------
-def get_gemini_response(prompt, student_data=None):
-    """Simulated LLM response."""
-    if not student_data:
-        return f"(Simulated Response: {prompt})"
-    return f"(Simulated AI Response for {student_data.get('personality','N/A')} personality: {prompt})"
+FAQS = {
+    "إيه هو ThinkPal؟": "ThinkPal منصة بتساعدك تعرف نفسك أكتر وتتعلم بالطريقة اللي تناسبك وكمان تديك خطة تعليمية واضحة خطوة بخطوة علشان توصل لهدفك.",
+    "هل الموقع للثانوي ولا الجامعة؟": "ThinkPal معمول بالأساس لطلاب الجامعة لكن أي طالب حابب يطور من نفسه أو يكتشف طريقه يقدر يستخدمه.",
+    "أنا ليه أجاوب على الأسئلة أول ما أدخل؟": "الأسئلة بتساعدنا نفهم طريقتك وشخصيتك علشان نعمل خطة مناسبة ليك.",
+    "الأسئلة اللي بتظهر صعبة شوية أجاوب إزاي؟": "مش امتحان ومفيش صح وغلط. جاوب بطريقتك.",
+    "الخطة التعليمية بتكون إيه بالظبط؟": "خطوات من مبتدئ لمتقدم + مصادر موثوقة وتمارين عملية.",
+    "هل المصادر كلها مجانية؟": "معظمها مجاني وفيه اختيارات مدفوعة بنرشحها أحيانًا.",
+    "هل لازم أمشي بالخطة زي ما هي؟": "الخطة مرنة وإنت اللي بتحدد السرعة.",
+    "يعني ThinkPal بديل للدروس أو الكورسات؟": "مش بديل—هو دليل/مرشد بيوضح الطريق.",
+    "هل في متابعة لتقدمي؟": "أيوة، Dashboard يوضح الإنجازات والاختبارات والتقييم والـBadges.",
+    "إيه هي Insights اللي بتظهرلي؟": "ملاحظات عملية عن نقاط القوة والتحسين بناءً على بياناتك.",
+    "هل فيه تواصل مع طلاب تانيين؟": "أيوة، فيه مجتمع داخلي ومُرشدين (Mentors).",
+    "هل المنصة بت��كز على الدراسة بس؟": "لا، كمان على تطوير الشخصية والمهارات وتحديد المستقبل.",
+    "الخصوصية آمنة؟": "أيوة، بياناتك محمية ومقفولة عليك.",
+    "لو وقفت في نص الطريق؟": "ولا يهمك—تقدر ترجع في أي وقت وتكمل من نفس مكانك.",
+
+    # English mirrors
+    "What is ThinkPal?": "ThinkPal helps you understand yourself and learn your way, with a step-by-step plan.",
+    "Is it for high school or university?": "Mainly for university students, but anyone can use it.",
+    "Why do I answer questions at the start?": "They tailor your plan to your style and goals.",
+    "Are the questions hard?": "No right/wrong; answer naturally.",
+    "What is the learning plan exactly?": "Phased from beginner to advanced, with trusted resources and practice.",
+    "Are all resources free?": "Many are free; some paid options may be suggested.",
+    "Do I have to follow the plan exactly?": "It's flexible; you control the pace.",
+    "Is ThinkPal a replacement for courses?": "It's a guide, not a replacement.",
+    "Do you track my progress?": "Yes—dashboard, tests, ratings, and badges.",
+    "What are the Insights?": "Actionable notes on strengths and areas to improve.",
+    "Can I connect with other students?": "Yes—community + mentors.",
+    "Is my data private?": "Yes—your data is protected.",
+    "What if I stop halfway?": "No problem, resume anytime."
+}
+
+FAQ_SYNONYMS = [
+    "لو وقفت", "نص الطريق", "رجوع", "resume", "stop halfway", "come back later",
+    "ايه هو", "what is thinkpal", "plan exactly", "sources free", "privacy safe",
+    "community", "mentors", "progress tracking", "insights meaning"
+]
+
+def _normalize(text: str) -> str:
+    t = text.lower().strip()
+    # remove diacritics / normalize Arabic
+    t = "".join(c for c in unicodedata.normalize("NFD", t) if unicodedata.category(c) != "Mn")
+    t = re.sub(r"[^\w\s\u0600-\u06FF]", " ", t)
+    t = re.sub(r"\s+", " ", t)
+    return t
+
+def find_faq_answer(user_input: str, cutoff: float = 0.6) -> str | None:
+    if not user_input: 
+        return None
+    ui = _normalize(user_input)
+
+    # exact/near match on known questions
+    questions = list(FAQS.keys())
+    norm_qs = {_normalize(q): q for q in questions}
+
+    # try close matches against normalized questions
+    match_keys = get_close_matches(ui, list(norm_qs.keys()), n=1, cutoff=cutoff)
+    if match_keys:
+        return FAQS[norm_qs[match_keys[0]]]
+
+    # fuzzy against synonyms -> pick best FAQ by similarity
+    candidates = questions + FAQ_SYNONYMS
+    best_q = max(candidates, key=lambda q: SequenceMatcher(None, ui, _normalize(q)).ratio())
+    if SequenceMatcher(None, ui, _normalize(best_q)).ratio() >= cutoff:
+        # map a synonym to a reasonable FAQ (heuristic)
+        # for stopping/resume
+        if any(k in ui for k in ["نص الطريق", "لو وقفت", "stop halfway", "resume"]):
+            return FAQS["لو وقفت في نص الطريق؟"]
+        # else: return closest question’s answer if it exists
+        if best_q in FAQS:
+            return FAQS[best_q]
+    return None
 
-def generate_ai_insights(student_data):
-    """Simulated AI insights."""
-    return f"(Insights: Learning style = {student_data.get('learning_style')}, Motivation = {student_data.get('motivation_level')})"
 
 # -----------------------------
-# FAQ system (Arabic + English)
+# Prompting
 # -----------------------------
-faqs = {
-    "إيه هو ThinkPal؟": "ThinkPal منصة بتساعدك تعرف نفسك أكتر وتتعلم بالطريقة اللي تناسبك...",
-    "What is ThinkPal?": "ThinkPal is a platform that helps you know yourself better...",
-    "لو وقفت في نص الطريق؟": "مفيش مشكلة، تقدر ترجع في أي وقت وتكمل من نفس المكان.",
-    "What if I stop halfway?": "No problem! You can always continue later from where you left off."
-}
+ROADMAP_QUERY = """
+Generate a personalized learning roadmap for a student with phases:
+- Beginner
+- Intermediate
+- Advanced
+- Challenge
+
+Consider: learning style, academic progress, personality, interests, goals, level,
+preferred methods, IQ, EQ, decision-making style, motivation, and study environment.
+
+Output strictly in plain text (no bold, no emojis, no AI disclaimers).
+Use clear headings and numbered lists.
+
+Sections required:
+1) Current Status
+2) Goals
+3) Recommended Resources & Activities (by Phase)
+4) Milestones (by Phase)
+"""
+
+def _compose_profile(student: dict) -> str:
+    mapping = [
+        ("learning_style", "Learning Style"),
+        ("academic_progress", "Academic Progress"),
+        ("personality", "Personality"),
+        ("interests", "Interests"),
+        ("goals", "Goals"),
+        ("level", "Level"),
+        ("preferred_methods", "Preferred Methods"),
+        ("iq_level", "IQ Level"),
+        ("eq_level", "EQ Level"),
+        ("decision_making_style", "Decision-Making Style"),
+        ("motivation_level", "Motivation Level"),
+        ("preferred_study_environment", "Preferred Study Environment"),
+        ("community_groups", "Community Groups"),
+    ]
+    parts = []
+    for key, label in mapping:
+        val = student.get(key)
+        if isinstance(val, list):
+            val = ", ".join(val)
+        if val:
+            parts.append(f"{label}: {val}")
+    return " | ".join(parts) if parts else "No student data provided."
+
+def get_gemini_response(query: str, student: dict | None = None) -> str:
+    profile = _compose_profile(student or {})
+    prompt = f"""Student Profile: {profile}
+
+Task:
+{query}
+
+Formatting:
+- Plain text only (no **, no markdown emphasis, no emojis, no disclaimers).
+- Use short headings and numbered lists where appropriate.
+- Keep it concise and practical."""
+
+    if _gemini_model:
+        try:
+            resp = _gemini_model.generate_content(prompt)
+            return getattr(resp, "text", "").strip() or "(Empty response)"
+        except Exception as e:
+            return f"(Gemini error fallback) {str(e)[:160]}"
+    # fallback (no API key)
+    return f"(Simulated) {prompt[:500]}..."
+
+def generate_ai_insights(student: dict) -> str:
+    profile = _compose_profile(student or {})
+    prompt = f"""Analyze the following student profile and provide insights:
+{profile}
+
+Requirements:
+- Plain text only (no **, no emojis, no disclaimers)
+- Bullet points for strengths and areas to improve
+- 5–8 lines max
+"""
+    if _gemini_model:
+        try:
+            resp = _gemini_model.generate_content(prompt)
+            return getattr(resp, "text", "").strip() or "(Empty response)"
+        except Exception as e:
+            return f"(Gemini error fallback) {str(e)[:160]}"
+    return f"(Simulated insights) {profile}"
 
-def find_faq_answer(user_input):
-    """Check if user_input matches any FAQ question."""
-    for q, a in faqs.items():
-        if user_input.strip().lower() in q.lower():
-            return a
-    return None
 
 # -----------------------------
-# Chat interface logic
+# Chat logic
 # -----------------------------
-def thinkpal_interface(student_id, user_input):
-    """Main chat interface logic."""
-    student_data = get_student_data(student_id)
-    roadmap_text, insights_text, chatbot_response_text = "", "", ""
-
-    if not student_data:
-        return ("❌ Student not found. Please add a profile first.", "", "")
-
-    if user_input.lower() == "roadmap":
-        roadmap_text = get_gemini_response("roadmap", student_data) or "Could not generate roadmap."
-    elif user_input.lower() == "insights":
-        insights_text = generate_ai_insights(student_data) or "Could not generate insights."
+def chat(student_id: str, message: str) -> tuple[str, str, str]:
+    """Returns (roadmap_text, insights_text, chatbot_response_text)"""
+    roadmap, insights, reply = "", "", ""
+    student = get_student(student_id)
+
+    if not student:
+        return ("❌ Student not found. Add a profile first.", "", "")
+
+    m = (message or "").strip()
+    if not m:
+        return ("", "", "Please enter a message.")
+
+    low = m.lower()
+    if low == "roadmap":
+        roadmap = get_gemini_response(ROADMAP_QUERY, student) or "Could not generate roadmap."
+    elif low == "insights":
+        insights = generate_ai_insights(student) or "Could not generate insights."
     else:
-        faq_answer = find_faq_answer(user_input)
-        chatbot_response_text = faq_answer if faq_answer else get_gemini_response(user_input, student_data) or "Sorry, could not process request."
+        faq = find_faq_answer(m, cutoff=0.58)
+        if faq:
+            reply = f"{faq}"
+        else:
+            reply = get_gemini_response(m, student) or "Sorry, I couldn't process that."
+    return roadmap, insights, reply
+
+
+# -----------------------------
+# Add / Update helpers for UI
+# -----------------------------
+ALL_FIELDS = [
+    "learning_style", "academic_progress", "personality", "interests", "goals",
+    "level", "preferred_methods", "iq_level", "eq_level",
+    "decision_making_style", "motivation_level",
+    "preferred_study_environment", "community_groups"
+]
 
-    return roadmap_text, insights_text, chatbot_response_text
+def create_student(
+    learning_style, academic_progress, personality, interests, goals, level,
+    preferred_methods, iq_level, eq_level, decision_making_style,
+    motivation_level, preferred_study_environment, community_groups
+):
+    data = {
+        "learning_style": learning_style,
+        "academic_progress": academic_progress,
+        "personality": personality,
+        "interests": interests,
+        "goals": goals,
+        "level": level,
+        "preferred_methods": [s.strip() for s in (preferred_methods or "").split(",") if s.strip()],
+        "iq_level": iq_level,
+        "eq_level": eq_level,
+        "decision_making_style": decision_making_style,
+        "motivation_level": motivation_level,
+        "preferred_study_environment": preferred_study_environment,
+        "community_groups": [s.strip() for s in (community_groups or "").split(",") if s.strip()],
+    }
+    new_id = add_student(data)
+    # return status, preview json, new dropdown choices, new default
+    return (
+        f"🎉 Created {new_id}",
+        json.dumps(data, ensure_ascii=False, indent=2),
+        gr.Dropdown.update(choices=list_student_ids(), value=new_id)
+    )
 
-def add_new_student(data_json):
-    """Add student from JSON string."""
-    try:
-        data = json.loads(data_json)
-    except json.JSONDecodeError:
-        return "❌ Invalid JSON. Please check your input."
+def load_student_to_form(student_id: str):
+    s = get_student(student_id)
+    if not s:
+        # return empties
+        return [""] * 13
+    return [
+        s.get("learning_style", ""),
+        s.get("academic_progress", ""),
+        s.get("personality", ""),
+        s.get("interests", ""),
+        s.get("goals", ""),
+        s.get("level", ""),
+        ", ".join(s.get("preferred_methods", [])),
+        s.get("iq_level", ""),
+        s.get("eq_level", ""),
+        s.get("decision_making_style", ""),
+        s.get("motivation_level", ""),
+        s.get("preferred_study_environment", ""),
+        ", ".join(s.get("community_groups", [])),
+    ]
+
+def apply_update(
+    student_id,
+    learning_style, academic_progress, personality, interests, goals, level,
+    preferred_methods, iq_level, eq_level, decision_making_style,
+    motivation_level, preferred_study_environment, community_groups
+):
+    updates = {
+        "learning_style": learning_style,
+        "academic_progress": academic_progress,
+        "personality": personality,
+        "interests": interests,
+        "goals": goals,
+        "level": level,
+        "preferred_methods": [s.strip() for s in (preferred_methods or "").split(",") if s.strip()],
+        "iq_level": iq_level,
+        "eq_level": eq_level,
+        "decision_making_style": decision_making_style,
+        "motivation_level": motivation_level,
+        "preferred_study_environment": preferred_study_environment,
+        "community_groups": [s.strip() for s in (community_groups or "").split(",") if s.strip()],
+    }
+    msg = update_student(student_id, updates)
+    preview = json.dumps(get_student(student_id) or {}, ensure_ascii=False, indent=2)
+    return msg, preview
 
-    student_id = add_student_data(data)
-    return f"✅ Student added with ID: {student_id}"
 
 # -----------------------------
-# Gradio UI
+# UI
 # -----------------------------
-with gr.Blocks(theme=gr.themes.Soft()) as demo:
-    gr.Markdown("## 🎓 ThinkPal - Personalized Learning Assistant")
+THEME = gr.themes.Soft().set(
+    button_primary_background="linear-gradient(90deg, #6C63FF, #00BCD4)",
+    button_primary_text_color="#ffffff",
+    block_background="#0f1220",
+    block_title_text_color="#e8eaf6",
+    body_background_fill="#0b0e1a",
+    body_text_color="#e0e0e0",
+    input_background_fill="#14182b",
+    input_border_color="#2a2f4a",
+    input_text_color="#e0e0e0",
+)
+
+with gr.Blocks(theme=THEME, css="""
+#header {padding: 24px 0 8px;}
+#header h1 {margin:0; font-size: 2rem;}
+.small {opacity:.85; font-size:.9rem}
+.card {border:1px solid #2a2f4a; border-radius:12px; padding:12px;}
+""") as demo:
+    gr.HTML("""
+    <div id="header">
+      <h1>🎓 ThinkPal – Personalized Learning Assistant</h1>
+      <div class="small">Roadmaps, insights, and a friendly FAQ — tailored to each student.</div>
+    </div>
+    """)
 
     with gr.Tab("💬 Chat"):
         with gr.Row():
-            student_id_input = gr.Textbox(label="Enter Student ID", placeholder="student_1")
-            user_input = gr.Textbox(label="Your Question", placeholder="Type roadmap, insights, or FAQ...")
-        submit_btn = gr.Button("Ask")
-        roadmap_output = gr.Textbox(label="Roadmap", lines=8)
-        insights_output = gr.Textbox(label="Insights", lines=6)
-        chatbot_output = gr.Textbox(label="Chatbot Response", lines=4)
-        submit_btn.click(thinkpal_interface, [student_id_input, user_input], [roadmap_output, insights_output, chatbot_output])
+            student_dd = gr.Dropdown(
+                label="Select Student",
+                choices=list_student_ids() or [],
+                value=(list_student_ids() or [None])[0] if list_student_ids() else None
+            )
+            user_msg = gr.Textbox(
+                label="Your Message",
+                placeholder="Type: roadmap, insights, or any question (Arabic/English)",
+            )
+        ask_btn = gr.Button("Ask", variant="primary")
+        with gr.Row():
+            roadmap_out = gr.Textbox(label="Roadmap", lines=14, elem_classes=["card"])
+            insights_out = gr.Textbox(label="Insights", lines=10, elem_classes=["card"])
+        chatbot_out = gr.Textbox(label="Response", lines=6, elem_classes=["card"])
+
+        ask_btn.click(
+            fn=chat,
+            inputs=[student_dd, user_msg],
+            outputs=[roadmap_out, insights_out, chatbot_out]
+        )
 
     with gr.Tab("➕ Add Student"):
-        gr.Markdown("Paste student profile data as JSON to add a new student.")
-        new_student_data = gr.Textbox(label="Student Data (JSON)", lines=10,
-                                      placeholder='{"learning_style": "visual", "goals": "improve math"}')
-        add_btn = gr.Button("Add Student")
-        add_output = gr.Textbox(label="Result")
-        add_btn.click(add_new_student, inputs=[new_student_data], outputs=[add_output])
-
-# For Hugging Face Spaces
+        gr.Markdown("Fill the form. Lists accept comma-separated values (e.g., `online videos, interactive exercises`).")
+        with gr.Row():
+            learning_style = gr.Textbox(label="Learning Style")
+            academic_progress = gr.Textbox(label="Academic Progress")
+            personality = gr.Textbox(label="Personality")
+        with gr.Row():
+            interests = gr.Textbox(label="Interests")
+            goals = gr.Textbox(label="Goals")
+            level = gr.Textbox(label="Level")
+        preferred_methods = gr.Textbox(label="Preferred Methods (comma-separated)")
+        with gr.Row():
+            iq_level = gr.Textbox(label="IQ Level")
+            eq_level = gr.Textbox(label="EQ Level")
+            decision_style = gr.Textbox(label="Decision-Making Style")
+        with gr.Row():
+            motivation_level = gr.Textbox(label="Motivation Level")
+            study_env = gr.Textbox(label="Preferred Study Environment")
+            community_groups = gr.Textbox(label="Community Groups (comma-separated)")
+
+        create_btn = gr.Button("Create Profile", variant="primary")
+        status_new = gr.Textbox(label="Status", interactive=False)
+        preview_new = gr.Textbox(label="Saved Profile Preview", lines=10)
+
+        # also update the chat dropdown after create
+        create_btn.click(
+            fn=create_student,
+            inputs=[learning_style, academic_progress, personality, interests, goals, level,
+                    preferred_methods, iq_level, eq_level, decision_style,
+                    motivation_level, study_env, community_groups],
+            outputs=[status_new, preview_new, student_dd]
+        )
+
+    with gr.Tab("✏️ Update Student"):
+        gr.Markdown("Pick a student, load their data, edit fields you want, then save.")
+        target_id = gr.Dropdown(label="Student", choices=list_student_ids() or [])
+        load_btn = gr.Button("Load Profile")
+        with gr.Row():
+            u_learning_style = gr.Textbox(label="Learning Style")
+            u_academic_progress = gr.Textbox(label="Academic Progress")
+            u_personality = gr.Textbox(label="Personality")
+        with gr.Row():
+            u_interests = gr.Textbox(label="Interests")
+            u_goals = gr.Textbox(label="Goals")
+            u_level = gr.Textbox(label="Level")
+        u_preferred_methods = gr.Textbox(label="Preferred Methods (comma-separated)")
+        with gr.Row():
+            u_iq_level = gr.Textbox(label="IQ Level")
+            u_eq_level = gr.Textbox(label="EQ Level")
+            u_decision_style = gr.Textbox(label="Decision-Making Style")
+        with gr.Row():
+            u_motivation_level = gr.Textbox(label="Motivation Level")
+            u_study_env = gr.Textbox(label="Preferred Study Environment")
+            u_community_groups = gr.Textbox(label="Community Groups (comma-separated)")
+
+        save_btn = gr.Button("Save Changes", variant="primary")
+        status_upd = gr.Textbox(label="Status", interactive=False)
+        preview_upd = gr.Textbox(label="Updated Profile Preview", lines=10)
+
+        load_btn.click(
+            fn=load_student_to_form,
+            inputs=[target_id],
+            outputs=[u_learning_style, u_academic_progress, u_personality,
+                     u_interests, u_goals, u_level, u_preferred_methods,
+                     u_iq_level, u_eq_level, u_decision_style, u_motivation_level,
+                     u_study_env, u_community_groups]
+        )
+
+        save_btn.click(
+            fn=apply_update,
+            inputs=[target_id, u_learning_style, u_academic_progress, u_personality,
+                    u_interests, u_goals, u_level, u_preferred_methods,
+                    u_iq_level, u_eq_level, u_decision_style, u_motivation_level,
+                    u_study_env, u_community_groups],
+            outputs=[status_upd, preview_upd]
+        )
+
 if __name__ == "__main__":
-    demo.launch()
+    # Space-friendly: server will bind host/port automatically
+    demo.launch()