Update app.py

app.py

@@ -1,13 +1,15 @@
+# app.py
 import gradio as gr
+import json
 
-# ------------------------------
-# Data (minimal, in-file)
-# ------------------------------
-RUBRIC_WEIGHTS = {
-    "grit": 0.18, "risk": 0.12, "time_per_week": 0.14, "runway_months": 0.16,
-    "customer_access": 0.12, "validation_skill": 0.10, "ops_skill": 0.08, "finance_skill": 0.10
-}
+SYSTEM_PROMPT = (
+    "You are a friendly tutor for Entrepreneurial Readiness and Paths. "
+    "Be practical and concise. If the user ran the assessment or path explorer, use that info."
+)
 
+# =========================
+# Domains (unchanged)
+# =========================
 PATHS = {
     "tech": [
         {"path":"Micro-SaaS","difficulty":3,"benefits":"High margins, scalable, global reach",
@@ -55,56 +57,116 @@ PATHS = {
     ]
 }
 
-SYSTEM_PROMPT = (
-    "You are a friendly tutor for Entrepreneurial Readiness and Paths. "
-    "Be practical and concise. If the user ran the assessment or path explorer, use that info."
-)
+# =========================
+# Readiness factors (your list)
+# =========================
+WEIGHTS = {
+    "savings": 0.10,
+    "income": 0.08,
+    "bills": 0.08,                 # inverse
+    "entertainment": 0.04,         # inverse
+    "assets": 0.06,
+    "sales_skills": 0.14,
+    "confidence": 0.10,
+    "dependents": 0.06,            # inverse
+    "age": 0.04,                   # very small, symmetric
+    "idea_level": 0.10,
+    "entrepreneurial_experience": 0.10,
+    "risk": 0.10,
+}
+
+CAP = {
+    "savings": 20000,              # USD
+    "income": 8000,                # USD / month
+    "bills": 5000,                 # USD / month (inverse)
+    "entertainment": 1000,         # USD / month (inverse)
+    "assets": 100000,              # USD (liquid-ish)
+    "dependents_max": 3,           # 0..3+ (inverse)
+}
+
+IDEA_LEVEL_MAP = {
+    "none": 0.0,
+    "exploring": 0.25,
+    "validated_problem": 0.5,
+    "prototype": 0.75,
+    "mvp_with_users": 1.0,
+}
+
+def _nz(x, default=0.0):
+    try:
+        return float(x) if x is not None else float(default)
+    except Exception:
+        return float(default)
+
+def _clamp01(v): return max(0.0, min(1.0, float(v)))
+def _direct_norm(v, cap):   return _clamp01(_nz(v) / float(cap))
+def _inverse_norm(v, cap):  return 1.0 - _direct_norm(v, cap)
+
+def _age_norm(age):
+    """Mild symmetric curve centered ~35; tiny effect (≤0.2)."""
+    a = _nz(age, 35)
+    penalty = min(abs(a - 35.0) / 35.0, 1.0) * 0.2
+    return _clamp01(1.0 - penalty)
+
+def _dependents_norm(dep):
+    d = max(0, int(_nz(dep, 0)))
+    base = 1.0 - min(d / float(CAP["dependents_max"]), 1.0)
+    return _clamp01(base)
 
 # ------------------------------
-# Readiness scoring (0–100)
+# Readiness scoring (0–100) using your factors
 # ------------------------------
 def compute_readiness(payload):
-    # normalize
-    grit = payload["grit"]/10
-    risk = payload["risk"]/10
-    time_norm = min(payload["time_per_week"], 40)/40
-    runway_norm = min(payload["runway_months"], 24)/24
-    customer_access = payload["customer_access"]/10
-    validation_skill = payload["validation_skill"]/10
-    ops_skill = payload["ops_skill"]/10
-    finance_skill = payload["finance_skill"]/10
-
-    score = 100 * (
-        RUBRIC_WEIGHTS["grit"]*grit +
-        RUBRIC_WEIGHTS["risk"]*risk +
-        RUBRIC_WEIGHTS["time_per_week"]*time_norm +
-        RUBRIC_WEIGHTS["runway_months"]*runway_norm +
-        RUBRIC_WEIGHTS["customer_access"]*customer_access +
-        RUBRIC_WEIGHTS["validation_skill"]*validation_skill +
-        RUBRIC_WEIGHTS["ops_skill"]*ops_skill +
-        RUBRIC_WEIGHTS["finance_skill"]*finance_skill
-    )
-    score = int(round(score))
+    n = {
+        "savings": _direct_norm(payload["savings"], CAP["savings"]),
+        "income": _direct_norm(payload["income"], CAP["income"]),
+        "bills": _inverse_norm(payload["bills"], CAP["bills"]),
+        "entertainment": _inverse_norm(payload["entertainment"], CAP["entertainment"]),
+        "assets": _direct_norm(payload["assets"], CAP["assets"]),
+        "sales_skills": _clamp01(_nz(payload["sales_skills"]) / 10.0),
+        "confidence": _clamp01(_nz(payload["confidence"]) / 10.0),
+        "dependents": _dependents_norm(payload["dependents"]),
+        "age": _age_norm(payload["age"]),
+        "idea_level": IDEA_LEVEL_MAP.get(payload["idea_level"], 0.0),
+        "entrepreneurial_experience": _clamp01(_nz(payload["entrepreneurial_experience"]) / 10.0),
+        "risk": _clamp01(_nz(payload["risk"]) / 10.0),
+    }
+
+    total = sum(WEIGHTS[k] * n[k] for k in WEIGHTS.keys())
+    score = int(round(100 * total))
     tier = "Starter" if score < 55 else ("Building" if score < 75 else "Launch-ready")
 
     tips = []
-    if runway_norm < 0.35: tips.append("Build 6–12 months runway or run as a side project.")
-    if time_norm < 0.5: tips.append("Protect ~8–12 hrs/week for interviews & experiments.")
-    if customer_access < 0.6: tips.append("Line up 10–20 target users for interviews.")
-    if validation_skill < 0.6: tips.append("Run a demand test (landing page/preorder) before building.")
-    if finance_skill < 0.5: tips.append("Track cash runway monthly.")
-    if ops_skill < 0.5: tips.append("Create a weekly ops checklist to reduce chaos.")
-    return {"score":score, "tier":tier, "tips":tips}
+    # Finance levers
+    if n["savings"] < 0.5 or n["assets"] < 0.4:
+        tips.append("Run a 60–90 day runway sprint: reduce burn and build a buffer.")
+    if n["bills"] < 0.6 or n["entertainment"] < 0.6:
+        tips.append("Do a weekly expense audit and a 30-day no-spend on non-essentials.")
+    if n["income"] < 0.5:
+        tips.append("Spin up a simple service for cash: 3 outreach/day → 2 pilot clients.")
+    # Skill/mindset levers
+    if n["sales_skills"] < 0.6:
+        tips.append("Do 20 cold DMs/day for 5 days; refine your offer script.")
+    if n["confidence"] < 0.6:
+        tips.append("Post build-in-public for 10 days to desensitize and attract allies.")
+    if n["entrepreneurial_experience"] < 0.5:
+        tips.append("Run a 2-week micro-project: interviews → small paid pilot.")
+    if n["idea_level"] < 0.5:
+        tips.append("Advance one notch: exploring → validated problem → prototype → MVP.")
+    # Risk
+    if n["risk"] < 0.5:
+        tips.append("Set a ‘risk budget’: small, reversible tests with clear stop-lines.")
+
+    return {"score": score, "tier": tier, "tips": tips[:5], "normalized": n}
 
 # ------------------------------
-# Path suggestions helper
+# Path suggestions helper (unchanged)
 # ------------------------------
 def suggest_paths(interests, experience):
     results = []
     for domain in interests or []:
         for item in PATHS.get(domain, []):
             diff = item["difficulty"]
-            # adjust for experience
             if experience == "beginner": diff = min(5, diff + 1)
             if experience == "advanced": diff = max(1, diff - 1)
             results.append({
@@ -115,7 +177,6 @@ def suggest_paths(interests, experience):
                 "key_skills": item["skills"],
                 "starter_plan": item["starter"],
             })
-    # keep it short
     return results[:6]
 
 # ------------------------------
@@ -124,16 +185,15 @@ def suggest_paths(interests, experience):
 def local_reply(user_msg, history, assessment_state, path_state):
     text = (user_msg or "").lower()
 
-    # reference readiness
     if "score" in text or "ready" in text or "readiness" in text:
         if isinstance(assessment_state, dict) and "score" in assessment_state:
             s = assessment_state["score"]
             t = assessment_state.get("tier", "?")
-            return f"Your readiness is **{s}/100 ({t})**. Top tip: {assessment_state.get('tips', ['Run small demand tests first.'])[0]}"
+            tip = (assessment_state.get("tips") or ["Run small demand tests first."])[0]
+            return f"Your readiness is **{s}/100 ({t})**. Top tip: {tip}"
         else:
             return "Run **Assess readiness** on the right, then ask me again 🙂"
 
-    # reference paths
     if "path" in text or "idea" in text or "domain" in text:
         if isinstance(path_state, dict) and path_state.get("suggestions"):
             sug = path_state["suggestions"][0]
@@ -144,7 +204,6 @@ def local_reply(user_msg, history, assessment_state, path_state):
         else:
             return "Pick a few interests under **Path Explorer**, hit **Suggest paths**, then ask me which to start with."
 
-    # detect domain mention
     for domain in PATHS.keys():
         if domain in text:
             first = PATHS[domain][0]
@@ -152,7 +211,6 @@ def local_reply(user_msg, history, assessment_state, path_state):
                     f"(difficulty {first['difficulty']}/5). "
                     f"Why it can pay off: {first['benefits']}. "
                     f"Starter plan: {', '.join(first['starter'][:3])}.")
-    # default helpful tip
     return ("Start with a small **demand test**: a landing page and 5–10 user interviews. "
             "Measure real intent (signups/preorders) before you build.")
 
@@ -160,7 +218,7 @@ def local_reply(user_msg, history, assessment_state, path_state):
 # Gradio UI
 # ------------------------------
 with gr.Blocks(theme="soft", fill_height=True) as demo:
-    gr.Markdown("## Entrepreneurial Tutor testing \nAsk about readiness or paths. Use the tools on the right to feed me context.")
+    gr.Markdown("## Entrepreneurial Tutor (domains kept, assessment replaced)")
 
     with gr.Row():
         # Chat
@@ -172,21 +230,32 @@ with gr.Blocks(theme="soft", fill_height=True) as demo:
 
         # Tools
         with gr.Column(scale=2):
-            gr.Markdown("### Quick Readiness Assessment")
-            grit = gr.Slider(0,10, value=6, step=1, label="Grit / persistence")
-            risk = gr.Slider(0,10, value=5, step=1, label="Comfort with risk")
-            time_per_week = gr.Slider(0,40, value=8, step=1, label="Time available per week (hrs)")
-            runway_months = gr.Slider(0,24, value=3, step=1, label="Financial runway (months)")
-            customer_access = gr.Slider(0,10, value=5, step=1, label="Access to target customers")
-            validation_skill = gr.Slider(0,10, value=4, step=1, label="Validation / testing skill")
-            ops_skill = gr.Slider(0,10, value=4, step=1, label="Operations / delivery skill")
-            finance_skill = gr.Slider(0,10, value=3, step=1, label="Finance / budgeting")
+            gr.Markdown("### Quick Readiness Assessment (your factors)")
+            with gr.Row():
+                savings = gr.Number(value=2000, label="Savings (USD)", precision=0)
+                income = gr.Number(value=2500, label="Income/mo (USD)", precision=0)
+            with gr.Row():
+                bills = gr.Number(value=1500, label="Bills/mo (USD)", precision=0)
+                entertainment = gr.Number(value=200, label="Entertainment/mo (USD)", precision=0)
+            assets = gr.Number(value=0, label="Assets (USD)", precision=0)
+
+            sales_skills = gr.Slider(0,10, value=5, step=1, label="Sales skills (0–10)")
+            confidence = gr.Slider(0,10, value=5, step=1, label="Confidence (0–10)")
+            dependents = gr.Slider(0,6, value=0, step=1, label="Dependents (count)")
+            age = gr.Slider(15,80, value=25, step=1, label="Age")
+            idea_level = gr.Radio(
+                choices=list(IDEA_LEVEL_MAP.keys()),
+                value="exploring",
+                label="Idea level"
+            )
+            entrepreneurial_experience = gr.Slider(0,10, value=3, step=1, label="Entrepreneurial experience (0–10)")
+            risk = gr.Slider(0,10, value=5, step=1, label="Risk tolerance (0–10)")
 
             assess_btn = gr.Button("Assess readiness")
             assessment_state = gr.State({})
             assess_out = gr.JSON(label="Assessment Result")
 
-            gr.Markdown("### Path Explorer")
+            gr.Markdown("### Path Explorer (domains)")
             interests = gr.CheckboxGroup(
                 choices=list(PATHS.keys()),
                 value=["tech"],
@@ -202,18 +271,22 @@ with gr.Blocks(theme="soft", fill_height=True) as demo:
             paths_out = gr.JSON(label="Suggested Paths")
 
     # Wiring
-    def do_assess(grit, risk, time_per_week, runway_months, customer_access, validation_skill, ops_skill, finance_skill):
+    def do_assess(savings, income, bills, entertainment, assets,
+                  sales_skills, confidence, dependents, age,
+                  idea_level, entrepreneurial_experience, risk):
         payload = {
-            "grit":grit,"risk":risk,"time_per_week":time_per_week,"runway_months":runway_months,
-            "customer_access":customer_access,"validation_skill":validation_skill,
-            "ops_skill":ops_skill,"finance_skill":finance_skill
+            "savings": savings, "income": income, "bills": bills, "entertainment": entertainment, "assets": assets,
+            "sales_skills": sales_skills, "confidence": confidence, "dependents": dependents, "age": age,
+            "idea_level": idea_level, "entrepreneurial_experience": entrepreneurial_experience, "risk": risk
         }
         result = compute_readiness(payload)
         return result, result  # show + store
 
     assess_btn.click(
         do_assess,
-        inputs=[grit, risk, time_per_week, runway_months, customer_access, validation_skill, ops_skill, finance_skill],
+        inputs=[savings, income, bills, entertainment, assets,
+                sales_skills, confidence, dependents, age,
+                idea_level, entrepreneurial_experience, risk],
         outputs=[assess_out, assessment_state]
     )