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app.py

@@ -3,8 +3,6 @@ import gradio as gr
 import pandas as pd
 from typing import Dict, Any
 from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline
-from textwrap import dedent
-
 
 LLM_ID = "HuggingFaceTB/SmolLM2-135M-Instruct"
 tokenizer = AutoTokenizer.from_pretrained(LLM_ID)
@@ -18,7 +16,7 @@ llm = pipeline(
 def projectile_calc(v0_mps: float, theta_deg: float, y0_m: float, g: float, weight_kg: float) -> Dict[str, Any]:
     errors = []
     if not (0 < v0_mps <= 500): errors.append("Initial speed must be in (0, 500] m/s.")
-    if not (-10 <= theta_deg <= 90): errors.append("Launch angle must be between -10° and 90°.")
+    if not (-10 <= theta_deg <= 90): errors.append("Launch angle must be between -10 and 90 degrees.")
     if not (0 <= y0_m <= 1000): errors.append("Initial height must be in [0, 1000] m.")
     if not (1 <= g <= 50): errors.append("Gravity must be in [1, 50] m/s^2.")
     if not (0.05 <= weight_kg <= 50): errors.append("Ball weight must be in [0.05, 50] kg.")
@@ -64,9 +62,10 @@ def projectile_calc(v0_mps: float, theta_deg: float, y0_m: float, g: float, weig
         }
     }
 
-SYSTEM_PROMPT = (
-    "You write a single concise sentence using ONLY numbers provided in the JSON. "
-    "Do not invent numbers or facts. Use units exactly as given; round to 2–3 sig figs if needed."
+SYSTEM_MSG = (
+    "You are a careful technical writer. "
+    "Write EXACTLY ONE sentence using ONLY numbers provided in the JSON. "
+    "Do not invent or rename fields; keep units as given; use ~2–3 sig figs."
 )
 
 def llm_one_sentence(structured: Dict[str, Any]) -> str:
@@ -93,31 +92,23 @@ def llm_one_sentence(structured: Dict[str, Any]) -> str:
         }
     }
 
-    system_msg = (
-        "You are a careful technical writer. "
-        "Write EXACTLY ONE sentence using ONLY numbers provided in the JSON. "
-        "Do not invent or rename fields; keep units as given; use ~2–3 sig figs."
-    )
-
-    # Show the exact sentence shape we want.
-    instruction = '''Use only these keys: inputs, derived, outputs.
-    Return exactly one sentence in this form (fill in the braces with the JSON values):
+    # Exact sentence shape we want.
+    instruction = """Use only these keys: inputs, derived, outputs.
+Return exactly one sentence in this form (fill in the braces with the JSON values):
 
-    If you threw a ball that weighed {weight_kg} kg at v0={v0_mps} m/s, θ={theta_deg}, from y0={y0_m} m under g={g_mps2} m/s^2,
-    it would stay in the air for {time_of_flight_s} s, reach {max_height_m} m, travel {range_m} m, and impact at {impact_speed_mps} m/s.
-    '''
+If you threw a ball that weighed {weight_kg} kg at v0={v0_mps} m/s, theta={theta_deg} deg, from y0={y0_m} m under g={g_mps2} m/s^2,
+it would stay in the air for {time_of_flight_s} s, reach {max_height_m} m, travel {range_m} m, and impact at {impact_speed_mps} m/s.
+"""
 
-    user_msg = "
-".join([
-      "JSON:",
-      json.dumps(payload, indent=2),
-      "",
-      "Produce the single sentence as specified."
-  ])
+    user_msg = "\n".join([
+        "JSON:",
+        json.dumps(payload, indent=2),
+        "",
+        "Produce the single sentence as specified."
+    ])
 
-    # ✅ Use the tokenizer's chat template
     messages = [
-        {"role": "system", "content": system_msg},
+        {"role": "system", "content": SYSTEM_MSG},
         {"role": "user", "content": instruction},
         {"role": "user", "content": user_msg},
     ]
@@ -132,12 +123,12 @@ def llm_one_sentence(structured: Dict[str, Any]) -> str:
     )
     text = out[0]["generated_text"].strip()
 
-    # Minimal fallback: if the model didn't produce a sensible one-liner, synthesize it.
+    # Fallback if the model strays
     if ("If you threw a ball" not in text) or (len(text.split()) < 6):
         p = payload
         text = (
             f"If you threw a ball that weighed {p['inputs']['weight_kg']} kg at v0={p['inputs']['v0_mps']} m/s, "
-            f"θ={p['inputs']['theta_deg']}, from y0={p['inputs']['y0_m']} m under g={p['inputs']['g_mps2']} m/s^2, "
+            f"theta={p['inputs']['theta_deg']} deg, from y0={p['inputs']['y0_m']} m under g={p['inputs']['g_mps2']} m/s^2, "
             f"it would stay in the air for {p['outputs']['time_of_flight_s']} s, "
             f"reach {p['outputs']['max_height_m']} m, travel {p['outputs']['range_m']} m, "
             f"and impact at {p['outputs']['impact_speed_mps']} m/s."
@@ -172,9 +163,9 @@ with gr.Blocks(title="Projectile Motion — Deterministic + One-Sentence LLM") a
     gr.Markdown("Deterministic projectile motion (no air resistance). See all inputs and derived values, plus a single, grounded sentence.")
 
     with gr.Row():
-        v0 = gr.Slider(1, 200, value=30.0, step=0.5, label="Initial speed v₀ [m/s]")
-        theta = gr.Slider(-10, 90, value=45.0, step=0.5, label="Launch angle θ [deg]")
-        y0 = gr.Slider(0, 20, value=1.5, step=0.1, label="Initial height y₀ [m]")
+        v0 = gr.Slider(1, 200, value=30.0, step=0.5, label="Initial speed v0 [m/s]")
+        theta = gr.Slider(-10, 90, value=45.0, step=0.5, label="Launch angle theta [deg]")
+        y0 = gr.Slider(0, 20, value=1.5, step=0.1, label="Initial height y0 [m]")
         g = gr.Slider(5, 20, value=9.81, step=0.01, label="Gravity g [m/s^2]")
         w = gr.Slider(0.05, 10.0, value=0.43, step=0.01, label="Ball weight [kg]")