Update app.py

app.py

@@ -1,4 +1,3 @@
-# app.py
 import asyncio
 import re
 from typing import Literal
@@ -9,8 +8,8 @@ from llama_cpp import Llama
 
 # ---------------- MODEL CONFIG ---------------- #
 
-# IMPORTANT: For HuggingFace Spaces, the model file is inside the repo folder
-MODEL_PATH = "model/Phi-3.1-mini-4k-instruct-IQ2_M.gguf"
+# Model is in ROOT of the repository, not inside a folder
+MODEL_PATH = "/code/Phi-3.1-mini-4k-instruct-IQ2_M.gguf"
 
 # CPU settings for llama.cpp
 N_THREADS = 4
@@ -21,7 +20,7 @@ N_GPU_LAYERS = 0
 # Concurrency limit
 MAX_CONCURRENT_REQUESTS = 6
 
-# Unique token to force controlled stopping
+# Token to force stopping the generation
 END_TOKEN = "###END_OF_RESPONSE###"
 
 print("Loading model:", MODEL_PATH)
@@ -41,7 +40,7 @@ app = FastAPI(title="FormatAI Humanizer Backend")
 
 app.add_middleware(
     CORSMiddleware,
-    allow_origins=["*"],     # allow all origins (Vercel frontend)
+    allow_origins=["*"],  # Vercel frontend allowed
     allow_methods=["*"],
     allow_headers=["*"],
 )
@@ -62,29 +61,29 @@ STYLE_PROMPTS = {
     "professional": (
         "STYLE: PROFESSIONAL\n"
         "Rewrite the user's text in a STRICTLY professional, corporate, formal tone. "
-        "Use respectful and clear business language. Do NOT add explanations. Output ONLY the rewritten text, "
-        f"then write {END_TOKEN}."
+        "Use respectful and clear business language. Do NOT add explanations. "
+        f"Output ONLY the rewritten text, then write {END_TOKEN}."
     ),
 
     "casual": (
         "STYLE: CASUAL\n"
-        "Rewrite the user's text in a friendly, natural, conversational tone. Use contractions and human-like flow. "
-        "Do NOT add explanations. Output ONLY the rewritten text, then write "
-        f"{END_TOKEN}."
+        "Rewrite the user's text in a friendly, conversational, relaxed tone. "
+        "Use contractions and natural flow. Do NOT add explanations. "
+        f"Output ONLY the rewritten text, then write {END_TOKEN}."
     ),
 
     "academic": (
         "STYLE: ACADEMIC\n"
-        "Rewrite the user's text in formal academic language suitable for scholarly work. "
-        "Use precise and objective vocabulary. Do NOT add explanations. Output ONLY the rewritten text, "
-        f"then write {END_TOKEN}."
+        "Rewrite the user's text in precise, formal academic language suitable for scholarly writing. "
+        "Use objective vocabulary and clear structure. Do NOT add explanations. "
+        f"Output ONLY the rewritten text, then write {END_TOKEN}."
     ),
 
     "marketing": (
         "STYLE: MARKETING\n"
-        "Rewrite the user's text in persuasive, benefit-focused marketing copy. "
-        "Use strong emotional hooks and punchy messaging. Do NOT add explanations. Output ONLY the rewritten text, "
-        f"then write {END_TOKEN}."
+        "Rewrite the user's text into persuasive, compelling marketing language. "
+        "Use emotional hooks, strong benefits, and engaging tone. Do NOT add explanations. "
+        f"Output ONLY the rewritten text, then write {END_TOKEN}."
     ),
 }
 
@@ -92,14 +91,14 @@ STYLE_PROMPTS = {
 # ---------------- HELPERS ---------------- #
 
 def clean_output(raw: str) -> str:
-    """Strip junk tokens and trim to final output."""
+    """Trim unwanted tokens and cleanup."""
     if not raw:
         return ""
 
-    # Remove system markers
+    # Remove system markers if any appear
     raw = re.sub(r"<\|/?(system|assistant|user|end)\|>", "", raw, flags=re.I)
 
-    # Stop at END_TOKEN
+    # Cut off at END_TOKEN
     if END_TOKEN in raw:
         raw = raw.split(END_TOKEN)[0]
 
@@ -109,9 +108,8 @@ def clean_output(raw: str) -> str:
 
 
 def build_prompt(text: str, style: str) -> str:
-    """Create strict prompt for selected style."""
+    """Build prompt for the selected style."""
     system = STYLE_PROMPTS[style]
-
     return (
         f"<|system|>\n{system}\n\n"
         f"<|user|>\n{text}\n\n"
@@ -157,11 +155,11 @@ async def transform(req: TransformRequest):
     if req.style not in STYLE_PROMPTS:
         raise HTTPException(400, "Invalid style")
 
-    # More creativity for marketing
+    # Marketing = more creativity
     temperature = 0.65 if req.style == "marketing" else 0.25
 
     prompt = build_prompt(text, req.style)
-    transformed = await call_llm(prompt, temperature=temperature)
+    transformed = await call_llm(prompt, temperature)
 
     return {
         "original": text,
@@ -174,7 +172,7 @@ async def transform(req: TransformRequest):
 
 @app.post("/api/humanize")
 async def humanize(req: HumanizeRequest):
-    """Old endpoint - always uses casual."""
+    """Fallback endpoint — always uses casual."""
     prompt = build_prompt(req.text.strip(), "casual")
     out = await call_llm(prompt, temperature=0.4)
     return {"result": out}