Update app.py

app.py

@@ -1,58 +1,48 @@
-from fastapi import FastAPI, Header, HTTPException
-from pydantic import BaseModel
-from transformers import AutoTokenizer, AutoModelForCausalLM
-import torch
-
-app = FastAPI()
-
-# -----------------------------
-# MODEL
-# -----------------------------
-MODEL_NAME = "lfm-research/LFM-2.5-1.2B-Instruct"
-
-tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME)
-
-model = AutoModelForCausalLM.from_pretrained(
-    MODEL_NAME,
-    device_map="auto",
-    torch_dtype=torch.float16
-)
-
-# -----------------------------
-# YOUR CUSTOM API KEY
-# -----------------------------
-API_KEY = "Model12134-1344"
-
-class Prompt(BaseModel):
-    message: str
-
-@app.post("/chat")
-def chat(
-    prompt: Prompt,
-    x_api_key: str = Header(None)
-):
-    # ---- API KEY VALIDATION ----
-    if not x_api_key:
-        raise HTTPException(status_code=401, detail="API key missing")
-
-    if x_api_key != API_KEY:
-        raise HTTPException(status_code=403, detail="Invalid API key")
-
-    inputs = tokenizer(
-        prompt.message,
-        return_tensors="pt"
-    ).to(model.device)
-
-    outputs = model.generate(
-        **inputs,
-        max_new_tokens=256,
-        temperature=0.3,
-        do_sample=True
-    )
-
-    response = tokenizer.decode(
-        outputs[0][inputs["input_ids"].shape[-1]:],
-        skip_special_tokens=True
-    )
-
-    return {"response": response}
+from fastapi import FastAPI, Header, HTTPException
+from pydantic import BaseModel
+from transformers import AutoTokenizer, AutoModelForCausalLM
+import torch
+
+app = FastAPI()
+
+# -----------------------------
+# PUBLIC MODEL (NO HF TOKEN)
+# -----------------------------
+MODEL_NAME = "LiquidAI/LFM2.5-1.2B-Instruct"
+
+tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME)
+
+model = AutoModelForCausalLM.from_pretrained(
+    MODEL_NAME,
+    device_map="auto",
+    torch_dtype=torch.float16
+)
+
+# -----------------------------
+# YOUR CUSTOM API KEY
+# -----------------------------
+API_KEY = "Model12134-1344"
+
+class Prompt(BaseModel):
+    message: str
+
+@app.post("/chat")
+def chat(prompt: Prompt, x_api_key: str = Header(None)):
+    if x_api_key != API_KEY:
+        raise HTTPException(status_code=403, detail="Invalid API key")
+
+    inputs = tokenizer(prompt.message, return_tensors="pt").to(model.device)
+
+    outputs = model.generate(
+        **inputs,
+        max_new_tokens=256,
+        temperature=0.3,
+        do_sample=True
+    )
+
+    response = tokenizer.decode(
+        outputs[0][inputs["input_ids"].shape[-1]:],
+        skip_special_tokens=True
+    )
+
+    return {"response": response}