Create app.py

app.py

@@ -0,0 +1,23 @@
+from fastapi import FastAPI
+from pydantic import BaseModel
+from fastapi.responses import JSONResponse
+from transformers import pipeline
+
+# Load an instruction-tuned model for generation
+# This model must be supported on CPU; you can change it if needed
+pipe = pipeline("text-generation", model="mistralai/Mistral-7B-Instruct-v0.1", max_new_tokens=100)
+
+app = FastAPI()
+
+class LaTeXRequest(BaseModel):
+    latex: str
+
+@app.post("/fix")
+async def fix_latex(data: LaTeXRequest):
+    prompt = f"Fix this malformed LaTeX expression so it's valid and simple:\n```{data.latex}```\nFixed:"
+    try:
+        result = pipe(prompt, do_sample=False)[0]["generated_text"]
+        fixed = result.split("Fixed:")[-1].strip("` \n")
+        return JSONResponse(content={"fixed_latex": fixed})
+    except Exception as e:
+        return JSONResponse(content={"error": str(e)}, status_code=500)