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d5bd0f8 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 | from fastapi import FastAPI
from pydantic import BaseModel
import os
import requests
app = FastAPI(title="lean-llm-starter inference wrapper")
LLAMA_URL = os.getenv("LLAMA_URL", "http://localhost:8080")
PROMPT_PATH = os.getenv("PROMPT_PATH", "prompt.txt")
class CompletionRequest(BaseModel):
prompt: str
max_tokens: int = 1024
temperature: float = 0.0
stop: list[str] = ["<|user|>"]
@app.get("/health")
def health() -> dict:
return {"status": "ok"}
@app.post("/v1/completions")
def complete(req: CompletionRequest) -> dict:
template = open(PROMPT_PATH, encoding="utf-8").read()
prompt = template.replace("{{THEOREM_STATEMENT}}", req.prompt)
response = requests.post(
f"{LLAMA_URL}/completion",
json={
"prompt": prompt,
"n_predict": req.max_tokens,
"temperature": req.temperature,
"stop": req.stop,
},
timeout=120,
)
response.raise_for_status()
payload = response.json()
return {"choices": [{"text": payload.get("content", "")}]}
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