2025-04-22 08:08:24 -07:00

59 lines
1.8 KiB
Python

import logging
import httpx
from django.conf import settings
logger = logging.getLogger("paperless.ai.client")
def run_llm_query(prompt: str) -> str:
logger.debug(
"Running LLM query against %s with model %s",
settings.LLM_BACKEND,
settings.LLM_MODEL,
)
match settings.LLM_BACKEND:
case "openai":
result = _run_openai_query(prompt)
case "ollama":
result = _run_ollama_query(prompt)
case _:
raise ValueError(f"Unsupported LLM backend: {settings.LLM_BACKEND}")
logger.debug("LLM query result: %s", result)
return result
def _run_ollama_query(prompt: str) -> str:
with httpx.Client(timeout=30.0) as client:
response = client.post(
f"{settings.OLLAMA_URL}/api/chat",
json={
"model": settings.LLM_MODEL,
"messages": [{"role": "user", "content": prompt}],
"stream": False,
},
)
response.raise_for_status()
return response.json()["message"]["content"]
def _run_openai_query(prompt: str) -> str:
if not settings.LLM_API_KEY:
raise RuntimeError("PAPERLESS_LLM_API_KEY is not set")
with httpx.Client(timeout=30.0) as client:
response = client.post(
f"{settings.OPENAI_URL}/v1/chat/completions",
headers={
"Authorization": f"Bearer {settings.LLM_API_KEY}",
"Content-Type": "application/json",
},
json={
"model": settings.LLM_MODEL,
"messages": [{"role": "user", "content": prompt}],
"temperature": 0.3,
},
)
response.raise_for_status()
return response.json()["choices"][0]["message"]["content"]