Mireya Cueto Garrido
4d2ced85a3
Require LLM_BASE_URL and LLM_API_KEY for automatic generation, add per-user rate limits, stop publishing backend/LLM settings in docker-compose, and document secure deployment.
77 lines
2.7 KiB
Python
77 lines
2.7 KiB
Python
import httpx
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from app.core.config import Settings
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from app.core.errors import LLMUnavailableError
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class LLMClient:
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"""Cliente para el API de chat de Sinbad2IA (Ollama-compatible en UJA)."""
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def __init__(self, settings: Settings) -> None:
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self.settings = settings
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def _chat_url(self) -> str:
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base = self.settings.llm_base_url.rstrip("/")
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if base.endswith("/api/chat"):
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return base
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return f"{base}/api/chat"
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async def generate(self, prompt: str) -> str:
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if not self.settings.llm_ready:
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raise LLMUnavailableError("Automatic AI generation is not available")
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payload = {
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"model": self.settings.llm_model,
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"messages": [
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{
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"role": "user",
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"content": (
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"Genera preguntas de examen en formato JSON válido para importar en Moodle. "
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"Responde únicamente con el JSON solicitado, sin texto adicional ni bloques markdown.\n\n"
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f"{prompt}"
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),
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},
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],
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"stream": False,
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}
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headers = {"Content-Type": "application/json"}
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if self.settings.llm_api_key:
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headers["Authorization"] = f"Bearer {self.settings.llm_api_key}"
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try:
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async with httpx.AsyncClient(timeout=self.settings.llm_timeout_seconds) as client:
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response = await client.post(self._chat_url(), json=payload, headers=headers)
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response.raise_for_status()
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except httpx.HTTPError as exc:
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raise LLMUnavailableError("LLM request failed") from exc
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content = _extract_assistant_content(response.json())
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if not content.strip():
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raise LLMUnavailableError("LLM returned empty content")
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return content
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def _extract_assistant_content(data: object) -> str:
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"""Soporta respuesta Sinbad2IA/Ollama (`message.content`) y OpenAI (`choices`)."""
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if not isinstance(data, dict):
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raise LLMUnavailableError("LLM response is not a JSON object")
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message = data.get("message")
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if isinstance(message, dict):
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content = message.get("content")
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if isinstance(content, str) and content.strip():
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return content
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choices = data.get("choices")
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if isinstance(choices, list) and choices:
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first = choices[0]
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if isinstance(first, dict):
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msg = first.get("message")
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if isinstance(msg, dict):
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content = msg.get("content")
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if isinstance(content, str) and content.strip():
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return content
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raise LLMUnavailableError("LLM response did not include message content")
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