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# retoor <retoor@molodetz.nl>
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from __future__ import annotations
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import logging
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from typing import Any
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import httpx
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from devplacepy import stealth
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from .config import Settings
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from .cost import record_usage
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from .errors import LLMError
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logger = logging.getLogger("devii.llm")
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class LLMClient:
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def __init__(self, settings: Settings) -> None:
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self._settings = settings
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self._client = stealth.stealth_async_client(
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timeout=settings.timeout_seconds,
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headers={
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"Authorization": f"Bearer {settings.ai_key}",
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"Content-Type": "application/json",
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},
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)
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async def aclose(self) -> None:
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await self._client.aclose()
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async def complete(
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self,
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messages: list[dict[str, Any]],
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tools: list[dict[str, Any]],
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) -> dict[str, Any]:
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payload = {
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"model": self._settings.ai_model,
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"messages": messages,
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"tools": tools,
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"tool_choice": "auto",
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}
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try:
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logger.debug("LLM request with %d messages", len(messages))
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response = await self._client.post(self._settings.ai_url, json=payload)
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except httpx.HTTPError as exc:
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raise LLMError(f"Could not reach the model endpoint: {exc}") from exc
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if response.status_code >= 400:
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raise LLMError(
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f"Model endpoint returned {response.status_code}: {self._reason(response)}",
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status=response.status_code,
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body=response.text[:500],
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)
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try:
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data = response.json()
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except ValueError as exc:
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raise LLMError("Model endpoint returned invalid JSON.") from exc
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choices = data.get("choices")
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if not choices:
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raise LLMError("Model response contained no choices.", body=str(data)[:500])
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message = choices[0].get("message")
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if message is None:
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raise LLMError("Model response contained no message.", body=str(data)[:500])
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record_usage(data.get("usage"))
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logger.debug(
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"LLM response received (tool_calls=%s)", bool(message.get("tool_calls"))
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)
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return message
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async def complete_text(
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self, messages: list[dict[str, Any]], temperature: float = 0.0
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) -> str:
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payload = {
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"model": self._settings.ai_model,
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"messages": messages,
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"temperature": temperature,
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}
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try:
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response = await self._client.post(self._settings.ai_url, json=payload)
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except httpx.HTTPError as exc:
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raise LLMError(f"Could not reach the model endpoint: {exc}") from exc
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if response.status_code >= 400:
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raise LLMError(
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f"Model endpoint returned {response.status_code}: {self._reason(response)}"
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)
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try:
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data = response.json()
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content = data["choices"][0]["message"]["content"] or ""
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except (ValueError, KeyError, IndexError) as exc:
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raise LLMError("Model endpoint returned an unexpected response.") from exc
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record_usage(data.get("usage"))
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return content
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async def summarize(self, text: str) -> str:
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payload = {
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"model": self._settings.ai_model,
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"messages": [
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{
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"role": "system",
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"content": "You are a precise technical summarizer.",
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},
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{"role": "user", "content": text},
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],
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"temperature": 0.0,
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}
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try:
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response = await self._client.post(self._settings.ai_url, json=payload)
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except httpx.HTTPError as exc:
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raise LLMError(f"Could not reach the model endpoint: {exc}") from exc
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if response.status_code >= 400:
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raise LLMError(
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f"Model endpoint returned {response.status_code}: {self._reason(response)}"
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)
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try:
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data = response.json()
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content = data["choices"][0]["message"]["content"] or ""
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except (ValueError, KeyError, IndexError) as exc:
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raise LLMError(
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"Model summarization returned an unexpected response."
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) from exc
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record_usage(data.get("usage"))
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return content
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@staticmethod
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def _reason(response: httpx.Response) -> str:
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try:
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error = response.json().get("error")
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except ValueError:
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return response.text[:200] or response.reason_phrase
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if isinstance(error, dict):
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return str(error.get("message", error))
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if error:
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return str(error)
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return response.reason_phrase
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