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| import json | |
| import os | |
| import threading | |
| from typing import Any | |
| from langchain_openai import ChatOpenAI | |
| from openai import OpenAI | |
| from src.adapters.interfaces.llm import LLM | |
| from src.config import config | |
| _THINKING_DISABLED = {"thinking": {"type": "disabled"}} | |
| def _deepseek_client_kwargs() -> dict[str, Any]: | |
| return { | |
| "api_key": config.deepseek.api_key, | |
| "base_url": config.deepseek.base_url, | |
| "timeout": 120.0, | |
| "max_retries": 3, | |
| } | |
| class _DeepSeekLLMBase(LLM): | |
| def __init__(self, model: str): | |
| self.model = model | |
| self._client: OpenAI | None = None | |
| self._langchain_model: ChatOpenAI | None = None | |
| self._lock = threading.Lock() | |
| self._pid = os.getpid() | |
| def _check_fork(self) -> None: | |
| if os.getpid() != self._pid: | |
| self._client = None | |
| self._langchain_model = None | |
| self._pid = os.getpid() | |
| def client(self) -> OpenAI: | |
| self._check_fork() | |
| if self._client is None: | |
| with self._lock: | |
| if self._client is None: | |
| self._client = OpenAI(**_deepseek_client_kwargs()) | |
| return self._client | |
| def langchain_model(self) -> ChatOpenAI: | |
| self._check_fork() | |
| if self._langchain_model is None: | |
| with self._lock: | |
| if self._langchain_model is None: | |
| self._langchain_model = ChatOpenAI( | |
| model=self.model, | |
| **_deepseek_client_kwargs(), | |
| extra_body=_THINKING_DISABLED, | |
| ) | |
| return self._langchain_model | |
| def generate_text(self, prompt: str, max_new_tokens: int = None) -> str: | |
| response = self.client.chat.completions.create( | |
| model=self.model, | |
| messages=[{"role": "user", "content": prompt}], | |
| **({"max_tokens": max_new_tokens} if max_new_tokens else {}), | |
| extra_body=_THINKING_DISABLED, | |
| ) | |
| return response.choices[0].message.content | |
| def generate_json( | |
| self, prompt: str, max_new_tokens: int = None, max_retries: int = 3 | |
| ) -> dict: | |
| response = None | |
| while max_retries > 0 and response is None: | |
| try: | |
| _response = self.client.chat.completions.create( | |
| model=self.model, | |
| messages=[{"role": "user", "content": prompt}], | |
| **({"max_tokens": max_new_tokens} if max_new_tokens else {}), | |
| response_format={"type": "json_object"}, | |
| extra_body=_THINKING_DISABLED, | |
| ) | |
| _response = ( | |
| _response.choices[0].message.content.strip("```json").strip("```") | |
| ) | |
| response = json.loads(_response) | |
| except Exception as e: | |
| max_retries -= 1 | |
| if max_retries <= 0: | |
| raise e | |
| return response | |
| class DeepSeekLLMClientSmall(_DeepSeekLLMBase): | |
| def __init__(self): | |
| super().__init__(config.deepseek.small_llm_model) | |
| class DeepSeekLLMClientLarge(_DeepSeekLLMBase): | |
| def __init__(self): | |
| super().__init__(config.deepseek.large_llm_model) | |
| _llm_small_client_deepseek = DeepSeekLLMClientSmall() | |
| _llm_large_client_deepseek = DeepSeekLLMClientLarge() | |