| 18 | |
| 19 | |
| 20 | class llm_client(): |
| 21 | def __init__(self, args): |
| 22 | self.model = args["llm_model"] |
| 23 | self.base_url = args["llm_url"] |
| 24 | self.api_key = args["llm_api_key"] |
| 25 | self.client = OpenAI(base_url=self.base_url, api_key=self.api_key, http_client=httpx.Client(verify=False)) |
| 26 | def call(self, user_prompt: str, system_prompt: str = "") -> str: |
| 27 | |
| 28 | completion = self.client.chat.completions.create( |
| 29 | model=self.model, |
| 30 | messages=[ |
| 31 | { |
| 32 | "role": "system", |
| 33 | "content": system_prompt if system_prompt else "You are a helpful assistant." |
| 34 | }, |
| 35 | { |
| 36 | "role": "user", |
| 37 | "content": user_prompt |
| 38 | } |
| 39 | ] |
| 40 | ) |
| 41 | |
| 42 | self.response = completion.choices[0].message.content |
| 43 | |
| 44 | class TripleScorer: |
| 45 | def __init__(self, triple_path:str, triple_soure_path:str , output_path:str = None): |