| 15 | return lang_name |
| 16 | |
| 17 | class Translator: |
| 18 | |
| 19 | def __init__(self, |
| 20 | openai_api_key: str = None, |
| 21 | model_name: str = "gpt-3.5-turbo"): |
| 22 | self.openai_api_key = openai_api_key |
| 23 | self.model_name = model_name |
| 24 | self.init_flag = False |
| 25 | |
| 26 | def init_model(self): |
| 27 | llm = self.create_openai_model(self.openai_api_key, self.model_name) |
| 28 | prompt = self.create_prompt() |
| 29 | self.chain = LLMChain(llm=llm, prompt=prompt) |
| 30 | self.init_flag = True |
| 31 | |
| 32 | def __call__(self, inputs: Dict[str, str]) -> Dict[str, str]: |
| 33 | if not self.init_flag: |
| 34 | self.init_model() |
| 35 | |
| 36 | question = inputs["input"] |
| 37 | answer = inputs["output"] |
| 38 | |
| 39 | src_lang = detect_lang(answer) |
| 40 | tgt_lang = detect_lang(question) |
| 41 | |
| 42 | if src_lang != tgt_lang: |
| 43 | translated_answer = self.chain.run(text=answer, language=tgt_lang) |
| 44 | outputs = deepcopy(inputs) |
| 45 | outputs["output"] = translated_answer |
| 46 | return outputs |
| 47 | else: |
| 48 | return inputs |
| 49 | |
| 50 | def create_openai_model(self, openai_api_key: str, model_name: str) -> OpenAI: |
| 51 | if openai_api_key is None: |
| 52 | openai_api_key = os.environ.get('OPENAI_API_KEY') |
| 53 | llm = OpenAI(model_name=model_name, |
| 54 | temperature=0.0, |
| 55 | openai_api_key=openai_api_key) |
| 56 | return llm |
| 57 | |
| 58 | def create_prompt(self) -> PromptTemplate: |
| 59 | template = """ |
| 60 | Translate to {language}: {text} => |
| 61 | """ |
| 62 | prompt = PromptTemplate( |
| 63 | input_variables=["text", "language"], |
| 64 | template=template |
| 65 | ) |
| 66 | return prompt |
| 67 | |
| 68 | if __name__ == "__main__": |
| 69 | lang = { |
no outgoing calls
no test coverage detected