def process()

in LLM/openai_api_language_model.py [0:0]

• 32 lines of code
• 7 McCabe index (conditional complexity)

    def process(self, prompt):
            logger.debug("call api language model...")
            self.chat.append({"role": self.user_role, "content": prompt})

            language_code = None
            if isinstance(prompt, tuple):
                prompt, language_code = prompt
                if language_code[-5:] == "-auto":
                    language_code = language_code[:-5]
                    prompt = f"Please reply to my message in {WHISPER_LANGUAGE_TO_LLM_LANGUAGE[language_code]}. " + prompt
            
            response = self.client.chat.completions.create(
                model=self.model_name,
                messages=[
                    {"role": self.user_role, "content": prompt},
                ],
                stream=self.stream
            )
            if self.stream:
                generated_text, printable_text = "", ""
                for chunk in response:
                    new_text = chunk.choices[0].delta.content or ""
                    generated_text += new_text
                    printable_text += new_text
                    sentences = sent_tokenize(printable_text)
                    if len(sentences) > 1:
                        yield sentences[0], language_code
                        printable_text = new_text
                self.chat.append({"role": "assistant", "content": generated_text})
                # don't forget last sentence
                yield printable_text, language_code
            else:
                generated_text = response.choices[0].message.content
                self.chat.append({"role": "assistant", "content": generated_text})
                yield generated_text, language_code