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from typing import List, Optional |
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def intent_detection( |
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text: str, |
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model: str, |
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candidate_intents: Optional[List[str]] = None, |
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custom_instructions: str = "", |
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use_llm: bool = True |
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) -> str: |
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if not text or not text.strip(): |
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return "Please enter input text." |
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if use_llm: |
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return _intent_detection_with_llm(text, model, candidate_intents, custom_instructions) |
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else: |
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return _intent_detection_with_traditional(text, model, candidate_intents) |
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from llms import LLM |
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def _intent_detection_with_llm( |
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text: str, |
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model: str, |
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candidate_intents: Optional[List[str]], |
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custom_instructions: str |
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) -> str: |
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try: |
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llm = LLM(model=model) |
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if candidate_intents: |
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prompt = ( |
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f"Classify the intent of the following text from this list: {', '.join(candidate_intents)}.\n" |
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f"Return ONLY the best intent name.\n" |
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+ (f"{custom_instructions}\n" if custom_instructions else "") |
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+ f"Text: {text}\nIntent:" |
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) |
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else: |
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prompt = ( |
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f"Detect the intent of the following text.\n" |
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f"Return ONLY the intent name, do not explain.\n" |
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+ (f"{custom_instructions}\n" if custom_instructions else "") |
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+ f"Text: {text}\nIntent:" |
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) |
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result = llm.generate(prompt) |
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return result.strip() |
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except Exception as e: |
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print(f"Error in LLM intent detection: {str(e)}") |
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return "Oops! Something went wrong. Please try again later." |
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def _intent_detection_with_traditional( |
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text: str, |
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model: str, |
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candidate_intents: Optional[List[str]] |
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) -> str: |
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return "[Traditional model intent detection not implemented yet]" |
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