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fix: suggest questions more max_tokens (#35533)
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@ -13,8 +13,6 @@ from core.llm_generator.output_parser.rule_config_generator import RuleConfigGen
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from core.llm_generator.output_parser.suggested_questions_after_answer import SuggestedQuestionsAfterAnswerOutputParser
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from core.llm_generator.prompts import (
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CONVERSATION_TITLE_PROMPT,
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DEFAULT_SUGGESTED_QUESTIONS_MAX_TOKENS,
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DEFAULT_SUGGESTED_QUESTIONS_TEMPERATURE,
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GENERATOR_QA_PROMPT,
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JAVASCRIPT_CODE_GENERATOR_PROMPT_TEMPLATE,
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LLM_MODIFY_CODE_SYSTEM,
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@ -217,8 +215,8 @@ class LLMGenerator:
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else:
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# Default-model generation keeps the built-in suggested-questions tuning.
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model_parameters = {
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"max_tokens": DEFAULT_SUGGESTED_QUESTIONS_MAX_TOKENS,
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"temperature": DEFAULT_SUGGESTED_QUESTIONS_TEMPERATURE,
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"max_tokens": 2560,
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"temperature": 0.0,
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}
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stop = []
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@ -10,7 +10,14 @@ logger = logging.getLogger(__name__)
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class SuggestedQuestionsAfterAnswerOutputParser:
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def __init__(self, instruction_prompt: str | None = None) -> None:
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self._instruction_prompt = instruction_prompt or DEFAULT_SUGGESTED_QUESTIONS_AFTER_ANSWER_INSTRUCTION_PROMPT
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self._instruction_prompt = self._build_instruction_prompt(instruction_prompt)
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@staticmethod
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def _build_instruction_prompt(instruction_prompt: str | None) -> str:
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if not instruction_prompt or not instruction_prompt.strip():
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return DEFAULT_SUGGESTED_QUESTIONS_AFTER_ANSWER_INSTRUCTION_PROMPT
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return f'{instruction_prompt}\nYou must output a JSON array like ["question1", "question2", "question3"].'
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def get_format_instructions(self) -> str:
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return self._instruction_prompt
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@ -104,9 +104,6 @@ DEFAULT_SUGGESTED_QUESTIONS_AFTER_ANSWER_INSTRUCTION_PROMPT = (
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'["question1","question2","question3"]\n'
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)
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DEFAULT_SUGGESTED_QUESTIONS_MAX_TOKENS = 256
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DEFAULT_SUGGESTED_QUESTIONS_TEMPERATURE = 0.0
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GENERATOR_QA_PROMPT = (
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"<Task> The user will send a long text. Generate a Question and Answer pairs only using the knowledge"
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" in the long text. Please think step by step."
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