| @@ -2,7 +2,7 @@ METADATA_FILTER_SYSTEM_PROMPT = """ | |||
| ### Job Description', | |||
| You are a text metadata extract engine that extract text's metadata based on user input and set the metadata value | |||
| ### Task | |||
| Your task is to ONLY extract the metadatas that exist in the input text from the provided metadata list and Use the following operators ["=", "!=", ">", "<", ">=", "<="] to express logical relationships, then return result in JSON format with the key "metadata_fields" and value "metadata_field_value" and comparison operator "comparison_operator". | |||
| Your task is to ONLY extract the metadatas that exist in the input text from the provided metadata list and Use the following operators ["contains", "not contains", "start with", "end with", "is", "is not", "empty", "not empty", "=", "≠", ">", "<", "≥", "≤", "before", "after"] to express logical relationships, then return result in JSON format with the key "metadata_fields" and value "metadata_field_value" and comparison operator "comparison_operator". | |||
| ### Format | |||
| The input text is in the variable input_text. Metadata are specified as a list in the variable metadata_fields. | |||
| ### Constraint | |||
| @@ -32,11 +32,11 @@ from core.workflow.nodes.knowledge_retrieval.template_prompts import ( | |||
| METADATA_FILTER_COMPLETION_PROMPT, | |||
| METADATA_FILTER_SYSTEM_PROMPT, | |||
| METADATA_FILTER_USER_PROMPT_1, | |||
| METADATA_FILTER_USER_PROMPT_2, | |||
| METADATA_FILTER_USER_PROMPT_3, | |||
| ) | |||
| from core.workflow.nodes.llm.entities import LLMNodeChatModelMessage, LLMNodeCompletionModelPromptTemplate | |||
| from core.workflow.nodes.llm.node import LLMNode | |||
| from core.workflow.nodes.question_classifier.template_prompts import QUESTION_CLASSIFIER_USER_PROMPT_2 | |||
| from extensions.ext_database import db | |||
| from extensions.ext_redis import redis_client | |||
| from libs.json_in_md_parser import parse_and_check_json_markdown | |||
| @@ -618,7 +618,7 @@ class KnowledgeRetrievalNode(LLMNode): | |||
| ) | |||
| prompt_messages.append(assistant_prompt_message_1) | |||
| user_prompt_message_2 = LLMNodeChatModelMessage( | |||
| role=PromptMessageRole.USER, text=QUESTION_CLASSIFIER_USER_PROMPT_2 | |||
| role=PromptMessageRole.USER, text=METADATA_FILTER_USER_PROMPT_2 | |||
| ) | |||
| prompt_messages.append(user_prompt_message_2) | |||
| assistant_prompt_message_2 = LLMNodeChatModelMessage( | |||
| @@ -2,7 +2,7 @@ METADATA_FILTER_SYSTEM_PROMPT = """ | |||
| ### Job Description', | |||
| You are a text metadata extract engine that extract text's metadata based on user input and set the metadata value | |||
| ### Task | |||
| Your task is to ONLY extract the metadatas that exist in the input text from the provided metadata list and Use the following operators ["=", "!=", ">", "<", ">=", "<="] to express logical relationships, then return result in JSON format with the key "metadata_fields" and value "metadata_field_value" and comparison operator "comparison_operator". | |||
| Your task is to ONLY extract the metadatas that exist in the input text from the provided metadata list and Use the following operators ["contains", "not contains", "start with", "end with", "is", "is not", "empty", "not empty", "=", "≠", ">", "<", "≥", "≤", "before", "after"] to express logical relationships, then return result in JSON format with the key "metadata_fields" and value "metadata_field_value" and comparison operator "comparison_operator". | |||
| ### Format | |||
| The input text is in the variable input_text. Metadata are specified as a list in the variable metadata_fields. | |||
| ### Constraint | |||