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support instruction in classifier node (#4913)

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Jyong 2024-06-04 20:07:54 +08:00 committed by GitHub
parent 4e3b0c5aea
commit c7bddb637b
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1 changed files with 34 additions and 1 deletions
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35
api/core/workflow/nodes/question_classifier/question_classifier_node.py
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@ -12,6 +12,7 @@ from core.prompt.advanced_prompt_transform import AdvancedPromptTransform
from core.prompt.entities.advanced_prompt_entities import ChatModelMessage, CompletionModelPromptTemplate
from core.prompt.simple_prompt_transform import ModelMode
from core.prompt.utils.prompt_message_util import PromptMessageUtil
from core.prompt.utils.prompt_template_parser import PromptTemplateParser
from core.workflow.entities.base_node_data_entities import BaseNodeData
from core.workflow.entities.node_entities import NodeRunMetadataKey, NodeRunResult, NodeType
from core.workflow.entities.variable_pool import VariablePool
@ -26,6 +27,7 @@ from core.workflow.nodes.question_classifier.template_prompts import (
QUESTION_CLASSIFIER_USER_PROMPT_2,
QUESTION_CLASSIFIER_USER_PROMPT_3,
)
from core.workflow.utils.variable_template_parser import VariableTemplateParser
from libs.json_in_md_parser import parse_and_check_json_markdown
from models.workflow import WorkflowNodeExecutionStatus
@ -47,6 +49,9 @@ class QuestionClassifierNode(LLMNode):
model_instance, model_config = self._fetch_model_config(node_data.model)
# fetch memory
memory = self._fetch_memory(node_data.memory, variable_pool, model_instance)
# fetch instruction
instruction = self._format_instruction(node_data.instruction, variable_pool)
node_data.instruction = instruction
# fetch prompt messages
prompt_messages, stop = self._fetch_prompt(
node_data=node_data,
@ -122,6 +127,12 @@ class QuestionClassifierNode(LLMNode):
node_data = node_data
node_data = cast(cls._node_data_cls, node_data)
variable_mapping = {'query': node_data.query_variable_selector}
variable_selectors = []
if node_data.instruction:
variable_template_parser = VariableTemplateParser(template=node_data.instruction)
variable_selectors.extend(variable_template_parser.extract_variable_selectors())
for variable_selector in variable_selectors:
variable_mapping[variable_selector.variable] = variable_selector.value_selector
return variable_mapping
@classmethod
@ -269,8 +280,30 @@ class QuestionClassifierNode(LLMNode):
text=QUESTION_CLASSIFIER_COMPLETION_PROMPT.format(histories=memory_str,
input_text=input_text,
categories=json.dumps(categories),
classification_instructions=instruction, ensure_ascii=False)
classification_instructions=instruction,
ensure_ascii=False)
)
else:
raise ValueError(f"Model mode {model_mode} not support.")
def _format_instruction(self, instruction: str, variable_pool: VariablePool) -> str:
inputs = {}
variable_selectors = []
variable_template_parser = VariableTemplateParser(template=instruction)
variable_selectors.extend(variable_template_parser.extract_variable_selectors())
for variable_selector in variable_selectors:
variable_value = variable_pool.get_variable_value(variable_selector.value_selector)
if variable_value is None:
raise ValueError(f'Variable {variable_selector.variable} not found')
inputs[variable_selector.variable] = variable_value
prompt_template = PromptTemplateParser(template=instruction, with_variable_tmpl=True)
prompt_inputs = {k: inputs[k] for k in prompt_template.variable_keys if k in inputs}
instruction = prompt_template.format(
prompt_inputs
)
return instruction