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add history message

This commit is contained in:
jyong 2024-03-29 18:58:59 +08:00
parent d673b4c219
commit 2d26c4745b
2 changed files with 22 additions and 7 deletions
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21
api/core/workflow/nodes/question_classifier/question_classifier_node.py
View File

@ -129,7 +129,7 @@ class QuestionClassifierNode(LLMNode):
:return:
"""
prompt_transform = AdvancedPromptTransform()
prompt_template = self._get_prompt_template(node_data, query)
prompt_template = self._get_prompt_template(node_data, query, memory)
prompt_messages = prompt_transform.get_prompt(
prompt_template=prompt_template,
inputs={},
@ -137,14 +137,15 @@ class QuestionClassifierNode(LLMNode):
files=[],
context=context,
memory_config=node_data.memory,
memory=memory,
memory=None,
model_config=model_config
)
stop = model_config.stop
return prompt_messages, stop
def _get_prompt_template(self, node_data: QuestionClassifierNodeData, query: str) \
def _get_prompt_template(self, node_data: QuestionClassifierNodeData, query: str,
memory: Optional[TokenBufferMemory]) \
-> Union[list[ChatModelMessage], CompletionModelPromptTemplate]:
model_mode = ModelMode.value_of(node_data.model.mode)
classes = node_data.classes
@ -152,12 +153,15 @@ class QuestionClassifierNode(LLMNode):
class_names_str = ','.join(class_names)
instruction = node_data.instruction if node_data.instruction else ''
input_text = query
memory_str = ''
if memory:
memory_str = memory.get_history_prompt_text(max_token_limit=2000,
message_limit=node_data.memory.window.size)
prompt_messages = []
if model_mode == ModelMode.CHAT:
system_prompt_messages = ChatModelMessage(
role=PromptMessageRole.SYSTEM,
text=QUESTION_CLASSIFIER_SYSTEM_PROMPT
text=QUESTION_CLASSIFIER_SYSTEM_PROMPT.format(histories=memory_str)
)
prompt_messages.append(system_prompt_messages)
user_prompt_message_1 = ChatModelMessage(
@ -182,14 +186,17 @@ class QuestionClassifierNode(LLMNode):
prompt_messages.append(assistant_prompt_message_2)
user_prompt_message_3 = ChatModelMessage(
role=PromptMessageRole.USER,
text=QUESTION_CLASSIFIER_USER_PROMPT_3.format(input_text=input_text, categories=class_names_str,
text=QUESTION_CLASSIFIER_USER_PROMPT_3.format(input_text=input_text,
categories=class_names_str,
classification_instructions=instruction)
)
prompt_messages.append(user_prompt_message_3)
return prompt_messages
elif model_mode == ModelMode.COMPLETION:
return CompletionModelPromptTemplate(
text=QUESTION_CLASSIFIER_COMPLETION_PROMPT.format(input_text=input_text, categories=class_names_str,
text=QUESTION_CLASSIFIER_COMPLETION_PROMPT.format(histories=memory_str,
input_text=input_text,
categories=class_names_str,
classification_instructions=instruction)
)

8
api/core/workflow/nodes/question_classifier/template_prompts.py
View File

@ -9,6 +9,11 @@ QUESTION_CLASSIFIER_SYSTEM_PROMPT = """
The input text is in the variable text_field.Categories are specified as a comma-separated list in the variable categories or left empty for automatic determination.Classification instructions may be included to improve the classification accuracy.
### Constraint
DO NOT include anything other than the JSON array in your response.
### Memory
Here is the chat histories between human and assistant, inside <histories></histories> XML tags.
<histories>
{histories}
</histories>
"""
QUESTION_CLASSIFIER_USER_PROMPT_1 = """
@ -58,6 +63,9 @@ Assistant:{{"keywords": ["recently", "great experience", "company", "service", "
</example>
### Memory
Here is the chat histories between human and assistant, inside <histories></histories> XML tags.
<histories>
{histories}
</histories>
### User Input
{{"input_text" : ["{input_text}"], "categories" : ["{categories}"],"classification_instruction" : ["{classification_instructions}"]}}
### Assistant Output