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from typing import Optional
from core.app.entities.app_invoke_entities import ModelConfigWithCredentialsEntity
from core.memory.token_buffer_memory import TokenBufferMemory
from core.model_manager import ModelInstance
from core.model_runtime.entities.message_entities import PromptMessage
from core.model_runtime.entities.model_entities import ModelPropertyKey
from core.prompt.entities.advanced_prompt_entities import MemoryConfig
class PromptTransform:
def _append_chat_histories(
self,
memory: TokenBufferMemory,
memory_config: MemoryConfig,
prompt_messages: list[PromptMessage],
model_config: ModelConfigWithCredentialsEntity,
) -> list[PromptMessage]:
rest_tokens = self._calculate_rest_token(prompt_messages, model_config)
histories = self._get_history_messages_list_from_memory(memory, memory_config, rest_tokens)
prompt_messages.extend(histories)
return prompt_messages
def _calculate_rest_token(
self, prompt_messages: list[PromptMessage], model_config: ModelConfigWithCredentialsEntity
) -> int:
rest_tokens = 2000
model_context_tokens = model_config.model_schema.model_properties.get(ModelPropertyKey.CONTEXT_SIZE)
if model_context_tokens:
model_instance = ModelInstance(
provider_model_bundle=model_config.provider_model_bundle, model=model_config.model
)
curr_message_tokens = model_instance.get_llm_num_tokens(prompt_messages)
max_tokens = 0
for parameter_rule in model_config.model_schema.parameter_rules:
if parameter_rule.name == "max_tokens" or (
parameter_rule.use_template and parameter_rule.use_template == "max_tokens"
):
max_tokens = (
model_config.parameters.get(parameter_rule.name)
or model_config.parameters.get(parameter_rule.use_template)
) or 0
rest_tokens = model_context_tokens - max_tokens - curr_message_tokens
rest_tokens = max(rest_tokens, 0)
return rest_tokens
def _get_history_messages_from_memory(
self,
memory: TokenBufferMemory,
memory_config: MemoryConfig,
max_token_limit: int,
human_prefix: Optional[str] = None,
ai_prefix: Optional[str] = None,
) -> str:
"""Get memory messages."""
kwargs = {"max_token_limit": max_token_limit}
if human_prefix:
kwargs["human_prefix"] = human_prefix
if ai_prefix:
kwargs["ai_prefix"] = ai_prefix
if memory_config.window.enabled and memory_config.window.size is not None and memory_config.window.size > 0:
kwargs["message_limit"] = memory_config.window.size
return memory.get_history_prompt_text(**kwargs)
def _get_history_messages_list_from_memory(
self, memory: TokenBufferMemory, memory_config: MemoryConfig, max_token_limit: int
) -> list[PromptMessage]:
"""Get memory messages."""
return memory.get_history_prompt_messages(
max_token_limit=max_token_limit,
message_limit=memory_config.window.size
if (
memory_config.window.enabled and memory_config.window.size is not None and memory_config.window.size > 0
)
else None,
)
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