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Code Issues Packages Projects Releases Wiki Activity

feat: server multi models support (#799)

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takatost
2023-08-12 00:57:00 +08:00
committed by GitHub
parent d8b712b325
commit 5fa2161b05
213 changed files with 10556 additions and 2579 deletions
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24
api/core/memory/read_only_conversation_token_db_buffer_shared_memory.py
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@@ -1,10 +1,10 @@
from typing import Any, List, Dict, Union
from typing import Any, List, Dict
from langchain.memory.chat_memory import BaseChatMemory
from langchain.schema import get_buffer_string, BaseMessage, HumanMessage, AIMessage, BaseLanguageModel
from langchain.schema import get_buffer_string, BaseMessage
from core.llm.streamable_chat_open_ai import StreamableChatOpenAI
from core.llm.streamable_open_ai import StreamableOpenAI
from core.model_providers.models.entity.message import PromptMessage, MessageType, to_lc_messages
from core.model_providers.models.llm.base import BaseLLM
from extensions.ext_database import db
from models.model import Conversation, Message
@@ -13,7 +13,7 @@ class ReadOnlyConversationTokenDBBufferSharedMemory(BaseChatMemory):
conversation: Conversation
human_prefix: str = "Human"
ai_prefix: str = "Assistant"
llm: BaseLanguageModel
model_instance: BaseLLM
memory_key: str = "chat_history"
max_token_limit: int = 2000
message_limit: int = 10
@@ -29,23 +29,23 @@ class ReadOnlyConversationTokenDBBufferSharedMemory(BaseChatMemory):
messages = list(reversed(messages))
chat_messages: List[BaseMessage] = []
chat_messages: List[PromptMessage] = []
for message in messages:
chat_messages.append(HumanMessage(content=message.query))
chat_messages.append(AIMessage(content=message.answer))
chat_messages.append(PromptMessage(content=message.query, type=MessageType.HUMAN))
chat_messages.append(PromptMessage(content=message.answer, type=MessageType.ASSISTANT))
if not chat_messages:
return chat_messages
return []
# prune the chat message if it exceeds the max token limit
curr_buffer_length = self.llm.get_num_tokens_from_messages(chat_messages)
curr_buffer_length = self.model_instance.get_num_tokens(chat_messages)
if curr_buffer_length > self.max_token_limit:
pruned_memory = []
while curr_buffer_length > self.max_token_limit and chat_messages:
pruned_memory.append(chat_messages.pop(0))
curr_buffer_length = self.llm.get_num_tokens_from_messages(chat_messages)
curr_buffer_length = self.model_instance.get_num_tokens(chat_messages)
return chat_messages
return to_lc_messages(chat_messages)
@property
def memory_variables(self) -> List[str]: