from khoj.processor.conversation import utils from langchain.schema import ChatMessage import factory import tiktoken class ChatMessageFactory(factory.Factory): class Meta: model = ChatMessage content = factory.Faker("paragraph") role = factory.Faker("name") class TestTruncateMessage: max_prompt_size = 4096 model_name = "gpt-3.5-turbo" encoder = tiktoken.encoding_for_model(model_name) def test_truncate_message_all_small(self): chat_messages = ChatMessageFactory.build_batch(500) tokens = sum([len(self.encoder.encode(message.content)) for message in chat_messages]) prompt = utils.truncate_messages(chat_messages, self.max_prompt_size, self.model_name) tokens = sum([len(self.encoder.encode(message.content)) for message in prompt]) # The original object has been modified. Verify certain properties assert len(chat_messages) < 500 assert len(chat_messages) > 1 assert prompt == chat_messages assert tokens <= self.max_prompt_size def test_truncate_message_first_large(self): chat_messages = ChatMessageFactory.build_batch(25) big_chat_message = ChatMessageFactory.build(content=factory.Faker("paragraph", nb_sentences=2000)) big_chat_message.content = big_chat_message.content + "\n" + "Question?" copy_big_chat_message = big_chat_message.copy() chat_messages.insert(0, big_chat_message) tokens = sum([len(self.encoder.encode(message.content)) for message in chat_messages]) prompt = utils.truncate_messages(chat_messages, self.max_prompt_size, self.model_name) tokens = sum([len(self.encoder.encode(message.content)) for message in prompt]) # The original object has been modified. Verify certain properties assert len(chat_messages) == 1 assert prompt[0] != copy_big_chat_message assert tokens <= self.max_prompt_size def test_truncate_message_last_large(self): chat_messages = ChatMessageFactory.build_batch(25) big_chat_message = ChatMessageFactory.build(content=factory.Faker("paragraph", nb_sentences=1000)) big_chat_message.content = big_chat_message.content + "\n" + "Question?" copy_big_chat_message = big_chat_message.copy() chat_messages.append(big_chat_message) tokens = sum([len(self.encoder.encode(message.content)) for message in chat_messages]) prompt = utils.truncate_messages(chat_messages, self.max_prompt_size, self.model_name) tokens = sum([len(self.encoder.encode(message.content)) for message in prompt]) # The original object has been modified. Verify certain properties assert len(chat_messages) < 26 assert len(chat_messages) > 1 assert prompt[0] != copy_big_chat_message assert tokens <= self.max_prompt_size