2023-06-06 01:58:29 +00:00
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from khoj.processor.conversation import utils
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from langchain.schema import ChatMessage
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import factory
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import tiktoken
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2023-06-06 02:29:23 +00:00
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2023-06-06 01:58:29 +00:00
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class ChatMessageFactory(factory.Factory):
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class Meta:
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model = ChatMessage
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2023-06-06 02:29:23 +00:00
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content = factory.Faker("paragraph")
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role = factory.Faker("name")
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2023-06-06 01:58:29 +00:00
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class TestTruncateMessage:
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max_prompt_size = 4096
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2023-06-06 02:29:23 +00:00
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model_name = "gpt-3.5-turbo"
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2023-06-06 01:58:29 +00:00
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encoder = tiktoken.encoding_for_model(model_name)
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def test_truncate_message_all_small(self):
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chat_messages = ChatMessageFactory.build_batch(500)
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tokens = sum([len(self.encoder.encode(message.content)) for message in chat_messages])
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2023-06-07 06:25:43 +00:00
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prompt = utils.truncate_messages(chat_messages, self.max_prompt_size, self.model_name)
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tokens = sum([len(self.encoder.encode(message.content)) for message in prompt])
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2023-06-06 01:58:29 +00:00
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# The original object has been modified. Verify certain properties
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assert len(chat_messages) < 500
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assert len(chat_messages) > 1
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assert prompt == chat_messages
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assert tokens <= self.max_prompt_size
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def test_truncate_message_first_large(self):
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chat_messages = ChatMessageFactory.build_batch(25)
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2023-06-13 23:32:47 +00:00
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big_chat_message = ChatMessageFactory.build(content=factory.Faker("paragraph", nb_sentences=2000))
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2023-06-06 01:58:29 +00:00
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big_chat_message.content = big_chat_message.content + "\n" + "Question?"
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copy_big_chat_message = big_chat_message.copy()
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chat_messages.insert(0, big_chat_message)
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tokens = sum([len(self.encoder.encode(message.content)) for message in chat_messages])
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2023-06-07 06:25:43 +00:00
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prompt = utils.truncate_messages(chat_messages, self.max_prompt_size, self.model_name)
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tokens = sum([len(self.encoder.encode(message.content)) for message in prompt])
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2023-06-06 01:58:29 +00:00
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# The original object has been modified. Verify certain properties
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assert len(chat_messages) == 1
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assert prompt[0] != copy_big_chat_message
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assert tokens <= self.max_prompt_size
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def test_truncate_message_last_large(self):
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chat_messages = ChatMessageFactory.build_batch(25)
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2023-06-06 02:29:23 +00:00
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big_chat_message = ChatMessageFactory.build(content=factory.Faker("paragraph", nb_sentences=1000))
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2023-06-06 01:58:29 +00:00
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big_chat_message.content = big_chat_message.content + "\n" + "Question?"
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copy_big_chat_message = big_chat_message.copy()
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2023-06-06 02:29:23 +00:00
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2023-06-06 01:58:29 +00:00
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chat_messages.append(big_chat_message)
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tokens = sum([len(self.encoder.encode(message.content)) for message in chat_messages])
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2023-06-07 06:25:43 +00:00
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prompt = utils.truncate_messages(chat_messages, self.max_prompt_size, self.model_name)
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tokens = sum([len(self.encoder.encode(message.content)) for message in prompt])
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2023-06-06 01:58:29 +00:00
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# The original object has been modified. Verify certain properties
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assert len(chat_messages) < 26
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assert len(chat_messages) > 1
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assert prompt[0] != copy_big_chat_message
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2023-06-07 06:25:43 +00:00
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assert tokens <= self.max_prompt_size
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