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9986c183ea
GPT-4o-mini is cheaper, smarter and can hold more context than GPT-3.5-turbo. In production, we also default to gpt-4o-mini, so makes sense to upgrade defaults and tests to work with it
115 lines
5 KiB
Python
115 lines
5 KiB
Python
import tiktoken
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from langchain.schema import ChatMessage
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from khoj.processor.conversation import utils
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class TestTruncateMessage:
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max_prompt_size = 10
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model_name = "gpt-4o-mini"
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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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# Arrange
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chat_history = generate_chat_history(50)
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# Act
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truncated_chat_history = utils.truncate_messages(chat_history, self.max_prompt_size, self.model_name)
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tokens = sum([len(self.encoder.encode(message.content)) for message in truncated_chat_history])
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# Assert
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# The original object has been modified. Verify certain properties
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assert len(chat_history) < 50
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assert len(chat_history) > 1
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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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# Arrange
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chat_history = generate_chat_history(5)
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big_chat_message = ChatMessage(role="user", content=f"{generate_content(6)}\nQuestion?")
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copy_big_chat_message = big_chat_message.copy()
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chat_history.insert(0, big_chat_message)
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tokens = sum([len(self.encoder.encode(message.content)) for message in chat_history])
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# Act
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truncated_chat_history = utils.truncate_messages(chat_history, self.max_prompt_size, self.model_name)
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tokens = sum([len(self.encoder.encode(message.content)) for message in truncated_chat_history])
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# Assert
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# The original object has been modified. Verify certain properties
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assert len(chat_history) == 1
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assert truncated_chat_history[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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# Arrange
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chat_history = generate_chat_history(5)
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chat_history[0].role = "system" # Mark the first message as system message
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big_chat_message = ChatMessage(role="user", content=f"{generate_content(11)}\nQuestion?")
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copy_big_chat_message = big_chat_message.copy()
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chat_history.insert(0, big_chat_message)
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initial_tokens = sum([len(self.encoder.encode(message.content)) for message in chat_history])
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# Act
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truncated_chat_history = utils.truncate_messages(chat_history, self.max_prompt_size, self.model_name)
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final_tokens = sum([len(self.encoder.encode(message.content)) for message in truncated_chat_history])
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# Assert
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# The original object has been modified. Verify certain properties.
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assert (
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len(truncated_chat_history) == len(chat_history) + 1
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) # Because the system_prompt is popped off from the chat_messages list
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assert len(truncated_chat_history) < 10
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assert len(truncated_chat_history) > 1
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assert truncated_chat_history[0] != copy_big_chat_message
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assert initial_tokens > self.max_prompt_size
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assert final_tokens <= self.max_prompt_size
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def test_truncate_single_large_non_system_message(self):
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# Arrange
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big_chat_message = ChatMessage(role="user", content=f"{generate_content(11)}\nQuestion?")
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copy_big_chat_message = big_chat_message.copy()
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chat_messages = [big_chat_message]
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initial_tokens = sum([len(self.encoder.encode(message.content)) for message in chat_messages])
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# Act
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truncated_chat_history = utils.truncate_messages(chat_messages, self.max_prompt_size, self.model_name)
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final_tokens = sum([len(self.encoder.encode(message.content)) for message in truncated_chat_history])
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# Assert
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# The original object has been modified. Verify certain properties
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assert initial_tokens > self.max_prompt_size
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assert final_tokens <= self.max_prompt_size
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assert len(chat_messages) == 1
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assert truncated_chat_history[0] != copy_big_chat_message
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def test_truncate_single_large_question(self):
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# Arrange
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big_chat_message_content = " ".join(["hi"] * (self.max_prompt_size + 1))
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big_chat_message = ChatMessage(role="user", content=big_chat_message_content)
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copy_big_chat_message = big_chat_message.copy()
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chat_messages = [big_chat_message]
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initial_tokens = sum([len(self.encoder.encode(message.content)) for message in chat_messages])
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# Act
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truncated_chat_history = utils.truncate_messages(chat_messages, self.max_prompt_size, self.model_name)
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final_tokens = sum([len(self.encoder.encode(message.content)) for message in truncated_chat_history])
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# Assert
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# The original object has been modified. Verify certain properties
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assert initial_tokens > self.max_prompt_size
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assert final_tokens <= self.max_prompt_size
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assert len(chat_messages) == 1
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assert truncated_chat_history[0] != copy_big_chat_message
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def generate_content(count):
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return " ".join([f"{index}" for index, _ in enumerate(range(count))])
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def generate_chat_history(count):
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return [
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ChatMessage(role="user" if index % 2 == 0 else "assistant", content=f"{index}")
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for index, _ in enumerate(range(count))
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]
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