File size: 4,349 Bytes
ce676f7 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 | # SPDX-FileCopyrightText: 2022-present deepset GmbH <info@deepset.ai>
#
# SPDX-License-Identifier: Apache-2.0
import pytest
from transformers import AutoTokenizer
from haystack.dataclasses import ChatMessage, ChatRole
from haystack.components.generators.openai_utils import _convert_message_to_openai_format
def test_from_assistant_with_valid_content():
content = "Hello, how can I assist you?"
message = ChatMessage.from_assistant(content)
assert message.content == content
assert message.role == ChatRole.ASSISTANT
def test_from_user_with_valid_content():
content = "I have a question."
message = ChatMessage.from_user(content)
assert message.content == content
assert message.role == ChatRole.USER
def test_from_system_with_valid_content():
content = "System message."
message = ChatMessage.from_system(content)
assert message.content == content
assert message.role == ChatRole.SYSTEM
def test_with_empty_content():
message = ChatMessage.from_user("")
assert message.content == ""
def test_from_function_with_empty_name():
content = "Function call"
message = ChatMessage.from_function(content, "")
assert message.content == content
assert message.name == ""
def test_to_openai_format():
message = ChatMessage.from_system("You are good assistant")
assert _convert_message_to_openai_format(message) == {"role": "system", "content": "You are good assistant"}
message = ChatMessage.from_user("I have a question")
assert _convert_message_to_openai_format(message) == {"role": "user", "content": "I have a question"}
message = ChatMessage.from_function("Function call", "function_name")
assert _convert_message_to_openai_format(message) == {
"role": "function",
"content": "Function call",
"name": "function_name",
}
@pytest.mark.integration
def test_apply_chat_templating_on_chat_message():
messages = [ChatMessage.from_system("You are good assistant"), ChatMessage.from_user("I have a question")]
tokenizer = AutoTokenizer.from_pretrained("HuggingFaceH4/zephyr-7b-beta")
formatted_messages = [_convert_message_to_openai_format(m) for m in messages]
tokenized_messages = tokenizer.apply_chat_template(formatted_messages, tokenize=False)
assert tokenized_messages == "<|system|>\nYou are good assistant</s>\n<|user|>\nI have a question</s>\n"
@pytest.mark.integration
def test_apply_custom_chat_templating_on_chat_message():
anthropic_template = (
"{%- for message in messages %}"
"{%- if message.role == 'user' %}\n\nHuman: {{ message.content.strip() }}"
"{%- elif message.role == 'assistant' %}\n\nAssistant: {{ message.content.strip() }}"
"{%- elif message.role == 'function' %}{{ raise('anthropic does not support function calls.') }}"
"{%- elif message.role == 'system' and loop.index == 1 %}{{ message.content }}"
"{%- else %}{{ raise('Invalid message role: ' + message.role) }}"
"{%- endif %}"
"{%- endfor %}"
"\n\nAssistant:"
)
messages = [ChatMessage.from_system("You are good assistant"), ChatMessage.from_user("I have a question")]
# could be any tokenizer, let's use the one we already likely have in cache
tokenizer = AutoTokenizer.from_pretrained("HuggingFaceH4/zephyr-7b-beta")
formatted_messages = [_convert_message_to_openai_format(m) for m in messages]
tokenized_messages = tokenizer.apply_chat_template(
formatted_messages, chat_template=anthropic_template, tokenize=False
)
assert tokenized_messages == "You are good assistant\nHuman: I have a question\nAssistant:"
def test_to_dict():
message = ChatMessage.from_user("content")
message.meta["some"] = "some"
assert message.to_dict() == {"content": "content", "role": "user", "name": None, "meta": {"some": "some"}}
def test_from_dict():
assert ChatMessage.from_dict(data={"content": "text", "role": "user", "name": None}) == ChatMessage(
content="text", role=ChatRole("user"), name=None, meta={}
)
def test_from_dict_with_meta():
assert ChatMessage.from_dict(
data={"content": "text", "role": "user", "name": None, "meta": {"something": "something"}}
) == ChatMessage(content="text", role=ChatRole("user"), name=None, meta={"something": "something"})
|