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LLaMA-Factory-310P3
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fix data entry

This commit is contained in:
hiyouga 2024-02-23 18:29:24 +08:00
parent 6bf4c1274f
commit 354f13c01a
5 changed files with 37 additions and 34 deletions
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21
src/llmtuner/api/app.py
View File

@ -75,11 +75,11 @@ def create_app(chat_model: "ChatModel") -> "FastAPI":
semaphore = asyncio.Semaphore(int(os.environ.get("MAX_CONCURRENT", 1)))
role_mapping = {
Role.USER: DataRole.USER,
Role.ASSISTANT: DataRole.ASSISTANT,
Role.SYSTEM: DataRole.SYSTEM,
Role.FUNCTION: DataRole.FUNCTION,
Role.TOOL: DataRole.OBSERVATION,
Role.USER: DataRole.USER.value,
Role.ASSISTANT: DataRole.ASSISTANT.value,
Role.SYSTEM: DataRole.SYSTEM.value,
Role.FUNCTION: DataRole.FUNCTION.value,
Role.TOOL: DataRole.OBSERVATION.value,
}
@app.get("/v1/models", response_model=ModelList)
@ -95,7 +95,7 @@ def create_app(chat_model: "ChatModel") -> "FastAPI":
if len(request.messages) == 0:
raise HTTPException(status_code=status.HTTP_400_BAD_REQUEST, detail="Invalid length")
if role_mapping[request.messages[0].role] == DataRole.SYSTEM:
if request.messages[0].role == Role.SYSTEM:
system = request.messages.pop(0).content
else:
system = ""
@ -105,11 +105,12 @@ def create_app(chat_model: "ChatModel") -> "FastAPI":
input_messages = []
for i, message in enumerate(request.messages):
if i % 2 == 0 and message.role not in [Role.USER, Role.TOOL]:
raise HTTPException(status_code=status.HTTP_400_BAD_REQUEST, detail="Invalid role")
elif i % 2 == 1 and message.role not in [Role.ASSISTANT, Role.FUNCTION]:
raise HTTPException(status_code=status.HTTP_400_BAD_REQUEST, detail="Invalid role")
input_messages.append({"role": role_mapping[message.role], "content": message.content})
if i % 2 == 0 and input_messages[i]["role"] not in [DataRole.USER, DataRole.OBSERVATION]:
raise HTTPException(status_code=status.HTTP_400_BAD_REQUEST, detail="Invalid role")
elif i % 2 == 1 and input_messages[i]["role"] not in [DataRole.ASSISTANT, DataRole.FUNCTION]:
raise HTTPException(status_code=status.HTTP_400_BAD_REQUEST, detail="Invalid role")
tool_list = request.tools
if isinstance(tool_list, list) and len(tool_list):

22
src/llmtuner/data/aligner.py
View File

@ -19,8 +19,8 @@ def convert_alpaca(examples: Dict[str, List[Any]], dataset_attr: "DatasetAttr")
prompt = []
if dataset_attr.history and isinstance(examples[dataset_attr.history][i], list):
for old_prompt, old_response in examples[dataset_attr.history][i]:
prompt.append({"role": Role.USER, "content": old_prompt})
prompt.append({"role": Role.ASSISTANT, "content": old_response})
prompt.append({"role": Role.USER.value, "content": old_prompt})
prompt.append({"role": Role.ASSISTANT.value, "content": old_response})
content = []
if dataset_attr.prompt and examples[dataset_attr.prompt][i]:
@ -29,12 +29,14 @@ def convert_alpaca(examples: Dict[str, List[Any]], dataset_attr: "DatasetAttr")
if dataset_attr.query and examples[dataset_attr.query][i]:
content.append(examples[dataset_attr.query][i])
prompt.append({"role": Role.USER, "content": "\n".join(content)})
prompt.append({"role": Role.USER.value, "content": "\n".join(content)})
if dataset_attr.response and isinstance(examples[dataset_attr.response][i], list):
response = [{"role": Role.ASSISTANT, "content": content} for content in examples[dataset_attr.response][i]]
response = [
{"role": Role.ASSISTANT.value, "content": content} for content in examples[dataset_attr.response][i]
]
elif dataset_attr.response and isinstance(examples[dataset_attr.response][i], str):
response = [{"role": Role.ASSISTANT, "content": examples[dataset_attr.response][i]}]
response = [{"role": Role.ASSISTANT.value, "content": examples[dataset_attr.response][i]}]
else:
response = []
@ -49,11 +51,11 @@ def convert_alpaca(examples: Dict[str, List[Any]], dataset_attr: "DatasetAttr")
def convert_sharegpt(examples: Dict[str, List[Any]], dataset_attr: "DatasetAttr") -> Dict[str, List[Any]]:
outputs = {"prompt": [], "response": [], "system": [], "tools": []}
tag_mapping = {
dataset_attr.user_tag: Role.USER,
dataset_attr.assistant_tag: Role.ASSISTANT,
dataset_attr.observation_tag: Role.OBSERVATION,
dataset_attr.function_tag: Role.FUNCTION,
dataset_attr.system_tag: Role.SYSTEM,
dataset_attr.user_tag: Role.USER.value,
dataset_attr.assistant_tag: Role.ASSISTANT.value,
dataset_attr.observation_tag: Role.OBSERVATION.value,
dataset_attr.function_tag: Role.FUNCTION.value,
dataset_attr.system_tag: Role.SYSTEM.value,
}
odd_tags = (dataset_attr.user_tag, dataset_attr.observation_tag)
even_tags = (dataset_attr.assistant_tag, dataset_attr.function_tag)

2
src/llmtuner/data/preprocess.py
View File

@ -146,7 +146,7 @@ def preprocess_unsupervised_dataset(
if len(examples["response"][i]) == 1:
messages = examples["prompt"][i] + examples["response"][i]
else:
messages = examples["prompt"][i] + [{"role": Role.ASSISTANT, "content": ""}]
messages = examples["prompt"][i] + [{"role": Role.ASSISTANT.value, "content": ""}]
input_ids, labels = template.encode_oneturn(
tokenizer,

20
src/llmtuner/data/template.py
View File

@ -88,16 +88,16 @@ class Template:
elif i > 0 and i % 2 == 0:
elements += self.format_separator.apply()
if message["role"] == Role.USER:
if message["role"] == Role.USER.value:
elements += self.format_user.apply(content=message["content"], idx=str(i // 2))
elif message["role"] == Role.ASSISTANT:
elif message["role"] == Role.ASSISTANT.value:
elements += self.format_assistant.apply(content=message["content"])
elif message["role"] == Role.OBSERVATION:
elif message["role"] == Role.OBSERVATION.value:
elements += self.format_observation.apply(content=message["content"])
elif message["role"] == Role.FUNCTION:
elif message["role"] == Role.FUNCTION.value:
elements += self.format_function.apply(content=message["content"])
else:
raise NotImplementedError
raise NotImplementedError("Unexpected role: {}".format(message["role"]))
encoded_messages.append(self._convert_elements_to_ids(tokenizer, elements))
@ -179,16 +179,16 @@ class Llama2Template(Template):
elif i > 0 and i % 2 == 0:
elements += self.format_separator.apply()
if message["role"] == Role.USER:
if message["role"] == Role.USER.value:
elements += self.format_user.apply(content=system_text + message["content"])
elif message["role"] == Role.ASSISTANT:
elif message["role"] == Role.ASSISTANT.value:
elements += self.format_assistant.apply(content=message["content"])
elif message["role"] == Role.OBSERVATION:
elif message["role"] == Role.OBSERVATION.value:
elements += self.format_observation.apply(content=message["content"])
elif message["role"] == Role.FUNCTION:
elif message["role"] == Role.FUNCTION.value:
elements += self.format_function.apply(content=message["content"])
else:
raise NotImplementedError
raise NotImplementedError("Unexpected role: {}".format(message["role"]))
encoded_messages.append(self._convert_elements_to_ids(tokenizer, elements))

6
src/llmtuner/webui/chatter.py
View File

@ -115,7 +115,7 @@ class WebChatModel(ChatModel):
temperature: float,
) -> Generator[Tuple[Sequence[Tuple[str, str]], Sequence[Tuple[str, str]]], None, None]:
chatbot.append([query, ""])
query_messages = messages + [{"role": Role.USER, "content": query}]
query_messages = messages + [{"role": Role.USER.value, "content": query}]
response = ""
for new_text in self.stream_chat(
query_messages, system, tools, max_new_tokens=max_new_tokens, top_p=top_p, temperature=temperature
@ -130,10 +130,10 @@ class WebChatModel(ChatModel):
name, arguments = result
arguments = json.loads(arguments)
tool_call = json.dumps({"name": name, "arguments": arguments}, ensure_ascii=False)
output_messages = query_messages + [{"role": Role.FUNCTION, "content": tool_call}]
output_messages = query_messages + [{"role": Role.FUNCTION.value, "content": tool_call}]
bot_text = "```json\n" + tool_call + "\n```"
else:
output_messages = query_messages + [{"role": Role.ASSISTANT, "content": result}]
output_messages = query_messages + [{"role": Role.ASSISTANT.value, "content": result}]
bot_text = result
chatbot[-1] = [query, self.postprocess(bot_text)]