mirror of
https://github.com/JasonYANG170/CodeGeeX4.git
synced 2024-11-23 20:26:29 +00:00
58 lines
2.4 KiB
Python
58 lines
2.4 KiB
Python
|
from typing import Iterator
|
||
|
|
|
||
|
|
import torch
|
||
|
|
from langchain_core.language_models.chat_models import BaseChatModel
|
||
|
|
from langchain_core.messages import BaseMessage, AIMessageChunk
|
||
|
|
from langchain_core.outputs import ChatGenerationChunk, ChatResult, ChatGeneration
|
||
|
|
from pydantic import Field
|
||
|
|
from transformers import AutoModel, AutoTokenizer
|
||
|
|
from utils.prompts import SYS_PROMPT
|
||
|
|
|
||
|
|
|
||
|
|
class CodegeexChatModel(BaseChatModel):
|
||
|
|
device: str = Field(description="device to load the model")
|
||
|
|
tokenizer = Field(description="model's tokenizer")
|
||
|
|
model = Field(description="Codegeex model")
|
||
|
|
temperature: float = Field(description="temperature to use for the model.")
|
||
|
|
|
||
|
|
def __init__(self, args):
|
||
|
|
super().__init__()
|
||
|
|
self.device = args.device
|
||
|
|
self.tokenizer = AutoTokenizer.from_pretrained(args.model_name_or_path, trust_remote_code=True)
|
||
|
|
self.model = AutoModel.from_pretrained(
|
||
|
|
args.model_name_or_path,
|
||
|
|
trust_remote_code=True
|
||
|
|
).to(args.device).eval()
|
||
|
|
self.temperature = args.temperature
|
||
|
|
print("Model has been initialized.")
|
||
|
|
|
||
|
|
def _llm_type(self) -> str:
|
||
|
|
return "codegeex"
|
||
|
|
|
||
|
|
@torch.inference_mode()
|
||
|
|
def _generate(self, messages, **kwargs):
|
||
|
|
try:
|
||
|
|
response, _ = self.model.chat(
|
||
|
|
self.tokenizer,
|
||
|
|
query=messages[0].content,
|
||
|
|
history=[{"role": "system", "content": SYS_PROMPT}],
|
||
|
|
max_new_tokens=1024,
|
||
|
|
temperature=self.temperature
|
||
|
|
)
|
||
|
|
return ChatResult(generations=[ChatGeneration(message=BaseMessage(content=response, type='ai'))])
|
||
|
|
except Exception as e:
|
||
|
|
return ChatResult(generations=[ChatGeneration(message=BaseMessage(content=repr(e), type='ai'))])
|
||
|
|
|
||
|
|
def _stream(self, messages: list[BaseMessage], **kwargs) -> Iterator[ChatGenerationChunk]:
|
||
|
|
try:
|
||
|
|
for response, _ in self.model.stream_chat(
|
||
|
|
self.tokenizer,
|
||
|
|
query=messages[0].content,
|
||
|
|
history=[{"role": "system", "content": SYS_PROMPT}],
|
||
|
|
max_new_tokens=1024,
|
||
|
|
temperature=self.temperature
|
||
|
|
):
|
||
|
|
yield ChatGenerationChunk(message=AIMessageChunk(content=response))
|
||
|
|
except Exception as e:
|
||
|
|
yield ChatGenerationChunk(message=AIMessageChunk(content=f"Fail to generate, cause by {e}"))
|