embodied_explainer / handler.py
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the latest version based on inference.py
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import os
import base64
import tempfile
from inference import Chat, get_conv_template
import torch
def save_base64_to_tempfile(base64_str, suffix):
header_removed = base64_str
# 去除可能的data:image/...;base64,前缀
if ',' in base64_str:
header_removed = base64_str.split(',', 1)[1]
data = base64.b64decode(header_removed)
tmp = tempfile.NamedTemporaryFile(delete=False, suffix=suffix)
tmp.write(data)
tmp.close()
return tmp.name
class EndpointHandler:
def __init__(self, model_path: str):
device = "cuda" if torch.cuda.is_available() else "cpu"
self.chat = Chat(
model_path=model_path,
device=device,
num_gpus=1,
max_new_tokens=1024,
load_8bit=False,
)
self.vision_feature = None
self.modal_type = "text"
self.chat.conv = get_conv_template("husky").copy()
def __call__(self, data: dict) -> dict:
# reset conversation if specified
if data.get("clear_history"):
self.chat.conv = get_conv_template("husky").copy()
self.vision_feature = None
self.modal_type = "text"
prompt = data.get("inputs", "")
image_input = data.get("image", None)
video_input = data.get("video", None)
# 判断image输入是路径还是base64字符串
if image_input:
if os.path.exists(image_input):
# 直接用路径
self.vision_feature = self.chat.get_image_embedding(image_input)
else:
# base64字符串,保存临时文件再处理
tmp_path = save_base64_to_tempfile(image_input, suffix=".jpg")
self.vision_feature = self.chat.get_image_embedding(tmp_path)
os.unlink(tmp_path) # 删除临时文件
self.modal_type = "image"
self.chat.conv = get_conv_template("husky").copy()
elif video_input:
if os.path.exists(video_input):
self.vision_feature = self.chat.get_video_embedding(video_input)
else:
tmp_path = save_base64_to_tempfile(video_input, suffix=".mp4")
self.vision_feature = self.chat.get_video_embedding(tmp_path)
os.unlink(tmp_path)
self.modal_type = "video"
self.chat.conv = get_conv_template("husky").copy()
else:
self.modal_type = "text"
self.vision_feature = None
conversations = self.chat.ask(prompt, self.chat.conv, modal_type=self.modal_type)
output = self.chat.answer(conversations, self.vision_feature, modal_type=self.modal_type)
# 更新对话历史
self.chat.conv.messages[-1][1] = output.strip()
return {"output": output.strip()}