Spaces:
Sleeping
Sleeping
fix: 修复缓存权限和根路径404问题
Browse files- modules/ai_model.py +44 -14
modules/ai_model.py
CHANGED
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@@ -15,6 +15,9 @@ class AIModel:
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self.model_name = model_name
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self.model = None
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self.processor = None
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self._initialize_model()
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def _setup_cache_dirs(self):
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@@ -30,43 +33,70 @@ class AIModel:
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log.info(f"设置缓存目录: {cache_dir}")
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def _authenticate_hf(self):
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try:
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#
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if
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cache_dir = "/app/.cache/huggingface"
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login(token=
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log.info("✅ HuggingFace 认证成功")
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else:
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log.
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except Exception as e:
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log.error(f"❌ HuggingFace 认证失败: {e}")
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def _initialize_model(self):
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"""初始化Gemma模型
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try:
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log.info(f"正在加载模型: {self.model_name}")
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cache_dir = "/app/.cache/huggingface"
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self.model = Gemma3nForConditionalGeneration.from_pretrained(
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self.model_name,
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device_map="auto",
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torch_dtype=torch.bfloat16,
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).eval()
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self.processor = AutoProcessor.from_pretrained(
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self.model_name,
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trust_remote_code=True,
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)
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log.info("✅ Gemma AI 模型初始化成功")
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self.model_name = model_name
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self.model = None
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self.processor = None
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# 设置缓存目录
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self._setup_cache_dirs()
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self._initialize_model()
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def _setup_cache_dirs(self):
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log.info(f"设置缓存目录: {cache_dir}")
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def _authenticate_hf(self):
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"""HuggingFace认证"""
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try:
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# 检查所有可能的环境变量
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assitant_token = os.getenv("Assitant_tocken")
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hf_token = os.getenv("HUGGINGFACE_HUB_TOKEN")
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hf_token_alt = os.getenv("HF_TOKEN")
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log.info("=== 环境变量调试 ===")
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log.info(f"Assitant_tocken: {'存在' if assitant_token else '不存在'}")
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log.info(f"HUGGINGFACE_HUB_TOKEN: {'存在' if hf_token else '不存在'}")
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log.info(f"HF_TOKEN: {'存在' if hf_token_alt else '不存在'}")
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# 使用找到的token
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token_to_use = assitant_token or hf_token or hf_token_alt
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if token_to_use:
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log.info(f"使用token: {token_to_use[:10]}...")
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# 设置缓存目录用于认证
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cache_dir = "/app/.cache/huggingface"
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login(token=token_to_use, add_to_git_credential=False)
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log.info("✅ HuggingFace 认证成功")
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return token_to_use
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else:
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log.error("❌ 未找到任何有效的 HuggingFace token")
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return None
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except Exception as e:
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log.error(f"❌ HuggingFace 认证失败: {e}")
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return None
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def _initialize_model(self):
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"""初始化Gemma模型"""
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try:
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log.info(f"正在加载模型: {self.model_name}")
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# 先进行认证并获取token
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token = self._authenticate_hf()
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if not token:
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log.error("❌ 无法获取有效token,模型加载失败")
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self.model = None
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self.processor = None
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return
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# 设置缓存目录
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cache_dir = "/app/.cache/huggingface"
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self.model = Gemma3nForConditionalGeneration.from_pretrained(
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self.model_name,
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device_map="auto",
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torch_dtype=torch.bfloat16,
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trust_remote_code=True,
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token=token,
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cache_dir=cache_dir, # 明确指定缓存目录
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use_auth_token=token
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).eval()
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self.processor = AutoProcessor.from_pretrained(
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self.model_name,
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trust_remote_code=True,
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token=token,
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cache_dir=cache_dir, # 明确指定缓存目录
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use_auth_token=token
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)
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log.info("✅ Gemma AI 模型初始化成功")
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