SYMBOL INDEX (70 symbols across 5 files)

FILE: RAG/Embeddings.py
  class BaseEmbeddings (line 21) | class BaseEmbeddings:
    method __init__ (line 25) | def __init__(self, path: str, is_api: bool) -> None:
    method get_embedding (line 29) | def get_embedding(self, text: str, model: str) -> List[float]:
    method cosine_similarity (line 33) | def cosine_similarity(cls, vector1: List[float], vector2: List[float])...
  class OpenAIEmbedding (line 44) | class OpenAIEmbedding(BaseEmbeddings):
    method __init__ (line 48) | def __init__(self, path: str = '', is_api: bool = True) -> None:
    method get_embedding (line 56) | def get_embedding(self, text: str, model: str = "text-embedding-3-larg...
  class JinaEmbedding (line 63) | class JinaEmbedding(BaseEmbeddings):
    method __init__ (line 67) | def __init__(self, path: str = 'jinaai/jina-embeddings-v2-base-zh', is...
    method get_embedding (line 71) | def get_embedding(self, text: str) -> List[float]:
    method load_model (line 74) | def load_model(self):
  class ZhipuEmbedding (line 84) | class ZhipuEmbedding(BaseEmbeddings):
    method __init__ (line 88) | def __init__(self, path: str = '', is_api: bool = True) -> None:
    method get_embedding (line 94) | def get_embedding(self, text: str) -> List[float]:
  class DashscopeEmbedding (line 101) | class DashscopeEmbedding(BaseEmbeddings):
    method __init__ (line 105) | def __init__(self, path: str = '', is_api: bool = True) -> None:
    method get_embedding (line 112) | def get_embedding(self, text: str, model: str='text-embedding-v1') -> ...
  class BgeEmbedding (line 120) | class BgeEmbedding(BaseEmbeddings):
    method __init__ (line 125) | def __init__(self, path: str = 'BAAI/bge-base-zh-v1.5', is_api: bool =...
    method get_embedding (line 129) | def get_embedding(self, text: str) -> List[float]:
    method load_model (line 139) | def load_model(self, path: str):
  class BgeWithAPIEmbedding (line 153) | class BgeWithAPIEmbedding(BaseEmbeddings):
    method __init__ (line 157) | def __init__(self, path: str = '', is_api: bool = True) -> None:
    method get_embedding (line 165) | def get_embedding(self, text: str, model: str = "BAAI/bge-m3") -> List...

FILE: RAG/LLM.py
  class BaseModel (line 33) | class BaseModel:
    method __init__ (line 34) | def __init__(self, path: str = '') -> None:
    method chat (line 37) | def chat(self, prompt: str, history: List[dict], content: str) -> str:
    method load_model (line 40) | def load_model(self):
  class OpenAIChat (line 43) | class OpenAIChat(BaseModel):
    method __init__ (line 44) | def __init__(self, path: str = '', model: str = "gpt-3.5-turbo-1106") ...
    method chat (line 48) | def chat(self, prompt: str, history: List[dict], content: str) -> str:
  class InternLMChat (line 62) | class InternLMChat(BaseModel):
    method __init__ (line 63) | def __init__(self, path: str = '') -> None:
    method chat (line 67) | def chat(self, prompt: str, history: List = [], content: str='') -> str:
    method load_model (line 73) | def load_model(self):
  class DashscopeChat (line 79) | class DashscopeChat(BaseModel):
    method __init__ (line 80) | def __init__(self, path: str = '', model: str = "qwen-turbo") -> None:
    method chat (line 84) | def chat(self, prompt: str, history: List[Dict], content: str) -> str:
  class ZhipuChat (line 98) | class ZhipuChat(BaseModel):
    method __init__ (line 99) | def __init__(self, path: str = '', model: str = "glm-4") -> None:
    method chat (line 105) | def chat(self, prompt: str, history: List[Dict], content: str) -> str:
  class SiliconflowChat (line 115) | class SiliconflowChat(BaseModel):
    method __init__ (line 116) | def __init__(self, path: str = '', model: str = "Qwen/Qwen2.5-7B-Instr...
    method chat (line 120) | def chat(self, prompt: str, history: List[dict], content: str) -> str:

FILE: RAG/Reranker.py
  class BaseReranker (line 15) | class BaseReranker:
    method __init__ (line 20) | def __init__(self, path: str) -> None:
    method rerank (line 23) | def rerank(self, text: str, content: List[str], k: int) -> List[str]:
  class BgeReranker (line 27) | class BgeReranker(BaseReranker):
    method __init__ (line 32) | def __init__(self, path: str = 'BAAI/bge-reranker-base') -> None:
    method rerank (line 36) | def rerank(self, text: str, content: List[str], k: int) -> List[str]:
    method load_model (line 46) | def load_model(self, path: str):

FILE: RAG/VectorBase.py
  class VectorStore (line 19) | class VectorStore:
    method __init__ (line 20) | def __init__(self, document: List[str] = ['']) -> None:
    method get_vector (line 23) | def get_vector(self, EmbeddingModel: BaseEmbeddings) -> List[List[floa...
    method persist (line 30) | def persist(self, path: str = 'storage'):
    method load_vector (line 39) | def load_vector(self, path: str = 'storage'):
    method get_similarity (line 45) | def get_similarity(self, vector1: List[float], vector2: List[float]) -...
    method query (line 48) | def query(self, query: str, EmbeddingModel: BaseEmbeddings, k: int = 1...

FILE: RAG/utils.py
  class ReadFiles (line 26) | class ReadFiles:
    method __init__ (line 31) | def __init__(self, path: str) -> None:
    method get_files (line 35) | def get_files(self):
    method get_content (line 51) | def get_content(self, max_token_len: int = 600, cover_content: int = 1...
    method get_chunk (line 62) | def get_chunk(cls, text: str, max_token_len: int = 600, cover_content:...
    method read_file_content (line 109) | def read_file_content(cls, file_path: str):
    method read_pdf (line 121) | def read_pdf(cls, file_path: str):
    method read_markdown (line 131) | def read_markdown(cls, file_path: str):
    method read_text (line 144) | def read_text(cls, file_path: str):
  class Documents (line 150) | class Documents:
    method __init__ (line 154) | def __init__(self, path: str = '') -> None:
    method get_content (line 157) | def get_content(self):