Files
DB-GPT/pilot/source_embedding/knowledge_embedding.py
2023-05-15 22:12:50 +08:00

34 lines
1.7 KiB
Python

from pilot.source_embedding.csv_embedding import CSVEmbedding
from pilot.source_embedding.markdown_embedding import MarkdownEmbedding
from pilot.source_embedding.pdf_embedding import PDFEmbedding
class KnowledgeEmbedding:
def __init__(self, file_path, model_name, vector_store_config):
"""Initialize with Loader url, model_name, vector_store_config"""
self.file_path = file_path
self.model_name = model_name
self.vector_store_config = vector_store_config
self.vector_store_type = "default"
self.knowledge_embedding_client = self.init_knowledge_embedding()
def knowledge_embedding(self):
self.knowledge_embedding_client.source_embedding()
def init_knowledge_embedding(self):
if self.file_path.endswith(".pdf"):
embedding = PDFEmbedding(file_path=self.file_path, model_name=self.model_name,
vector_store_config=self.vector_store_config)
elif self.file_path.endswith(".md"):
embedding = MarkdownEmbedding(file_path=self.file_path, model_name=self.model_name, vector_store_config=self.vector_store_config)
elif self.file_path.endswith(".csv"):
embedding = CSVEmbedding(file_path=self.file_path, model_name=self.model_name,
vector_store_config=self.vector_store_config)
elif self.vector_store_type == "default":
embedding = MarkdownEmbedding(file_path=self.file_path, model_name=self.model_name, vector_store_config=self.vector_store_config)
return embedding
def similar_search(self, text, topk):
return self.knowledge_embedding_client.similar_search(text, topk)