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feature:add markdown embedding

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chenketing
2023-05-14 23:26:05 +08:00
parent 8ee288a8fd
commit 293ba94d22
4 changed files with 69 additions and 5 deletions
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7
pilot/server/webserver.py
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@@ -14,7 +14,7 @@ from urllib.parse import urljoin
from pilot.configs.model_config import DB_SETTINGS, KNOWLEDGE_UPLOAD_ROOT_PATH, MODEL_NAME_PATH, VS_ROOT_PATH
from pilot.server.vectordb_qa import KnownLedgeBaseQA
from pilot.connections.mysql import MySQLOperator
from pilot.source_embedding.pdf_embedding import PDFEmbedding
from pilot.source_embedding.knowledge_embedding import KnowledgeEmbedding
from pilot.vector_store.extract_tovec import get_vector_storelist, load_knownledge_from_doc, knownledge_tovec_st
from pilot.configs.model_config import LOGDIR, VICUNA_MODEL_SERVER, LLM_MODEL, DATASETS_DIR
@@ -539,12 +539,11 @@ def knowledge_embedding_store(vs_id, files):
filename = os.path.split(file.name)[-1]
shutil.move(file.name, os.path.join(KNOWLEDGE_UPLOAD_ROOT_PATH, vs_id, filename))
knowledge_embedding = PDFEmbedding(file_path=os.path.join(KNOWLEDGE_UPLOAD_ROOT_PATH, vs_id, filename), model_name=MODEL_NAME_PATH,
vector_store_config={"vector_store_name": vs_id,
knowledge_embedding = KnowledgeEmbedding.knowledge_embedding(os.path.join(KNOWLEDGE_UPLOAD_ROOT_PATH, vs_id, filename), MODEL_NAME_PATH, {"vector_store_name": vs_id,
"vector_store_path": KNOWLEDGE_UPLOAD_ROOT_PATH})
knowledge_embedding.source_embedding()
logger.info("knowledge embedding success")
return os.path.join(KNOWLEDGE_UPLOAD_ROOT_PATH, vs_id, filename + ".vectordb")
return os.path.join(KNOWLEDGE_UPLOAD_ROOT_PATH, vs_id, vs_id + ".vectordb")
if __name__ == "__main__":