github/DB-GPT
1
0
Fork 0
mirror of https://github.com/csunny/DB-GPT.git synced 2025-07-24 12:45:45 +00:00
Code Issues Packages Projects Releases Wiki Activity

feature:knowledge embedding update

Browse Source
This commit is contained in:
aries-ckt 2023-05-18 20:23:06 +08:00
parent 2656a8030e
commit c82907c963
1 changed files with 2 additions and 2 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

4
pilot/server/webserver.py
View File

@ -19,7 +19,7 @@ from langchain import PromptTemplate
ROOT_PATH = os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
sys.path.append(ROOT_PATH)
from pilot.configs.model_config import DB_SETTINGS, KNOWLEDGE_UPLOAD_ROOT_PATH, LLM_MODEL_CONFIG, TOP_RETURN_SIZE
from pilot.configs.model_config import DB_SETTINGS, KNOWLEDGE_UPLOAD_ROOT_PATH, LLM_MODEL_CONFIG, VECTOR_SEARCH_TOP_K
from pilot.server.vectordb_qa import KnownLedgeBaseQA
from pilot.connections.mysql import MySQLOperator
from pilot.source_embedding.knowledge_embedding import KnowledgeEmbedding
@ -262,7 +262,7 @@ def http_bot(state, mode, sql_mode, db_selector, temperature, max_new_tokens, re
vector_store_config={"vector_store_name": vector_store_name["vs_name"],
"vector_store_path": KNOWLEDGE_UPLOAD_ROOT_PATH})
query = state.messages[-2][1]
docs = knowledge_embedding_client.similar_search(query, TOP_RETURN_SIZE)
docs = knowledge_embedding_client.similar_search(query, VECTOR_SEARCH_TOP_K)
context = [d.page_content for d in docs]
prompt_template = PromptTemplate(
template=conv_qa_prompt_template,