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feature:knowledge embedding update

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aries-ckt 2023-05-18 20:23:06 +08:00
parent 2656a8030e
commit c82907c963
1 changed files with 2 additions and 2 deletions
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pilot/server/webserver.py
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@ -19,7 +19,7 @@ from langchain import PromptTemplate
ROOT_PATH = os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__)))) ROOT_PATH = os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
sys.path.append(ROOT_PATH) 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.server.vectordb_qa import KnownLedgeBaseQA
from pilot.connections.mysql import MySQLOperator from pilot.connections.mysql import MySQLOperator
from pilot.source_embedding.knowledge_embedding import KnowledgeEmbedding 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_config={"vector_store_name": vector_store_name["vs_name"],
"vector_store_path": KNOWLEDGE_UPLOAD_ROOT_PATH}) "vector_store_path": KNOWLEDGE_UPLOAD_ROOT_PATH})
query = state.messages[-2][1] 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] context = [d.page_content for d in docs]
prompt_template = PromptTemplate( prompt_template = PromptTemplate(
template=conv_qa_prompt_template, template=conv_qa_prompt_template,