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from logger import logger
from typing import Dict, Any, Union
import streamlit as st
from backend.constants.myscale_tables import MYSCALE_TABLES
from backend.constants.variables import CHAINS_RETRIEVERS_MAPPING
from backend.construct.build_chains import build_retrieval_qa_with_sources_chain
from backend.construct.build_retriever_tool import create_retriever_tool
from backend.construct.build_retrievers import build_self_query_retriever, build_vector_sql_db_chain_retriever
from backend.types.chains_and_retrievers import ChainsAndRetrievers, MetadataColumn
from langchain_community.embeddings import HuggingFaceEmbeddings, HuggingFaceInstructEmbeddings, \
SentenceTransformerEmbeddings
@st.cache_resource
def load_embedding_model_for_table(table_name: str) -> \
Union[SentenceTransformerEmbeddings, HuggingFaceInstructEmbeddings]:
with st.spinner(f"Loading embedding models for [{table_name}] ..."):
embeddings = MYSCALE_TABLES[table_name].emb_model()
return embeddings
@st.cache_resource
def load_embedding_models() -> Dict[str, Union[HuggingFaceEmbeddings, HuggingFaceInstructEmbeddings]]:
embedding_models = {}
for table in MYSCALE_TABLES:
embedding_models[table] = load_embedding_model_for_table(table)
return embedding_models
@st.cache_resource
def update_retriever_tools():
retrievers_tools = {}
for table in MYSCALE_TABLES:
logger.info(f"Updating retriever tools [<retriever>, <sql_retriever>] for table {table}")
retrievers_tools.update(
{
f"{table} + Self Querying": create_retriever_tool(
st.session_state[CHAINS_RETRIEVERS_MAPPING][table]["retriever"],
*MYSCALE_TABLES[table].tool_desc
),
f"{table} + Vector SQL": create_retriever_tool(
st.session_state[CHAINS_RETRIEVERS_MAPPING][table]["sql_retriever"],
*MYSCALE_TABLES[table].tool_desc
),
})
return retrievers_tools
@st.cache_resource
def build_chains_retriever_for_table(table_name: str) -> ChainsAndRetrievers:
metadata_col_attributes = MYSCALE_TABLES[table_name].metadata_col_attributes
self_query_retriever = build_self_query_retriever(table_name)
self_query_chain = build_retrieval_qa_with_sources_chain(
table_name=table_name,
retriever=self_query_retriever,
chain_name="Self Query Retriever"
)
vector_sql_retriever = build_vector_sql_db_chain_retriever(table_name)
vector_sql_chain = build_retrieval_qa_with_sources_chain(
table_name=table_name,
retriever=vector_sql_retriever,
chain_name="Vector SQL DB Retriever"
)
metadata_columns = [
MetadataColumn(
name=attribute.name,
desc=attribute.description,
type=attribute.type
)
for attribute in metadata_col_attributes
]
return ChainsAndRetrievers(
metadata_columns=metadata_columns,
# for self query
retriever=self_query_retriever,
chain=self_query_chain,
# for vector sql
sql_retriever=vector_sql_retriever,
sql_chain=vector_sql_chain
)
@st.cache_resource
def build_chains_and_retrievers() -> Dict[str, Dict[str, Any]]:
chains_and_retrievers = {}
for table in MYSCALE_TABLES:
logger.info(f"Building chains, retrievers for table {table}")
chains_and_retrievers[table] = build_chains_retriever_for_table(table).to_dict()
return chains_and_retrievers
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