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|
import hashlib
import os
from typing import List
import psycopg
from langchain_core.documents.base import Document
TABLES = """
CREATE TABLE IF NOT EXISTS chunk (
id serial PRIMARY KEY,
data text)
CREATE TABLE IF NOT EXISTS document (
hash text PRIMARY KEY)
"""
class Documents:
def __init__(self) -> None:
self.conn = psycopg.connect(
f"dbname={os.environ['RAG_DB_NAME']} user={os.environ['RAG_USER']}"
)
self.__create_content_table()
def close(self):
self.conn.close()
def __create_content_table(self):
with self.conn.cursor() as cur:
cur.execute(TABLES)
self.conn.commit()
def __hash(self, chunks: List[Document]) -> str:
document = str.encode("".join([chunk.page_content for chunk in chunks]))
return hashlib.sha256(document).hexdigest()
def add_document(self, chunks: List[Document]) -> bool:
with self.conn.cursor() as cur:
hash = self.__hash(chunks)
cur.execute(
"""
SELECT * FROM document
WHERE
hash = %s
""",
hash,
)
exist = cur.fetchone()
if exist is None:
cur.execute(
"""
INSERT INTO document
(hash) VALUES
(%s)
""",
hash,
)
self.conn.commit()
return exist is not None
def add_chunk(self, data: str):
with self.conn.cursor() as cur:
cur.execute(
"""
INSERT INTO chunk
(data) VALUES
(%s)
""",
data,
)
self.conn.commit()
def get_chunk(self, id: int):
with self.conn.cursor() as cur:
cur.execute(
"""
SELECT * FROM chunk
WHERE
id = %s
""",
str(id),
)
chunk = cur.fetchone()
self.conn.commit()
return chunk
|
