PGVector with Agents for querying a DB

[feddionisio]

langchain Documentation https://python.langchain.com/v0.1/docs/use_cases/sql/agents/

CODE from langchain_community.utilities import SQLDatabase from langchain_community.agent_toolkits import create_sql_agent from langchain_openai import AzureChatOpenAI import os from langchain_core.example_selectors import SemanticSimilarityExampleSelector from langchain_openai import AzureOpenAIEmbeddings

from langchain_postgres import PGVector from langchain_postgres.vectorstores import PGVector import os import psycopg2

os.environ["AZURE_OPENAI_API_KEY"] = "api_key" os.environ["AZURE_OPENAI_API_TYPE"] = "ap_type" os.environ["AZURE_OPENAI_ENDPOINT"] = "azure_openai_endpoint" os.environ["AZURE_OPENAI_API_VERSION"] = "2024-02-01" os.environ["AZURE_OPENAI_CHAT_DEPLOYMENT_NAME"] = "deployment_model_name"

examples = [ {"input": "Describe article name ...", "query": "SELECT compatibility FROM article ...';"} ]

AzureEmbeddings = AzureOpenAIEmbeddings(model="embedding-model-name") connection = "postgresql+psycopg://YYY:XXXX@localhost/ZZZ" collection_name = "collection_name"

vectorstore = PGVector( embeddings=AzureEmbeddings, collection_name=collection_name, connection=connection, use_jsonb=True, )

example_selector = SemanticSimilarityExampleSelector.from_examples( examples, AzureEmbeddings, vectorstore, k=5, input_keys=["input"], )

ERROR INFO File "C:\Users\user\Projects\project\langchain_sql.py", line 53, in example_selector = SemanticSimilarityExampleSelector.from_examples( File "C:\Users\user\Projects\project\venv\lib\site-packages\langchain_core\example_selectors\semantic_similarity.py", line 133, in from_examples vectorstore = vectorstore_cls.from_texts( File "C:\Users\user\Projects\project\venv\lib\site-packages\langchain_postgres\vectorstores.py", line 1496, in from_texts return cls.from( File "C:\Users\user\Projects\project\venv\lib\site-packages\langchain_postgres\vectorstores.py", line 660, in __from store = cls( File "C:\Users\user\Projects\project\venv\lib\site-packages\langchain_postgres\vectorstores.py", line 414, in init__ raise ValueError( ValueError: connection should be a connection string or an instance of sqlalchemy.engine.Engine or sqlalchemy.ext.asyncio.engine.AsyncEngine

SYSTEM INFO langchain 0.2.6 langchain-community 0.2.5 langchain-core 0.2.10 langchain-experimental 0.0.61 langchain-openai 0.1.8 langchain-postgres 0.0.9 langchain-text-splitters 0.2.1 psycopg 3.1.19 psycopg-binary 3.1.19 psycopg-pool 3.2.2 psycopg2-binary 2.9.6

COMMENTS Already tried to include or not psycopg within the connection string "postgresql+psycopg:..." the error doesn't change