PGVector with Agents for querying a DB #78
Description
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