Add PostgreSQL session example using SQLAlchemy and asyncpg

01_ai_agents_first/22_sesssion_memory/postgresql_session/Readme.md

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+# PostgreSQL Session Example with SQLAlchemy and asyncpg
+
+This example demonstrates how to use SQLAlchemy with the asyncpg driver to create a conversational agent that interacts with a PostgreSQL database. The agent uses the `openai-agents` library and stores session memory in PostgreSQL.
+
+## Requirements
+
+Add the following packages to your `pyproject.toml` dependencies:
+
+- `asyncpg`
+- `sqlalchemy`
+- `openai-agents`
+
+
+## Database URL Format
+
+To use the asyncpg driver, your database URL must include `+asyncpg`:
+
+```python
+
+POSTGRES_DB_URL = "postgresql+asyncpg://test:test@test/openai_agent?sslmode=require&channel_binding=require"
+
+```
+
+## Sample Code
+
+```python
+
+from agents import Agent, AsyncOpenAI, OpenAIChatCompletionsModel, Runner
+from agents.extensions.memory.sqlalchemy_session import SQLAlchemySession
+from sqlalchemy.ext.asyncio import create_async_engine
+from dotenv import load_dotenv, find_dotenv
+import os
+
+# Load environment variables from .env file
+load_dotenv(find_dotenv())
+
+# Retrieve the API key
+GEMINI_API_KEY = os.getenv("GEMINI_API_KEY")
+
+# Initialize the external client
+externel_client = AsyncOpenAI(
+    api_key=GEMINI_API_KEY,
+    base_url="https://generativelanguage.googleapis.com/v1beta/openai/",
+)
+
+# Initialize the model
+model = OpenAIChatCompletionsModel(
+    model="gemini-2.5-flash", openai_client=externel_client
+)
+
+# Initialize the agent
+agent = Agent(name="Assistant Agent", model=model)
+
+# The PostgreSQL connection string using the asyncpg driver
+POSTGRES_DB_URL = os.getenv("POSTGRES_DB_URL")
+
+# Create a clean URL without the problematic keywords
+CLEAN_DB_URL = POSTGRES_DB_URL.split("?")[0]
+
+# Create an async SQLAlchemy engine with the SSL configuration
+# The `connect_args` dictionary passes the `ssl` parameter to asyncpg
+engine = create_async_engine(CLEAN_DB_URL, connect_args={"ssl": "require"})
+
+
+# Create a session using SQLAlchemySession, passing the engine
+session = SQLAlchemySession("conversation_123", engine=engine, create_tables=True)
+
+print("--- Running first query with PostgreSQL session ---")
+result1 = Runner.run_sync(
+    agent, "What city is the Golden Gate Bridge in?", session=session
+)
+print("Agent 01 :", result1.final_output)
+
+print("\n--- Running second query with PostgreSQL session ---")
+# The session object remembers the previous turn
+result2 = Runner.run_sync(agent, "What state is it in?", session=session)
+print("Agent 02 :", result2.final_output)
+
+```
+
+## Notes
+- The session object will remember previous turns, enabling conversational memory.
+- Make sure your database allows SSL connections as required by Neon and asyncpg.

01_ai_agents_first/22_sesssion_memory/postgresql_session/main.py

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+from agents import Agent, AsyncOpenAI, OpenAIChatCompletionsModel, Runner
+from agents.extensions.memory.sqlalchemy_session import SQLAlchemySession
+from sqlalchemy.ext.asyncio import create_async_engine
+from dotenv import load_dotenv, find_dotenv
+import os
+
+# Load environment variables from .env file
+load_dotenv(find_dotenv())
+
+# Retrieve the API key
+GEMINI_API_KEY = os.getenv("GEMINI_API_KEY")
+
+# Initialize the external client
+externel_client = AsyncOpenAI(
+    api_key=GEMINI_API_KEY,
+    base_url="https://generativelanguage.googleapis.com/v1beta/openai/",
+)
+
+# Initialize the model
+model = OpenAIChatCompletionsModel(
+    model="gemini-2.5-flash", openai_client=externel_client
+)
+
+# Initialize the agent
+agent = Agent(name="Assistant Agent", model=model)
+
+# The PostgreSQL connection string using the asyncpg driver
+POSTGRES_DB_URL = os.getenv("POSTGRES_DB_URL")
+
+# Create a clean URL without the problematic keywords
+CLEAN_DB_URL = POSTGRES_DB_URL.split("?")[0]
+
+# Create an async SQLAlchemy engine with the SSL configuration
+# The `connect_args` dictionary passes the `ssl` parameter to asyncpg
+engine = create_async_engine(CLEAN_DB_URL, connect_args={"ssl": "require"})
+
+# Create a session using SQLAlchemySession, passing the engine
+session = SQLAlchemySession("conversation_123", engine=engine, create_tables=True)
+
+print("--- Running first query with PostgreSQL session ---")
+result1 = Runner.run_sync(
+    agent, "What city is the Golden Gate Bridge in?", session=session
+)
+print("Agent 01 :", result1.final_output)
+
+print("\n--- Running second query with PostgreSQL session ---")
+# The session object remembers the previous turn
+result2 = Runner.run_sync(agent, "What state is it in?", session=session)
+print("Agent 02 :", result2.final_output)