Metadata-Version: 2.1
Name: langchain-postgres
Version: 0.0.1
Summary: An integration package connecting Postgres and LangChain
Home-page: https://github.com/langchain-ai/langchain
License: MIT
Requires-Python: >=3.8.1,<4.0
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Programming Language :: Python :: 3.13
Requires-Dist: langchain-core (>=0.1,<0.2)
Requires-Dist: psycopg (>=3.1.18,<4.0.0)
Project-URL: Repository, https://github.com/langchain-ai/langchain
Project-URL: Source Code, https://github.com/langchain-ai/langchain/tree/master/libs/partners/postgres
Description-Content-Type: text/markdown

# langchain-postgres

The `langchain-postgres` package is an integration package managed by the core LangChain team.

This package contains implementations of core abstractions using `Postgres`.

The package is released under the MIT license. 

Feel free to use the abstraction as provided or else modify them / extend them as appropriate for your own application.

## Installation

```bash
pip install -U langchain-postgres
```

## Usage

### ChatMessageHistory

The chat message history abstraction helps to persist chat message history 
in a postgres table.

PostgresChatMessageHistory is parameterized using a `table_name` and a `session_id`.

The `table_name` is the name of the table in the database where 
the chat messages will be stored.

The `session_id` is a unique identifier for the chat session. It can be assigned
by the caller using `uuid.uuid4()`.

```python
import uuid

from langchain_core.messages import SystemMessage, AIMessage, HumanMessage
from langchain_postgres import PostgresChatMessageHistory
import psycopg

# Establish a synchronous connection to the database
# (or use psycopg.AsyncConnection for async)
conn_info = ... # Fill in with your connection info
sync_connection = psycopg.connect(conn_info)

# Create the table schema (only needs to be done once)
table_name = "chat_history"
PostgresChatMessageHistory.create_schema(sync_connection, table_name)

session_id = str(uuid.uuid4())

# Initialize the chat history manager
chat_history = PostgresChatMessageHistory(
    table_name,
    session_id,
    sync_connection=sync_connection
)

# Add messages to the chat history
chat_history.add_messages([
    SystemMessage(content="Meow"),
    AIMessage(content="woof"),
    HumanMessage(content="bark"),
])

print(chat_history.messages)
```

