Strategy for caching session data/Short-term-memory

[simeonwetzel]

A strategy is needed to decide where session data (state) is stored (server side / client side). This applies to API responses as well as chat history.

[simeonwetzel]

Implemention details:

1. Database initialization:
   The server initializes a SQLite database on startup:
   

   innovation-prize/search-app/server/app/server.py

   Line 39 in df7c010

   memory = AsyncSqliteSaver.from_conn_string(":memory:")

2. Session creation:
   Each client must create a session by calling the create_session endpoint:
   curl -X POST http://localhost:8000/create_session
   

   innovation-prize/search-app/server/app/server.py

   Line 123 in df7c010

   async def create_session(response: Response):

This endpoint generates a session_id, which is then stored in a session cookie:

3. Session Management:
   When the langgraph state graph (chatbot) is initialized, the session_id is used to create a unique entry in the SQLite database. Each interaction with the graph (i.e., user input and AI response) results in a checkpoint being saved in the database. This checkpoint includes information such as:

• Chat history
• Search criteria
• Spatial context
• Search results
  This checkpoint functions as a form of short-term memory.

4. Limitations and Benefits:
   Currently, checkpoints are not retained if the server is restarted. However, this approach allows different clients to maintain their own sessions and respective memories even when using a single SQLite database.