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Conversation & Session Management Samples
These samples demonstrate different approaches to managing conversation history and session state in Agent Framework.
Samples
| File | Description |
|---|---|
suspend_resume_session.py |
Suspend and resume conversation sessions, comparing service-managed sessions (Azure AI Foundry) with in-memory sessions (OpenAI). |
custom_history_provider.py |
Implement a custom history provider by extending HistoryProvider, enabling conversation persistence in your preferred storage backend. |
file_history_provider.py |
Use the experimental FileHistoryProvider with FoundryChatClient and a function tool so the local JSON Lines file shows the full tool-calling loop. |
file_history_provider_conversation_persistence.py |
Persist a tool-driven weather conversation with FileHistoryProvider, inspect the stored JSONL records, and continue with another city. |
cosmos_history_provider.py |
Use Azure Cosmos DB as a history provider for durable conversation storage with CosmosHistoryProvider. |
cosmos_history_provider_conversation_persistence.py |
Persist and resume conversations across application restarts using CosmosHistoryProvider — serialize session state, restore it, and continue with full Cosmos DB history. |
cosmos_history_provider_messages.py |
Direct message history operations — retrieve stored messages as a transcript, clear session history, and verify data deletion. |
cosmos_history_provider_sessions.py |
Multi-session and multi-tenant management — per-tenant session isolation, list_sessions() to enumerate, switch between sessions, and resume specific conversations. |
redis_history_provider.py |
Use Redis as a history provider for persistent conversation history storage across sessions. |
Prerequisites
For suspend_resume_session.py:
FOUNDRY_PROJECT_ENDPOINT: Your Azure AI Foundry project endpoint (service-managed session)FOUNDRY_MODEL: The Foundry model deployment nameOPENAI_API_KEY: Your OpenAI API key (in-memory session)- Azure CLI authentication (
az login)
For custom_history_provider.py:
OPENAI_API_KEY: Your OpenAI API key
For file_history_provider.py:
FOUNDRY_PROJECT_ENDPOINT: Your Azure AI Foundry project endpointFOUNDRY_MODEL: The Foundry model deployment name- Azure CLI authentication (
az login) - The sample writes plaintext JSONL conversation logs to disk; use a trusted local directory and avoid treating the history files as secure secret storage
For file_history_provider_conversation_persistence.py:
FOUNDRY_PROJECT_ENDPOINT: Your Azure AI Foundry project endpointFOUNDRY_MODEL: The Foundry model deployment name- Azure CLI authentication (
az login) - The sample writes plaintext JSONL conversation logs to disk; use a trusted local directory and avoid treating the history files as secure secret storage
For Cosmos DB samples (cosmos_history_provider*.py):
FOUNDRY_PROJECT_ENDPOINT: Your Azure AI Foundry project endpointFOUNDRY_MODEL: The Foundry model deployment nameAZURE_COSMOS_ENDPOINT: Your Azure Cosmos DB account endpointAZURE_COSMOS_DATABASE_NAME: The database that stores conversation historyAZURE_COSMOS_CONTAINER_NAME: The container that stores conversation history- Either
AZURE_COSMOS_KEYor Azure CLI authentication (az login)
For redis_history_provider.py:
OPENAI_API_KEY: Your OpenAI API key- A running Redis server — default URL is
redis://localhost:6379- Override via the
REDIS_URLenvironment variable for remote or authenticated instances - Quickstart with Docker:
docker run -d --name redis-stack -p 6379:6379 redis/redis-stack-server:latest
- Override via the