# Sessions
> Step-by-step guide to using sessions for conversational memory in Cognee
A minimal guide to enabling conversational memory with sessions. When you use the same `session_id` across searches, Cognee remembers previous questions and answers, enabling contextually aware follow-up questions.
## Before You Start
* Complete [Quickstart](../getting-started/quickstart) to understand basic operations
* Ensure you have [LLM Providers](../setup-configuration/llm-providers) configured
* Read [Sessions and Caching](../core-concepts/sessions-and-caching) for conceptual overview
* Configure your cache adapter before using sessions. See [Cache Adapters](../core-concepts/sessions-and-caching#cache-adapters) for Redis and Filesystem setup instructions.
## Code in Action
```python theme={null}
import asyncio
import cognee
from cognee import SearchType
from cognee.modules.users.methods import get_default_user
from cognee.modules.retrieval.utils.session_cache import set_session_user_context_variable
async def main():
# Prepare knowledge base
await cognee.add([
"Alice moved to Paris in 2010. She works as a software engineer.",
"Bob lives in New York. He is a data scientist.",
"Alice and Bob met at a conference in 2015."
])
await cognee.cognify()
# Set user context (required for sessions)
user = await get_default_user()
await set_session_user_context_variable(user)
# First search - starts a new session
result1 = await cognee.search(
query_type=SearchType.GRAPH_COMPLETION,
query_text="Where does Alice live?",
session_id="conversation_1"
)
print("First answer:", result1[0])
# Follow-up search - uses conversation history
result2 = await cognee.search(
query_type=SearchType.GRAPH_COMPLETION,
query_text="What does she do for work?",
session_id="conversation_1" # Same session
)
print("Follow-up answer:", result2[0])
# The LLM knows "she" refers to Alice from previous context
# Different session - no memory of previous conversation
result3 = await cognee.search(
query_type=SearchType.GRAPH_COMPLETION,
query_text="What does she do for work?",
session_id="conversation_2" # New session
)
print("New session answer:", result3[0])
# This won't know who "she" refers to
asyncio.run(main())
```
This example works with either Redis or Filesystem adapter. Configure your chosen adapter in the [Before you start](#before-you-start) section above.
## What Just Happened
### Step 1: Prepare Knowledge Base
```python theme={null}
await cognee.add([
"Alice moved to Paris in 2010. She works as a software engineer.",
"Bob lives in New York. He is a data scientist.",
"Alice and Bob met at a conference in 2015."
])
await cognee.cognify()
```
Before you can search with sessions, you need to have data in your knowledge base. Use `cognee.add()` to ingest data and `cognee.cognify()` to build the knowledge graph.
### Step 2: Set User Context
```python theme={null}
from cognee.modules.users.methods import get_default_user
from cognee.modules.retrieval.utils.session_cache import set_session_user_context_variable
user = await get_default_user()
await set_session_user_context_variable(user)
```
Sessions require a user context to associate conversation history with a specific user. This must be set before using `session_id` in searches.
### Step 3: Use Session ID in Searches
```python theme={null}
result = await cognee.search(
query_type=SearchType.GRAPH_COMPLETION,
query_text="Where does Alice live?",
session_id="conversation_1"
)
```
The `session_id` parameter creates or continues a conversation thread. All searches with the same `session_id` share conversation history.
### Step 4: Follow-up Questions
```python theme={null}
result = await cognee.search(
query_type=SearchType.GRAPH_COMPLETION,
query_text="What does she do for work?",
session_id="conversation_1" # Same session
)
```
When you use the same `session_id`, Cognee automatically includes previous Q\&A turns in the LLM prompt, enabling contextual follow-up questions.
### Step 5: Multiple Sessions
```python theme={null}
# Session 1
await cognee.search(query_text="Question 1", session_id="session_1")
await cognee.search(query_text="Follow-up", session_id="session_1")
# Session 2 (independent)
await cognee.search(query_text="Question 1", session_id="session_2")
```
Each `session_id` maintains its own conversation history. Sessions are isolated from each other.
## Advanced Usage
Use meaningful session IDs to organize conversations:
```python theme={null}
# User-specific sessions
await cognee.search(query_text="...", session_id=f"user_{user_id}_chat")
# Topic-specific sessions
await cognee.search(query_text="...", session_id="project_planning")
await cognee.search(query_text="...", session_id="bug_discussion")
```
Session IDs are arbitrary strings—use whatever naming scheme fits your application.
Sessions expire after 24 hours by default. To customize TTL, configure it in your cache adapter settings. Expired sessions are automatically cleaned up and won't affect new searches.
If caching is disabled or unavailable, searches work normally but without conversational memory:
```dotenv theme={null}
CACHING=false
```
Or simply omit `session_id` from search calls. The system gracefully handles missing cache backends.
Understand how sessions work conceptually
Learn about search parameters and types
Configure cache adapters and providers
---
> To find navigation and other pages in this documentation, fetch the llms.txt file at: https://docs.cognee.ai/llms.txt