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Python: Remove unsupported memory scoping params from mem0/redis samples and docs (#4367)

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* Python: Remove unsupported memory scoping params from samples and docs

Fixes #4353

The `Mem0ContextProvider` and `RedisContextProvider` no longer support
`thread_id` or `scope_to_per_operation_thread_id` parameters. This commit
updates the affected samples and READMEs to use only the currently
supported API (`user_id`, `agent_id`, `application_id`).

Changes:
- mem0_sessions.py: Remove `thread_id` and
  `scope_to_per_operation_thread_id` from examples 1 and 2, rewrite to
  demonstrate user-scoped and agent-scoped memory patterns
- redis_sessions.py: Update module docstring to remove references to
  removed thread scoping params
- mem0/README.md: Update Memory Scoping docs to reflect current API
- redis/README.md: Remove `thread_id` and
  `scope_to_per_operation_thread_id` references from docs

* Address Copilot review: rename thread_scope functions, fix docstring

- Rename `example_global_thread_scope` -> `example_global_memory_scope`
- Rename `example_per_operation_thread_scope` -> `example_agent_scoped_memory`
- Update example 2 docstring to mention `application_id` alongside
  `user_id` and `agent_id` since it's set in the provider config
- Update module docstring scenario 2 to include `application_id`

* fix: rebase onto main, address giles17 review feedback

- Resolve merge conflicts by rebasing all 4 original files onto current main
- Address giles17's agent review suggestions:
  - mem0_basic.py: update comment to remove thread_id from scoping list
  - mem0_oss.py: update comment to remove thread_id from scoping list
  - redis_sessions.py: rename Example 2 from "Agent-Scoped Memory" to
    "Hybrid Vector Search" to accurately describe what it demonstrates
  - redis/README.md: update Example 2 description to match renamed example

---------

Co-authored-by: Tao Chen <taochen@microsoft.com>
Co-authored-by: Giles Odigwe <79032838+giles17@users.noreply.github.com>
This commit is contained in:
L. Elaine Dazzio
2026-03-31 21:57:23 +00:00
committed by GitHub
co-authored by Tao Chen Giles Odigwe
parent 3a49b1d6dd
commit 1e527a328c
6 changed files with 81 additions and 99 deletions
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python/samples/02-agents/context_providers/redis/README.md
+5 -6
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@@ -11,7 +11,7 @@ This folder contains an example demonstrating how to use the Redis context provi
| [`azure_redis_conversation.py`](azure_redis_conversation.py) | Demonstrates conversation persistence with RedisHistoryProvider and Azure Redis with Azure AD (Entra ID) authentication using credential provider. |
| [`redis_basics.py`](redis_basics.py) | Shows standalone provider usage and agent integration. Demonstrates writing messages to Redis, retrieving context via full‑text or hybrid vector search, and persisting preferences across threads. Also includes a simple tool example whose outputs are remembered. |
| [`redis_conversation.py`](redis_conversation.py) | Simple example showing conversation persistence with RedisContextProvider using traditional connection string authentication. |
| [`redis_sessions.py`](redis_sessions.py) | Demonstrates thread scoping. Includes: (1) global thread scope with a fixed `thread_id` shared across operations; (2) per‑operation thread scope where `scope_to_per_operation_thread_id=True` binds memory to a single thread for the provider's lifetime; and (3) multiple agents with isolated memory via different `agent_id` values. |
| [`redis_sessions.py`](redis_sessions.py) | Demonstrates memory scoping strategies. Includes: (1) global memory scope with `application_id`, `agent_id`, and `user_id` shared across operations; (2) hybrid vector search using a custom OpenAI vectorizer for richer context retrieval; and (3) multiple agents with isolated memory via different `agent_id` values. |
## Prerequisites
@@ -61,8 +61,7 @@ The provider supports both full‑text only and hybrid vector search:
- Set `vectorizer_choice` to `"openai"` or `"hf"` to enable embeddings and hybrid search.
- When using a vectorizer, also set `vector_field_name` (e.g., `"vector"`).
- Partition fields for scoping memory: `application_id`, `agent_id`, `user_id`, `thread_id`.
- Thread scoping: `scope_to_per_operation_thread_id=True` isolates memory per operation thread.
- Partition fields for scoping memory: `application_id`, `agent_id`, `user_id`.
- Index management: `index_name`, `overwrite_redis_index`, `drop_redis_index`.
## What the example does
@@ -104,8 +103,8 @@ You should see the agent responses and, when using embeddings, context retrieved
### Memory scoping
- Global scope: set `application_id`, `agent_id`, `user_id`, or `thread_id` on the provider to filter memory.
- Per‑operation thread scope: set `scope_to_per_operation_thread_id=True` to isolate memory to the current thread created by the framework.
- Global scope: set `application_id`, `agent_id`, or `user_id` on the provider to filter memory.
- Agent isolation: use different `agent_id` values to keep memories separated for different agent personas.
### Hybrid vector search (optional)
@@ -118,7 +117,7 @@ You should see the agent responses and, when using embeddings, context retrieved
## Troubleshooting
- Ensure at least one of `application_id`, `agent_id`, `user_id`, or `thread_id` is set; the provider requires a scope.
- Ensure at least one of `application_id`, `agent_id`, or `user_id` is set; the provider requires a scope.
- Verify `FOUNDRY_PROJECT_ENDPOINT` and `FOUNDRY_MODEL` are set for the chat client.
- If using embeddings, verify `OPENAI_API_KEY` is set and reachable.
- Make sure Redis exposes RediSearch (Redis Stack image or managed service with search enabled).