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Copilot b05fc9e849 Python: Add load_dotenv() to samples for .env file support (#4043 )

* Initial plan

* Add load_dotenv() to 303 Python samples for environment variable loading

Co-authored-by: TaoChenOSU <12570346+TaoChenOSU@users.noreply.github.com>

* Update SAMPLE_GUIDELINES.md to document load_dotenv() requirement

Co-authored-by: TaoChenOSU <12570346+TaoChenOSU@users.noreply.github.com>

* Update samples README.md to document .env file usage

Co-authored-by: TaoChenOSU <12570346+TaoChenOSU@users.noreply.github.com>

* Run ruff format on all changed sample files

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* Clarify load_dotenv() usage in README - local dev vs production

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* Remove deprecated getting_started folder as requested

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* Document env_file_path parameter for per-client configuration

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* Merge main branch to resolve conflicts

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* Fix run_evaluation.py file that was empty in merge commit

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* Remove dotnet changes from merge - out of scope for this PR

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* Remove package and test changes from merge - only sample changes needed

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* Remove test_func_utils.py - only sample changes needed

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* Revert sample files not in original changeset - keep only load_dotenv additions

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* Move load_dotenv() outside snippet tag in 06_host_your_agent.py

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* Fix comment placement - move load_dotenv before code comments

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* Fix load_dotenv() placement across all samples - after docstring, before code comments

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* Merge latest main branch with load_dotenv changes

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* Remove non-sample changes from merge - keep only load_dotenv additions

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* Revert non-load_dotenv sample changes from merge

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* Fix run_evaluation.py - use main's improved version (file already had load_dotenv)

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* Manual update

* Manual update 2

* Fix Role usage and load_dotenv placement per PR review feedback

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* Fix Role usage - use string literals not enum attributes

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* Fix SAMPLE_GUIDELINES.md example - load_dotenv before docstring per guidance

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* Move load_dotenv() before docstrings in all samples per SAMPLE_GUIDELINES ordering

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* Address PR review: rename files, fix placement, add session usage, remove note

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* Update Redis README to reference renamed file redis_history_provider.py

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---------

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Co-authored-by: TaoChenOSU <12570346+TaoChenOSU@users.noreply.github.com>
Co-authored-by: Tao Chen <taochen@microsoft.com>
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Co-authored-by: Eduard van Valkenburg <eavanvalkenburg@users.noreply.github.com>

b05fc9e849 · 2026-02-19 10:55:13 +00:00

History

mem0_basic.py

Python: Add load_dotenv() to samples for .env file support (#4043 )

2026-02-19 10:55:13 +00:00

mem0_oss.py

Python: Add load_dotenv() to samples for .env file support (#4043 )

2026-02-19 10:55:13 +00:00

mem0_sessions.py

Python: Add load_dotenv() to samples for .env file support (#4043 )

2026-02-19 10:55:13 +00:00

README.md

Python: [BREAKING] PR2 — Wire context provider pipeline, remove old types, update all consumers (#3850 )

2026-02-12 21:00:32 +00:00

README.md

Mem0 Context Provider Examples

Mem0 is a self-improving memory layer for Large Language Models that enables applications to have long-term memory capabilities. The Agent Framework's Mem0 context provider integrates with Mem0's API to provide persistent memory across conversation sessions.

This folder contains examples demonstrating how to use the Mem0 context provider with the Agent Framework for persistent memory and context management across conversations.

Examples

File	Description
`mem0_basic.py`	Basic example of using Mem0 context provider to store and retrieve user preferences across different conversation threads.
`mem0_sessions.py`	Advanced example demonstrating different thread scoping strategies with Mem0. Covers global thread scope (memories shared across all operations), per-operation thread scope (memories isolated per thread), and multiple agents with different memory configurations for personal vs. work contexts.
`mem0_oss.py`	Example of using the Mem0 Open Source self-hosted version as the context provider. Demonstrates setup and configuration for local deployment.

Prerequisites

Required Resources

Mem0 API Key - Sign up for a Mem0 account and get your API key - or self-host Mem0 Open Source
Azure AI project endpoint (used in these examples)
Azure CLI authentication (run az login)

Configuration

Environment Variables

Set the following environment variables:

For Mem0 Platform:

MEM0_API_KEY: Your Mem0 API key (alternatively, pass it as api_key parameter to Mem0Provider). Not required if you are self-hosting Mem0 Open Source

For Mem0 Open Source:

OPENAI_API_KEY: Your OpenAI API key (used by Mem0 OSS for embedding generation and automatic memory extraction)

For Azure AI:

AZURE_AI_PROJECT_ENDPOINT: Your Azure AI project endpoint
AZURE_AI_MODEL_DEPLOYMENT_NAME: The name of your model deployment

Key Concepts

Memory Scoping

The Mem0 context provider supports different scoping strategies:

Global Scope (scope_to_per_operation_thread_id=False): Memories are shared across all conversation threads
Thread Scope (scope_to_per_operation_thread_id=True): Memories are isolated per conversation thread

Memory Association

Mem0 records can be associated with different identifiers:

user_id: Associate memories with a specific user
agent_id: Associate memories with a specific agent
thread_id: Associate memories with a specific conversation thread
application_id: Associate memories with an application context