mirror of https://github.com/microsoft/agent-framework.git synced 2026-06-16 21:04:09 +08:00

Files

T

westey d7027fc1f9 Python: [BREAKING] Align FileAccess tools with .NET — directory discovery and recursive search (#6476 )

* Align FileAccess tools with .Net; add directory discovery and recursive search

* Fix choices field description: spacing, line length, grammar

Addresses PR review: separate concatenated string literals with proper
spacing/newlines, wrap lines under the 120-char Ruff limit, and fix
"doesn't" -> "don't".

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

* Address PR comments

---------

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

d7027fc1f9 · 2026-06-15 06:55:21 +00:00

History

azure_ai_search

Python: Add Hyperlight CodeAct package and docs (#5185 )

2026-04-17 00:49:44 +00:00

code_act

Python: feat: add agent-framework-monty (Monty-backed CodeAct provider) (#5915 )

2026-05-20 00:35:23 +00:00

file_access_data_processing

Python: [BREAKING] Align FileAccess tools with .NET — directory discovery and recursive search (#6476 )

2026-06-15 06:55:21 +00:00

mem0

Python: Fix broken samples and add missing READMEs (#5038 )

2026-04-01 21:35:16 +00:00

neo4j

Python: Adds sample documentation for two separate Neo4j context providers for retrieval and memory (#4010 )

2026-04-07 09:57:35 +00:00

neo4j_memory

Python: Adds sample documentation for two separate Neo4j context providers for retrieval and memory (#4010 )

2026-04-07 09:57:35 +00:00

redis

Python: Fix broken samples and add missing READMEs (#5038 )

2026-04-01 21:35:16 +00:00

azure_ai_foundry_memory.py

Python: [BREAKING] Standardize model selection on model (#4999 )

2026-04-01 19:00:18 +00:00

README.md

Python: Adding AgentFileStore and FileAccessProvider to support file access operations. (#6099 )

2026-05-28 20:09:50 +00:00

simple_context_provider.py

Python: Fix broken samples and add missing READMEs (#5038 )

2026-04-01 21:35:16 +00:00

README.md

Context Provider Samples

These samples demonstrate how to use context providers to enrich agent conversations with external knowledge — from custom logic to Azure AI Search (RAG) and memory services.

Samples

File / Folder	Description
`simple_context_provider.py`	Implement a custom context provider by extending `ContextProvider` to extract and inject structured user information across turns.
`azure_ai_foundry_memory.py`	Use `FoundryMemoryProvider` to add semantic memory — automatically retrieves, searches, and stores memories via Azure AI Foundry.
`file_access_data_processing/`	Use `FileAccessProvider` with `FileSystemAgentFileStore` to give an agent read/write/search access to a folder of CSV data files. See its own README.
`azure_ai_search/`	Retrieval Augmented Generation (RAG) with Azure AI Search in semantic and agentic modes. See its own README.
`mem0/`	Memory-powered context using the Mem0 integration (open-source and managed). See its own README.
`redis/`	Redis-backed context providers for conversation memory and sessions. See its own README.

Prerequisites

For simple_context_provider.py:

FOUNDRY_PROJECT_ENDPOINT: Your Azure AI Foundry project endpoint
FOUNDRY_MODEL: Model deployment name
Azure CLI authentication (az login)

For azure_ai_foundry_memory.py:

FOUNDRY_PROJECT_ENDPOINT: Your Azure AI Foundry project endpoint
FOUNDRY_MODEL: Chat/responses model deployment name
AZURE_OPENAI_EMBEDDING_DEPLOYMENT_NAME: Embedding model deployment name (e.g., text-embedding-ada-002)
Azure CLI authentication (az login)

For file_access_data_processing/:

FOUNDRY_PROJECT_ENDPOINT: Your Azure AI Foundry project endpoint
FOUNDRY_MODEL: Chat model deployment name
Azure CLI authentication (az login)

See each subfolder's README for provider-specific prerequisites.