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

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Eduard van Valkenburg a2856d3b92 Python: restructure: Python samples into progressive 01-05 layout (#3862 )

* restructure: Python samples into progressive 01-05 layout

- 01-get-started/: 6 numbered steps (hello agent → hosting)
- 02-agents/: all agent concept samples (tools, middleware, providers, etc.)
- 03-workflows/: ALL existing workflow samples preserved as-is
- 04-hosting/: azure-functions, durabletask, a2a
- 05-end-to-end/: demos, evaluation, hosted agents
- Old files moved to _to_delete/ for review
- Added AGENTS.md with structure documentation
- autogen-migration/ and semantic-kernel-migration/ preserved at root

* fix: switch to AzureOpenAI Foundry, fix CI failures

- Switch all 01-get-started samples to AzureOpenAIResponsesClient with
  Azure AI Foundry project endpoint (AZURE_AI_PROJECT_ENDPOINT +
  AZURE_OPENAI_RESPONSES_DEPLOYMENT_NAME + AzureCliCredential)
- Add _to_delete/ and 05-end-to-end/ to pyrightconfig.samples.json excludes
- Fix test paths in packages/ that referenced old getting_started/ dirs:
  durabletask conftest + streaming test, azurefunctions conftest,
  devui conftest + capture_messages + openai_sdk_integration
- Fix workflow_as_agent_human_in_the_loop.py import (sibling import)
- Update hosting READMEs and tool comment paths
- Replace root README.md with new structure overview
- Update AGENTS.md to document Azure OpenAI Foundry as default provider

* cleanup: remove _to_delete folder, copy resource files to active dirs

All files in _to_delete/ were either:
- Exact duplicates of files in the new structure (240 files)
- Same file with only comment path updates (100 files)
- One import-fix diff (workflow_as_agent_human_in_the_loop.py)
- One superseded minimal_sample.py

Resource files (sample.pdf, countries.json, employees.pdf, weather.json)
copied to 02-agents/sample_assets/ and 02-agents/resources/ since active
samples reference them.

* fix: address PR review comments, centralize resources, remove root duplicates

- Fix type annotation in 04_memory.py (string union -> proper types)
- Fix old sample paths in observability files
- Fix grammar/spelling in observability samples
- Move sample_assets/ and resources/ to shared/ folder
- Remove 8 duplicate observability files from 02-agents root
- Update resource path references in multimodal_input and provider samples

* fix: update broken links from old getting_started paths to new structure

- Update relative paths in READMEs: getting_started/ → 01-get-started/,
  02-agents/, 03-workflows/, 04-hosting/, 05-end-to-end/
- Fix absolute GitHub URLs in package READMEs
- Fix broken link in ollama package README

* fix: convert absolute GitHub URLs to relative paths for link checker

Absolute URLs to python/samples/ on main branch 404 until PR merges.
Converted to relative paths that linkspector can verify locally.

* fix: update link for handoff sample moved to orchestrations/

* fix: update chatkit-integration README path from demos/ to 05-end-to-end/

* fix: update broken links in orchestrations README to match flat directory structure

2026-02-12 17:36:36 +00:00

2.9 KiB

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Ollama Examples

This folder contains examples demonstrating how to use Ollama models with the Agent Framework.

Prerequisites

Install Ollama: Download and install Ollama from ollama.com
Start Ollama: Ensure Ollama is running on your local machine
Pull a model: Run ollama pull mistral (or any other model you prefer)
- For function calling examples, use models that support tool calling like mistral or qwen2.5
- For reasoning examples, use models that support reasoning like qwen3:8b
- For multimodal examples, use models like gemma3:4b

Note

: Not all models support all features. Function calling, reasoning, and multimodal capabilities depend on the specific model you're using.

Recommended Approach

The recommended way to use Ollama with Agent Framework is via the native OllamaChatClient from the agent-framework-ollama package. This provides full support for Ollama-specific features like reasoning mode.

Alternatively, you can use the OpenAIChatClient configured to point to your local Ollama server, which may be useful if you're already familiar with the OpenAI client interface.

Examples

File	Description
`ollama_agent_basic.py`	Basic Ollama agent with tool calling using native Ollama Chat Client. Shows both streaming and non-streaming responses.
`ollama_agent_reasoning.py`	Ollama agent with reasoning capabilities using native Ollama Chat Client. Shows how to enable thinking/reasoning mode.
`ollama_chat_client.py`	Direct usage of the native Ollama Chat Client with tool calling.
`ollama_chat_multimodal.py`	Ollama Chat Client with multimodal (image) input capabilities.
`ollama_with_openai_chat_client.py`	Alternative approach using OpenAI Chat Client configured to use local Ollama models.

Configuration

The examples use environment variables for configuration. Set the appropriate variables based on which example you're running:

For Native Ollama Examples

Set the following environment variables:

OLLAMA_HOST: The base URL for your Ollama server (optional, defaults to http://localhost:11434)
- Example: export OLLAMA_HOST="http://localhost:11434"
OLLAMA_MODEL_ID: The model name to use
- Example: export OLLAMA_MODEL_ID="qwen2.5:8b"
- Must be a model you have pulled with Ollama

For OpenAI Client with Ollama (`ollama_with_openai_chat_client.py`)