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/microsoft-foundry

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Build, deploy, evaluate, optimize, fine-tune, and manage Microsoft Foundry agents, models, and resources end to end. USE FOR: foundry, azd ai agent, azd provision/deploy, hosted agent scaffold/develop/run/deploy/troubleshoot, prompt agent create, create agent, update agent, add tool to agent, invoke agent, agent.yaml, agent insights, pull agent insights, evaluate agent, batch eval, continuous eval, continuous monitoring, agent CI/CD, optimize prompt, improve prompt, prompt optimizer, optimize agent instructions, Agent Optimizer scaffold, dataset curation from traces, deploy model, model fine-tuning (SFT/DPO/RFT), Foundry project, RBAC, role assignment, permissions, quota, capacity, region, deployment failure, AI Services, create Foundry resource, knowledge index, customize deployment, onboard, availability, training-data, grader, distillation, large file upload. DO NOT USE FOR: Azure Functions, App Service, general Azure deploy (use azure-deploy), general Azure prep (use azure-prepare).

194 files
1.1 MB
MIT
Updated last week
GitHub
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Use this Skill: https://skilld.dev/gh/microsoft/skills/microsoft-foundry

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finetuningreferenceslarge-file-uploads.md

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Large File Uploads

The standard client.files.create() silently fails on JSONL files >~150MB (Azure returns 500 during job execution). Use the chunked Uploads API:

upload = client.uploads.create(filename="data.jsonl", purpose="fine-tune", bytes=file_size, mime_type="application/jsonl")
part_ids = []
with open(filepath, "rb") as f:
    while chunk := f.read(64 * 1024 * 1024):  # 64MB chunks
        part = client.uploads.parts.create(upload_id=upload.id, data=chunk)
        part_ids.append(part.id)
completed = client.uploads.complete(upload_id=upload.id, part_ids=part_ids)
file_id = completed.file.id

Important: Requires openai.AzureOpenAI() client, NOT openai.OpenAI() with /v1/ URL. The project endpoint returns 404 for upload operations.

File Size	Method
< 100MB	Standard `files.create()`
100MB–5GB	Chunked Uploads API
> 5GB	Split dataset

Source: SKILL.md on GitHub

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This skill provides a comprehensive environment for managing the end-to-end lifecycle of AI agents, models, and infrastructure on Microsoft Foundry. It includes sub-skills for deployment, evaluation, fine-tuning, and troubleshooting. The skill utilizes dynamic code execution and shell command wrappers, which are used within the context of local development and cloud orchestration. All external resources and dependencies originate from trusted organizations and well-known services.
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Signed by skilld at 04110d9. This ties the file your Agent reads to that commit on GitHub. It does not review the instructions.

Last checked against GitHub yesterday.

Activeupdated last week

Capability

metadata: { "author": "Microsoft", "version": "1.2.26" }

/microsoft-foundry