Gemini API Dev
google-gemini/gemini-skills
A skill your agent uses when writing code that calls the Gemini API for text generation, multi-turn chat, multimodal understanding, image generation, video generation, speech generation (TTS), voice…
Shift Python apps dem from Azure OpenAI Chat Completions go Responses API.
$ npx skills add microsoft/ai-agents-for-beginners --skill azure-openai-to-responses -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install microsoft/ai-agents-for-beginners azure-openai-to-responses --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/microsoft/ai-agents-for-beginners.git skills-src && mkdir -p .claude/skills && cp -r skills-src/translations/pcm/.agents/skills/azure-openai-to-responses .claude/skills/azure-openai-to-responses && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "azure-openai-to-responses" agent skill from https://github.com/microsoft/ai-agents-for-beginners/tree/main/translations/pcm/.agents/skills/azure-openai-to-responses into .claude/skills/azure-openai-to-responses/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "azure-openai-to-responses", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/microsoft/ai-agents-for-beginners/tree/main/translations/pcm/.agents/skills/azure-openai-to-responsesType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add microsoft/ai-agents-for-beginners --skill azure-openai-to-responses -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install microsoft/ai-agents-for-beginners azure-openai-to-responses --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/microsoft/ai-agents-for-beginners.git skills-src && mkdir -p .agents/skills && cp -r skills-src/translations/pcm/.agents/skills/azure-openai-to-responses .agents/skills/azure-openai-to-responses && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "azure-openai-to-responses" agent skill from https://github.com/microsoft/ai-agents-for-beginners/tree/main/translations/pcm/.agents/skills/azure-openai-to-responses into .agents/skills/azure-openai-to-responses/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "azure-openai-to-responses", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add microsoft/ai-agents-for-beginners --skill azure-openai-to-responses -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install microsoft/ai-agents-for-beginners azure-openai-to-responses --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/microsoft/ai-agents-for-beginners.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/translations/pcm/.agents/skills/azure-openai-to-responses .cursor/skills/azure-openai-to-responses && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "azure-openai-to-responses" agent skill from https://github.com/microsoft/ai-agents-for-beginners/tree/main/translations/pcm/.agents/skills/azure-openai-to-responses into .cursor/skills/azure-openai-to-responses/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "azure-openai-to-responses", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/microsoft/ai-agents-for-beginners.git --path translations/pcm/.agents/skills/azure-openai-to-responses--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add microsoft/ai-agents-for-beginners --skill azure-openai-to-responses -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install microsoft/ai-agents-for-beginners azure-openai-to-responses --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/microsoft/ai-agents-for-beginners.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/translations/pcm/.agents/skills/azure-openai-to-responses .gemini/skills/azure-openai-to-responses && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "azure-openai-to-responses" agent skill from https://github.com/microsoft/ai-agents-for-beginners/tree/main/translations/pcm/.agents/skills/azure-openai-to-responses into .gemini/skills/azure-openai-to-responses/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "azure-openai-to-responses", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install microsoft/ai-agents-for-beginners azure-openai-to-responsesInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add microsoft/ai-agents-for-beginners --skill azure-openai-to-responses -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/microsoft/ai-agents-for-beginners.git skills-src && mkdir -p .github/skills && cp -r skills-src/translations/pcm/.agents/skills/azure-openai-to-responses .github/skills/azure-openai-to-responses && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "azure-openai-to-responses" agent skill from https://github.com/microsoft/ai-agents-for-beginners/tree/main/translations/pcm/.agents/skills/azure-openai-to-responses into .github/skills/azure-openai-to-responses/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "azure-openai-to-responses", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add microsoft/ai-agents-for-beginners --skill azure-openai-to-responses -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install microsoft/ai-agents-for-beginners azure-openai-to-responses --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/microsoft/ai-agents-for-beginners.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/translations/pcm/.agents/skills/azure-openai-to-responses .opencode/skills/azure-openai-to-responses && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "azure-openai-to-responses" agent skill from https://github.com/microsoft/ai-agents-for-beginners/tree/main/translations/pcm/.agents/skills/azure-openai-to-responses into .opencode/skills/azure-openai-to-responses/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "azure-openai-to-responses", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
azure-openai-to-responsesShift Python apps dem from Azure OpenAI Chat Completions go Responses API.
Azure Openai To Responses is an agent skill from microsoft/ai-agents-for-beginners, published by the product's own GitHub organization. Shift Python apps dem from Azure OpenAI Chat Completions go Responses API. E cover AzureOpenAI/AsyncAzureOpenAI client shift go v1 endpoint, streaming, tools, structured output, multi-turn, EntraID auth, plus model compatibility checks. Na Python-focused, Azure OpenAI-specific. USE FOR: shift go responses API, change from chat completions, openai responses, upgrade openai SDK, responses API migration, move from completions go responses, gpt-5 migration, azure openai python migration, chat completions go…
Its SKILL.md is about 6k tokens, which your agent loads only when the skill is triggered. The skill folder holds 4 other files, including reference files (for example `references/cheat-sheet.md`, `references/test-migration.md` and `references/troubleshooting.md`).
It sits in AI & LLM Engineering, covering LLM API integration and Structured output and tool calling. It works with OpenAI, Azure OpenAI, Microsoft Azure and Python. The repository describes itself as: 18 Lessons to Get Started Building AI Agents. The licence is MIT.
3 steps, taken from the step headings in SKILL.md.
Read from SKILL.md and the folder at commit ff2ba66. It shows what the files ask for, not the result of running them.
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Shell commands in SKILL.md call:
rgpythongitFrom the folder's file list and the shell code blocks in SKILL.md.
Hosts in commands or code, which the agent is likely to contact:
cdn.jsdelivr.netAlso links to:
learn.microsoft.comaka.msnpmjs.complatform.openai.comgithub.comFrom URLs in SKILL.md, links to its own repository left out.
Names these keys or tokens, usually read from environment variables:
AZURE_OPENAI_API_KEYFrom names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Azure Openai To Responses loads about 6k tokens when it runs, and up to ~19k if it reads all its reference files. Until then it costs about 209 tokens; SKILL.md has 2,243 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
The automated check noted patterns worth knowing about, such as sudo or a known installer.
API_VERSION` environment variables from `.env`, app settings, and Bicep/infra files.ENAI_CLIENT_ID` → `AZURE_CLIENT_ID` for `.env`, app settings, Bicep/infra, and test fixtures (standard Azure Identity SDAutomated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
The full file from microsoft/ai-agents-for-beginners at commit ff2ba66, republished under its MIT licence (© microsoft). 2,243 words, ~6,018 tokens.
.claude/skills/azure-openai-to-responses/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.AUTHORITATIVE GUIDANCE — FOLLOW EXACTLY
Dis skill dey migrate Python code wey dey use Azure OpenAI Chat Completions come use di unified Responses API. Abeg follow dis instructions sharply. No try do your own mapping of parameters or create new API shapes.
Activate dis skill wen user want:
AzureOpenAI/AsyncAzureOpenAI go standard OpenAI/AsyncOpenAI client with di v1 endpointAzureOpenAI constructors or api_versionBefore you migrate, make sure say your Azure OpenAI deployment support Responses API.
import os
from openai import OpenAI
client = OpenAI(
api_key=os.environ["AZURE_OPENAI_API_KEY"],
base_url=f"{os.environ['AZURE_OPENAI_ENDPOINT'].rstrip('/')}/openai/v1/",
)
try:
resp = client.responses.create(
model=os.environ["AZURE_OPENAI_DEPLOYMENT"],
input="ping",
max_output_tokens=50,
store=False,
)
print(f"✅ Deployment supports Responses API: {resp.output_text}")
except Exception as e:
print(f"❌ Deployment does NOT support Responses API: {e}")Note:
max_output_tokensget minimum 16 for Azure OpenAI. If value less than 16, e go return 400 error. Use 50+ for smoke tests.
If e return 404, e mean say di deployment model no de support Responses yet — check di reference down or redeploy with correct model.
Run di built-in model compatibility tool to see wetin dey available with Responses API support for your region:
python migrate.py models --subscription YOUR_SUB_ID --location YOUR_REGIONDis one dey query Azure ARM live and show compatibility matrix — which models dey support Responses, structured output, tools, etc. Use --filter gpt-5.1,gpt-5.2 to narrow results or --json for scripting.
python migrate.py models (see am above — region-specific, always updated)WARNING: Older models (before
gpt-4.1) fit no fit support all Responses API features fully.Known limitations with older models:
reasoningparameter: No support for many non-reasoning models. Only migratereasoningif e already dey for original code.seedparameter: No dey support at all for Responses API — remove from all requests.- Structured output via
text.format: Older models no sure to enforcestrict: trueJSON schemas well.- Tool orchestration: GPT-5+ dey manage tool calls as part of internal reasoning. Older models for Responses still dey work but dem no get dis deep integration.
- Temperature constraints: Wen you dey migrate to
gpt-5, temperature gats be blank or set to1. Older models no get dis kind limit.
O-series models get them own special parameter limits. If your app dey target o-series models during migration:
temperature: Gats be 1 (or no include am). O-series no fit take other values.max_completion_tokens → max_output_tokens: Apps wey dey use Azure-specific max_completion_tokens must switch go max_output_tokens. Set am high (4096+) because reasoning tokens dey count against limit.reasoning_effort: If app dey use reasoning_effort (low/medium/high), keep am — Responses API support this for o-series models.response.output_text.delta fit show late than GPT models.top_p: No support for o-series — remove if e dey.Action — proactive model advisory: During scan, check which model app dey target (deployment names, env vars, config). If model before gpt-4.1 (no be gpt-4.1+), tell user beforehand:
gpt-5.1, gpt-5.2) get better tool orchestration, structured output enforcement, reasoning, and cross-region availability.No block or refuse migrate based on model version. Dis advisory be just info.
GitHub Models (
models.github.ai,models.inference.ai.azure.com) no support Responses API.
If codebase get GitHub Models path (look for base_url wey point to models.github.ai or models.inference.ai.azure.com), remove am completely during migration. Responses API need Azure OpenAI, OpenAI, or compatible local endpoint (e.g., Ollama with Responses support).
Action during scan:
Plenty apps dey use higher-level frameworks on top of OpenAI. When you dey migrate dem, the framework own API go change — no be only the underlying OpenAI calls.
Check your MAF version first — migration depends on whether you dey on MAF 1.0.0+ or before 1.0.0 beta/rc.
OpenAIChatClient dey use Responses API already — no migration needed. If codebase dey use old OpenAIChatCompletionClient (we dey use chat.completions.create), switch am to OpenAIChatClient.
| Before | After |
|---|---|
from agent_framework.openai import OpenAIChatCompletionClient | from agent_framework.openai import OpenAIChatClient |
OpenAIChatCompletionClient(...) | OpenAIChatClient(...) |
To check your version: python -c "import agent_framework_openai; print(agent_framework_openai.__version__)"
For pre-1.0.0 MAF, OpenAIChatClient dey use Chat Completions. Upgrade to agent-framework-openai>=1.0.0 so that OpenAIChatClient go use Responses API by default.
No other changes dey needed — Agent and tools API still the same.
langchain-openai)Add use_responses_api=True to ChatOpenAI(). Change response access from .content to .text.
| Before | After |
|---|---|
ChatOpenAI(model=..., base_url=..., api_key=...) | ChatOpenAI(model=..., base_url=..., api_key=..., use_responses_api=True) |
result['messages'][-1].content | result['messages'][-1].text |
For complete before/after code examples, see cheat-sheet.md.
Responses API na server-side matter. Migrate your Python backend; frontend HTTP contract suppose no change unless your backend na thin pass-through — if na so, consider use Responses request shape to drop translation layer. If frontend dey call OpenAI directly with client-side key, make dem move those calls to backend first.
@microsoft/ai-chat-protocol deprecationThe @microsoft/ai-chat-protocol npm package don deprecate, make you replace am with ndjson-readablestream. If you see am for frontend:
<!-- Before -->
<script src="https://cdn.jsdelivr.net/npm/@microsoft/ai-chat-protocol@.../dist/iife/index.js"></script>
<!-- After -->
<script src="https://cdn.jsdelivr.net/npm/ndjson-readablestream@1.0.7/dist/ndjson-readablestream.umd.js"></script>AIChatProtocolClient instantiation (new ChatProtocol.AIChatProtocolClient("/chat")).client.getStreamedCompletion(messages) with direct fetch() call to backend streaming endpoint.for await (const response of result) with for await (const chunk of readNDJSONStream(response.body)).response.delta.content / response.error to chunk.delta.content / chunk.error.git add/git commit/git push; only produce working-tree edits.If your codebase dey use AzureOpenAI or AsyncAzureOpenAI constructors, migrate to standard OpenAI / AsyncOpenAI constructors first. Azure-specific constructors don deprecate for openai>=1.108.1.
The new /openai/v1 endpoint dey use standard OpenAI() client instead of AzureOpenAI(), no need api_version parameter, and e dey work the same for OpenAI and Azure OpenAI. Di same client code dey future-proof — no version management needed.
| Before | After |
|---|---|
AzureOpenAI | OpenAI |
AsyncAzureOpenAI | AsyncOpenAI |
azure_endpoint | base_url |
azure_ad_token_provider | api_key |
api_version=... | Remove completely |
api_version argument from client construction.AZURE_OPENAI_VERSION / AZURE_OPENAI_API_VERSION environment variables from .env, app settings, and Bicep/infra files.AZURE_OPENAI_CLIENT_ID → AZURE_CLIENT_ID for .env, app settings, Bicep/infra, and test fixtures (standard Azure Identity SDK convention).openai>=1.108.1 in requirements.txt or pyproject.toml.| Old env var | Action | Notes |
|---|---|---|
AZURE_OPENAI_VERSION | Remove | No need api_version with v1 endpoint |
AZURE_OPENAI_API_VERSION | Remove | Same as above |
AZURE_OPENAI_CLIENT_ID | Rename → AZURE_CLIENT_ID | Standard Azure Identity SDK convention for ManagedIdentityCredential(client_id=...) |
AZURE_OPENAI_ENDPOINT | Keep | Still need for base_url construction |
AZURE_OPENAI_CHAT_DEPLOYMENT | Keep | Use as model param in responses.create |
AZURE_OPENAI_API_KEY | Keep | Use as api_key for key-based auth |
For client setup code examples (sync, async, EntraID, API key, multi-tenant), see cheat-sheet.md.
Run the detect_legacy.py script to find all call sites wey need migration:
python skills/azure-openai-to-responses/scripts/detect_legacy.py .Or run these searches manually — every match be migration target:
# Ol API calls (gats rewrite)
rg "chat\.completions\.create"
rg "ChatCompletion\.create"
rg "Completion\.create"
# Old Azure client constructors (gats change)
rg "AzureOpenAI\("
rg "AsyncAzureOpenAI\("
# How responses path dem dey access (gats update)
rg "choices\[0\]\.message\.content"
rg "choices\[0\]\.delta\.content"
rg "choices\[0\]\.message\.function_call"
rg "choices\[0\]\.message\.tool_calls"
# Tool definitions wey dey old inside nested form (gats flatten)
rg '"function":\s*{\s*"name"'
rg "pydantic_function_tool"
# Tool results for old form (gats change to function_call_output)
rg '"role":\s*"tool"'
rg '"tool_call_id"'
# Old parameters (gats remove or change name)
rg "response_format"
rg "max_tokens\b" # change name to max_output_tokens
rg "['\"]seed['\"]" # remove entirely
# Old environment variables (gats clean)
rg "AZURE_OPENAI_API_VERSION|AZURE_OPENAI_VERSION"
rg "AZURE_OPENAI_CLIENT_ID" # e suppose be AZURE_CLIENT_ID
# GitHub Models endpoints (gats remove — Responses API no dey support)
rg "models\.github\.ai|models\.inference\.ai\.azure"
# Framework level old patterns (gats update)
rg "OpenAIChatCompletionClient" # MAF 1.0.0+: change to OpenAIChatClient
rg "ChatOpenAI\(" | grep -v "use_responses_api" # LangChain: need use_responses_api=True
# Test setup (gats update)
rg "ChatCompletionChunk|AsyncCompletions\.create" tests/
rg "_azure_ad_token_provider" tests/
rg "prompt_filter_results|content_filter_results" tests/
rg "choices\[0\]" tests/
# Content filter error body access (gats update — structure don change)
rg 'innererror.*content_filter_result|error\.body\["innererror"\]'
rg "content_filter_result\[" # Old singular form — now content_filter_results (multiple) inside content_filters array
# Raw HTTP calls go Chat Completions endpoint (gats update URL)
rg "/openai/deployments/.*/chat/completions"
rg "api-version="Chat Completions client: client.chat.completions.create → client.responses.create(...).
Azure client constructors: AzureOpenAI(...) → OpenAI(base_url=..., api_key=...).
Tools: change function-calling tool definitions from nested style ({"type": "function", "function": {"name": ...}}) go flat Responses style ({"type": "function", "name": ...}); use tool_choice; return tool results as {"type": "function_call_output", "call_id": ..., "output": ...} items (no be {"role": "tool", ...}).
Tool round-trips: wen model return function calls, add response.output items join the conversation (no be manual {"role": "assistant", "tool_calls": [...]} dict), den add function_call_output items for each result.
Few-shot tool examples: if conversation get hardcoded tool call examples, change dem to {"type": "function_call", "id": "fc_...", "call_id": "fc_...", ...} + {"type": "function_call_output", ...} items. IDs suppose start with fc_.
pydantic_function_tool(): dis helper still dey make old nested style and no go good wit responses.create(). Replace am wit manual tool definitions or flatten wrapper.
Multi-turn: keep conversation history for the app; pass earlier turns through input items.
Formatting: change Chat top-level response_format to text.format for Responses. Correct shape: text={"format": {"type": "json_schema", "name": "Output", "strict": True, "schema": {...}}}.
Content items: change Chat content[].type: "text" to Responses content[].type: "input_text" for user or system turns.
Image content items: change Chat content[].type: "image_url" to Responses content[].type: "input_image". The image_url field switch from nested object {"url": "..."} to flat string. Check cheat sheet for before and after examples.
Reasoning effort: ONLY migrate reasoning if e already dey for original code.
Content filter error handling: error body structure don change. Chat Completions used error.body["innererror"]["content_filter_result"] (singular); Responses API use error.body["content_filters"][0]["content_filter_results"] (plural inside array). Code wey dey use innererror go raise KeyError. Change am to use di new path.
Raw HTTP calls: if app dey call Azure OpenAI REST API directly (like requests, httpx, etc.) wen dem dey use /openai/deployments/{name}/chat/completions?api-version=..., change dem to /openai/v1/responses. Request body change: messages → input, add max_output_tokens and store: false, remove api-version param. Response body change: choices[0].message.content → output[0].content[0].text (note: output_text na SDK convenience property wey no dey raw REST JSON).
/openai/deployments/{name}/chat/completions to /openai/v1/responses.messages → input, max_tokens → max_output_tokens. temperature no change.response_format to text.format wit correct object.content[].type: "text" to Responses content[].type: "input_text" for system or user turns.content[].type: "image_url" to Responses content[].type: "input_image". Flatten image_url field from {"image_url": {"url": "..."}} to {"image_url": "..."} (plain string — e fit be HTTPS URL or data:image/...;base64,... data URI).| Chat Completions | Responses API |
|---|---|
prompt | input |
messages | input (array of items) |
max_tokens | max_output_tokens |
response_format | text.format (object) |
temperature | temperature (no change) |
stop | stop (no change) |
frequency_penalty | frequency_penalty (no change) |
presence_penalty | presence_penalty (no change) |
tools / function-calling | tools (no change) |
seed | Remove am (no support) |
store | store (set am to false) |
content[].type: "text" | content[].type: "input_text" |
content[].type: "image_url" | content[].type: "input_image" |
"image_url": {"url": "..."} | "image_url": "..." (flat string) |
For complete before/after code examples, see cheat-sheet.md.
For test infrastructure migration (mocks, snapshots, assertions), see test-migration.md.
For troubleshooting errors and gotchas, see troubleshooting.md.
store: false dey for all Responses requests.rg "chat\.completions\.create|ChatCompletion\.create|Completion\.create" for migrated files.rg "AzureOpenAI\(|AsyncAzureOpenAI\(" — all constructors use OpenAI/AsyncOpenAI with v1 endpoint.rg "models\.github\.ai|models\.inference\.ai\.azure" — GitHub Models code paths don remove.rg "OpenAIChatCompletionClient" — MAF 1.0.0+ uses OpenAIChatClient (wey dey use Responses API). For pre-1.0.0, upgrade to agent-framework-openai>=1.0.0.ChatOpenAI(...) calls get use_responses_api=True.rg "choices\[0\]" — all response reading dey use resp.output_text or Responses output format.response_format at top level; all structured output use text={"format": {...}}.openai>=1.108.1 and azure-identity dey requirements.txt or pyproject.toml; dependencies don reinstall.store=False set for every responses.create call.api_version for client build; remove AZURE_OPENAI_API_VERSION from env and infra.rg "ChatCompletionChunk|AsyncCompletions\.create|chat\.completions" tests/.rg "_azure_ad_token_provider" tests/ — assertions update to check isinstance(client, AsyncOpenAI) or base_url.rg "prompt_filter_results|content_filter_results" tests/ — Azure-specific filter mocks don remove.kwargs.get("input") no be kwargs.get("messages").choices[0], function_call, logprobs, etc.).pytest pass well wit zero failures after test update.responses.create return non-empty output_text.response.output_text.delta events wit non-empty deltas.text.format wit json_schema, json.loads(resp.output_text) go succeed and match the schema.output_text (no infinite loop).AsyncAzureOpenAI before, AsyncOpenAI equivalent go work wit await.| Package | Minimum Version |
|---|---|
openai | >=1.108.1 |
azure-identity | Latest (for EntraID auth) |
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SKILL.md and 3 other files (references) in translations/pcm/.agents/skills/azure-openai-to-responses of microsoft/ai-agents-for-beginners.
Open the folder on GitHubat commit ff2ba66
Azure Openai To Responses next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Azure Openai To Responses this skillmicrosoft/ai-agents-for-beginners | 77k | — | ~6k | Automated safety check: Notes | MIT | |
| Gemini API Devgoogle-gemini/gemini-skills | 4.3k | — | ~5.1k | Automated safety check: Pass | Apache-2.0 | |
| Gemini API DevAyuilos/Miffan | 225 | — | ~1.4k | Automated safety check: Pass | AGPL-3.0 | |
| Tool Designagentailor/fullstack-langgraph-nextjs-agent | 132 | — | ~3.2k | Automated safety check: Pass | MIT | |
| Azure AI Projects Python SDKmicrosoft/skills | 3.1k | — | ~2.8k | Automated safety check: Pass | MIT | |
| Azure AI Openai Dotnetmicrosoft/skills | 3.1k | 5 repos | ~3.4k | Automated safety check: Pass | MIT |
google-gemini/gemini-skills
A skill your agent uses when writing code that calls the Gemini API for text generation, multi-turn chat, multimodal understanding, image generation, video generation, speech generation (TTS), voice…
Ayuilos/Miffan
A skill your agent uses when building applications with Gemini API hosted models, including Gemini and Gemma 4, working with multimodal content (text, images, audio, video), implementing function…
agentailor/fullstack-langgraph-nextjs-agent
Design and verify tools that AI agents can actually use — for any framework or language (MCP servers, LangChain/LangGraph, function-calling, raw JSON schema; TypeScript, Python, or otherwise).
microsoft/skills
Reference for building on Microsoft Foundry with the azure-ai-projects Python SDK: project clients, versioned agents, evaluations, connections, datasets and indexes.
microsoft/skills
Azure OpenAI SDK for .NET. An agent skill from microsoft/skills.
coco-research/coco
A skill your agent uses when implementing GPT chat, streaming, function calling, embeddings for RAG, images, audio or batch jobs, or troubleshooting 429 rate limits and API or TypeScript errors.
microsoft/ai-agents-for-beginners
A skill your agent uses when the user asks to create, scaffold, or edit Jupyter notebooks (.ipynb) for experiments, explorations, or tutorials; prefer the bundled templates and run the helper script…
microsoft/ai-agents-for-beginners
Migrate Python apps from Azure OpenAI Chat Completions to the Responses API.
microsoft/ai-agents-for-beginners
Kasuta, kui kasutaja palub luua, üles ehitada või redigeerida Jupyteri märkmikke (.ipynb) katsetuste, uurimiste või juhendite jaoks; eelista kaasasolevaid malle ja käivita abiskript newnotebook.py…
microsoft/ai-agents-for-beginners
Käytetään, kun käyttäjä pyytää luomaan, alustamaan tai muokkaamaan Jupyter-muistikirjoja (.ipynb) kokeita, tutkimuksia tai opetusohjelmia varten; käytä mieluummin mukana olevia mallipohjia ja…
microsoft/ai-agents-for-beginners
À utiliser lorsque l'utilisateur demande de créer, structurer ou modifier des notebooks Jupyter (.ipynb) pour des expériences, explorations ou tutoriels ; privilégiez les modèles fournis et exécutez…
microsoft/ai-agents-for-beginners
उपयोग तब करें जब उपयोगकर्ता प्रयोगों, खोजों, या ट्यूटोरियल्स के लिए Jupyter नोटबुक (.ipynb) बनाने, स्कैफोल्ड करने, या संपादित करने के लिए कहे; पैकेज किए गए टेम्पलेट्स को प्राथमिकता दें और एक साफ…
Categories
Shift Python apps dem from Azure OpenAI Chat Completions go Responses API. Azure Openai To Responses is an agent skill from microsoft/ai-agents-for-beginners, published by the product's own GitHub organization. Shift Python apps dem from Azure OpenAI Chat Completions go Responses API.
Azure Openai To Responses fits situations like: : shift go responses API; change from chat completions; openai responses; upgrade openai SDK.
Run `npx skills add microsoft/ai-agents-for-beginners --skill azure-openai-to-responses -a claude-code`. Or copy the skill folder (translations/pcm/.agents/skills/azure-openai-to-responses in microsoft/ai-agents-for-beginners) into .claude/skills/azure-openai-to-responses in your project. Claude Code loads it when a task matches its description.
Run `npx skills add microsoft/ai-agents-for-beginners --skill azure-openai-to-responses -a codex`. Or copy the skill folder (translations/pcm/.agents/skills/azure-openai-to-responses in microsoft/ai-agents-for-beginners) into .agents/skills/azure-openai-to-responses in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add microsoft/ai-agents-for-beginners --skill azure-openai-to-responses -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/azure-openai-to-responses, .gemini/skills/azure-openai-to-responses, .github/skills/azure-openai-to-responses and .opencode/skills/azure-openai-to-responses in your project.
Going by SKILL.md and its folder, Azure Openai To Responses needs the command-line tools its instructions call (rg, python and git) and credentials named AZURE_OPENAI_API_KEY. Our summary lists: Python 3; A credential in AZURE_OPENAI_API_KEY.
SKILL.md names 6 domains. In commands or code: cdn.jsdelivr.net; the agent is likely to contact it when it follows the instructions. As links in the text: learn.microsoft.com, aka.ms, npmjs.com, platform.openai.com and github.com. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found notes only (mentions a .env file), nothing it rates as a warning. It is not a guarantee. Review the folder before installing.
Azure Openai To Responses is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.
About 6k tokens (SKILL.md is roughly 24k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 13k tokens, read only when the agent opens those files.
Skills that share tags, products or a category with Azure Openai To Responses: Gemini API Dev (google-gemini/gemini-skills, 4.3k stars), Gemini API Dev (Ayuilos/Miffan, 225 stars), Tool Design (agentailor/fullstack-langgraph-nextjs-agent, 132 stars) and Azure AI Projects Python SDK (microsoft/skills, 3.1k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
microsoft (a GitHub organization, an official publisher) maintains it in microsoft/ai-agents-for-beginners, which has 76,795 GitHub stars. The repository holds 122 skills in this directory. The repository was last updated on October 9, 2026.
Source: microsoft/ai-agents-for-beginners on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.