Migrate Python Apps from Azure OpenAI Chat Completions to Responses API

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.

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Triggers

Activate dis skill wen user want:

• Migrate a Python app from Azure OpenAI Chat Completions to Responses API
• Upgrade Python OpenAI SDK usage to di latest API shape for Azure OpenAI
• Prepare Python code for GPT-5 or newer models wey need Responses on Azure
• Switch from AzureOpenAI/AsyncAzureOpenAI go standard OpenAI/AsyncOpenAI client with di v1 endpoint
• Fix deprecation warnings wey concern AzureOpenAI constructors or api_version

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⚠️ Model Compatibility — CHECK FIRST

Before you migrate, make sure say your Azure OpenAI deployment support Responses API.

1. Smoke-test your deployment (fastest)

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_tokens get 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.

2. Check models wey dey your region (recommended)

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_REGION

Dis 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.

3. Full model support reference

• Live query: python migrate.py models (see am above — region-specific, always updated)
• Browse availability: Model summary table and region availability
• Quickstart & guidance: https://aka.ms/openai/start

⚠️ Older model limitations

WARNING: Older models (before gpt-4.1) fit no fit support all Responses API features fully.

Known limitations with older models:

• reasoning parameter: No support for many non-reasoning models. Only migrate reasoning if e already dey for original code.
• seed parameter: No dey support at all for Responses API — remove from all requests.
• Structured output via text.format: Older models no sure to enforce strict: true JSON 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 to 1. Older models no get dis kind limit.

O-series reasoning models (o1, o3-mini, o3, o4-mini)

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.
• Streaming behavior: O-series models fit hold output till reasoning finish before e dey send text delta events. Streaming still work, but first response.output_text.delta fit show late than GPT models.
• top_p: No support for o-series — remove if e dey.
• Tool use: O-series models support tools via Responses API same as GPT, but tool call orchestration quality depend on model.

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:

• Migration go work for basic text, chat, streaming, and tools for their current model.
• Newer models (gpt-5.1, gpt-5.2) get better tool orchestration, structured output enforcement, reasoning, and cross-region availability.
• Dem suppose think about upgrading deployment when dem ready — e no go block migration.

No block or refuse migrate based on model version. Dis advisory be just info.

GitHub Models no support Responses API

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:

• Flag any GitHub Models code paths for removal.

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Framework Migration

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.

Microsoft Agent Framework (MAF)

Check your MAF version first — migration depends on whether you dey on MAF 1.0.0+ or before 1.0.0 beta/rc.

MAF 1.0.0+ (agent-framework-openai >= 1.0.0)

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__)"

MAF pre-1.0.0 (beta/rc releases)

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 (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.

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Frontend Migration Guidance

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 deprecation

The @microsoft/ai-chat-protocol npm package don deprecate, make you replace am with ndjson-readablestream. If you see am for frontend:

1. Replace di CDN script tag:

   <!-- 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>
   

2. Remove AIChatProtocolClient instantiation (new ChatProtocol.AIChatProtocolClient("/chat")).
3. Replace client.getStreamedCompletion(messages) with direct fetch() call to backend streaming endpoint.
4. Replace for await (const response of result) with for await (const chunk of readNDJSONStream(response.body)).
5. Change property access from response.delta.content / response.error to chunk.delta.content / chunk.error.

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Goals

• List all Python call sites wey dey use Chat Completions or old Completions for Azure OpenAI.
• Propose migration plan and sequence for Python codebase.
• Apply safe, small edits to switch to Responses API.
• Update callers to use Responses output schema; no backcompat wrappers.
• Run tests/lints; fix small breaks introduced by migration.
• Prepare small, reviewable change sets and give final summary with diffs (no commit).

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Guardrails

• Only change files inside git workspace. No write outside.
• No preserve backward-compatibility shims; migrate code to new API shape.
• No leave tombstone/transition comments or backup files.
• Keep streaming semantics if e dey before; otherwise use non-streaming.
• Ask approval before run commands or network calls if approval mode dey.
• No run git add/git commit/git push; only produce working-tree edits.

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Step 0: Azure OpenAI Client Migration (Prerequisite)

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.

Why the v1 API path?

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.

Key changes

Before	After
AzureOpenAI	OpenAI
AsyncAzureOpenAI	AsyncOpenAI
azure_endpoint	base_url
azure_ad_token_provider	api_key
api_version=...	Remove completely

Cleanup checklist

• Remove api_version argument from client construction.
• Remove AZURE_OPENAI_VERSION / AZURE_OPENAI_API_VERSION environment variables from .env, app settings, and Bicep/infra files.
• Rename AZURE_OPENAI_CLIENT_ID → AZURE_CLIENT_ID for .env, app settings, Bicep/infra, and test fixtures (standard Azure Identity SDK convention).
• Ensure openai>=1.108.1 in requirements.txt or pyproject.toml.

Environment variable migration

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.

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Step 1: Detect Legacy Call Sites

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="

Heuristics (detect and rewrite)

• 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: .

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Step 2: Apply Migration

Migration notes (Chat Completions → Responses)

• Why migrate: Responses na one API wey dey handle text, tools, and streaming well-well; Chat Completions don old. Wit GPT-5, Responses dey needed for beta performance.
• HTTP: Azure endpoint change from /openai/deployments/{name}/chat/completions to /openai/v1/responses.
• Fields: change messages → input, max_tokens → max_output_tokens. temperature no change.
• Formatting: change response_format to text.format wit correct object.
• Content items: change Chat content[].type: "text" to Responses content[].type: "input_text" for system or user turns.
• Image content items: change Chat 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).

Parameter mapping reference

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.

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Data Retention & State

• Make sure store: false dey for all Responses requests.
• No rely on previous message IDs or server-stored context; keep state client side and minimize metadata.

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Acceptance Criteria

Code-level gates (all must pass)

• No find rg "chat\.completions\.create|ChatCompletion\.create|Completion\.create" for migrated files.
• No find rg "AzureOpenAI\(|AsyncAzureOpenAI\(" — all constructors use OpenAI/AsyncOpenAI with v1 endpoint.
• No find rg "models\.github\.ai|models\.inference\.ai\.azure" — GitHub Models code paths don remove.
• No find 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.
• All ChatOpenAI(...) calls get use_responses_api=True.
• No find rg "choices\[0\]" — all response reading dey use resp.output_text or Responses output format.
• No 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.
• No api_version for client build; remove AZURE_OPENAI_API_VERSION from env and infra.

Test infrastructure gates (all must pass)

• No find rg "ChatCompletionChunk|AsyncCompletions\.create|chat\.completions" tests/.
• No find rg "_azure_ad_token_provider" tests/ — assertions update to check isinstance(client, AsyncOpenAI) or base_url.
• No find rg "prompt_filter_results|content_filter_results" tests/ — Azure-specific filter mocks don remove.
• Mock fixtures use kwargs.get("input") no be kwargs.get("messages").
• Snapshot / golden files don update to Responses streaming shape (no choices[0], function_call, logprobs, etc.).
• pytest pass well wit zero failures after test update.

Behavioral gates (verify manually or with test harness)

• Basic completion: non-streaming responses.create return non-empty output_text.
• Stream parity: if original code use streaming, migrated code streams and yield response.output_text.delta events wit non-empty deltas.
• Structured output: if you dey use text.format wit json_schema, json.loads(resp.output_text) go succeed and match the schema.
• Tool-call loop: if you dey use tools, model go issue tool calls, app go run dem, then follow-up request go return final output_text (no infinite loop).
• Async parity: if you use AsyncAzureOpenAI before, AsyncOpenAI equivalent go work wit await.
• Error rate: no new 400/401/404 errors compared to pre-migration baseline.

Deliverables

• Summary go show edited files, before/after counts of old call sites, and next steps.
• Changes go be working-tree edits only (no commits).

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SDK Version Requirements

Package	Minimum Version
openai	>=1.108.1
azure-identity	Latest (for EntraID auth)

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References

• Cheat Sheet — all code snippets
• Test Migration — mocks, snapshots, assertions
• Troubleshooting — errors, risk table, gotchas
• detect_legacy.py — automated scanner
• Azure OpenAI Starter Kit
• Azure OpenAI Responses API docs
• Azure OpenAI API version lifecycle
• OpenAI Responses API reference

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Disclaimer: Dis document don translate wit AI translation service Co-op Translator. Even tho we dey try make am correct, abeg make you know say automated translation fit get errors or mistakes. Di original document for dia own language na im be di correct source. For important info, make person wey sabi human translation do am. We no go responsible for any misunderstanding or wrong understanding wey fit happen because of dis translation.