| name | azure-openai-to-responses |
| license | MIT |
| description | 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 responses, AzureOpenAI go OpenAI client, python azure openai upgrade. DO NOT USE FOR: build new apps from scratch (start with responses directly), Node/TypeScript/C#/Java/Go migrations (dis skill na Python-only), Azure infrastructure setup (use azure-prepare), deploy models (use microsoft-foundry). |
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.
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
⚠️ 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
⚠️ 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.
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.
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:
- Replace di CDN script tag:
<script src="https://cdn.jsdelivr.net/npm/@microsoft/ai-chat-protocol@.../dist/iife/index.js"></script>
<script src="https://cdn.jsdelivr.net/npm/ndjson-readablestream@1.0.7/dist/ndjson-readablestream.umd.js"></script>
- Remove
AIChatProtocolClient instantiation (new ChatProtocol.AIChatProtocolClient("/chat")).
- Replace
client.getStreamedCompletion(messages) with direct fetch() call to backend streaming endpoint.
- Replace
for await (const response of result) with for await (const chunk of readNDJSONStream(response.body)).
- Change property access from
response.delta.content / response.error to chunk.delta.content / chunk.error.
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).
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.
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.
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:
rg "chat\.completions\.create"
rg "ChatCompletion\.create"
rg "Completion\.create"
rg "AzureOpenAI\("
rg "AsyncAzureOpenAI\("
rg "choices\[0\]\.message\.content"
rg "choices\[0\]\.delta\.content"
rg "choices\[0\]\.message\.function_call"
rg "choices\[0\]\.message\.tool_calls"
rg '"function":\s*{\s*"name"'
rg "pydantic_function_tool"
rg '"role":\s*"tool"'
rg '"tool_call_id"'
rg "response_format"
rg "max_tokens\b"
rg "['\"]seed['\"]"
rg "AZURE_OPENAI_API_VERSION|AZURE_OPENAI_VERSION"
rg "AZURE_OPENAI_CLIENT_ID"
rg "models\.github\.ai|models\.inference\.ai\.azure"
rg "OpenAIChatCompletionClient"
rg "ChatOpenAI\(" | grep -v "use_responses_api"
rg "ChatCompletionChunk|AsyncCompletions\.create" tests/
rg "_azure_ad_token_provider" tests/
rg "prompt_filter_results|content_filter_results" tests/
rg "choices\[0\]" tests/
rg 'innererror.*content_filter_result|error\.body\["innererror"\]'
rg "content_filter_result\["
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: 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).
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.
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.
Acceptance Criteria
Code-level gates (all must pass)
Test infrastructure gates (all must pass)
Behavioral gates (verify manually or with test harness)
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).
SDK Version Requirements
| Package | Minimum Version |
|---|
openai | >=1.108.1 |
azure-identity | Latest (for EntraID auth) |
References
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.