Support Azure OpenAI
This commit is contained in:
Kunal Karmakar
@@ -203,6 +203,7 @@ def _make_provider(config: Config):
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from nanobot.providers.custom_provider import CustomProvider
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from nanobot.providers.litellm_provider import LiteLLMProvider
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from nanobot.providers.openai_codex_provider import OpenAICodexProvider
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from nanobot.providers.azure_openai_provider import AzureOpenAIProvider
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model = config.agents.defaults.model
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provider_name = config.get_provider_name(model)
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@@ -220,6 +221,20 @@ def _make_provider(config: Config):
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default_model=model,
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)
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# Azure OpenAI: direct Azure OpenAI endpoint with deployment name
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if provider_name == "azure_openai":
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if not p or not p.api_key or not p.api_base:
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console.print("[red]Error: Azure OpenAI requires api_key and api_base.[/red]")
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console.print("Set them in ~/.nanobot/config.json under providers.azure_openai section")
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console.print("Use the model field to specify the deployment name.")
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raise typer.Exit(1)
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return AzureOpenAIProvider(
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api_key=p.api_key,
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api_base=p.api_base,
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default_model=model,
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)
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from nanobot.providers.registry import find_by_name
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spec = find_by_name(provider_name)
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if not model.startswith("bedrock/") and not (p and p.api_key) and not (spec and spec.is_oauth):
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@@ -266,6 +266,7 @@ class ProvidersConfig(Base):
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"""Configuration for LLM providers."""
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custom: ProviderConfig = Field(default_factory=ProviderConfig) # Any OpenAI-compatible endpoint
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azure_openai: ProviderConfig = Field(default_factory=ProviderConfig) # Azure OpenAI (model = deployment name)
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anthropic: ProviderConfig = Field(default_factory=ProviderConfig)
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openai: ProviderConfig = Field(default_factory=ProviderConfig)
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openrouter: ProviderConfig = Field(default_factory=ProviderConfig)
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@@ -3,5 +3,6 @@
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from nanobot.providers.base import LLMProvider, LLMResponse
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from nanobot.providers.litellm_provider import LiteLLMProvider
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from nanobot.providers.openai_codex_provider import OpenAICodexProvider
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from nanobot.providers.azure_openai_provider import AzureOpenAIProvider
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__all__ = ["LLMProvider", "LLMResponse", "LiteLLMProvider", "OpenAICodexProvider"]
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__all__ = ["LLMProvider", "LLMResponse", "LiteLLMProvider", "OpenAICodexProvider", "AzureOpenAIProvider"]
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192
nanobot/providers/azure_openai_provider.py
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192
nanobot/providers/azure_openai_provider.py
Normal file
@@ -0,0 +1,192 @@
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"""Azure OpenAI provider implementation with API version 2024-10-21."""
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from __future__ import annotations
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import uuid
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from typing import Any
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from urllib.parse import urljoin
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import httpx
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import json_repair
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from nanobot.providers.base import LLMProvider, LLMResponse, ToolCallRequest
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class AzureOpenAIProvider(LLMProvider):
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"""
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Azure OpenAI provider with API version 2024-10-21 compliance.
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Features:
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- Hardcoded API version 2024-10-21
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- Uses model field as Azure deployment name in URL path
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- Uses api-key header instead of Authorization Bearer
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- Uses max_completion_tokens instead of max_tokens
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- Direct HTTP calls, bypasses LiteLLM
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"""
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def __init__(
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self,
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api_key: str = "",
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api_base: str = "",
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default_model: str = "gpt-5.2-chat",
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):
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super().__init__(api_key, api_base)
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self.default_model = default_model
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self.api_version = "2024-10-21"
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# Validate required parameters
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if not api_key:
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raise ValueError("Azure OpenAI api_key is required")
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if not api_base:
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raise ValueError("Azure OpenAI api_base is required")
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# Ensure api_base ends with /
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if not api_base.endswith('/'):
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api_base += '/'
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self.api_base = api_base
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def _build_chat_url(self, deployment_name: str) -> str:
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"""Build the Azure OpenAI chat completions URL."""
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# Azure OpenAI URL format:
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# https://{resource}.openai.azure.com/openai/deployments/{deployment}/chat/completions?api-version={version}
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base_url = self.api_base
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if not base_url.endswith('/'):
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base_url += '/'
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url = urljoin(
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base_url,
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f"openai/deployments/{deployment_name}/chat/completions"
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)
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return f"{url}?api-version={self.api_version}"
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def _build_headers(self) -> dict[str, str]:
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"""Build headers for Azure OpenAI API with api-key header."""
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return {
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"Content-Type": "application/json",
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"api-key": self.api_key, # Azure OpenAI uses api-key header, not Authorization
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"x-session-affinity": uuid.uuid4().hex, # For cache locality
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}
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def _prepare_request_payload(
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self,
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messages: list[dict[str, Any]],
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tools: list[dict[str, Any]] | None = None,
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model: str | None = None,
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max_tokens: int = 4096,
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temperature: float = 0.7,
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reasoning_effort: str | None = None,
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) -> dict[str, Any]:
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"""Prepare the request payload with Azure OpenAI 2024-10-21 compliance."""
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payload: dict[str, Any] = {
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"messages": self._sanitize_empty_content(messages),
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"max_completion_tokens": max(1, max_tokens), # Azure API 2024-10-21 uses max_completion_tokens
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"temperature": temperature,
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}
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if reasoning_effort:
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payload["reasoning_effort"] = reasoning_effort
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if tools:
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payload["tools"] = tools
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payload["tool_choice"] = "auto"
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return payload
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async def chat(
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self,
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messages: list[dict[str, Any]],
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tools: list[dict[str, Any]] | None = None,
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model: str | None = None,
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max_tokens: int = 4096,
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temperature: float = 0.7,
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reasoning_effort: str | None = None,
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) -> LLMResponse:
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"""
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Send a chat completion request to Azure OpenAI.
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Args:
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messages: List of message dicts with 'role' and 'content'.
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tools: Optional list of tool definitions in OpenAI format.
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model: Model identifier (used as deployment name).
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max_tokens: Maximum tokens in response (mapped to max_completion_tokens).
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temperature: Sampling temperature.
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reasoning_effort: Optional reasoning effort parameter.
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Returns:
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LLMResponse with content and/or tool calls.
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"""
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deployment_name = model or self.default_model
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url = self._build_chat_url(deployment_name)
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headers = self._build_headers()
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payload = self._prepare_request_payload(
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messages, tools, model, max_tokens, temperature, reasoning_effort
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)
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try:
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async with httpx.AsyncClient() as client:
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response = await client.post(url, headers=headers, json=payload)
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if response.status_code != 200:
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return LLMResponse(
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content=f"Azure OpenAI API Error {response.status_code}: {response.text}",
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finish_reason="error",
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)
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response_data = await response.json()
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return self._parse_response(response_data)
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except Exception as e:
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return LLMResponse(
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content=f"Error calling Azure OpenAI: {str(e)}",
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finish_reason="error",
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)
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def _parse_response(self, response: dict[str, Any]) -> LLMResponse:
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"""Parse Azure OpenAI response into our standard format."""
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try:
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choice = response["choices"][0]
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message = choice["message"]
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tool_calls = []
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if message.get("tool_calls"):
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for tc in message["tool_calls"]:
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# Parse arguments from JSON string if needed
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args = tc["function"]["arguments"]
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if isinstance(args, str):
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args = json_repair.loads(args)
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tool_calls.append(
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ToolCallRequest(
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id=tc["id"],
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name=tc["function"]["name"],
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arguments=args,
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)
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)
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usage = {}
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if response.get("usage"):
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usage_data = response["usage"]
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usage = {
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"prompt_tokens": usage_data.get("prompt_tokens", 0),
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"completion_tokens": usage_data.get("completion_tokens", 0),
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"total_tokens": usage_data.get("total_tokens", 0),
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}
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reasoning_content = message.get("reasoning_content") or None
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return LLMResponse(
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content=message.get("content"),
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tool_calls=tool_calls,
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finish_reason=choice.get("finish_reason", "stop"),
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usage=usage,
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reasoning_content=reasoning_content,
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)
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except (KeyError, IndexError) as e:
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return LLMResponse(
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content=f"Error parsing Azure OpenAI response: {str(e)}",
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finish_reason="error",
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)
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def get_default_model(self) -> str:
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"""Get the default model (also used as default deployment name)."""
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return self.default_model
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@@ -81,6 +81,16 @@ PROVIDERS: tuple[ProviderSpec, ...] = (
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is_direct=True,
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),
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# === Azure OpenAI (direct API calls with API version 2024-10-21) =====
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ProviderSpec(
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name="azure_openai",
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keywords=("azure", "azure-openai"),
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env_key="",
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display_name="Azure OpenAI",
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litellm_prefix="",
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is_direct=True,
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),
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# === Gateways (detected by api_key / api_base, not model name) =========
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# Gateways can route any model, so they win in fallback.
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356
tests/test_azure_openai_provider.py
Normal file
356
tests/test_azure_openai_provider.py
Normal file
@@ -0,0 +1,356 @@
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"""Test Azure OpenAI provider implementation (updated for model-based deployment names)."""
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import asyncio
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import pytest
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from unittest.mock import AsyncMock, patch
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from nanobot.providers.azure_openai_provider import AzureOpenAIProvider
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from nanobot.providers.base import LLMResponse
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def test_azure_openai_provider_init():
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"""Test AzureOpenAIProvider initialization without deployment_name."""
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provider = AzureOpenAIProvider(
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api_key="test-key",
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api_base="https://test-resource.openai.azure.com",
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default_model="gpt-4o-deployment",
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)
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assert provider.api_key == "test-key"
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assert provider.api_base == "https://test-resource.openai.azure.com/"
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assert provider.default_model == "gpt-4o-deployment"
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assert provider.api_version == "2024-10-21"
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def test_azure_openai_provider_init_validation():
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"""Test AzureOpenAIProvider initialization validation."""
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# Missing api_key
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with pytest.raises(ValueError, match="Azure OpenAI api_key is required"):
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AzureOpenAIProvider(api_key="", api_base="https://test.com")
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# Missing api_base
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with pytest.raises(ValueError, match="Azure OpenAI api_base is required"):
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AzureOpenAIProvider(api_key="test", api_base="")
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def test_build_chat_url():
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"""Test Azure OpenAI URL building with different deployment names."""
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provider = AzureOpenAIProvider(
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api_key="test-key",
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api_base="https://test-resource.openai.azure.com",
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default_model="gpt-4o",
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)
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# Test various deployment names
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test_cases = [
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("gpt-4o-deployment", "https://test-resource.openai.azure.com/openai/deployments/gpt-4o-deployment/chat/completions?api-version=2024-10-21"),
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("gpt-35-turbo", "https://test-resource.openai.azure.com/openai/deployments/gpt-35-turbo/chat/completions?api-version=2024-10-21"),
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("custom-model", "https://test-resource.openai.azure.com/openai/deployments/custom-model/chat/completions?api-version=2024-10-21"),
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]
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for deployment_name, expected_url in test_cases:
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url = provider._build_chat_url(deployment_name)
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assert url == expected_url
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def test_build_chat_url_api_base_without_slash():
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"""Test URL building when api_base doesn't end with slash."""
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provider = AzureOpenAIProvider(
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api_key="test-key",
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api_base="https://test-resource.openai.azure.com", # No trailing slash
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default_model="gpt-4o",
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)
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url = provider._build_chat_url("test-deployment")
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expected = "https://test-resource.openai.azure.com/openai/deployments/test-deployment/chat/completions?api-version=2024-10-21"
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assert url == expected
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def test_build_headers():
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"""Test Azure OpenAI header building with api-key authentication."""
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provider = AzureOpenAIProvider(
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api_key="test-api-key-123",
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api_base="https://test-resource.openai.azure.com",
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default_model="gpt-4o",
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)
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headers = provider._build_headers()
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assert headers["Content-Type"] == "application/json"
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assert headers["api-key"] == "test-api-key-123" # Azure OpenAI specific header
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assert "x-session-affinity" in headers
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def test_prepare_request_payload():
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"""Test request payload preparation with Azure OpenAI 2024-10-21 compliance."""
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provider = AzureOpenAIProvider(
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api_key="test-key",
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api_base="https://test-resource.openai.azure.com",
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default_model="gpt-4o",
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)
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messages = [{"role": "user", "content": "Hello"}]
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payload = provider._prepare_request_payload(messages, max_tokens=1500, temperature=0.8)
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assert payload["messages"] == messages
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assert payload["max_completion_tokens"] == 1500 # Azure API 2024-10-21 uses max_completion_tokens
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assert payload["temperature"] == 0.8
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assert "tools" not in payload
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# Test with tools
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tools = [{"type": "function", "function": {"name": "get_weather", "parameters": {}}}]
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payload_with_tools = provider._prepare_request_payload(messages, tools=tools)
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assert payload_with_tools["tools"] == tools
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assert payload_with_tools["tool_choice"] == "auto"
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# Test with reasoning_effort
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payload_with_reasoning = provider._prepare_request_payload(messages, reasoning_effort="medium")
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assert payload_with_reasoning["reasoning_effort"] == "medium"
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@pytest.mark.asyncio
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async def test_chat_success():
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"""Test successful chat request using model as deployment name."""
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provider = AzureOpenAIProvider(
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api_key="test-key",
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api_base="https://test-resource.openai.azure.com",
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default_model="gpt-4o-deployment",
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)
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# Mock response data
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mock_response_data = {
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"choices": [{
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"message": {
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"content": "Hello! How can I help you today?",
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"role": "assistant"
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},
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"finish_reason": "stop"
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}],
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"usage": {
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"prompt_tokens": 12,
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"completion_tokens": 18,
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"total_tokens": 30
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}
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}
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with patch("httpx.AsyncClient") as mock_client:
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mock_response = AsyncMock()
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mock_response.status_code = 200
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mock_response.json = AsyncMock(return_value=mock_response_data)
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mock_context = AsyncMock()
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mock_context.post = AsyncMock(return_value=mock_response)
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mock_client.return_value.__aenter__.return_value = mock_context
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# Test with specific model (deployment name)
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messages = [{"role": "user", "content": "Hello"}]
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result = await provider.chat(messages, model="custom-deployment")
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assert isinstance(result, LLMResponse)
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assert result.content == "Hello! How can I help you today?"
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assert result.finish_reason == "stop"
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assert result.usage["prompt_tokens"] == 12
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assert result.usage["completion_tokens"] == 18
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assert result.usage["total_tokens"] == 30
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# Verify URL was built with the provided model as deployment name
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call_args = mock_context.post.call_args
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expected_url = "https://test-resource.openai.azure.com/openai/deployments/custom-deployment/chat/completions?api-version=2024-10-21"
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assert call_args[0][0] == expected_url
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@pytest.mark.asyncio
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async def test_chat_uses_default_model_when_no_model_provided():
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"""Test that chat uses default_model when no model is specified."""
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provider = AzureOpenAIProvider(
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api_key="test-key",
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api_base="https://test-resource.openai.azure.com",
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default_model="default-deployment",
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)
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mock_response_data = {
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"choices": [{
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"message": {"content": "Response", "role": "assistant"},
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"finish_reason": "stop"
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}],
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"usage": {"prompt_tokens": 5, "completion_tokens": 5, "total_tokens": 10}
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}
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with patch("httpx.AsyncClient") as mock_client:
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mock_response = AsyncMock()
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mock_response.status_code = 200
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mock_response.json = AsyncMock(return_value=mock_response_data)
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mock_context = AsyncMock()
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mock_context.post = AsyncMock(return_value=mock_response)
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mock_client.return_value.__aenter__.return_value = mock_context
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messages = [{"role": "user", "content": "Test"}]
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await provider.chat(messages) # No model specified
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# Verify URL was built with default model as deployment name
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call_args = mock_context.post.call_args
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expected_url = "https://test-resource.openai.azure.com/openai/deployments/default-deployment/chat/completions?api-version=2024-10-21"
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assert call_args[0][0] == expected_url
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@pytest.mark.asyncio
|
||||
async def test_chat_with_tool_calls():
|
||||
"""Test chat request with tool calls in response."""
|
||||
provider = AzureOpenAIProvider(
|
||||
api_key="test-key",
|
||||
api_base="https://test-resource.openai.azure.com",
|
||||
default_model="gpt-4o",
|
||||
)
|
||||
|
||||
# Mock response with tool calls
|
||||
mock_response_data = {
|
||||
"choices": [{
|
||||
"message": {
|
||||
"content": None,
|
||||
"role": "assistant",
|
||||
"tool_calls": [{
|
||||
"id": "call_12345",
|
||||
"function": {
|
||||
"name": "get_weather",
|
||||
"arguments": '{"location": "San Francisco"}'
|
||||
}
|
||||
}]
|
||||
},
|
||||
"finish_reason": "tool_calls"
|
||||
}],
|
||||
"usage": {
|
||||
"prompt_tokens": 20,
|
||||
"completion_tokens": 15,
|
||||
"total_tokens": 35
|
||||
}
|
||||
}
|
||||
|
||||
with patch("httpx.AsyncClient") as mock_client:
|
||||
mock_response = AsyncMock()
|
||||
mock_response.status_code = 200
|
||||
mock_response.json = AsyncMock(return_value=mock_response_data)
|
||||
|
||||
mock_context = AsyncMock()
|
||||
mock_context.post = AsyncMock(return_value=mock_response)
|
||||
mock_client.return_value.__aenter__.return_value = mock_context
|
||||
|
||||
messages = [{"role": "user", "content": "What's the weather?"}]
|
||||
tools = [{"type": "function", "function": {"name": "get_weather", "parameters": {}}}]
|
||||
result = await provider.chat(messages, tools=tools, model="weather-model")
|
||||
|
||||
assert isinstance(result, LLMResponse)
|
||||
assert result.content is None
|
||||
assert result.finish_reason == "tool_calls"
|
||||
assert len(result.tool_calls) == 1
|
||||
assert result.tool_calls[0].name == "get_weather"
|
||||
assert result.tool_calls[0].arguments == {"location": "San Francisco"}
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_chat_api_error():
|
||||
"""Test chat request API error handling."""
|
||||
provider = AzureOpenAIProvider(
|
||||
api_key="test-key",
|
||||
api_base="https://test-resource.openai.azure.com",
|
||||
default_model="gpt-4o",
|
||||
)
|
||||
|
||||
with patch("httpx.AsyncClient") as mock_client:
|
||||
mock_response = AsyncMock()
|
||||
mock_response.status_code = 401
|
||||
mock_response.text = "Invalid authentication credentials"
|
||||
|
||||
mock_context = AsyncMock()
|
||||
mock_context.post = AsyncMock(return_value=mock_response)
|
||||
mock_client.return_value.__aenter__.return_value = mock_context
|
||||
|
||||
messages = [{"role": "user", "content": "Hello"}]
|
||||
result = await provider.chat(messages)
|
||||
|
||||
assert isinstance(result, LLMResponse)
|
||||
assert "Azure OpenAI API Error 401" in result.content
|
||||
assert "Invalid authentication credentials" in result.content
|
||||
assert result.finish_reason == "error"
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_chat_connection_error():
|
||||
"""Test chat request connection error handling."""
|
||||
provider = AzureOpenAIProvider(
|
||||
api_key="test-key",
|
||||
api_base="https://test-resource.openai.azure.com",
|
||||
default_model="gpt-4o",
|
||||
)
|
||||
|
||||
with patch("httpx.AsyncClient") as mock_client:
|
||||
mock_context = AsyncMock()
|
||||
mock_context.post = AsyncMock(side_effect=Exception("Connection failed"))
|
||||
mock_client.return_value.__aenter__.return_value = mock_context
|
||||
|
||||
messages = [{"role": "user", "content": "Hello"}]
|
||||
result = await provider.chat(messages)
|
||||
|
||||
assert isinstance(result, LLMResponse)
|
||||
assert "Error calling Azure OpenAI: Connection failed" in result.content
|
||||
assert result.finish_reason == "error"
|
||||
|
||||
|
||||
def test_parse_response_malformed():
|
||||
"""Test response parsing with malformed data."""
|
||||
provider = AzureOpenAIProvider(
|
||||
api_key="test-key",
|
||||
api_base="https://test-resource.openai.azure.com",
|
||||
default_model="gpt-4o",
|
||||
)
|
||||
|
||||
# Test with missing choices
|
||||
malformed_response = {"usage": {"prompt_tokens": 10}}
|
||||
result = provider._parse_response(malformed_response)
|
||||
|
||||
assert isinstance(result, LLMResponse)
|
||||
assert "Error parsing Azure OpenAI response" in result.content
|
||||
assert result.finish_reason == "error"
|
||||
|
||||
|
||||
def test_get_default_model():
|
||||
"""Test get_default_model method."""
|
||||
provider = AzureOpenAIProvider(
|
||||
api_key="test-key",
|
||||
api_base="https://test-resource.openai.azure.com",
|
||||
default_model="my-custom-deployment",
|
||||
)
|
||||
|
||||
assert provider.get_default_model() == "my-custom-deployment"
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
# Run basic tests
|
||||
print("Running basic Azure OpenAI provider tests...")
|
||||
|
||||
# Test initialization
|
||||
provider = AzureOpenAIProvider(
|
||||
api_key="test-key",
|
||||
api_base="https://test-resource.openai.azure.com",
|
||||
default_model="gpt-4o-deployment",
|
||||
)
|
||||
print("✅ Provider initialization successful")
|
||||
|
||||
# Test URL building
|
||||
url = provider._build_chat_url("my-deployment")
|
||||
expected = "https://test-resource.openai.azure.com/openai/deployments/my-deployment/chat/completions?api-version=2024-10-21"
|
||||
assert url == expected
|
||||
print("✅ URL building works correctly")
|
||||
|
||||
# Test headers
|
||||
headers = provider._build_headers()
|
||||
assert headers["api-key"] == "test-key"
|
||||
assert headers["Content-Type"] == "application/json"
|
||||
print("✅ Header building works correctly")
|
||||
|
||||
# Test payload preparation
|
||||
messages = [{"role": "user", "content": "Test"}]
|
||||
payload = provider._prepare_request_payload(messages, max_tokens=1000)
|
||||
assert payload["max_completion_tokens"] == 1000 # Azure 2024-10-21 format
|
||||
print("✅ Payload preparation works correctly")
|
||||
|
||||
print("✅ All basic tests passed! Updated test file is working correctly.")
|
||||
Reference in New Issue
Block a user