feat(llm): add Azure OpenAI integration

.cursorrules

@@ -22,6 +22,7 @@ venv/bin/python ./tools/llm_api.py --prompt "What is the capital of France?" --p
 
 The LLM API supports multiple providers:
 - OpenAI (default, model: gpt-4o)
+- Azure OpenAI (model: configured via AZURE_OPENAI_MODEL_DEPLOYMENT in .env file, defaults to gpt-4o-ms)
 - DeepSeek (model: deepseek-chat)
 - Anthropic (model: claude-3-sonnet-20240229)
 - Gemini (model: gemini-pro)

.env.example

@@ -1,4 +1,6 @@
 OPENAI_API_KEY=your_openai_api_key_here
 ANTHROPIC_API_KEY=your_anthropic_api_key_here
 DEEPSEEK_API_KEY=your_deepseek_api_key_here
-GOOGLE_API_KEY=your_google_api_key_here
+GOOGLE_API_KEY=your_google_api_key_here
+AZURE_OPENAI_API_KEY=your_azure_openai_api_key_here
+AZURE_OPENAI_MODEL_DEPLOYMENT=gpt-4o-ms

tests/test_llm_api.py

@@ -117,10 +117,22 @@ def setUp(self):
             'OPENAI_API_KEY': 'test-openai-key',
             'DEEPSEEK_API_KEY': 'test-deepseek-key',
             'ANTHROPIC_API_KEY': 'test-anthropic-key',
-            'GOOGLE_API_KEY': 'test-google-key'
+            'GOOGLE_API_KEY': 'test-google-key',
+            'AZURE_OPENAI_API_KEY': 'test-azure-key',
+            'AZURE_OPENAI_MODEL_DEPLOYMENT': 'test-model-deployment'
         })
         self.env_patcher.start()
-
+
+        # Set up Azure OpenAI mock
+        self.mock_azure_response = MagicMock()
+        self.mock_azure_choice = MagicMock()
+        self.mock_azure_message = MagicMock()
+        self.mock_azure_message.content = "Test Azure OpenAI response"
+        self.mock_azure_choice.message = self.mock_azure_message
+        self.mock_azure_response.choices = [self.mock_azure_choice]
+        self.mock_azure_client = MagicMock()
+        self.mock_azure_client.chat.completions.create.return_value = self.mock_azure_response
+
     def tearDown(self):
         self.env_patcher.stop()
 
@@ -132,6 +144,18 @@ def test_create_openai_client(self, mock_openai):
         mock_openai.assert_called_once_with(api_key='test-openai-key')
         self.assertEqual(client, self.mock_openai_client)
 
+    @unittest.skipIf(skip_llm_tests, skip_message)
+    @patch('tools.llm_api.AzureOpenAI')
+    def test_create_azure_client(self, mock_azure):
+        mock_azure.return_value = self.mock_azure_client
+        client = create_llm_client("azure")
+        mock_azure.assert_called_once_with(
+            api_key='test-azure-key',
+            api_version="2024-02-15-preview",
+            azure_endpoint="https://msopenai.openai.azure.com"
+        )
+        self.assertEqual(client, self.mock_azure_client)
+
     @unittest.skipIf(skip_llm_tests, skip_message)
     @patch('tools.llm_api.OpenAI')
     def test_create_deepseek_client(self, mock_openai):
@@ -186,6 +210,18 @@ def test_query_openai(self, mock_create_client):
             temperature=0.7
         )
 
+    @unittest.skipIf(skip_llm_tests, skip_message)
+    @patch('tools.llm_api.create_llm_client')
+    def test_query_azure(self, mock_create_client):
+        mock_create_client.return_value = self.mock_azure_client
+        response = query_llm("Test prompt", provider="azure")
+        self.assertEqual(response, "Test Azure OpenAI response")
+        self.mock_azure_client.chat.completions.create.assert_called_once_with(
+            model=os.getenv('AZURE_OPENAI_MODEL_DEPLOYMENT', 'gpt-4o-ms'),
+            messages=[{"role": "user", "content": "Test prompt"}],
+            temperature=0.7
+        )
+
     @unittest.skipIf(skip_llm_tests, skip_message)
     @patch('tools.llm_api.create_llm_client')
     def test_query_deepseek(self, mock_create_client):

tools/llm_api.py

@@ -1,7 +1,7 @@
 #!/usr/bin/env /workspace/tmp_windsurf/venv/bin/python3
 
 import google.generativeai as genai
-from openai import OpenAI
+from openai import OpenAI, AzureOpenAI
 from anthropic import Anthropic
 import argparse
 import os
@@ -51,6 +51,15 @@ def create_llm_client(provider="openai"):
         return OpenAI(
             api_key=api_key
         )
+    elif provider == "azure":
+        api_key = os.getenv('AZURE_OPENAI_API_KEY')
+        if not api_key:
+            raise ValueError("AZURE_OPENAI_API_KEY not found in environment variables")
+        return AzureOpenAI(
+            api_key=api_key,
+            api_version="2024-02-15-preview",
+            azure_endpoint="https://msopenai.openai.azure.com"
+        )
     elif provider == "deepseek":
         api_key = os.getenv('DEEPSEEK_API_KEY')
         if not api_key:
@@ -89,6 +98,8 @@ def query_llm(prompt, client=None, model=None, provider="openai"):
         if model is None:
             if provider == "openai":
                 model = "gpt-4o"
+            elif provider == "azure":
+                model = os.getenv('AZURE_OPENAI_MODEL_DEPLOYMENT', 'gpt-4o-ms')  # Get from env with fallback
             elif provider == "deepseek":
                 model = "deepseek-chat"
             elif provider == "anthropic":
@@ -98,7 +109,7 @@ def query_llm(prompt, client=None, model=None, provider="openai"):
             elif provider == "local":
                 model = "Qwen/Qwen2.5-32B-Instruct-AWQ"
 
-        if provider == "openai" or provider == "local" or provider == "deepseek":
+        if provider in ["openai", "local", "deepseek", "azure"]:
             response = client.chat.completions.create(
                 model=model,
                 messages=[
@@ -127,7 +138,7 @@ def query_llm(prompt, client=None, model=None, provider="openai"):
 def main():
     parser = argparse.ArgumentParser(description='Query an LLM with a prompt')
     parser.add_argument('--prompt', type=str, help='The prompt to send to the LLM', required=True)
-    parser.add_argument('--provider', choices=['openai','anthropic','gemini','local','deepseek'], default='openai', help='The API provider to use')
+    parser.add_argument('--provider', choices=['openai','anthropic','gemini','local','deepseek','azure'], default='openai', help='The API provider to use')
     parser.add_argument('--model', type=str, help='The model to use (default depends on provider)')
     args = parser.parse_args()
 
@@ -140,6 +151,8 @@ def main():
             args.model = "claude-3-5-sonnet-20241022"
         elif args.provider == 'gemini':
             args.model = "gemini-2.0-flash-exp"
+        elif args.provider == 'azure':
+            args.model = os.getenv('AZURE_OPENAI_MODEL_DEPLOYMENT', 'gpt-4o-ms')  # Get from env with fallback
 
     client = create_llm_client(args.provider)
     response = query_llm(args.prompt, client, model=args.model, provider=args.provider)