fix: address Gemini review feedback for PR #397

- Fix Ollama URL normalization bug (trailing slash edge case)
- Use rstrip('/') before checking /v1 suffix
- Add DRY pattern for Azure env var fallbacks
- Add final newline to azure_client.py
- Use shared OLLAMA_MODELS/AZURE_MODELS constants to avoid duplicates

cli/utils.py

@@ -14,6 +14,22 @@ ANALYST_ORDER = [
     ("Fundamentals Analyst", AnalystType.FUNDAMENTALS),
 ]
 
+# Shared model lists for providers with identical options in shallow/deep selections
+# Azure: deployment names are user-specific, so we provide common defaults
+AZURE_MODELS = [
+    ("GPT-4o (your deployment)", "gpt-4o"),
+    ("GPT-4o-mini (your deployment)", "gpt-4o-mini"),
+    ("GPT-4 Turbo (your deployment)", "gpt-4-turbo"),
+    ("Custom deployment name", "__custom__"),
+]
+
+# Ollama: same models for both shallow and deep (local inference)
+OLLAMA_MODELS = [
+    ("Qwen3:latest (8B, local)", "qwen3:latest"),
+    ("GPT-OSS:latest (20B, local)", "gpt-oss:latest"),
+    ("GLM-4.7-Flash:latest (30B, local)", "glm-4.7-flash:latest"),
+]
+
 
 def get_ticker() -> str:
     """Prompt the user to enter a ticker symbol."""
@@ -159,11 +175,8 @@ def select_shallow_thinking_agent(provider) -> str:
             ("NVIDIA Nemotron 3 Nano 30B (free)", "nvidia/nemotron-3-nano-30b-a3b:free"),
             ("Z.AI GLM 4.5 Air (free)", "z-ai/glm-4.5-air:free"),
         ],
-        "ollama": [
+        "ollama": OLLAMA_MODELS,
-            ("Qwen3:latest (8B, local)", "qwen3:latest"),
+        "azure": AZURE_MODELS,
-            ("GPT-OSS:latest (20B, local)", "gpt-oss:latest"),
-            ("GLM-4.7-Flash:latest (30B, local)", "glm-4.7-flash:latest"),
-        ],
     }
 
     choice = questionary.select(
@@ -226,11 +239,8 @@ def select_deep_thinking_agent(provider) -> str:
             ("Z.AI GLM 4.5 Air (free)", "z-ai/glm-4.5-air:free"),
             ("NVIDIA Nemotron 3 Nano 30B (free)", "nvidia/nemotron-3-nano-30b-a3b:free"),
         ],
-        "ollama": [
+        "ollama": OLLAMA_MODELS,
-            ("GLM-4.7-Flash:latest (30B, local)", "glm-4.7-flash:latest"),
+        "azure": AZURE_MODELS,
-            ("GPT-OSS:latest (20B, local)", "gpt-oss:latest"),
-            ("Qwen3:latest (8B, local)", "qwen3:latest"),
-        ],
     }
 
     choice = questionary.select(
@@ -265,6 +275,7 @@ def select_llm_provider() -> tuple[str, str]:
         ("xAI", "https://api.x.ai/v1"),
         ("Openrouter", "https://openrouter.ai/api/v1"),
         ("Ollama", "http://localhost:11434/v1"),
+        ("Azure OpenAI", "azure"),
     ]
     
     choice = questionary.select(

tradingagents/llm_clients/azure_client.py

@@ -0,0 +1,63 @@
+"""Azure OpenAI client implementation."""
+
+import os
+from typing import Any, Optional
+
+from langchain_openai import AzureChatOpenAI
+
+from .base_client import BaseLLMClient
+
+
+class AzureClient(BaseLLMClient):
+    """Client for Azure OpenAI provider.
+
+    Required environment variables:
+        AZURE_OPENAI_API_KEY: Your Azure OpenAI API key
+        AZURE_OPENAI_ENDPOINT: Your Azure endpoint (e.g., https://your-resource.openai.azure.com/)
+        OPENAI_API_VERSION: API version (e.g., 2024-02-15-preview)
+
+    Optional:
+        AZURE_DEPLOYMENT_NAME: Your deployment name (can also be passed as model parameter)
+    """
+
+    def __init__(
+        self,
+        model: str,
+        base_url: Optional[str] = None,
+        **kwargs,
+    ):
+        super().__init__(model, base_url, **kwargs)
+        # In Azure, model is the deployment name
+        self.deployment_name = model
+
+    def get_llm(self) -> Any:
+        """Return configured AzureChatOpenAI instance."""
+        llm_kwargs = {
+            "azure_deployment": self.deployment_name,
+        }
+
+        # Pass through Azure-specific kwargs
+        for key in ("timeout", "max_retries", "callbacks", "api_version",
+                    "azure_endpoint", "api_key", "http_client", "http_async_client"):
+            if key in self.kwargs:
+                llm_kwargs[key] = self.kwargs[key]
+
+        # Environment variable fallbacks (DRY pattern)
+        for kwarg_name, env_var in {
+            "azure_endpoint": "AZURE_OPENAI_ENDPOINT",
+            "api_key": "AZURE_OPENAI_API_KEY",
+        }.items():
+            if kwarg_name not in llm_kwargs:
+                value = os.environ.get(env_var)
+                if value:
+                    llm_kwargs[kwarg_name] = value
+
+        if "api_version" not in llm_kwargs:
+            api_version = os.environ.get("OPENAI_API_VERSION", "2024-02-15-preview")
+            llm_kwargs["api_version"] = api_version
+
+        return AzureChatOpenAI(**llm_kwargs)
+
+    def validate_model(self) -> bool:
+        """Validate Azure deployment name (always valid, Azure validates at runtime)."""
+        return bool(self.deployment_name)

tradingagents/llm_clients/factory.py

@@ -4,6 +4,7 @@ from .base_client import BaseLLMClient
 from .openai_client import OpenAIClient
 from .anthropic_client import AnthropicClient
 from .google_client import GoogleClient
+from .azure_client import AzureClient
 
 
 def create_llm_client(
@@ -15,8 +16,8 @@ def create_llm_client(
     """Create an LLM client for the specified provider.
 
     Args:
-        provider: LLM provider (openai, anthropic, google, xai, ollama, openrouter)
+        provider: LLM provider (openai, anthropic, google, azure, xai, ollama, openrouter)
-        model: Model name/identifier
+        model: Model name/identifier (for Azure, use deployment name)
         base_url: Optional base URL for API endpoint
         **kwargs: Additional provider-specific arguments
 
@@ -40,4 +41,7 @@ def create_llm_client(
     if provider_lower == "google":
         return GoogleClient(model, base_url, **kwargs)
 
+    if provider_lower == "azure":
+        return AzureClient(model, base_url, **kwargs)
+
     raise ValueError(f"Unsupported LLM provider: {provider}")

tradingagents/llm_clients/openai_client.py

@@ -54,7 +54,13 @@ class OpenAIClient(BaseLLMClient):
             if api_key:
                 llm_kwargs["api_key"] = api_key
         elif self.provider == "ollama":
-            llm_kwargs["base_url"] = "http://localhost:11434/v1"
+            # Support custom Ollama URL via base_url or OLLAMA_HOST env var
+            ollama_url = self.base_url or os.environ.get("OLLAMA_HOST", "http://localhost:11434")
+            # Ensure /v1 suffix for OpenAI-compatible API (handle trailing slash edge case)
+            ollama_url = ollama_url.rstrip("/")
+            if not ollama_url.endswith("/v1"):
+                ollama_url += "/v1"
+            llm_kwargs["base_url"] = ollama_url
             llm_kwargs["api_key"] = "ollama"  # Ollama doesn't require auth
         elif self.base_url:
             llm_kwargs["base_url"] = self.base_url