Merge c1ec37d830 into f362a160c3

.env.example

@@ -4,3 +4,7 @@ GOOGLE_API_KEY=
 ANTHROPIC_API_KEY=
 XAI_API_KEY=
 OPENROUTER_API_KEY=
+
+# vllm Configuration (optional)
+VLLM_API_BASE=http://localhost:8000/v1
+VLLM_API_KEY=

cli/main.py

@@ -556,6 +556,8 @@ def get_user_selections():
     # Step 7: Provider-specific thinking configuration
     thinking_level = None
     reasoning_effort = None
+    vllm_api_base = None
+    vllm_api_key = None
 
     provider_lower = selected_llm_provider.lower()
     if provider_lower == "google":
@@ -574,6 +576,14 @@ def get_user_selections():
             )
         )
         reasoning_effort = ask_openai_reasoning_effort()
+    elif provider_lower == "vllm":
+        console.print(
+            create_question_box(
+                "Step 7 : vLLM Configuration",
+                "Configure vLLM API configuration"
+            )
+        )
+        vllm_api_base, vllm_api_key = ask_vllm_config()
 
     return {
         "ticker": selected_ticker,
@@ -586,6 +596,8 @@ def get_user_selections():
         "deep_thinker": selected_deep_thinker,
         "google_thinking_level": thinking_level,
         "openai_reasoning_effort": reasoning_effort,
+        "vllm_api_base": vllm_api_base,
+        "vllm_api_key": vllm_api_key,
     }
 
 
@@ -911,7 +923,11 @@ def run_analysis():
     # Provider-specific thinking configuration
     config["google_thinking_level"] = selections.get("google_thinking_level")
     config["openai_reasoning_effort"] = selections.get("openai_reasoning_effort")
-
+    if selections["llm_provider"] == "vllm":
+        if selections.get("vllm_api_base"):
+            config["backend_url"] = selections["vllm_api_base"]
+        config["vllm_api_base"] = selections.get("vllm_api_base")
+        config["vllm_api_key"] = selections.get("vllm_api_key")
     # Create stats callback handler for tracking LLM/tool calls
     stats_handler = StatsCallbackHandler()
 

cli/utils.py

@@ -164,6 +164,7 @@ def select_shallow_thinking_agent(provider) -> str:
             ("GPT-OSS:latest (20B, local)", "gpt-oss:latest"),
             ("GLM-4.7-Flash:latest (30B, local)", "glm-4.7-flash:latest"),
         ],
+        "vllm": [("Qwen/Qwen3.5-2B", "Qwen/Qwen3.5-2B")]
     }
 
     choice = questionary.select(
@@ -231,6 +232,7 @@ def select_deep_thinking_agent(provider) -> str:
             ("GPT-OSS:latest (20B, local)", "gpt-oss:latest"),
             ("Qwen3:latest (8B, local)", "qwen3:latest"),
         ],
+        "vllm": [("Qwen/Qwen3.5-2B", "Qwen/Qwen3.5-2B")]
     }
 
     choice = questionary.select(
@@ -265,6 +267,7 @@ def select_llm_provider() -> tuple[str, str]:
         ("xAI", "https://api.x.ai/v1"),
         ("Openrouter", "https://openrouter.ai/api/v1"),
         ("Ollama", "http://localhost:11434/v1"),
+        ("vLLM", "http://localhost:8000/v1")
     ]
     
     choice = questionary.select(
@@ -329,3 +332,21 @@ def ask_gemini_thinking_config() -> str | None:
             ("pointer", "fg:green noinherit"),
         ]),
     ).ask()
+
+
+def ask_vllm_config() -> tuple[str | None, str | None]:
+    """Ask for VLLM configuration. """
+    import os
+    default_base = os.environ.get("VLLM_API_BASE", "https://localhost:8000/v1")
+    api_base = questionary.text("Enter VLLM API URL:", default=default_base, style=questionary.Style(
+        [
+            ("text", "fg:green"),
+            ("highlighted", "noinherit"),
+        ])).ask()
+    default_api_key = os.environ.get("VLLM_API_KEY", "")
+    api_key = questionary.text("Enter VLLM API Key:", default=default_api_key, style=questionary.Style(
+        [
+            ("text", "fg:green"),
+            ("highlighted", "noinherit"),
+        ])).ask()
+    return api_base.strip() if api_base else None, api_key.strip() if api_key else None

tradingagents/default_config.py

@@ -15,6 +15,7 @@ DEFAULT_CONFIG = {
     # Provider-specific thinking configuration
     "google_thinking_level": None,      # "high", "minimal", etc.
     "openai_reasoning_effort": None,    # "medium", "high", "low"
+    "vllm_api_base": None,              # vllm API base URL (defaults to http://localhost:8000/v1)
     # Debate and discussion settings
     "max_debate_rounds": 1,
     "max_risk_discuss_rounds": 1,

tradingagents/graph/trading_graph.py

@@ -78,16 +78,21 @@ class TradingAgentsGraph:
         if self.callbacks:
             llm_kwargs["callbacks"] = self.callbacks
 
+        provider = self.config["llm_provider"].lower()
+        if provider == "vllm":
+            base_url = self.config.get("vllm_api_base") or self.config["backend_url"]
+        else:
+            base_url = self.config["backend_url"]
         deep_client = create_llm_client(
             provider=self.config["llm_provider"],
             model=self.config["deep_think_llm"],
-            base_url=self.config.get("backend_url"),
+            base_url=base_url,
             **llm_kwargs,
         )
         quick_client = create_llm_client(
             provider=self.config["llm_provider"],
             model=self.config["quick_think_llm"],
-            base_url=self.config.get("backend_url"),
+            base_url=base_url,
             **llm_kwargs,
         )
 
@@ -148,6 +153,13 @@ class TradingAgentsGraph:
             if reasoning_effort:
                 kwargs["reasoning_effort"] = reasoning_effort
 
+        elif provider == "vllm":
+            # vllm specific settings
+            api_key = self.config.get("vllm_api_key")
+            if api_key:
+                kwargs["api_key"] = api_key
+            # Add any vllm-specific parameters here if needed
+
         return kwargs
 
     def _create_tool_nodes(self) -> Dict[str, ToolNode]:

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 .vllm_client import VLLMClient
 
 
 def create_llm_client(
@@ -15,7 +16,7 @@ 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, xai, ollama, openrouter, vllm)
         model: Model name/identifier
         base_url: Optional base URL for API endpoint
         **kwargs: Additional provider-specific arguments
@@ -46,4 +47,7 @@ def create_llm_client(
     if provider_lower == "google":
         return GoogleClient(model, base_url, **kwargs)
 
+    if provider_lower == "vllm":
+        return VLLMClient(model, base_url, **kwargs)
+
     raise ValueError(f"Unsupported LLM provider: {provider}")

tradingagents/llm_clients/validators.py

@@ -54,11 +54,11 @@ VALID_MODELS = {
 def validate_model(provider: str, model: str) -> bool:
     """Check if model name is valid for the given provider.
 
-    For ollama, openrouter - any model is accepted.
+    For ollama, openrouter, vllm - any model is accepted.
     """
     provider_lower = provider.lower()
 
-    if provider_lower in ("ollama", "openrouter"):
+    if provider_lower in ("ollama", "openrouter", "vllm"):
         return True
 
     if provider_lower not in VALID_MODELS:

tradingagents/llm_clients/vllm_client.py

@@ -0,0 +1,32 @@
+import os
+from typing import Any, Optional
+
+from langchain_openai import ChatOpenAI
+
+from .base_client import BaseLLMClient
+
+
+class VLLMClient(BaseLLMClient):
+    """Client for vllm models. Uses OpenAI-compatible API."""
+
+    def __init__(self, model: str, base_url: Optional[str] = None, **kwargs):
+        super().__init__(model, base_url, **kwargs)
+
+    def get_llm(self) -> Any:
+        """Return configured ChatOpenAI instance for vllm."""
+        llm_kwargs = {
+            "model": self.model,
+            "base_url": self.base_url or os.environ.get("VLLM_API_BASE", "http://localhost:8000/v1"),
+            "api_key": self.kwargs.get("api_key") or os.environ.get("VLLM_API_KEY") or "vllm",
+        }
+
+        # Add supported parameters
+        for key in ("temperature", "top_p", "max_tokens", "timeout", "max_retries", "callbacks"):
+            if key in self.kwargs:
+                llm_kwargs[key] = self.kwargs[key]
+
+        return ChatOpenAI(**llm_kwargs)
+
+    def validate_model(self) -> bool:
+        """Validate model name is provided."""
+        return bool(self.model and self.model.strip())