Merge pull request #379 from yang1002378395-cmyk/fix-ssl-http-client-support

fix: add http_client support for SSL certificate customization

README.md

@@ -28,6 +28,7 @@
 # TradingAgents: Multi-Agents LLM Financial Trading Framework
 
 ## News
+- [2026-03] **TradingAgents v0.2.1** released with GPT-5.4, Gemini 3.1, Claude 4.6 model coverage and improved system stability.
 - [2026-02] **TradingAgents v0.2.0** released with multi-provider LLM support (GPT-5.x, Gemini 3.x, Claude 4.x, Grok 4.x) and improved system architecture.
 - [2026-01] **Trading-R1** [Technical Report](https://arxiv.org/abs/2509.11420) released, with [Terminal](https://github.com/TauricResearch/Trading-R1) expected to land soon.
 

cli/utils.py

@@ -130,30 +130,30 @@ def select_shallow_thinking_agent(provider) -> str:
     """Select shallow thinking llm engine using an interactive selection."""
 
     # Define shallow thinking llm engine options with their corresponding model names
+    # Ordering: medium → light → heavy (balanced first for quick tasks)
+    # Within same tier, newer models first
     SHALLOW_AGENT_OPTIONS = {
         "openai": [
-            ("GPT-5 Mini - Cost-optimized reasoning", "gpt-5-mini"),
-            ("GPT-5 Nano - Ultra-fast, high-throughput", "gpt-5-nano"),
-            ("GPT-5.2 - Latest flagship", "gpt-5.2"),
-            ("GPT-5.1 - Flexible reasoning", "gpt-5.1"),
-            ("GPT-4.1 - Smartest non-reasoning, 1M context", "gpt-4.1"),
+            ("GPT-5 Mini - Balanced speed, cost, and capability", "gpt-5-mini"),
+            ("GPT-5 Nano - High-throughput, simple tasks", "gpt-5-nano"),
+            ("GPT-5.4 - Latest frontier, 1M context", "gpt-5.4"),
+            ("GPT-4.1 - Smartest non-reasoning model", "gpt-4.1"),
         ],
         "anthropic": [
-            ("Claude Haiku 4.5 - Fast + extended thinking", "claude-haiku-4-5"),
-            ("Claude Sonnet 4.5 - Best for agents/coding", "claude-sonnet-4-5"),
-            ("Claude Sonnet 4 - High-performance", "claude-sonnet-4-20250514"),
+            ("Claude Sonnet 4.6 - Best speed and intelligence balance", "claude-sonnet-4-6"),
+            ("Claude Haiku 4.5 - Fast, near-instant responses", "claude-haiku-4-5"),
+            ("Claude Sonnet 4.5 - Agents and coding", "claude-sonnet-4-5"),
         ],
         "google": [
             ("Gemini 3 Flash - Next-gen fast", "gemini-3-flash-preview"),
-            ("Gemini 2.5 Flash - Balanced, recommended", "gemini-2.5-flash"),
-            ("Gemini 3 Pro - Reasoning-first", "gemini-3-pro-preview"),
+            ("Gemini 2.5 Flash - Balanced, stable", "gemini-2.5-flash"),
+            ("Gemini 3.1 Flash Lite - Most cost-efficient", "gemini-3.1-flash-lite-preview"),
             ("Gemini 2.5 Flash Lite - Fast, low-cost", "gemini-2.5-flash-lite"),
         ],
         "xai": [
             ("Grok 4.1 Fast (Non-Reasoning) - Speed optimized, 2M ctx", "grok-4-1-fast-non-reasoning"),
             ("Grok 4 Fast (Non-Reasoning) - Speed optimized", "grok-4-fast-non-reasoning"),
             ("Grok 4.1 Fast (Reasoning) - High-performance, 2M ctx", "grok-4-1-fast-reasoning"),
-            ("Grok 4 Fast (Reasoning) - High-performance", "grok-4-fast-reasoning"),
         ],
         "openrouter": [
             ("NVIDIA Nemotron 3 Nano 30B (free)", "nvidia/nemotron-3-nano-30b-a3b:free"),
@@ -195,33 +195,32 @@ def select_deep_thinking_agent(provider) -> str:
     """Select deep thinking llm engine using an interactive selection."""
 
     # Define deep thinking llm engine options with their corresponding model names
+    # Ordering: heavy → medium → light (most capable first for deep tasks)
+    # Within same tier, newer models first
     DEEP_AGENT_OPTIONS = {
         "openai": [
-            ("GPT-5.2 - Latest flagship", "gpt-5.2"),
-            ("GPT-5.1 - Flexible reasoning", "gpt-5.1"),
-            ("GPT-5 - Advanced reasoning", "gpt-5"),
-            ("GPT-4.1 - Smartest non-reasoning, 1M context", "gpt-4.1"),
-            ("GPT-5 Mini - Cost-optimized reasoning", "gpt-5-mini"),
-            ("GPT-5 Nano - Ultra-fast, high-throughput", "gpt-5-nano"),
+            ("GPT-5.4 - Latest frontier, 1M context", "gpt-5.4"),
+            ("GPT-5.2 - Strong reasoning, cost-effective", "gpt-5.2"),
+            ("GPT-5 Mini - Balanced speed, cost, and capability", "gpt-5-mini"),
+            ("GPT-5.4 Pro - Most capable, expensive ($30/$180 per 1M tokens)", "gpt-5.4-pro"),
         ],
         "anthropic": [
-            ("Claude Sonnet 4.5 - Best for agents/coding", "claude-sonnet-4-5"),
+            ("Claude Opus 4.6 - Most intelligent, agents and coding", "claude-opus-4-6"),
             ("Claude Opus 4.5 - Premium, max intelligence", "claude-opus-4-5"),
-            ("Claude Opus 4.1 - Most capable model", "claude-opus-4-1-20250805"),
-            ("Claude Haiku 4.5 - Fast + extended thinking", "claude-haiku-4-5"),
-            ("Claude Sonnet 4 - High-performance", "claude-sonnet-4-20250514"),
+            ("Claude Sonnet 4.6 - Best speed and intelligence balance", "claude-sonnet-4-6"),
+            ("Claude Sonnet 4.5 - Agents and coding", "claude-sonnet-4-5"),
         ],
         "google": [
-            ("Gemini 3 Pro - Reasoning-first", "gemini-3-pro-preview"),
+            ("Gemini 3.1 Pro - Reasoning-first, complex workflows", "gemini-3.1-pro-preview"),
             ("Gemini 3 Flash - Next-gen fast", "gemini-3-flash-preview"),
-            ("Gemini 2.5 Flash - Balanced, recommended", "gemini-2.5-flash"),
+            ("Gemini 2.5 Pro - Stable pro model", "gemini-2.5-pro"),
+            ("Gemini 2.5 Flash - Balanced, stable", "gemini-2.5-flash"),
         ],
         "xai": [
+            ("Grok 4 - Flagship model", "grok-4-0709"),
             ("Grok 4.1 Fast (Reasoning) - High-performance, 2M ctx", "grok-4-1-fast-reasoning"),
             ("Grok 4 Fast (Reasoning) - High-performance", "grok-4-fast-reasoning"),
-            ("Grok 4 - Flagship model", "grok-4-0709"),
             ("Grok 4.1 Fast (Non-Reasoning) - Speed optimized, 2M ctx", "grok-4-1-fast-non-reasoning"),
-            ("Grok 4 Fast (Non-Reasoning) - Speed optimized", "grok-4-fast-non-reasoning"),
         ],
         "openrouter": [
             ("Z.AI GLM 4.5 Air (free)", "z-ai/glm-4.5-air:free"),

pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "setuptools.build_meta"
 
 [project]
 name = "tradingagents"
-version = "0.2.0"
+version = "0.2.1"
 description = "TradingAgents: Multi-Agents LLM Financial Trading Framework"
 readme = "README.md"
 requires-python = ">=3.10"

tradingagents/dataflows/stockstats_utils.py

@@ -6,6 +6,19 @@ import os
 from .config import get_config
 
 
+def _clean_dataframe(data: pd.DataFrame) -> pd.DataFrame:
+    """Normalize a stock DataFrame for stockstats: parse dates, drop invalid rows, fill price gaps."""
+    data["Date"] = pd.to_datetime(data["Date"], errors="coerce")
+    data = data.dropna(subset=["Date"])
+
+    price_cols = [c for c in ["Open", "High", "Low", "Close", "Volume"] if c in data.columns]
+    data[price_cols] = data[price_cols].apply(pd.to_numeric, errors="coerce")
+    data = data.dropna(subset=["Close"])
+    data[price_cols] = data[price_cols].ffill().bfill()
+
+    return data
+
+
 class StockstatsUtils:
     @staticmethod
     def get_stock_stats(
@@ -36,8 +49,7 @@ class StockstatsUtils:
         )
 
         if os.path.exists(data_file):
-            data = pd.read_csv(data_file)
-            data["Date"] = pd.to_datetime(data["Date"])
+            data = pd.read_csv(data_file, on_bad_lines="skip")
         else:
             data = yf.download(
                 symbol,
@@ -50,6 +62,7 @@ class StockstatsUtils:
             data = data.reset_index()
             data.to_csv(data_file, index=False)
 
+        data = _clean_dataframe(data)
         df = wrap(data)
         df["Date"] = df["Date"].dt.strftime("%Y-%m-%d")
         curr_date_str = curr_date_dt.strftime("%Y-%m-%d")

tradingagents/dataflows/y_finance.py

@@ -3,7 +3,7 @@ from datetime import datetime
 from dateutil.relativedelta import relativedelta
 import yfinance as yf
 import os
-from .stockstats_utils import StockstatsUtils
+from .stockstats_utils import StockstatsUtils, _clean_dataframe
 
 def get_YFin_data_online(
     symbol: Annotated[str, "ticker symbol of the company"],
@@ -209,31 +209,30 @@ def _get_stock_stats_bulk(
                 os.path.join(
                     config.get("data_cache_dir", "data"),
                     f"{symbol}-YFin-data-2015-01-01-2025-03-25.csv",
-                )
+                ),
+                on_bad_lines="skip",
             )
-            df = wrap(data)
         except FileNotFoundError:
             raise Exception("Stockstats fail: Yahoo Finance data not fetched yet!")
     else:
         # Online data fetching with caching
         today_date = pd.Timestamp.today()
         curr_date_dt = pd.to_datetime(curr_date)
-        
+
         end_date = today_date
         start_date = today_date - pd.DateOffset(years=15)
         start_date_str = start_date.strftime("%Y-%m-%d")
         end_date_str = end_date.strftime("%Y-%m-%d")
-        
+
         os.makedirs(config["data_cache_dir"], exist_ok=True)
-        
+
         data_file = os.path.join(
             config["data_cache_dir"],
             f"{symbol}-YFin-data-{start_date_str}-{end_date_str}.csv",
         )
-        
+
         if os.path.exists(data_file):
-            data = pd.read_csv(data_file)
-            data["Date"] = pd.to_datetime(data["Date"])
+            data = pd.read_csv(data_file, on_bad_lines="skip")
         else:
             data = yf.download(
                 symbol,
@@ -245,9 +244,10 @@ def _get_stock_stats_bulk(
             )
             data = data.reset_index()
             data.to_csv(data_file, index=False)
-        
-        df = wrap(data)
-        df["Date"] = df["Date"].dt.strftime("%Y-%m-%d")
+
+    data = _clean_dataframe(data)
+    df = wrap(data)
+    df["Date"] = df["Date"].dt.strftime("%Y-%m-%d")
     
     # Calculate the indicator for all rows at once
     df[indicator]  # This triggers stockstats to calculate the indicator

tradingagents/llm_clients/anthropic_client.py

@@ -16,7 +16,7 @@ class AnthropicClient(BaseLLMClient):
         """Return configured ChatAnthropic instance."""
         llm_kwargs = {"model": self.model}
 
-        for key in ("timeout", "max_retries", "api_key", "max_tokens", "callbacks"):
+        for key in ("timeout", "max_retries", "api_key", "max_tokens", "callbacks", "http_client", "http_async_client"):
             if key in self.kwargs:
                 llm_kwargs[key] = self.kwargs[key]
 

tradingagents/llm_clients/factory.py

@@ -19,6 +19,12 @@ def create_llm_client(
         model: Model name/identifier
         base_url: Optional base URL for API endpoint
         **kwargs: Additional provider-specific arguments
+            - http_client: Custom httpx.Client for SSL proxy or certificate customization
+            - http_async_client: Custom httpx.AsyncClient for async operations
+            - timeout: Request timeout in seconds
+            - max_retries: Maximum retry attempts
+            - api_key: API key for the provider
+            - callbacks: LangChain callbacks
 
     Returns:
         Configured BaseLLMClient instance

tradingagents/llm_clients/google_client.py

@@ -38,7 +38,7 @@ class GoogleClient(BaseLLMClient):
         """Return configured ChatGoogleGenerativeAI instance."""
         llm_kwargs = {"model": self.model}
 
-        for key in ("timeout", "max_retries", "google_api_key", "callbacks"):
+        for key in ("timeout", "max_retries", "google_api_key", "callbacks", "http_client", "http_async_client"):
             if key in self.kwargs:
                 llm_kwargs[key] = self.kwargs[key]
 

tradingagents/llm_clients/openai_client.py

@@ -8,25 +8,23 @@ from .validators import validate_model
 
 
 class UnifiedChatOpenAI(ChatOpenAI):
-    """ChatOpenAI subclass that strips incompatible params for certain models."""
+    """ChatOpenAI subclass that strips temperature/top_p for GPT-5 family models.
+
+    GPT-5 family models use reasoning natively. temperature/top_p are only
+    accepted when reasoning.effort is 'none'; with any other effort level
+    (or for older GPT-5/GPT-5-mini/GPT-5-nano which always reason) the API
+    rejects these params. Langchain defaults temperature=0.7, so we must
+    strip it to avoid errors.
+
+    Non-GPT-5 models (GPT-4.1, xAI, Ollama, etc.) are unaffected.
+    """
 
     def __init__(self, **kwargs):
-        model = kwargs.get("model", "")
-        if self._is_reasoning_model(model):
+        if "gpt-5" in kwargs.get("model", "").lower():
             kwargs.pop("temperature", None)
             kwargs.pop("top_p", None)
         super().__init__(**kwargs)
 
-    @staticmethod
-    def _is_reasoning_model(model: str) -> bool:
-        """Check if model is a reasoning model that doesn't support temperature."""
-        model_lower = model.lower()
-        return (
-            model_lower.startswith("o1")
-            or model_lower.startswith("o3")
-            or "gpt-5" in model_lower
-        )
-
 
 class OpenAIClient(BaseLLMClient):
     """Client for OpenAI, Ollama, OpenRouter, and xAI providers."""
@@ -61,7 +59,7 @@ class OpenAIClient(BaseLLMClient):
         elif self.base_url:
             llm_kwargs["base_url"] = self.base_url
 
-        for key in ("timeout", "max_retries", "reasoning_effort", "api_key", "callbacks"):
+        for key in ("timeout", "max_retries", "reasoning_effort", "api_key", "callbacks", "http_client", "http_async_client"):
             if key in self.kwargs:
                 llm_kwargs[key] = self.kwargs[key]
 

tradingagents/llm_clients/validators.py

@@ -6,59 +6,44 @@ Let LLM providers use their own defaults for unspecified params.
 
 VALID_MODELS = {
     "openai": [
-        # GPT-5 series (2025)
+        # GPT-5 series
+        "gpt-5.4-pro",
+        "gpt-5.4",
         "gpt-5.2",
         "gpt-5.1",
         "gpt-5",
         "gpt-5-mini",
         "gpt-5-nano",
-        # GPT-4.1 series (2025)
+        # GPT-4.1 series
         "gpt-4.1",
         "gpt-4.1-mini",
         "gpt-4.1-nano",
-        # o-series reasoning models
-        "o4-mini",
-        "o3",
-        "o3-mini",
-        "o1",
-        "o1-preview",
-        # GPT-4o series (legacy but still supported)
-        "gpt-4o",
-        "gpt-4o-mini",
     ],
     "anthropic": [
-        # Claude 4.5 series (2025)
+        # Claude 4.6 series (latest)
+        "claude-opus-4-6",
+        "claude-sonnet-4-6",
+        # Claude 4.5 series
         "claude-opus-4-5",
         "claude-sonnet-4-5",
         "claude-haiku-4-5",
-        # Claude 4.x series
-        "claude-opus-4-1-20250805",
-        "claude-sonnet-4-20250514",
-        # Claude 3.7 series
-        "claude-3-7-sonnet-20250219",
-        # Claude 3.5 series (legacy)
-        "claude-3-5-haiku-20241022",
-        "claude-3-5-sonnet-20241022",
     ],
     "google": [
+        # Gemini 3.1 series (preview)
+        "gemini-3.1-pro-preview",
+        "gemini-3.1-flash-lite-preview",
         # Gemini 3 series (preview)
-        "gemini-3-pro-preview",
         "gemini-3-flash-preview",
         # Gemini 2.5 series
         "gemini-2.5-pro",
         "gemini-2.5-flash",
         "gemini-2.5-flash-lite",
-        # Gemini 2.0 series
-        "gemini-2.0-flash",
-        "gemini-2.0-flash-lite",
     ],
     "xai": [
         # Grok 4.1 series
-        "grok-4-1-fast",
         "grok-4-1-fast-reasoning",
         "grok-4-1-fast-non-reasoning",
         # Grok 4 series
-        "grok-4",
         "grok-4-0709",
         "grok-4-fast-reasoning",
         "grok-4-fast-non-reasoning",