Merge 40bf4aee99 into fa4d01c23a

cli/main.py

@@ -569,6 +569,7 @@ def get_user_selections():
     thinking_level = None
     reasoning_effort = None
     anthropic_effort = None
+    bedrock_region = None
 
     provider_lower = selected_llm_provider.lower()
     if provider_lower == "google":
@@ -595,6 +596,14 @@ def get_user_selections():
             )
         )
         anthropic_effort = ask_anthropic_effort()
+    elif provider_lower == "bedrock":
+        console.print(
+            create_question_box(
+                "Step 8: AWS Region",
+                "Select the AWS region for Bedrock inference"
+            )
+        )
+        bedrock_region = ask_bedrock_region()
 
     return {
         "ticker": selected_ticker,
@@ -608,6 +617,7 @@ def get_user_selections():
         "google_thinking_level": thinking_level,
         "openai_reasoning_effort": reasoning_effort,
         "anthropic_effort": anthropic_effort,
+        "bedrock_region": bedrock_region,
         "output_language": output_language,
     }
 
@@ -942,6 +952,7 @@ def run_analysis():
     config["google_thinking_level"] = selections.get("google_thinking_level")
     config["openai_reasoning_effort"] = selections.get("openai_reasoning_effort")
     config["anthropic_effort"] = selections.get("anthropic_effort")
+    config["bedrock_region"] = selections.get("bedrock_region")
     config["output_language"] = selections.get("output_language", "English")
 
     # Create stats callback handler for tracking LLM/tool calls

cli/utils.py

@@ -240,6 +240,7 @@ def select_llm_provider() -> tuple[str, str | None]:
         ("Qwen", "qwen", "https://dashscope.aliyuncs.com/compatible-mode/v1"),
         ("GLM", "glm", "https://open.bigmodel.cn/api/paas/v4/"),
         ("OpenRouter", "openrouter", "https://openrouter.ai/api/v1"),
+        ("Amazon Bedrock", "bedrock", None),
         ("Azure OpenAI", "azure", None),
         ("Ollama", "ollama", "http://localhost:11434/v1"),
     ]
@@ -326,6 +327,25 @@ def ask_gemini_thinking_config() -> str | None:
     ).ask()
 
 
+def ask_bedrock_region() -> str:
+    """Ask for AWS Bedrock region."""
+    return questionary.select(
+        "Select AWS Region:",
+        choices=[
+            questionary.Choice("US East 1 (N. Virginia) - default", "us-east-1"),
+            questionary.Choice("US West 2 (Oregon)", "us-west-2"),
+            questionary.Choice("EU West 1 (Ireland)", "eu-west-1"),
+            questionary.Choice("AP Northeast 1 (Tokyo)", "ap-northeast-1"),
+            questionary.Choice("AP Southeast 1 (Singapore)", "ap-southeast-1"),
+        ],
+        style=questionary.Style([
+            ("selected", "fg:cyan noinherit"),
+            ("highlighted", "fg:cyan noinherit"),
+            ("pointer", "fg:cyan noinherit"),
+        ]),
+    ).ask()
+
+
 def ask_output_language() -> str:
     """Ask for report output language."""
     choice = questionary.select(

tradingagents/graph/trading_graph.py

@@ -151,6 +151,11 @@ class TradingAgentsGraph:
             if effort:
                 kwargs["effort"] = effort
 
+        elif provider == "bedrock":
+            region = self.config.get("bedrock_region")
+            if region:
+                kwargs["region_name"] = region
+
         return kwargs
 
     def _create_tool_nodes(self) -> Dict[str, ToolNode]:

tradingagents/llm_clients/bedrock_client.py

@@ -0,0 +1,54 @@
+from typing import Any, Optional
+
+from botocore.config import Config as BotoConfig
+from langchain_aws import ChatBedrockConverse
+
+from .base_client import BaseLLMClient, normalize_content
+
+_BEDROCK_MODELS = [
+    "us.anthropic.claude-sonnet-4-6",
+    "us.anthropic.claude-haiku-4-5-20251001-v1:0",
+    "us.anthropic.claude-opus-4-6-v1",
+    "us.anthropic.claude-sonnet-4-5-20250929-v1:0",
+]
+
+_PASSTHROUGH_KWARGS = (
+    "region_name",
+    "credentials_profile_name",
+    "max_tokens",
+    "temperature",
+    "callbacks",
+)
+
+
+class NormalizedChatBedrockConverse(ChatBedrockConverse):
+    def invoke(self, input, config=None, **kwargs):
+        return normalize_content(super().invoke(input, config, **kwargs))
+
+    async def ainvoke(self, input, config=None, **kwargs):
+        return normalize_content(await super().ainvoke(input, config, **kwargs))
+
+
+class BedrockClient(BaseLLMClient):
+    """Client for Amazon Bedrock models via ChatBedrockConverse."""
+
+    def __init__(self, model: str, base_url: Optional[str] = None, **kwargs):
+        super().__init__(model, base_url, **kwargs)
+
+    def get_llm(self) -> Any:
+        self.warn_if_unknown_model()
+        llm_kwargs = {
+            "model_id": self.model,
+            "config": BotoConfig(read_timeout=300, retries={"max_attempts": 3}),
+        }
+        if self.base_url and "openai.com" not in self.base_url:
+            llm_kwargs["endpoint_url"] = self.base_url
+        for key in _PASSTHROUGH_KWARGS:
+            if key in self.kwargs:
+                llm_kwargs[key] = self.kwargs[key]
+        if "region_name" not in llm_kwargs:
+            llm_kwargs["region_name"] = "us-east-1"
+        return NormalizedChatBedrockConverse(**llm_kwargs)
+
+    def validate_model(self) -> bool:
+        return self.model in _BEDROCK_MODELS

tradingagents/llm_clients/factory.py

@@ -5,6 +5,7 @@ from .openai_client import OpenAIClient
 from .anthropic_client import AnthropicClient
 from .google_client import GoogleClient
 from .azure_client import AzureOpenAIClient
+from .bedrock_client import BedrockClient
 
 # Providers that use the OpenAI-compatible chat completions API
 _OPENAI_COMPATIBLE = (
@@ -46,4 +47,7 @@ def create_llm_client(
     if provider_lower == "azure":
         return AzureOpenAIClient(model, base_url, **kwargs)
 
+    if provider_lower == "bedrock":
+        return BedrockClient(model, base_url, **kwargs)
+
     raise ValueError(f"Unsupported LLM provider: {provider}")

tradingagents/llm_clients/model_catalog.py

@@ -100,6 +100,16 @@ MODEL_OPTIONS: ProviderModeOptions = {
         ],
     },
     # OpenRouter: fetched dynamically. Azure: any deployed model name.
+    "bedrock": {
+        "quick": [
+            ("Claude Haiku 4.5 via Bedrock - Fast", "us.anthropic.claude-haiku-4-5-20251001-v1:0"),
+            ("Claude Sonnet 4.6 via Bedrock - Balanced", "us.anthropic.claude-sonnet-4-6"),
+        ],
+        "deep": [
+            ("Claude Sonnet 4.6 via Bedrock - Balanced", "us.anthropic.claude-sonnet-4-6"),
+            ("Claude Opus 4.6 via Bedrock - Most capable", "us.anthropic.claude-opus-4-6-v1"),
+        ],
+    },
     "ollama": {
         "quick": [
             ("Qwen3:latest (8B, local)", "qwen3:latest"),