Merge 8a8d1b5e5e into 59d6b2152d

.env.example

@@ -4,3 +4,7 @@ GOOGLE_API_KEY=
 ANTHROPIC_API_KEY=
 XAI_API_KEY=
 OPENROUTER_API_KEY=
+ZHIPU_API_KEY=
+
+# Yahoo Finance proxy (required in regions where Yahoo Finance is blocked/throttled)
+# YF_PROXY=http://127.0.0.1:7890

.gitignore

@@ -217,3 +217,8 @@ __marimo__/
 
 # Cache
 **/data_cache/
+
+# Reports
+reports/
+
+.claude/

CLAUDE.md

@@ -0,0 +1,87 @@
+# CLAUDE.md
+
+This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.
+
+## Project Overview
+
+TradingAgents is a multi-agent LLM trading framework (by TauricResearch) that simulates a real trading firm using LangGraph. Agents are organized into teams: Analysts (4 types), Researchers (bull/bear debate), Trader, Risk Management (3-way debate), and Portfolio Manager.
+
+## Build & Install
+
+```bash
+# Install (Python >=3.10, 3.13 recommended)
+pip install .
+# or with uv:
+uv pip install .
+```
+
+Environment variables go in `.env` (see `.env.example` for required API keys).
+
+## Running
+
+```bash
+# CLI (installed entry point)
+tradingagents
+
+# Programmatic usage (see main.py for example)
+from tradingagents.graph.trading_graph import TradingAgentsGraph
+ta = TradingAgentsGraph(debug=True, config=config)
+_, decision = ta.propagate("NVDA", "2024-05-10")
+```
+
+## Testing
+
+```bash
+# Run all tests (unittest-based, no pytest)
+python -m unittest discover -s tests
+
+# Run a single test module
+python -m unittest tests.test_model_validation
+python -m unittest tests.test_ticker_symbol_handling
+python -m unittest tests.test_google_api_key
+```
+
+No linter or formatter is formally configured (Ruff may be used informally).
+
+## Architecture
+
+### LangGraph State Machine
+
+The core is a **StateGraph** compiled in `tradingagents/graph/setup.py`:
+
+```
+START -> Market Analyst -> Social Media Analyst -> News Analyst -> Fundamentals Analyst
+      -> Bull/Bear Researcher Debate (multi-round)
+      -> Research Manager (deep_think_llm)
+      -> Trader
+      -> Risk Debate: Aggressive/Conservative/Neutral (multi-round)
+      -> Portfolio Manager (deep_think_llm) -> END
+```
+
+State flows through `AgentState` (extends LangGraph `MessagesState`) defined in `tradingagents/agents/utils/agent_states.py`. Nested `InvestDebateState` and `RiskDebateState` track debate rounds.
+
+### Two-LLM Tier System
+
+- **`quick_think_llm`**: Analysts, researchers, risk debators, trader
+- **`deep_think_llm`**: Research Manager and Portfolio Manager (final decision-makers)
+
+### Key Module Relationships
+
+- **`tradingagents/graph/trading_graph.py`** — `TradingAgentsGraph` is the main orchestrator. Creates LLM clients, initializes agent nodes, compiles the graph, and exposes `propagate(ticker, date)`.
+- **`tradingagents/graph/setup.py`** — `GraphSetup` wires agent nodes into the StateGraph with conditional edges from `conditional_logic.py`.
+- **`tradingagents/agents/`** — Each agent type has a `create_*()` factory function returning a callable graph node. All re-exported from `__init__.py`.
+- **`tradingagents/dataflows/interface.py`** — Vendor routing (strategy pattern) dispatches data calls to `yfinance` (default) or `alpha_vantage`, with automatic fallback on rate limits.
+- **`tradingagents/llm_clients/factory.py`** — `create_llm_client()` dispatches to provider-specific clients (`OpenAIClient` handles openai/ollama/openrouter/xai, plus `AnthropicClient`, `GoogleClient`). All extend `BaseLLMClient` ABC.
+- **`tradingagents/agents/utils/memory.py`** — `FinancialSituationMemory` uses BM25 retrieval for learning from past decisions via `reflect_and_remember()`.
+
+### Configuration
+
+`tradingagents/default_config.py` holds `DEFAULT_CONFIG` with: LLM provider/model settings, debate round limits, data vendor routing, results directory (overridable via `TRADINGAGENTS_RESULTS_DIR` env var), and provider-specific thinking configs.
+
+### CLI
+
+`cli/main.py` is a Typer app (~50K) providing an interactive Rich UI. Entry point registered as `tradingagents` console script.
+
+### Docker
+
+Multi-stage Dockerfile (python:3.12-slim). `docker-compose.yml` has optional Ollama profile (`docker compose --profile ollama up`).

cli/utils.py

@@ -240,6 +240,7 @@ def select_llm_provider() -> tuple[str, str | None]:
         ("Google", None),  # google-genai SDK manages its own endpoint
         ("Anthropic", "https://api.anthropic.com/"),
         ("xAI", "https://api.x.ai/v1"),
+        ("Zhipu", "https://open.bigmodel.cn/api/coding/paas/v4"),
         ("Openrouter", "https://openrouter.ai/api/v1"),
         ("Ollama", "http://localhost:11434/v1"),
     ]

tradingagents/dataflows/interface.py

@@ -23,6 +23,7 @@ from .alpha_vantage import (
     get_global_news as get_alpha_vantage_global_news,
 )
 from .alpha_vantage_common import AlphaVantageRateLimitError
+from yfinance.exceptions import YFRateLimitError
 
 # Configuration and routing logic
 from .config import get_config
@@ -156,7 +157,7 @@ def route_to_vendor(method: str, *args, **kwargs):
 
         try:
             return impl_func(*args, **kwargs)
-        except AlphaVantageRateLimitError:
-            continue  # Only rate limits trigger fallback
+        except (AlphaVantageRateLimitError, YFRateLimitError):
+            continue  # Rate limits trigger fallback to next vendor
 
     raise RuntimeError(f"No available vendor for '{method}'")

tradingagents/dataflows/stockstats_utils.py

@@ -11,8 +11,13 @@ from .config import get_config
 
 logger = logging.getLogger(__name__)
 
+# Apply proxy from environment for yfinance requests
+_yf_proxy = os.environ.get("YF_PROXY")
+if _yf_proxy:
+    yf.set_config(proxy=_yf_proxy)
 
-def yf_retry(func, max_retries=3, base_delay=2.0):
+
+def yf_retry(func, max_retries=5, base_delay=5.0):
     """Execute a yfinance call with exponential backoff on rate limits.
 
     yfinance raises YFRateLimitError on HTTP 429 responses but does not

tradingagents/llm_clients/factory.py

@@ -15,7 +15,7 @@ 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, zhipu)
         model: Model name/identifier
         base_url: Optional base URL for API endpoint
         **kwargs: Additional provider-specific arguments
@@ -34,7 +34,7 @@ def create_llm_client(
     """
     provider_lower = provider.lower()
 
-    if provider_lower in ("openai", "ollama", "openrouter"):
+    if provider_lower in ("openai", "ollama", "openrouter", "zhipu"):
         return OpenAIClient(model, base_url, provider=provider_lower, **kwargs)
 
     if provider_lower == "xai":

tradingagents/llm_clients/model_catalog.py

@@ -77,6 +77,18 @@ MODEL_OPTIONS: ProviderModeOptions = {
             ("Qwen3:latest (8B, local)", "qwen3:latest"),
         ],
     },
+    "zhipu": {
+        "quick": [
+            ("GLM-4.5-Air - Fast, cost-effective", "glm-4.5-air"),
+            ("GLM-4.7 - Strong coding, 200K context", "glm-4.7"),
+            ("GLM-5.1 - Latest flagship, reasoning", "glm-5.1"),
+        ],
+        "deep": [
+            ("GLM-5.1 - Latest flagship, reasoning", "glm-5.1"),
+            ("GLM-4.7 - Strong coding, 200K context", "glm-4.7"),
+            ("GLM-4.5-Air - Fast, cost-effective", "glm-4.5-air"),
+        ],
+    },
 }
 
 

tradingagents/llm_clients/openai_client.py

@@ -29,11 +29,12 @@ _PROVIDER_CONFIG = {
     "xai": ("https://api.x.ai/v1", "XAI_API_KEY"),
     "openrouter": ("https://openrouter.ai/api/v1", "OPENROUTER_API_KEY"),
     "ollama": ("http://localhost:11434/v1", None),
+    "zhipu": ("https://open.bigmodel.cn/api/coding/paas/v4", "ZHIPU_API_KEY"),
 }
 
 
 class OpenAIClient(BaseLLMClient):
-    """Client for OpenAI, Ollama, OpenRouter, and xAI providers.
+    """Client for OpenAI, Ollama, OpenRouter, xAI, and Zhipu providers.
 
     For native OpenAI models, uses the Responses API (/v1/responses) which
     supports reasoning_effort with function tools across all model families