fix: allow .env variables to override DEFAULT_CONFIG values

Merged origin/main and resolved all 8 conflicting files:
- CLAUDE.md: merged MISTAKES.md ref + Project Tracking section + env override docs
- cli/main.py: kept top-level json import, kept try/except in run_pipeline
- tool_runner.py: kept descriptive comments for MAX_TOOL_ROUNDS
- alpha_vantage_common.py: kept thread-safe rate limiter, robust error handling
- interface.py: kept broader exception catch (AlphaVantageError + ConnectionError + TimeoutError)
- default_config.py: kept _env()/_env_int() env var overrides with load_dotenv() at module level
- scanner_graph.py: kept debug mode fix (stream for debug, invoke for result)
- macro_bridge.py: kept get_running_loop() over deprecated get_event_loop()

Co-authored-by: aguzererler <6199053+aguzererler@users.noreply.github.com>

.env.example

@@ -1,6 +1,23 @@
-# LLM Providers (set the one you use)
+# LLM Provider API Keys (set the ones you use)
 OPENAI_API_KEY=
 GOOGLE_API_KEY=
 ANTHROPIC_API_KEY=
 XAI_API_KEY=
 OPENROUTER_API_KEY=
+
+# Data Provider API Keys
+ALPHA_VANTAGE_API_KEY=
+
+# ── Configuration overrides ──────────────────────────────────────────
+# Any setting in DEFAULT_CONFIG can be overridden with a
+# TRADINGAGENTS_<KEY> environment variable.  Unset or empty values
+# are ignored (the hardcoded default is kept).
+#
+# Examples:
+#   TRADINGAGENTS_LLM_PROVIDER=openrouter
+#   TRADINGAGENTS_QUICK_THINK_LLM=deepseek/deepseek-chat-v3-0324
+#   TRADINGAGENTS_DEEP_THINK_LLM=deepseek/deepseek-r1-0528
+#   TRADINGAGENTS_BACKEND_URL=https://openrouter.ai/api/v1
+#   TRADINGAGENTS_RESULTS_DIR=./my_results
+#   TRADINGAGENTS_MAX_DEBATE_ROUNDS=2
+#   TRADINGAGENTS_VENDOR_SCANNER_DATA=alpha_vantage

CLAUDE.md

@@ -102,16 +102,13 @@ OpenAI, Anthropic, Google, xAI, OpenRouter, Ollama
 - `PROGRESS.md` — Feature progress, what works, TODOs
 - `MISTAKES.md` — Past bugs and lessons learned (9 documented mistakes)
 
-## Current LLM Configuration (Hybrid)
+## LLM Configuration
 
-```
+Per-tier provider overrides in `tradingagents/default_config.py`:
-quick_think: qwen3.5:27b via Ollama (http://192.168.50.76:11434)
+- Each tier (`quick_think`, `mid_think`, `deep_think`) can have its own `_llm_provider` and `_backend_url`
-mid_think:   qwen3.5:27b via Ollama (http://192.168.50.76:11434)
+- Falls back to top-level `llm_provider` and `backend_url` when per-tier values are None
-deep_think:  deepseek/deepseek-r1-0528 via OpenRouter
+- All config values overridable via `TRADINGAGENTS_<KEY>` env vars
-```
+- Keys for LLM providers: `.env` file (e.g., `OPENROUTER_API_KEY`, `ALPHA_VANTAGE_API_KEY`)
-
-Config: `tradingagents/default_config.py` (per-tier `_llm_provider` keys)
-Keys: `.env` file (`OPENROUTER_API_KEY`, `ALPHA_VANTAGE_API_KEY`)
 
 ## Running the Scanner
 

cli/main.py

@@ -1,5 +1,6 @@
 from typing import Optional
 import datetime
+import json
 import typer
 from pathlib import Path
 from functools import wraps
@@ -1201,8 +1202,6 @@ def run_scan(date: Optional[str] = None):
         raise typer.Exit(1)
 
     # Save reports
-    import json as _json
-
     for key in ["geopolitical_report", "market_movers_report", "sector_performance_report",
                 "industry_deep_dive_report", "macro_scan_summary"]:
         content = result.get(key, "")
@@ -1217,7 +1216,7 @@ def run_scan(date: Optional[str] = None):
 
         # Try to parse and show watchlist table
         try:
-            summary_data = _json.loads(summary)
+            summary_data = json.loads(summary)
             stocks = summary_data.get("stocks_to_investigate", [])
             if stocks:
                 table = Table(title="Stocks to Investigate", box=box.ROUNDED)
@@ -1235,16 +1234,16 @@ def run_scan(date: Optional[str] = None):
                         s.get("thesis_angle", ""),
                     )
                 console.print(table)
-        except (_json.JSONDecodeError, KeyError):
+        except (json.JSONDecodeError, KeyError):
             pass  # Summary wasn't valid JSON — already printed as markdown
 
+
     console.print(f"\n[green]Results saved to {save_dir}[/green]")
 
 
 def run_pipeline():
     """Full pipeline: scan -> filter -> per-ticker deep dive."""
     import asyncio
-    import json as _json
     from tradingagents.pipeline.macro_bridge import (
         parse_macro_output,
         filter_candidates,
@@ -1293,10 +1292,14 @@ def run_pipeline():
     output_dir = Path("results/macro_pipeline")
 
     console.print(f"\n[cyan]Running TradingAgents for {len(candidates)} tickers...[/cyan]")
-    with Live(Spinner("dots", text="Analyzing..."), console=console, transient=True):
+    try:
-        results = asyncio.run(
+        with Live(Spinner("dots", text="Analyzing..."), console=console, transient=True):
-            run_all_tickers(candidates, macro_context, config, analysis_date)
+            results = asyncio.run(
-        )
+                run_all_tickers(candidates, macro_context, config, analysis_date)
+            )
+    except Exception as e:
+        console.print(f"[red]Pipeline failed: {e}[/red]")
+        raise typer.Exit(1)
 
     save_results(results, macro_context, output_dir)
 

main.py

@@ -1,11 +1,13 @@
-from tradingagents.graph.trading_graph import TradingAgentsGraph
-from tradingagents.default_config import DEFAULT_CONFIG
-
 from dotenv import load_dotenv
 
-# Load environment variables from .env file
+# Load environment variables from .env file BEFORE importing any
+# tradingagents modules so TRADINGAGENTS_* vars are visible to
+# DEFAULT_CONFIG at import time.
 load_dotenv()
 
+from tradingagents.graph.trading_graph import TradingAgentsGraph
+from tradingagents.default_config import DEFAULT_CONFIG
+
 # Create a custom config
 config = DEFAULT_CONFIG.copy()
 config["deep_think_llm"] = "gpt-5-mini"  # Use a different model

pyproject.toml

@@ -19,6 +19,7 @@ dependencies = [
     "langgraph>=0.4.8",
     "pandas>=2.3.0",
     "parsel>=1.10.0",
+    "python-dotenv>=1.0.0",
     "pytz>=2025.2",
     "questionary>=2.1.0",
     "rank-bm25>=0.2.2",

tests/test_env_override.py

@@ -0,0 +1,108 @@
+"""Tests that TRADINGAGENTS_* environment variables override DEFAULT_CONFIG."""
+
+import importlib
+import os
+from unittest.mock import patch
+
+import pytest
+
+
+class TestEnvOverridesDefaults:
+    """Verify that setting TRADINGAGENTS_<KEY> env vars changes DEFAULT_CONFIG."""
+
+    def _reload_config(self):
+        """Force-reimport default_config so the module-level dict is rebuilt."""
+        import tradingagents.default_config as mod
+
+        importlib.reload(mod)
+        return mod.DEFAULT_CONFIG
+
+    def test_llm_provider_override(self):
+        with patch.dict(os.environ, {"TRADINGAGENTS_LLM_PROVIDER": "openrouter"}):
+            cfg = self._reload_config()
+            assert cfg["llm_provider"] == "openrouter"
+
+    def test_backend_url_override(self):
+        with patch.dict(os.environ, {"TRADINGAGENTS_BACKEND_URL": "http://localhost:1234"}):
+            cfg = self._reload_config()
+            assert cfg["backend_url"] == "http://localhost:1234"
+
+    def test_deep_think_llm_override(self):
+        with patch.dict(os.environ, {"TRADINGAGENTS_DEEP_THINK_LLM": "deepseek/deepseek-r1"}):
+            cfg = self._reload_config()
+            assert cfg["deep_think_llm"] == "deepseek/deepseek-r1"
+
+    def test_quick_think_llm_override(self):
+        with patch.dict(os.environ, {"TRADINGAGENTS_QUICK_THINK_LLM": "gpt-4o-mini"}):
+            cfg = self._reload_config()
+            assert cfg["quick_think_llm"] == "gpt-4o-mini"
+
+    def test_mid_think_llm_none_by_default(self):
+        """mid_think_llm defaults to None (falls back to quick_think_llm)."""
+        with patch.dict(os.environ, {}, clear=False):
+            # Remove the env var if it happens to be set
+            os.environ.pop("TRADINGAGENTS_MID_THINK_LLM", None)
+            cfg = self._reload_config()
+            assert cfg["mid_think_llm"] is None
+
+    def test_mid_think_llm_override(self):
+        with patch.dict(os.environ, {"TRADINGAGENTS_MID_THINK_LLM": "gpt-4o"}):
+            cfg = self._reload_config()
+            assert cfg["mid_think_llm"] == "gpt-4o"
+
+    def test_empty_env_var_keeps_default(self):
+        """An empty string is treated the same as unset (keeps the default)."""
+        with patch.dict(os.environ, {"TRADINGAGENTS_LLM_PROVIDER": ""}):
+            cfg = self._reload_config()
+            assert cfg["llm_provider"] == "openai"
+
+    def test_empty_env_var_keeps_none_default(self):
+        """An empty string for a None-default field stays None."""
+        with patch.dict(os.environ, {"TRADINGAGENTS_DEEP_THINK_LLM_PROVIDER": ""}):
+            cfg = self._reload_config()
+            assert cfg["deep_think_llm_provider"] is None
+
+    def test_per_tier_provider_override(self):
+        with patch.dict(os.environ, {"TRADINGAGENTS_DEEP_THINK_LLM_PROVIDER": "anthropic"}):
+            cfg = self._reload_config()
+            assert cfg["deep_think_llm_provider"] == "anthropic"
+
+    def test_per_tier_backend_url_override(self):
+        with patch.dict(os.environ, {"TRADINGAGENTS_MID_THINK_BACKEND_URL": "http://my-ollama:11434"}):
+            cfg = self._reload_config()
+            assert cfg["mid_think_backend_url"] == "http://my-ollama:11434"
+
+    def test_max_debate_rounds_int(self):
+        with patch.dict(os.environ, {"TRADINGAGENTS_MAX_DEBATE_ROUNDS": "3"}):
+            cfg = self._reload_config()
+            assert cfg["max_debate_rounds"] == 3
+
+    def test_max_debate_rounds_bad_value(self):
+        """Non-numeric string falls back to hardcoded default."""
+        with patch.dict(os.environ, {"TRADINGAGENTS_MAX_DEBATE_ROUNDS": "abc"}):
+            cfg = self._reload_config()
+            assert cfg["max_debate_rounds"] == 1
+
+    def test_results_dir_override(self):
+        with patch.dict(os.environ, {"TRADINGAGENTS_RESULTS_DIR": "/tmp/my_results"}):
+            cfg = self._reload_config()
+            assert cfg["results_dir"] == "/tmp/my_results"
+
+    def test_vendor_scanner_data_override(self):
+        with patch.dict(os.environ, {"TRADINGAGENTS_VENDOR_SCANNER_DATA": "alpha_vantage"}):
+            cfg = self._reload_config()
+            assert cfg["data_vendors"]["scanner_data"] == "alpha_vantage"
+
+    def test_defaults_unchanged_when_no_env_set(self):
+        """Without any TRADINGAGENTS_* vars, defaults are the original hardcoded values."""
+        # Clear all TRADINGAGENTS_ vars
+        env_clean = {k: v for k, v in os.environ.items() if not k.startswith("TRADINGAGENTS_")}
+        with patch.dict(os.environ, env_clean, clear=True):
+            cfg = self._reload_config()
+            assert cfg["llm_provider"] == "openai"
+            assert cfg["deep_think_llm"] == "gpt-5.2"
+            assert cfg["mid_think_llm"] is None
+            assert cfg["quick_think_llm"] == "gpt-5-mini"
+            assert cfg["backend_url"] == "https://api.openai.com/v1"
+            assert cfg["max_debate_rounds"] == 1
+            assert cfg["data_vendors"]["scanner_data"] == "yfinance"

tradingagents/agents/utils/tool_runner.py

@@ -12,7 +12,9 @@ from typing import Any, List
 from langchain_core.messages import AIMessage, ToolMessage
 
 
-MAX_TOOL_ROUNDS = 5  # safety limit to avoid infinite loops
+# Most LLM tool-calling patterns resolve within 2-3 rounds;
+# 5 provides headroom for complex scenarios while preventing runaway loops.
+MAX_TOOL_ROUNDS = 5
 
 
 def run_tool_loop(

tradingagents/dataflows/alpha_vantage_common.py

@@ -2,6 +2,8 @@ import os
 import requests
 import pandas as pd
 import json
+import threading
+import time as _time
 from datetime import datetime
 from io import StringIO
 
@@ -73,8 +75,6 @@ class ThirdPartyParseError(AlphaVantageError):
 
 # ─── Rate-limited request helper ─────────────────────────────────────────────
 
-import threading
-import time as _time
 
 _rate_lock = threading.Lock()
 _call_timestamps: list[float] = []
@@ -83,14 +83,30 @@ _RATE_LIMIT = 75  # calls per minute (Alpha Vantage premium)
 
 def _rate_limited_request(function_name: str, params: dict, timeout: int = 30) -> dict | str:
     """Make an API request with rate limiting (75 calls/min for premium key)."""
+    sleep_time = 0.0
     with _rate_lock:
         now = _time.time()
         # Remove timestamps older than 60 seconds
         _call_timestamps[:] = [t for t in _call_timestamps if now - t < 60]
         if len(_call_timestamps) >= _RATE_LIMIT:
             sleep_time = 60 - (now - _call_timestamps[0]) + 0.1
-            _time.sleep(sleep_time)
+
+    # Sleep outside the lock to avoid blocking other threads
+    if sleep_time > 0:
+        _time.sleep(sleep_time)
+
+    # Re-check and register under lock to avoid races where multiple
+    # threads calculate similar sleep times and then all fire at once.
+    with _rate_lock:
+        now = _time.time()
+        _call_timestamps[:] = [t for t in _call_timestamps if now - t < 60]
+        if len(_call_timestamps) >= _RATE_LIMIT:
+            # Another thread filled the window while we slept — wait again
+            extra_sleep = 60 - (now - _call_timestamps[0]) + 0.1
+            _time.sleep(extra_sleep)
         _call_timestamps.append(_time.time())
+
+
     return _make_api_request(function_name, params, timeout=timeout)
 
 
@@ -131,6 +147,8 @@ def _make_api_request(function_name: str, params: dict, timeout: int = 30) -> di
         )
     except requests.exceptions.ConnectionError as exc:
         raise ThirdPartyError(f"Connection error: function={function_name}, error={exc}")
+    except requests.exceptions.RequestException as exc:
+        raise ThirdPartyError(f"Request failed: function={function_name}, error={exc}")
 
     # HTTP-level errors
     if response.status_code == 401:
@@ -146,7 +164,13 @@ def _make_api_request(function_name: str, params: dict, timeout: int = 30) -> di
             f"Server error: status={response.status_code}, function={function_name}, "
             f"body={response.text[:200]}"
         )
-    response.raise_for_status()
+    try:
+        response.raise_for_status()
+    except requests.exceptions.HTTPError as exc:
+        raise ThirdPartyError(
+            f"HTTP error: status={response.status_code}, function={function_name}, "
+            f"body={response.text[:200]}"
+        ) from exc
 
     response_text = response.text
 

tradingagents/dataflows/interface.py

@@ -201,7 +201,7 @@ def route_to_vendor(method: str, *args, **kwargs):
 
         try:
             return impl_func(*args, **kwargs)
-        except AlphaVantageError:
+        except (AlphaVantageError, ConnectionError, TimeoutError):
-            continue  # Any AV error triggers fallback to next vendor
+            continue  # Any AV error or connection/timeout triggers fallback to next vendor
 
     raise RuntimeError(f"No available vendor for '{method}'")

tradingagents/default_config.py

@@ -1,45 +1,83 @@
 import os
+from pathlib import Path
+
+from dotenv import load_dotenv
+
+# Load .env so that TRADINGAGENTS_* variables are available before
+# DEFAULT_CONFIG is evaluated.  CWD is checked first, then the project
+# root (two levels up from this file).  load_dotenv never overwrites
+# variables that are already present in the environment.
+load_dotenv()
+load_dotenv(Path(__file__).resolve().parent.parent / ".env")
+
+
+def _env(key: str, default=None):
+    """Read ``TRADINGAGENTS_<KEY>`` from the environment.
+
+    Returns *default* when the variable is unset **or** empty, so that
+    ``TRADINGAGENTS_MID_THINK_LLM=`` in a ``.env`` file is treated the
+    same as not setting it at all (preserving the ``None`` semantics for
+    "fall back to the parent setting").
+    """
+    val = os.getenv(f"TRADINGAGENTS_{key.upper()}")
+    if not val:  # None or ""
+        return default
+    return val
+
+
+def _env_int(key: str, default=None):
+    """Like :func:`_env` but coerces the value to ``int``."""
+    val = _env(key)
+    if val is None:
+        return default
+    try:
+        return int(val)
+    except (ValueError, TypeError):
+        return default
+
 
 DEFAULT_CONFIG = {
     "project_dir": os.path.abspath(os.path.join(os.path.dirname(__file__), ".")),
-    "results_dir": os.getenv("TRADINGAGENTS_RESULTS_DIR", "./results"),
+    "results_dir": _env("RESULTS_DIR", "./results"),
     "data_cache_dir": os.path.join(
         os.path.abspath(os.path.join(os.path.dirname(__file__), ".")),
         "dataflows/data_cache",
     ),
-    # LLM settings
+    # LLM settings — all overridable via TRADINGAGENTS_<KEY> env vars
-    "mid_think_llm": "qwen3.5:27b",              # falls back to quick_think_llm when None
+    "llm_provider": _env("LLM_PROVIDER", "openai"),
-    "quick_think_llm": "qwen3.5:27b",
+    "deep_think_llm": _env("DEEP_THINK_LLM", "gpt-5.2"),
+    "mid_think_llm": _env("MID_THINK_LLM"),              # falls back to quick_think_llm when None
+    "quick_think_llm": _env("QUICK_THINK_LLM", "gpt-5-mini"),
+    "backend_url": _env("BACKEND_URL", "https://api.openai.com/v1"),
     # Per-role provider overrides (fall back to llm_provider / backend_url when None)
-    "deep_think_llm_provider": "openrouter",
+    "deep_think_llm_provider": _env("DEEP_THINK_LLM_PROVIDER"),    # e.g. "google", "anthropic", "openrouter"
-    "deep_think_llm": "deepseek/deepseek-r1-0528",
+    "deep_think_backend_url": _env("DEEP_THINK_BACKEND_URL"),       # override backend URL for deep-think model
-    "deep_think_backend_url": None,     # uses OpenRouter's default URL
+    "mid_think_llm_provider": _env("MID_THINK_LLM_PROVIDER"),      # e.g. "ollama"
-    "mid_think_llm_provider": "ollama",     # falls back to ollama
+    "mid_think_backend_url": _env("MID_THINK_BACKEND_URL"),         # override backend URL for mid-think model
-    "mid_think_backend_url": "http://192.168.50.76:11434",      # falls back to backend_url (ollama host)
+    "quick_think_llm_provider": _env("QUICK_THINK_LLM_PROVIDER"),  # e.g. "openai", "ollama"
-    "quick_think_llm_provider": "ollama",   # falls back to ollama
+    "quick_think_backend_url": _env("QUICK_THINK_BACKEND_URL"),     # override backend URL for quick-think model
-    "quick_think_backend_url": "http://192.168.50.76:11434",    # falls back to backend_url (ollama host)
     # Provider-specific thinking configuration (applies to all roles unless overridden)
-    "google_thinking_level": None,      # "high", "minimal", etc.
+    "google_thinking_level": _env("GOOGLE_THINKING_LEVEL"),      # "high", "minimal", etc.
-    "openai_reasoning_effort": None,    # "medium", "high", "low"
+    "openai_reasoning_effort": _env("OPENAI_REASONING_EFFORT"),  # "medium", "high", "low"
     # Per-role provider-specific thinking configuration
-    "deep_think_google_thinking_level": None,
+    "deep_think_google_thinking_level": _env("DEEP_THINK_GOOGLE_THINKING_LEVEL"),
-    "deep_think_openai_reasoning_effort": None,
+    "deep_think_openai_reasoning_effort": _env("DEEP_THINK_OPENAI_REASONING_EFFORT"),
-    "mid_think_google_thinking_level": None,
+    "mid_think_google_thinking_level": _env("MID_THINK_GOOGLE_THINKING_LEVEL"),
-    "mid_think_openai_reasoning_effort": None,
+    "mid_think_openai_reasoning_effort": _env("MID_THINK_OPENAI_REASONING_EFFORT"),
-    "quick_think_google_thinking_level": None,
+    "quick_think_google_thinking_level": _env("QUICK_THINK_GOOGLE_THINKING_LEVEL"),
-    "quick_think_openai_reasoning_effort": None,
+    "quick_think_openai_reasoning_effort": _env("QUICK_THINK_OPENAI_REASONING_EFFORT"),
     # Debate and discussion settings
-    "max_debate_rounds": 1,
+    "max_debate_rounds": _env_int("MAX_DEBATE_ROUNDS", 1),
-    "max_risk_discuss_rounds": 1,
+    "max_risk_discuss_rounds": _env_int("MAX_RISK_DISCUSS_ROUNDS", 1),
-    "max_recur_limit": 100,
+    "max_recur_limit": _env_int("MAX_RECUR_LIMIT", 100),
     # Data vendor configuration
     # Category-level configuration (default for all tools in category)
     "data_vendors": {
-        "core_stock_apis": "yfinance",       # Options: alpha_vantage, yfinance
+        "core_stock_apis": _env("VENDOR_CORE_STOCK_APIS", "yfinance"),
-        "technical_indicators": "yfinance",  # Options: alpha_vantage, yfinance
+        "technical_indicators": _env("VENDOR_TECHNICAL_INDICATORS", "yfinance"),
-        "fundamental_data": "yfinance",      # Options: alpha_vantage, yfinance
+        "fundamental_data": _env("VENDOR_FUNDAMENTAL_DATA", "yfinance"),
-        "news_data": "yfinance",             # Options: alpha_vantage, yfinance
+        "news_data": _env("VENDOR_NEWS_DATA", "yfinance"),
-        "scanner_data": "alpha_vantage",      # Options: alpha_vantage (primary), yfinance (fallback)
+        "scanner_data": _env("VENDOR_SCANNER_DATA", "yfinance"),
     },
     # Tool-level configuration (takes precedence over category-level)
     "tool_vendors": {

tradingagents/graph/scanner_graph.py

@@ -139,9 +139,10 @@ class ScannerGraph:
         }
 
         if self.debug:
-            trace = []
+            # stream() yields partial state updates; use invoke() for the
+            # full accumulated state and print chunks for debugging only.
             for chunk in self.graph.stream(initial_state):
-                trace.append(chunk)
+                print(f"[scanner debug] chunk keys: {list(chunk.keys())}")
-            return trace[-1] if trace else initial_state
+            # Fall through to invoke() for the correct accumulated result
 
         return self.graph.invoke(initial_state)

tradingagents/pipeline/macro_bridge.py

@@ -238,10 +238,10 @@ async def run_all_tickers(
         List of TickerResult in completion order.
     """
     semaphore = asyncio.Semaphore(max_concurrent)
-    loop = asyncio.get_event_loop()
 
     async def _run_one(candidate: StockCandidate) -> TickerResult:
         async with semaphore:
+            loop = asyncio.get_running_loop()
             # TradingAgentsGraph is synchronous — run it in a thread pool
             return await loop.run_in_executor(
                 None,