Merge pull request #9 from aguzererler/copilot/fix-allow-env-variables-override-config

fix: allow .env variables to override DEFAULT_CONFIG values

.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

@@ -75,6 +75,7 @@ OpenAI, Anthropic, Google, xAI, OpenRouter, Ollama
 - LLM tiers configuration
 - Vendor routing
 - Debate rounds settings
+- All values overridable via `TRADINGAGENTS_<KEY>` env vars (see `.env.example`)
 
 ## Patterns to Follow
 
@@ -91,27 +92,38 @@ OpenAI, Anthropic, Google, xAI, OpenRouter, Ollama
 - **Tool execution**: Trading graph uses `ToolNode` in graph. Scanner agents use `run_tool_loop()` inline. If `bind_tools()` is used, there MUST be a tool execution path.
 - **yfinance DataFrames**: `top_companies` has ticker as INDEX, not column. Always check `.index` and `.columns`.
 - **yfinance Sector/Industry**: `Sector.overview` has NO performance data. Use ETF proxies for performance.
-- **Vendor fallback**: Functions inside `route_to_vendor` must RAISE on failure, not embed errors in return values. Catch `AlphaVantageError` (base class), not just `RateLimitError`.
+- **Vendor fallback**: Functions inside `route_to_vendor` must RAISE on failure, not embed errors in return values. Catch `(AlphaVantageError, ConnectionError, TimeoutError)`, not just `RateLimitError`.
 - **LangGraph parallel writes**: Any state field written by parallel nodes MUST have a reducer (`Annotated[str, reducer_fn]`).
 - **Ollama remote host**: Never hardcode `localhost:11434`. Use configured `base_url`.
-- **.env loading**: Check actual env var values when debugging auth. Worktree and main repo may have different `.env` files.
+- **.env loading**: `load_dotenv()` runs at module level in `default_config.py` — import-order-independent. Check actual env var values when debugging auth.
+- **Rate limiter locks**: Never hold a lock during `sleep()` or IO. Release, sleep, re-acquire.
+- **Config fallback keys**: `llm_provider` and `backend_url` must always exist at top level — `scanner_graph.py` and `trading_graph.py` use them as fallbacks.
 
 ## Project Tracking Files
 
-- `DECISIONS.md` — Architecture decision records (vendor strategy, LLM setup, tool execution)
+- `DECISIONS.md` — Architecture decision records (vendor strategy, LLM setup, tool execution, env overrides)
 - `PROGRESS.md` — Feature progress, what works, TODOs
-- `MISTAKES.md` — Past bugs and lessons learned (9 documented mistakes)
+- `MISTAKES.md` — Past bugs and lessons learned (10 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`)
+
+### Env Var Override Convention
+
+```env
+# Pattern: TRADINGAGENTS_<UPPERCASE_KEY>=value
+TRADINGAGENTS_LLM_PROVIDER=openrouter
+TRADINGAGENTS_DEEP_THINK_LLM=deepseek/deepseek-r1-0528
+TRADINGAGENTS_MAX_DEBATE_ROUNDS=3
+TRADINGAGENTS_VENDOR_SCANNER_DATA=alpha_vantage
 ```
 
-Config: `tradingagents/default_config.py` (per-tier `_llm_provider` keys)
+Empty or unset vars preserve the hardcoded default. `None`-default fields (like `mid_think_llm`) stay `None` when unset, preserving fallback semantics.
-Keys: `.env` file (`OPENROUTER_API_KEY`, `ALPHA_VANTAGE_API_KEY`)
 
 ## Running the Scanner
 

DECISIONS.md

@@ -105,10 +105,75 @@ Download 6 months of history via `yf.download()` and compute 1-day, 1-week, 1-mo
 ## Decision 007: .env Loading Strategy
 
 **Date**: 2026-03-17
-**Status**: Implemented ✅
+**Status**: Superseded by Decision 008 ⚠️
 
 **Context**: `load_dotenv()` loads from CWD. When running from a git worktree, the worktree `.env` may have placeholder values while the main repo `.env` has real keys.
 
 **Decision**: `cli/main.py` calls `load_dotenv()` (CWD) then `load_dotenv(Path(__file__).parent.parent / ".env")` as fallback. The worktree `.env` was also updated with real API keys.
 
 **Note for future**: If `.env` issues recur, check which `.env` file is being picked up. The worktree and main repo each have their own `.env`.
+
+**Update**: Decision 008 moves `load_dotenv()` into `default_config.py` itself, making it import-order-independent. The CLI-level `load_dotenv()` in `main.py` is now defense-in-depth only.
+
+---
+
+## Decision 008: Environment Variable Config Overrides
+
+**Date**: 2026-03-17
+**Status**: Implemented ✅
+
+**Context**: `DEFAULT_CONFIG` hardcoded all values (LLM providers, models, vendor routing, debate rounds). Users had to edit `default_config.py` to change any setting. The `load_dotenv()` call in `cli/main.py` ran *after* `DEFAULT_CONFIG` was already evaluated at import time, so env vars like `TRADINGAGENTS_LLM_PROVIDER` had no effect. This also created a latent bug (Mistake #9): `llm_provider` and `backend_url` were removed from the config but `scanner_graph.py` still referenced them as fallbacks.
+
+**Decision**:
+1. **Module-level `.env` loading**: `default_config.py` calls `load_dotenv()` at the top of the module, before `DEFAULT_CONFIG` is evaluated. Loads from CWD first, then falls back to project root (`Path(__file__).resolve().parent.parent / ".env"`).
+2. **`_env()` / `_env_int()` helpers**: Read `TRADINGAGENTS_<KEY>` from environment. Return the hardcoded default when the env var is unset or empty (preserving `None` semantics for per-tier fallbacks).
+3. **Restored top-level keys**: `llm_provider` (default: `"openai"`) and `backend_url` (default: `"https://api.openai.com/v1"`) restored as env-overridable keys. Resolves Mistake #9.
+4. **All config keys overridable**: LLM models, providers, backend URLs, debate rounds, data vendor categories — all follow the `TRADINGAGENTS_<KEY>` pattern.
+5. **Explicit dependency**: Added `python-dotenv>=1.0.0` to `pyproject.toml` (was used but undeclared).
+
+**Naming convention**: `TRADINGAGENTS_` prefix + uppercase config key. Examples:
+```
+TRADINGAGENTS_LLM_PROVIDER=openrouter
+TRADINGAGENTS_DEEP_THINK_LLM=deepseek/deepseek-r1-0528
+TRADINGAGENTS_MAX_DEBATE_ROUNDS=3
+TRADINGAGENTS_VENDOR_SCANNER_DATA=alpha_vantage
+```
+
+**Files changed**:
+- `tradingagents/default_config.py` — core implementation
+- `main.py` — moved `load_dotenv()` before imports (defense-in-depth)
+- `pyproject.toml` — added `python-dotenv>=1.0.0`
+- `.env.example` — documented all overrides
+- `tests/test_env_override.py` — 15 tests
+
+**Alternative considered**: YAML/TOML config file. Rejected — env vars are simpler, work with Docker/CI, and don't require a new config file format.
+
+---
+
+## Decision 009: Thread-Safe Rate Limiter for Alpha Vantage
+
+**Date**: 2026-03-17
+**Status**: Implemented ✅
+
+**Context**: The Alpha Vantage rate limiter in `alpha_vantage_common.py` initially slept *inside* the lock when re-checking the rate window. This blocked all other threads from making API requests during the sleep period, effectively serializing all AV calls.
+
+**Decision**: Two-phase rate limiting:
+1. **First check**: Acquire lock, check timestamps, release lock, sleep if needed.
+2. **Re-check loop**: Acquire lock, re-check timestamps. If still over limit, release lock *before* sleeping, then retry. Only append timestamp and break when under the limit.
+
+This ensures the lock is never held during `sleep()` calls.
+
+**File**: `tradingagents/dataflows/alpha_vantage_common.py`
+
+---
+
+## Decision 010: Broader Vendor Fallback Exception Handling
+
+**Date**: 2026-03-17
+**Status**: Implemented ✅
+
+**Context**: `route_to_vendor()` only caught `AlphaVantageError` for fallback. But network issues (`ConnectionError`, `TimeoutError`) from the `requests` library wouldn't trigger fallback — they'd crash the pipeline instead.
+
+**Decision**: Broadened the catch in `route_to_vendor()` to `(AlphaVantageError, ConnectionError, TimeoutError)`. Similarly, `_make_api_request()` now catches `requests.exceptions.RequestException` as a general fallback and wraps `raise_for_status()` in a try/except to convert HTTP errors to `ThirdPartyError`.
+
+**Files**: `tradingagents/dataflows/interface.py`, `tradingagents/dataflows/alpha_vantage_common.py`

MISTAKES.md

@@ -96,6 +96,27 @@ Documenting bugs and wrong assumptions to avoid repeating them.
 
 **What happened**: Removed `llm_provider` from `default_config.py` (since we have per-tier providers). But `scanner_graph.py` line 78 does `self.config.get(f"{tier}_llm_provider") or self.config["llm_provider"]` — would crash if per-tier provider is ever None.
 
-**Status**: Works currently because per-tier providers are always set. But it's a latent bug.
+**Status**: ✅ RESOLVED in PR #9. Top-level `llm_provider` (default: `"openai"`) and `backend_url` (default: `"https://api.openai.com/v1"`) restored as env-overridable config keys. Per-tier providers safely fall back to these when `None`.
 
-**TODO**: Add a safe fallback or remove the dead code path.
+**Lesson**: Always preserve fallback keys that downstream code depends on. When refactoring config, grep for all references before removing keys.
+
+---
+
+## Mistake 10: Rate limiter held lock during sleep
+
+**What happened**: The Alpha Vantage rate limiter's re-check path in `_rate_limited_request()` called `_time.sleep(extra_sleep)` while holding `_rate_lock`. This blocked all other threads from making API requests during the sleep period, effectively serializing all AV calls even though the pipeline runs parallel scanner agents.
+
+**Root cause**: Initial implementation only had one lock section. When the re-check-after-sleep pattern was added to prevent race conditions, the sleep was left inside the `with _rate_lock:` block.
+
+**Fix**: Restructured the re-check as a `while True` loop that releases the lock before sleeping:
+```python
+while True:
+    with _rate_lock:
+        if len(_call_timestamps) < _RATE_LIMIT:
+            _call_timestamps.append(_time.time())
+            break
+        extra_sleep = 60 - (now - _call_timestamps[0]) + 0.1
+    _time.sleep(extra_sleep)  # ← outside lock
+```
+
+**Lesson**: Never hold a lock during a sleep/IO operation. Always release the lock, perform the blocking operation, then re-acquire.

PROGRESS.md

@@ -15,10 +15,11 @@ The 3-phase scanner pipeline runs successfully from `python -m cli.main scan --d
 | Phase 3: Macro Synthesis | ✅ | OpenRouter/DeepSeek R1, pure LLM synthesis (no tools) |
 | Parallel fan-out (Phase 1) | ✅ | LangGraph with `_last_value` reducers |
 | Tool execution loop | ✅ | `run_tool_loop()` in `tool_runner.py` |
-| Data vendor fallback | ✅ | AV → yfinance fallback on `AlphaVantageError` |
+| Data vendor fallback | ✅ | AV → yfinance fallback on `AlphaVantageError`, `ConnectionError`, `TimeoutError` |
 | CLI `--date` flag | ✅ | `python -m cli.main scan --date YYYY-MM-DD` |
-| .env loading | ✅ | Keys loaded from project root `.env` |
+| .env loading | ✅ | `load_dotenv()` at module level in `default_config.py` — import-order-independent |
-| Tests (23 total) | ✅ | 14 original + 9 scanner fallback tests |
+| Env var config overrides | ✅ | All `DEFAULT_CONFIG` keys overridable via `TRADINGAGENTS_<KEY>` env vars |
+| Tests (38 total) | ✅ | 14 original + 9 scanner fallback + 15 env override tests |
 
 ### Output Quality (Sample Run 2026-03-17)
 
@@ -41,14 +42,40 @@ The 3-phase scanner pipeline runs successfully from `python -m cli.main scan --d
 - `tradingagents/graph/scanner_setup.py` — LangGraph workflow setup
 - `tradingagents/dataflows/yfinance_scanner.py` — yfinance data for scanner
 - `tradingagents/dataflows/alpha_vantage_scanner.py` — Alpha Vantage data for scanner
+- `tradingagents/pipeline/macro_bridge.py` — scan → filter → per-ticker analysis bridge
 - `tests/test_scanner_fallback.py` — 9 fallback tests
+- `tests/test_env_override.py` — 15 env override tests
 
 **Modified files:**
-- `tradingagents/default_config.py` — per-tier LLM provider config (hybrid setup)
+- `tradingagents/default_config.py` — env var overrides via `_env()`/`_env_int()` helpers, `load_dotenv()` at module level, restored top-level `llm_provider` and `backend_url` keys
 - `tradingagents/llm_clients/openai_client.py` — Ollama remote host support
-- `tradingagents/dataflows/interface.py` — broadened fallback catch to `AlphaVantageError`
+- `tradingagents/dataflows/interface.py` — broadened fallback catch to `(AlphaVantageError, ConnectionError, TimeoutError)`
-- `cli/main.py` — `scan` command with `--date` flag, `.env` loading fix
+- `tradingagents/dataflows/alpha_vantage_common.py` — thread-safe rate limiter (sleep outside lock), broader `RequestException` catch, wrapped `raise_for_status`
-- `.env` — real API keys
+- `tradingagents/graph/scanner_graph.py` — debug mode fix (stream for debug, invoke for result)
+- `tradingagents/pipeline/macro_bridge.py` — `get_running_loop()` over deprecated `get_event_loop()`
+- `cli/main.py` — `scan` command with `--date` flag, `try/except` in `run_pipeline`, `.env` loading fix
+- `main.py` — `load_dotenv()` before tradingagents imports
+- `pyproject.toml` — `python-dotenv>=1.0.0` dependency declared
+- `.env.example` — documented all `TRADINGAGENTS_*` overrides and `ALPHA_VANTAGE_API_KEY`
+
+---
+
+## Milestone: Env Var Config Overrides ✅ COMPLETE (PR #9)
+
+All `DEFAULT_CONFIG` values are now overridable via `TRADINGAGENTS_<KEY>` environment variables without code changes. This resolves the latent bug from Mistake #9 (missing top-level `llm_provider`).
+
+### What Changed
+
+| Component | Detail |
+|-----------|--------|
+| `default_config.py` | `load_dotenv()` at module level + `_env()`/`_env_int()` helpers |
+| Top-level fallback keys | Restored `llm_provider` and `backend_url` (defaults: `"openai"`, `"https://api.openai.com/v1"`) |
+| Per-tier overrides | All `None` by default — fall back to top-level when not set via env |
+| Integer config keys | `max_debate_rounds`, `max_risk_discuss_rounds`, `max_recur_limit` use `_env_int()` |
+| Data vendor keys | `data_vendors.*` overridable via `TRADINGAGENTS_VENDOR_<CATEGORY>` |
+| `.env.example` | Complete reference of all overridable settings |
+| `python-dotenv` | Added to `pyproject.toml` as explicit dependency |
+| Tests | 15 new tests in `tests/test_env_override.py` |
 
 ---
 
@@ -78,4 +105,4 @@ The 3-phase scanner pipeline runs successfully from `python -m cli.main scan --d
 
 - [ ] **Streaming output**: Scanner currently runs with `Live(Spinner(...))` — no intermediate output. Could stream phase completions to the console.
 
-- [ ] **Remove top-level `llm_provider` references**: `scanner_graph.py` lines 69, 78 still fall back to `self.config["llm_provider"]` which doesn't exist in current config. Works because per-tier providers are always set, but will crash if they're ever `None`.
+- [x] ~~**Remove top-level `llm_provider` references**~~: Resolved in PR #9 — `llm_provider` and `backend_url` restored as top-level keys with `"openai"` / `"https://api.openai.com/v1"` defaults. Per-tier providers fall back to these when `None`.

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 +83,34 @@ _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)
+
-        _call_timestamps.append(_time.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.
+    while True:
+        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
+            else:
+                _call_timestamps.append(_time.time())
+                break
+        # Sleep outside the lock to avoid blocking other threads
+        _time.sleep(extra_sleep)
+
+
     return _make_api_request(function_name, params, timeout=timeout)
 
 
@@ -131,6 +151,8 @@ 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 +168,13 @@ 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,