Merge pull request #9 from aguzererler/copilot/fix-allow-env-variables-override-config
fix: allow .env variables to override DEFAULT_CONFIG values
This commit is contained in:
ahmet guzererler
GitHub
commit
dc27874930
19
.env.example
19
.env.example
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@ -1,6 +1,23 @@
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# LLM Providers (set the one you use)
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# LLM Provider API Keys (set the ones you use)
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OPENAI_API_KEY=
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GOOGLE_API_KEY=
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ANTHROPIC_API_KEY=
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XAI_API_KEY=
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OPENROUTER_API_KEY=
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# Data Provider API Keys
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ALPHA_VANTAGE_API_KEY=
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# ── Configuration overrides ──────────────────────────────────────────
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# Any setting in DEFAULT_CONFIG can be overridden with a
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# TRADINGAGENTS_<KEY> environment variable. Unset or empty values
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# are ignored (the hardcoded default is kept).
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#
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# Examples:
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# TRADINGAGENTS_LLM_PROVIDER=openrouter
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# TRADINGAGENTS_QUICK_THINK_LLM=deepseek/deepseek-chat-v3-0324
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# TRADINGAGENTS_DEEP_THINK_LLM=deepseek/deepseek-r1-0528
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# TRADINGAGENTS_BACKEND_URL=https://openrouter.ai/api/v1
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# TRADINGAGENTS_RESULTS_DIR=./my_results
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# TRADINGAGENTS_MAX_DEBATE_ROUNDS=2
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# TRADINGAGENTS_VENDOR_SCANNER_DATA=alpha_vantage
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34
CLAUDE.md
34
CLAUDE.md
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@ -75,6 +75,7 @@ OpenAI, Anthropic, Google, xAI, OpenRouter, Ollama
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- LLM tiers configuration
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- Vendor routing
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- Debate rounds settings
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- All values overridable via `TRADINGAGENTS_<KEY>` env vars (see `.env.example`)
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## Patterns to Follow
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@ -91,27 +92,38 @@ OpenAI, Anthropic, Google, xAI, OpenRouter, Ollama
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- **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.
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- **yfinance DataFrames**: `top_companies` has ticker as INDEX, not column. Always check `.index` and `.columns`.
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- **yfinance Sector/Industry**: `Sector.overview` has NO performance data. Use ETF proxies for performance.
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- **Vendor fallback**: Functions inside `route_to_vendor` must RAISE on failure, not embed errors in return values. Catch `AlphaVantageError` (base class), not just `RateLimitError`.
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- **Vendor fallback**: Functions inside `route_to_vendor` must RAISE on failure, not embed errors in return values. Catch `(AlphaVantageError, ConnectionError, TimeoutError)`, not just `RateLimitError`.
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- **LangGraph parallel writes**: Any state field written by parallel nodes MUST have a reducer (`Annotated[str, reducer_fn]`).
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- **Ollama remote host**: Never hardcode `localhost:11434`. Use configured `base_url`.
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- **.env loading**: Check actual env var values when debugging auth. Worktree and main repo may have different `.env` files.
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- **.env loading**: `load_dotenv()` runs at module level in `default_config.py` — import-order-independent. Check actual env var values when debugging auth.
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- **Rate limiter locks**: Never hold a lock during `sleep()` or IO. Release, sleep, re-acquire.
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- **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.
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## Project Tracking Files
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- `DECISIONS.md` — Architecture decision records (vendor strategy, LLM setup, tool execution)
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- `DECISIONS.md` — Architecture decision records (vendor strategy, LLM setup, tool execution, env overrides)
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- `PROGRESS.md` — Feature progress, what works, TODOs
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- `MISTAKES.md` — Past bugs and lessons learned (9 documented mistakes)
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- `MISTAKES.md` — Past bugs and lessons learned (10 documented mistakes)
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## Current LLM Configuration (Hybrid)
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## LLM Configuration
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```
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quick_think: qwen3.5:27b via Ollama (http://192.168.50.76:11434)
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mid_think: qwen3.5:27b via Ollama (http://192.168.50.76:11434)
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deep_think: deepseek/deepseek-r1-0528 via OpenRouter
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Per-tier provider overrides in `tradingagents/default_config.py`:
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- Each tier (`quick_think`, `mid_think`, `deep_think`) can have its own `_llm_provider` and `_backend_url`
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- Falls back to top-level `llm_provider` and `backend_url` when per-tier values are None
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- All config values overridable via `TRADINGAGENTS_<KEY>` env vars
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- Keys for LLM providers: `.env` file (e.g., `OPENROUTER_API_KEY`, `ALPHA_VANTAGE_API_KEY`)
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### Env Var Override Convention
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```env
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# Pattern: TRADINGAGENTS_<UPPERCASE_KEY>=value
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TRADINGAGENTS_LLM_PROVIDER=openrouter
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TRADINGAGENTS_DEEP_THINK_LLM=deepseek/deepseek-r1-0528
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TRADINGAGENTS_MAX_DEBATE_ROUNDS=3
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TRADINGAGENTS_VENDOR_SCANNER_DATA=alpha_vantage
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```
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Config: `tradingagents/default_config.py` (per-tier `_llm_provider` keys)
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Keys: `.env` file (`OPENROUTER_API_KEY`, `ALPHA_VANTAGE_API_KEY`)
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Empty or unset vars preserve the hardcoded default. `None`-default fields (like `mid_think_llm`) stay `None` when unset, preserving fallback semantics.
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## Running the Scanner
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67
DECISIONS.md
67
DECISIONS.md
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@ -105,10 +105,75 @@ Download 6 months of history via `yf.download()` and compute 1-day, 1-week, 1-mo
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## Decision 007: .env Loading Strategy
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**Date**: 2026-03-17
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**Status**: Implemented ✅
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**Status**: Superseded by Decision 008 ⚠️
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**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.
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**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.
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**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`.
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**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.
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---
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## Decision 008: Environment Variable Config Overrides
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**Date**: 2026-03-17
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**Status**: Implemented ✅
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**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.
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**Decision**:
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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"`).
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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).
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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.
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4. **All config keys overridable**: LLM models, providers, backend URLs, debate rounds, data vendor categories — all follow the `TRADINGAGENTS_<KEY>` pattern.
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5. **Explicit dependency**: Added `python-dotenv>=1.0.0` to `pyproject.toml` (was used but undeclared).
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**Naming convention**: `TRADINGAGENTS_` prefix + uppercase config key. Examples:
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```
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TRADINGAGENTS_LLM_PROVIDER=openrouter
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TRADINGAGENTS_DEEP_THINK_LLM=deepseek/deepseek-r1-0528
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TRADINGAGENTS_MAX_DEBATE_ROUNDS=3
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TRADINGAGENTS_VENDOR_SCANNER_DATA=alpha_vantage
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```
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**Files changed**:
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- `tradingagents/default_config.py` — core implementation
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- `main.py` — moved `load_dotenv()` before imports (defense-in-depth)
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- `pyproject.toml` — added `python-dotenv>=1.0.0`
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- `.env.example` — documented all overrides
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- `tests/test_env_override.py` — 15 tests
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**Alternative considered**: YAML/TOML config file. Rejected — env vars are simpler, work with Docker/CI, and don't require a new config file format.
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---
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## Decision 009: Thread-Safe Rate Limiter for Alpha Vantage
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**Date**: 2026-03-17
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**Status**: Implemented ✅
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**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.
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**Decision**: Two-phase rate limiting:
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1. **First check**: Acquire lock, check timestamps, release lock, sleep if needed.
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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.
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This ensures the lock is never held during `sleep()` calls.
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**File**: `tradingagents/dataflows/alpha_vantage_common.py`
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---
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## Decision 010: Broader Vendor Fallback Exception Handling
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**Date**: 2026-03-17
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**Status**: Implemented ✅
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**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.
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**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`.
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**Files**: `tradingagents/dataflows/interface.py`, `tradingagents/dataflows/alpha_vantage_common.py`
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25
MISTAKES.md
25
MISTAKES.md
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@ -96,6 +96,27 @@ Documenting bugs and wrong assumptions to avoid repeating them.
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**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.
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**Status**: Works currently because per-tier providers are always set. But it's a latent bug.
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**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`.
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**TODO**: Add a safe fallback or remove the dead code path.
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**Lesson**: Always preserve fallback keys that downstream code depends on. When refactoring config, grep for all references before removing keys.
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---
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## Mistake 10: Rate limiter held lock during sleep
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**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.
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**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.
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**Fix**: Restructured the re-check as a `while True` loop that releases the lock before sleeping:
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```python
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while True:
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with _rate_lock:
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if len(_call_timestamps) < _RATE_LIMIT:
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_call_timestamps.append(_time.time())
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break
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extra_sleep = 60 - (now - _call_timestamps[0]) + 0.1
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_time.sleep(extra_sleep) # ← outside lock
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```
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**Lesson**: Never hold a lock during a sleep/IO operation. Always release the lock, perform the blocking operation, then re-acquire.
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43
PROGRESS.md
43
PROGRESS.md
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@ -15,10 +15,11 @@ The 3-phase scanner pipeline runs successfully from `python -m cli.main scan --d
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| Phase 3: Macro Synthesis | ✅ | OpenRouter/DeepSeek R1, pure LLM synthesis (no tools) |
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| Parallel fan-out (Phase 1) | ✅ | LangGraph with `_last_value` reducers |
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| Tool execution loop | ✅ | `run_tool_loop()` in `tool_runner.py` |
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| Data vendor fallback | ✅ | AV → yfinance fallback on `AlphaVantageError` |
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| Data vendor fallback | ✅ | AV → yfinance fallback on `AlphaVantageError`, `ConnectionError`, `TimeoutError` |
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| CLI `--date` flag | ✅ | `python -m cli.main scan --date YYYY-MM-DD` |
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| .env loading | ✅ | Keys loaded from project root `.env` |
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| Tests (23 total) | ✅ | 14 original + 9 scanner fallback tests |
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| .env loading | ✅ | `load_dotenv()` at module level in `default_config.py` — import-order-independent |
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| Env var config overrides | ✅ | All `DEFAULT_CONFIG` keys overridable via `TRADINGAGENTS_<KEY>` env vars |
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| Tests (38 total) | ✅ | 14 original + 9 scanner fallback + 15 env override tests |
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### Output Quality (Sample Run 2026-03-17)
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@ -41,14 +42,40 @@ The 3-phase scanner pipeline runs successfully from `python -m cli.main scan --d
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- `tradingagents/graph/scanner_setup.py` — LangGraph workflow setup
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- `tradingagents/dataflows/yfinance_scanner.py` — yfinance data for scanner
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- `tradingagents/dataflows/alpha_vantage_scanner.py` — Alpha Vantage data for scanner
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- `tradingagents/pipeline/macro_bridge.py` — scan → filter → per-ticker analysis bridge
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- `tests/test_scanner_fallback.py` — 9 fallback tests
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- `tests/test_env_override.py` — 15 env override tests
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**Modified files:**
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- `tradingagents/default_config.py` — per-tier LLM provider config (hybrid setup)
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- `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
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- `tradingagents/llm_clients/openai_client.py` — Ollama remote host support
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- `tradingagents/dataflows/interface.py` — broadened fallback catch to `AlphaVantageError`
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- `cli/main.py` — `scan` command with `--date` flag, `.env` loading fix
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- `.env` — real API keys
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- `tradingagents/dataflows/interface.py` — broadened fallback catch to `(AlphaVantageError, ConnectionError, TimeoutError)`
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- `tradingagents/dataflows/alpha_vantage_common.py` — thread-safe rate limiter (sleep outside lock), broader `RequestException` catch, wrapped `raise_for_status`
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- `tradingagents/graph/scanner_graph.py` — debug mode fix (stream for debug, invoke for result)
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- `tradingagents/pipeline/macro_bridge.py` — `get_running_loop()` over deprecated `get_event_loop()`
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- `cli/main.py` — `scan` command with `--date` flag, `try/except` in `run_pipeline`, `.env` loading fix
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- `main.py` — `load_dotenv()` before tradingagents imports
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- `pyproject.toml` — `python-dotenv>=1.0.0` dependency declared
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- `.env.example` — documented all `TRADINGAGENTS_*` overrides and `ALPHA_VANTAGE_API_KEY`
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---
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## Milestone: Env Var Config Overrides ✅ COMPLETE (PR #9)
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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`).
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### What Changed
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| Component | Detail |
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|-----------|--------|
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| `default_config.py` | `load_dotenv()` at module level + `_env()`/`_env_int()` helpers |
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| Top-level fallback keys | Restored `llm_provider` and `backend_url` (defaults: `"openai"`, `"https://api.openai.com/v1"`) |
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| Per-tier overrides | All `None` by default — fall back to top-level when not set via env |
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| Integer config keys | `max_debate_rounds`, `max_risk_discuss_rounds`, `max_recur_limit` use `_env_int()` |
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| Data vendor keys | `data_vendors.*` overridable via `TRADINGAGENTS_VENDOR_<CATEGORY>` |
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| `.env.example` | Complete reference of all overridable settings |
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| `python-dotenv` | Added to `pyproject.toml` as explicit dependency |
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| Tests | 15 new tests in `tests/test_env_override.py` |
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---
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@ -78,4 +105,4 @@ The 3-phase scanner pipeline runs successfully from `python -m cli.main scan --d
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- [ ] **Streaming output**: Scanner currently runs with `Live(Spinner(...))` — no intermediate output. Could stream phase completions to the console.
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- [ ] **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`.
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- [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`.
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13
cli/main.py
13
cli/main.py
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@ -1,5 +1,6 @@
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from typing import Optional
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import datetime
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import json
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import typer
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from pathlib import Path
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from functools import wraps
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@ -1201,8 +1202,6 @@ def run_scan(date: Optional[str] = None):
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raise typer.Exit(1)
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# Save reports
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import json as _json
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for key in ["geopolitical_report", "market_movers_report", "sector_performance_report",
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"industry_deep_dive_report", "macro_scan_summary"]:
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content = result.get(key, "")
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@ -1217,7 +1216,7 @@ def run_scan(date: Optional[str] = None):
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# Try to parse and show watchlist table
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try:
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summary_data = _json.loads(summary)
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summary_data = json.loads(summary)
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stocks = summary_data.get("stocks_to_investigate", [])
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if stocks:
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table = Table(title="Stocks to Investigate", box=box.ROUNDED)
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@ -1235,16 +1234,16 @@ def run_scan(date: Optional[str] = None):
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s.get("thesis_angle", ""),
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)
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console.print(table)
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except (_json.JSONDecodeError, KeyError):
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except (json.JSONDecodeError, KeyError):
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pass # Summary wasn't valid JSON — already printed as markdown
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console.print(f"\n[green]Results saved to {save_dir}[/green]")
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def run_pipeline():
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"""Full pipeline: scan -> filter -> per-ticker deep dive."""
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import asyncio
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import json as _json
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from tradingagents.pipeline.macro_bridge import (
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parse_macro_output,
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filter_candidates,
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@ -1293,10 +1292,14 @@ def run_pipeline():
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output_dir = Path("results/macro_pipeline")
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console.print(f"\n[cyan]Running TradingAgents for {len(candidates)} tickers...[/cyan]")
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try:
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with Live(Spinner("dots", text="Analyzing..."), console=console, transient=True):
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results = asyncio.run(
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run_all_tickers(candidates, macro_context, config, analysis_date)
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)
|
||||
except Exception as e:
|
||||
console.print(f"[red]Pipeline failed: {e}[/red]")
|
||||
raise typer.Exit(1)
|
||||
|
||||
save_results(results, macro_context, output_dir)
|
||||
|
||||
|
|
|
|||
10
main.py
10
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
|
||||
|
|
|
|||
|
|
@ -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",
|
||||
|
|
|
|||
|
|
@ -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"
|
||||
|
|
@ -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(
|
||||
|
|
|
|||
|
|
@ -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
|
||||
|
||||
# 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]}"
|
||||
)
|
||||
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
|
||||
|
||||
|
|
|
|||
|
|
@ -201,7 +201,7 @@ def route_to_vendor(method: str, *args, **kwargs):
|
|||
|
||||
try:
|
||||
return impl_func(*args, **kwargs)
|
||||
except AlphaVantageError:
|
||||
continue # Any AV error triggers fallback to next vendor
|
||||
except (AlphaVantageError, ConnectionError, TimeoutError):
|
||||
continue # Any AV error or connection/timeout triggers fallback to next vendor
|
||||
|
||||
raise RuntimeError(f"No available vendor for '{method}'")
|
||||
|
|
@ -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
|
||||
"mid_think_llm": "qwen3.5:27b", # falls back to quick_think_llm when None
|
||||
"quick_think_llm": "qwen3.5:27b",
|
||||
# LLM settings — all overridable via TRADINGAGENTS_<KEY> env vars
|
||||
"llm_provider": _env("LLM_PROVIDER", "openai"),
|
||||
"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": "deepseek/deepseek-r1-0528",
|
||||
"deep_think_backend_url": None, # uses OpenRouter's default URL
|
||||
"mid_think_llm_provider": "ollama", # falls back to ollama
|
||||
"mid_think_backend_url": "http://192.168.50.76:11434", # falls back to backend_url (ollama host)
|
||||
"quick_think_llm_provider": "ollama", # falls back to ollama
|
||||
"quick_think_backend_url": "http://192.168.50.76:11434", # falls back to backend_url (ollama host)
|
||||
"deep_think_llm_provider": _env("DEEP_THINK_LLM_PROVIDER"), # e.g. "google", "anthropic", "openrouter"
|
||||
"deep_think_backend_url": _env("DEEP_THINK_BACKEND_URL"), # override backend URL for deep-think model
|
||||
"mid_think_llm_provider": _env("MID_THINK_LLM_PROVIDER"), # e.g. "ollama"
|
||||
"mid_think_backend_url": _env("MID_THINK_BACKEND_URL"), # override backend URL for mid-think model
|
||||
"quick_think_llm_provider": _env("QUICK_THINK_LLM_PROVIDER"), # e.g. "openai", "ollama"
|
||||
"quick_think_backend_url": _env("QUICK_THINK_BACKEND_URL"), # override backend URL for quick-think model
|
||||
# Provider-specific thinking configuration (applies to all roles unless overridden)
|
||||
"google_thinking_level": None, # "high", "minimal", etc.
|
||||
"openai_reasoning_effort": None, # "medium", "high", "low"
|
||||
"google_thinking_level": _env("GOOGLE_THINKING_LEVEL"), # "high", "minimal", etc.
|
||||
"openai_reasoning_effort": _env("OPENAI_REASONING_EFFORT"), # "medium", "high", "low"
|
||||
# Per-role provider-specific thinking configuration
|
||||
"deep_think_google_thinking_level": None,
|
||||
"deep_think_openai_reasoning_effort": None,
|
||||
"mid_think_google_thinking_level": None,
|
||||
"mid_think_openai_reasoning_effort": None,
|
||||
"quick_think_google_thinking_level": None,
|
||||
"quick_think_openai_reasoning_effort": None,
|
||||
"deep_think_google_thinking_level": _env("DEEP_THINK_GOOGLE_THINKING_LEVEL"),
|
||||
"deep_think_openai_reasoning_effort": _env("DEEP_THINK_OPENAI_REASONING_EFFORT"),
|
||||
"mid_think_google_thinking_level": _env("MID_THINK_GOOGLE_THINKING_LEVEL"),
|
||||
"mid_think_openai_reasoning_effort": _env("MID_THINK_OPENAI_REASONING_EFFORT"),
|
||||
"quick_think_google_thinking_level": _env("QUICK_THINK_GOOGLE_THINKING_LEVEL"),
|
||||
"quick_think_openai_reasoning_effort": _env("QUICK_THINK_OPENAI_REASONING_EFFORT"),
|
||||
# Debate and discussion settings
|
||||
"max_debate_rounds": 1,
|
||||
"max_risk_discuss_rounds": 1,
|
||||
"max_recur_limit": 100,
|
||||
"max_debate_rounds": _env_int("MAX_DEBATE_ROUNDS", 1),
|
||||
"max_risk_discuss_rounds": _env_int("MAX_RISK_DISCUSS_ROUNDS", 1),
|
||||
"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
|
||||
"technical_indicators": "yfinance", # Options: alpha_vantage, yfinance
|
||||
"fundamental_data": "yfinance", # Options: alpha_vantage, yfinance
|
||||
"news_data": "yfinance", # Options: alpha_vantage, yfinance
|
||||
"scanner_data": "alpha_vantage", # Options: alpha_vantage (primary), yfinance (fallback)
|
||||
"core_stock_apis": _env("VENDOR_CORE_STOCK_APIS", "yfinance"),
|
||||
"technical_indicators": _env("VENDOR_TECHNICAL_INDICATORS", "yfinance"),
|
||||
"fundamental_data": _env("VENDOR_FUNDAMENTAL_DATA", "yfinance"),
|
||||
"news_data": _env("VENDOR_NEWS_DATA", "yfinance"),
|
||||
"scanner_data": _env("VENDOR_SCANNER_DATA", "yfinance"),
|
||||
},
|
||||
# Tool-level configuration (takes precedence over category-level)
|
||||
"tool_vendors": {
|
||||
|
|
|
|||
|
|
@ -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)
|
||||
return trace[-1] if trace else initial_state
|
||||
print(f"[scanner debug] chunk keys: {list(chunk.keys())}")
|
||||
# Fall through to invoke() for the correct accumulated result
|
||||
|
||||
return self.graph.invoke(initial_state)
|
||||
|
|
|
|||
|
|
@ -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,
|
||||
|
|
|
|||
Loading…
Reference in New Issue