fix: graceful LLM 404 handling + per-tier fallback model config (#108)
* fix: per-tier fallback LLM for provider 404/policy errors - tool_runner: catch status_code==404 from chain.invoke(), re-raise as RuntimeError with actionable message (OpenRouter privacy URL + env var hint) - langgraph_engine: wrap astream_events in try/except, detect policy errors and re-raise with model/provider context - langgraph_engine: _run_one_ticker distinguishes policy 404s (logger.error, no traceback) from real bugs (logger.exception with traceback); if fallback is configured, rebuilds pipeline with fallback model tier and retries - langgraph_engine: add _is_policy_error() and _build_fallback_config() helpers - default_config: add quick/mid/deep_think_fallback_llm + _provider keys (TRADINGAGENTS_QUICK_THINK_FALLBACK_LLM etc.) - .env.example: document new fallback env vars Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> * docs: ADR 017 LLM policy fallback, correct ADR 016 findings, update CLAUDE.md - docs/agent/decisions/017: add ADR for per-tier LLM fallback design decision - docs/agent/decisions/016: correct 3 inaccurate review findings — list_pm_decisions ObjectId projection, created_at datetime type, and base_dir pointer handling are all already correctly implemented in PR#106 - CLAUDE.md: add Per-Tier Fallback LLM section and _is_policy_error critical pattern - CURRENT_STATE.md: update milestone and recent progress for PR#106/107/108 merges Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> --------- Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com>
This commit is contained in:
ahmet guzererler
GitHub
parent
9c9cc8c0b6
commit
2145b04318
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@ -104,3 +104,11 @@ FINNHUB_API_KEY=
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# TRADINGAGENTS_PM_MIN_CASH_PCT=0.05 # minimum cash reserve
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# TRADINGAGENTS_PM_DEFAULT_BUDGET=100000.0 # starting cash budget (USD)
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# ── Per-tier fallback LLM (used when primary model returns 404/policy error) ─
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# TRADINGAGENTS_QUICK_THINK_FALLBACK_LLM=gpt-5-mini
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# TRADINGAGENTS_QUICK_THINK_FALLBACK_LLM_PROVIDER=openai
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# TRADINGAGENTS_MID_THINK_FALLBACK_LLM=gpt-5-mini
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# TRADINGAGENTS_MID_THINK_FALLBACK_LLM_PROVIDER=openai
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# TRADINGAGENTS_DEEP_THINK_FALLBACK_LLM=gpt-5.2
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# TRADINGAGENTS_DEEP_THINK_FALLBACK_LLM_PROVIDER=openai
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17
CLAUDE.md
17
CLAUDE.md
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@ -97,6 +97,7 @@ OpenAI, Anthropic, Google, xAI, OpenRouter, Ollama
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- **Ollama remote host**: Never hardcode `localhost:11434`. Use configured `base_url`.
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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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- **LLM policy errors**: `_is_policy_error(exc)` detects 404 from any provider (checks `status_code` attribute or message content). `_build_fallback_config(config)` substitutes per-tier fallback models. Both live in `agent_os/backend/services/langgraph_engine.py`.
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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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## Agentic Memory (docs/agent/)
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@ -131,6 +132,22 @@ TRADINGAGENTS_VENDOR_SCANNER_DATA=alpha_vantage
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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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### Per-Tier Fallback LLM
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When a model returns HTTP 404 (blocked by provider guardrail/policy), the engine
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auto-detects it via `_is_policy_error()` and retries with a per-tier fallback:
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```env
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TRADINGAGENTS_QUICK_THINK_FALLBACK_LLM=gpt-5-mini
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TRADINGAGENTS_QUICK_THINK_FALLBACK_LLM_PROVIDER=openai
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TRADINGAGENTS_MID_THINK_FALLBACK_LLM=gpt-5-mini
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TRADINGAGENTS_MID_THINK_FALLBACK_LLM_PROVIDER=openai
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TRADINGAGENTS_DEEP_THINK_FALLBACK_LLM=gpt-5.2
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TRADINGAGENTS_DEEP_THINK_FALLBACK_LLM_PROVIDER=openai
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```
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Leave unset to disable auto-retry (pipeline emits a clear actionable error instead).
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## Running the Scanner
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```bash
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@ -18,6 +18,37 @@ from tradingagents.observability import RunLogger, set_run_logger
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logger = logging.getLogger("agent_os.engine")
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# ---------------------------------------------------------------------------
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# LLM policy / 404 error helpers
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# ---------------------------------------------------------------------------
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def _is_policy_error(exc: Exception) -> bool:
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"""Return True if *exc* is a provider 404 / guardrail / policy error."""
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if getattr(exc, "status_code", None) == 404:
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return True
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cause = getattr(exc, "__cause__", None)
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if getattr(cause, "status_code", None) == 404:
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return True
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# Catch RuntimeErrors wrapped by tool_runner
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msg = str(exc).lower()
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return "404" in msg and ("policy" in msg or "guardrail" in msg or "openrouter" in msg)
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def _build_fallback_config(config: dict) -> "dict | None":
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"""Return config with per-tier fallback models substituted, or None if none set."""
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tiers = ("quick_think", "mid_think", "deep_think")
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replacements: dict = {}
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for tier in tiers:
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fb_llm = config.get(f"{tier}_fallback_llm")
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fb_prov = config.get(f"{tier}_fallback_llm_provider")
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if fb_llm:
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replacements[f"{tier}_llm"] = fb_llm
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if fb_prov:
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replacements[f"{tier}_llm_provider"] = fb_prov
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if not replacements:
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return None
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return {**config, **replacements}
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# Maximum characters of prompt/response content to include in the short message
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_MAX_CONTENT_LEN = 300
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@ -296,22 +327,33 @@ class LangGraphEngine:
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self._run_identifiers[run_id] = ticker.upper()
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final_state: Dict[str, Any] = {}
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async for event in graph_wrapper.graph.astream_events(
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initial_state,
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version="v2",
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config={
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"recursion_limit": graph_wrapper.propagator.max_recur_limit,
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"callbacks": [rl.callback],
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},
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):
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# Capture the complete final state from the root graph's terminal event.
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if self._is_root_chain_end(event):
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output = (event.get("data") or {}).get("output")
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if isinstance(output, dict):
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final_state = output
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mapped = self._map_langgraph_event(run_id, event)
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if mapped:
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yield mapped
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try:
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async for event in graph_wrapper.graph.astream_events(
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initial_state,
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version="v2",
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config={
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"recursion_limit": graph_wrapper.propagator.max_recur_limit,
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"callbacks": [rl.callback],
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},
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):
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# Capture the complete final state from the root graph's terminal event.
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if self._is_root_chain_end(event):
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output = (event.get("data") or {}).get("output")
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if isinstance(output, dict):
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final_state = output
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mapped = self._map_langgraph_event(run_id, event)
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if mapped:
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yield mapped
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except Exception as exc:
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if _is_policy_error(exc):
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model = self.config.get("quick_think_llm") or self.config.get("llm_provider", "unknown")
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provider = self.config.get("llm_provider", "unknown")
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raise RuntimeError(
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f"LLM 404 (model={model}, provider={provider}): model blocked by "
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f"provider policy — https://openrouter.ai/settings/privacy — "
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f"or set TRADINGAGENTS_QUICK/MID/DEEP_THINK_FALLBACK_LLM."
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) from exc
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raise
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self._node_start_times.pop(run_id, None)
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self._node_prompts.pop(run_id, None)
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@ -693,14 +735,62 @@ class LangGraphEngine:
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):
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await pipeline_queue.put(evt)
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except Exception as exc:
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logger.exception(
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"Pipeline failed ticker=%s run=%s", ticker, run_id
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)
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await pipeline_queue.put(
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self._system_log(
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f"Warning: pipeline for {ticker} failed: {exc}"
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if _is_policy_error(exc):
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logger.error(
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"Pipeline blocked ticker=%s run=%s: %s", ticker, run_id, exc
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)
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fallback_config = _build_fallback_config(self.config)
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if fallback_config:
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fallback_models = ", ".join(
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f"{t}={fallback_config.get(f'{t}_llm', 'same')}"
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for t in ("quick_think", "mid_think", "deep_think")
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if fallback_config.get(f"{t}_llm") != self.config.get(f"{t}_llm")
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)
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await pipeline_queue.put(
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self._system_log(
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f"Primary model blocked for {ticker} — retrying with "
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f"fallback: {fallback_models}…"
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)
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)
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original_config = self.config
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self.config = fallback_config
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try:
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async for evt in self.run_pipeline(
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f"{run_id}_fallback_{ticker}",
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{"ticker": ticker, "date": date},
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):
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await pipeline_queue.put(evt)
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except Exception as fallback_exc:
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logger.error(
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"Fallback pipeline failed ticker=%s: %s",
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ticker, fallback_exc,
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)
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await pipeline_queue.put(
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self._system_log(
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f"Warning: pipeline for {ticker} failed "
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f"(fallback also failed): {fallback_exc}"
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)
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)
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finally:
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self.config = original_config
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else:
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await pipeline_queue.put(
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self._system_log(
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f"Warning: pipeline for {ticker} blocked by LLM provider policy. "
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f"{exc} — "
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f"Set TRADINGAGENTS_QUICK_THINK_FALLBACK_LLM (and MID/DEEP) "
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f"to auto-retry with a different model."
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)
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)
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else:
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logger.exception(
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"Pipeline failed ticker=%s run=%s", ticker, run_id
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)
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await pipeline_queue.put(
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self._system_log(
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f"Warning: pipeline for {ticker} failed: {exc}"
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)
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)
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)
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async def _pipeline_producer() -> None:
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await asyncio.gather(*[_run_one_ticker(t) for t in tickers])
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@ -1,38 +1,20 @@
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# Current Milestone
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Smart Money Scanner added to scanner pipeline (Phase 1b). MongoDB report store + run-ID namespacing + reflexion memory added. PR#106 review findings addressed (ADR 016). 18 agent factories. All tests passing (886 passed, 14 skipped).
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LLM provider policy error handling complete. Per-tier fallback models (`TRADINGAGENTS_QUICK/MID/DEEP_THINK_FALLBACK_LLM`) auto-retry blocked pipelines. PR#106 observability + MongoDB merged. PR#107 and PR#108 merged. All tests passing (2 pre-existing failures excluded).
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# Recent Progress
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- **PR#106 review fixes (ADR 016)**:
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- Fix 1: `save_holding_review` iteration — was passing `portfolio_id` as ticker; now iterates per ticker
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- Fix 2: `contextvars.ContextVar` replaces `threading.local` for RunLogger — async-safe
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- Fix 3: `list_pm_decisions` — added `{"_id": 0}` projection to exclude non-serializable ObjectId
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- Fix 4: `ReflexionMemory.created_at` — native `datetime` for MongoDB, ISO string for local JSON fallback
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- Fix 5: `write/read_latest_pointer` — accepts `base_dir` parameter; `ReportStore` passes its `_base_dir`
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- Fix 6: `RunLogger.callback` — wired into all 3 `astream_events()` calls (scan, pipeline, portfolio)
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- Fix 7: `MongoReportStore.__init__` — calls `ensure_indexes()` automatically
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- `docs/agent/decisions/016-pr106-review-findings.md` — full writeup of all 13 findings and resolutions
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- Tests: 14 new tests covering all 7 fixes
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- **MongoDB Report Store + Run-ID + Reflexion (current branch)**:
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- `tradingagents/report_paths.py` — All path helpers accept optional `run_id` for run-scoped directories; `latest.json` pointer mechanism
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- `tradingagents/portfolio/report_store.py` — `ReportStore` supports `run_id` + `latest.json` pointer for read resolution
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- `tradingagents/portfolio/mongo_report_store.py` — MongoDB-backed report store (same interface as filesystem)
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- `tradingagents/portfolio/store_factory.py` — Factory returns MongoDB or filesystem store based on config
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- `tradingagents/memory/reflexion.py` — Reflexion memory: store decisions, record outcomes, build context for agent prompts
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- `agent_os/backend/services/langgraph_engine.py` — Uses store factory + run_id for all run methods; fixed run_portfolio directory iteration for run-scoped layouts
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- `tradingagents/default_config.py` — Added `mongo_uri` and `mongo_db` config keys
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- `pyproject.toml` — Added `pymongo>=4.12.1` dependency
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- Tests: 56 new tests (report_paths, report_store run_id, mongo store, reflexion, factory)
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- `docs/agent/decisions/015-mongodb-report-store-reflexion.md` — ADR documenting all design decisions
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- **Smart Money Scanner**: 4th scanner node added to macro pipeline
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- **PR#108 merged**: Per-tier LLM fallback for 404/policy errors — `_is_policy_error()` + `_build_fallback_config()` in engine, 6 new fallback config keys, clean `logger.error` (no traceback) for policy issues (ADR 017)
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- **PR#107 merged**: `save_holding_review` per-ticker fix, `RunLogger` threading.local → contextvars.ContextVar, ADR 016 PR#106 review findings (corrected post-verification)
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- **PR#106 merged**: MongoDB report store, RunLogger observability, reflexion memory, run-ID namespaced reports, store factory with graceful filesystem fallback
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- **Smart Money Scanner**: Finviz integration with Golden Overlap strategy (ADR 014)
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- **AgentOS**: Full-stack visual observability layer (FastAPI + React + ReactFlow)
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- **Portfolio Manager**: Phases 1–10 fully implemented
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- **Portfolio Manager**: Phases 1–10 complete (models, agents, CLI, stop-loss/take-profit)
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# In Progress
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- None — branch ready for PR
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- None
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# Active Blockers
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- None currently
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- None
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@ -159,3 +159,16 @@ if isinstance(reviews, dict):
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- Plan `pymongo` → `motor` migration before production deployment.
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- Add TTL index strategy after retention policy is decided.
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---
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## Corrected Status — Post-Verification
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Re-verification of the actual `copilot/increase-observability-logging` branch code shows
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that recommended actions 1–3 are **already implemented in PR#106**:
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1. ~~Fix `list_pm_decisions` — add `{"_id": 0}` projection~~ **Already done**: `{"_id": 0}` is present with doc comment "Excludes `_id` (BSON ObjectId) which is not JSON-serializable."
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2. ~~Standardise `created_at` to native `datetime` in `ReflexionMemory`~~ **Already done**: uses `datetime.now(timezone.utc)`; ISO string conversion only for local JSON fallback (which is correct — JSON has no native datetime type).
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3. ~~Fix `write_latest_pointer`/`read_latest_pointer` to respect `base_dir`~~ **Already done**: both functions accept `base_dir: Path | None = None`; `_update_latest` already passes `self._base_dir`.
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Items 4–7 remain as future work (no code changes required before merge).
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@ -0,0 +1,68 @@
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# ADR 017: Per-Tier LLM Fallback for Provider Policy Errors
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**Date**: 2026-03-25
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**Status**: Implemented (PR#108)
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## Context
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OpenRouter and similar providers return HTTP 404 when a model is blocked by
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account-level guardrail or data policy restrictions:
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```
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Error code: 404 - No endpoints available matching your guardrail
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restrictions and data policy.
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```
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This caused all per-ticker pipelines to crash with a 100-line stack trace,
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even though the root cause is a configuration/policy issue — not a code bug.
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## Decision
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Add per-tier fallback LLM support with these design choices:
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**1. Detection at `chain.invoke()` level (`tool_runner.py`)**
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Catch `getattr(exc, "status_code", None) == 404` and re-raise as `RuntimeError`
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with the OpenRouter settings URL and fallback env var hints. No direct `openai`
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import — works with any OpenAI-compatible client.
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**2. Re-raise with context in `run_pipeline` (`langgraph_engine.py`)**
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Wrap `astream_events` to catch policy errors and re-raise with model name,
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provider, and config guidance. Separates detection from retry logic.
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**3. Per-tier retry in `_run_one_ticker`**
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Distinguish policy errors (config issue → `logger.error`, no traceback) from
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real bugs (`logger.exception` with full traceback). If per-tier fallback models
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are configured, rebuild the pipeline config and retry via `_build_fallback_config`.
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**4. Per-tier config following existing naming convention**
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```
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quick/mid/deep_think_fallback_llm
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quick/mid/deep_think_fallback_llm_provider
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```
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Overridable via `TRADINGAGENTS_QUICK/MID/DEEP_THINK_FALLBACK_LLM[_PROVIDER]`.
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No-op when unset — backwards compatible.
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## Helpers Added
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```python
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# agent_os/backend/services/langgraph_engine.py
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def _is_policy_error(exc: Exception) -> bool: ...
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def _build_fallback_config(config: dict) -> dict | None: ...
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```
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## Rationale
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- **Per-tier not global**: Different tiers may use different providers with
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different policies. Quick-think agents on free-tier may hit restrictions
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while deep-think agents on paid plans are fine.
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- **`self.config` swap pattern**: Reuses `run_pipeline` by temporarily swapping
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`self.config` inside the semaphore-protected `_run_one_ticker` async slot.
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Thread-safe; `finally` always restores original config.
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- **No direct `openai` import**: Detection via `getattr(exc, "status_code")`
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works with any OpenAI-compatible client (OpenRouter, xAI, Ollama, etc.).
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## Consequences
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- 404 policy errors no longer print 100-line tracebacks in logs
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- Operators can add fallback models in `.env` without code changes
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- New config keys documented in `CLAUDE.md` and `.env.example`
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|
|
@ -57,7 +57,17 @@ def run_tool_loop(
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result = None
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for _ in range(max_rounds):
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result: AIMessage = chain.invoke(current_messages)
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try:
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result: AIMessage = chain.invoke(current_messages)
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except Exception as exc:
|
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if getattr(exc, "status_code", None) == 404:
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raise RuntimeError(
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f"LLM returned 404 — model may be blocked by provider policy.\n"
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f"Original: {exc}\n"
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f"If using OpenRouter: https://openrouter.ai/settings/privacy\n"
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f"Or set TRADINGAGENTS_QUICK/MID/DEEP_THINK_FALLBACK_LLM."
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) from exc
|
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raise
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current_messages.append(result)
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||||
|
||||
if not result.tool_calls:
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||||
|
|
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@ -70,6 +70,23 @@ DEFAULT_CONFIG = {
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|||
"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
|
||||
# Per-tier fallback LLM — used automatically when primary model returns 404
|
||||
# (e.g. blocked by provider policy). Leave unset to disable auto-retry.
|
||||
# Each tier falls back independently; set only the tiers you need.
|
||||
#
|
||||
# Example .env:
|
||||
# TRADINGAGENTS_QUICK_THINK_FALLBACK_LLM=gpt-5-mini
|
||||
# TRADINGAGENTS_QUICK_THINK_FALLBACK_LLM_PROVIDER=openai
|
||||
# TRADINGAGENTS_MID_THINK_FALLBACK_LLM=gpt-5-mini
|
||||
# TRADINGAGENTS_MID_THINK_FALLBACK_LLM_PROVIDER=openai
|
||||
# TRADINGAGENTS_DEEP_THINK_FALLBACK_LLM=gpt-5.2
|
||||
# TRADINGAGENTS_DEEP_THINK_FALLBACK_LLM_PROVIDER=openai
|
||||
"quick_think_fallback_llm": _env("QUICK_THINK_FALLBACK_LLM"),
|
||||
"quick_think_fallback_llm_provider": _env("QUICK_THINK_FALLBACK_LLM_PROVIDER"),
|
||||
"mid_think_fallback_llm": _env("MID_THINK_FALLBACK_LLM"),
|
||||
"mid_think_fallback_llm_provider": _env("MID_THINK_FALLBACK_LLM_PROVIDER"),
|
||||
"deep_think_fallback_llm": _env("DEEP_THINK_FALLBACK_LLM"),
|
||||
"deep_think_fallback_llm_provider": _env("DEEP_THINK_FALLBACK_LLM_PROVIDER"),
|
||||
# Provider-specific thinking configuration (applies to all roles unless overridden)
|
||||
"google_thinking_level": _env("GOOGLE_THINKING_LEVEL"), # "high", "minimal", etc.
|
||||
"openai_reasoning_effort": _env("OPENAI_REASONING_EFFORT"), # "medium", "high", "low"
|
||||
|
|
|
|||
Loading…
Reference in New Issue