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https://github.com/MODSetter/SurfSense.git
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chore: ran linting
This commit is contained in:
Anish Sarkar
parent
b9b4d0b377
commit
cd25175b84
14 changed files with 78 additions and 82 deletions
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@ -286,9 +286,7 @@ def initialize_openrouter_integration():
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if new_configs:
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config.GLOBAL_LLM_CONFIGS.extend(new_configs)
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free_count = sum(
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1 for c in new_configs if c.get("billing_tier") == "free"
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)
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free_count = sum(1 for c in new_configs if c.get("billing_tier") == "free")
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premium_count = sum(
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1 for c in new_configs if c.get("billing_tier") == "premium"
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)
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@ -277,9 +277,7 @@ async def resolve_or_get_pinned_llm_config_id(
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c for c in _global_candidates() if int(c.get("id", 0)) not in excluded_ids
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]
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if not candidates:
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raise ValueError(
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"No usable global LLM configs are available for Auto mode"
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)
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raise ValueError("No usable global LLM configs are available for Auto mode")
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candidate_by_id = {int(c["id"]): c for c in candidates}
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# Reuse an existing valid pin without re-checking current quota (no silent
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@ -405,9 +405,7 @@ class OpenRouterIntegrationService:
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# Re-blend health scores against the freshly fetched catalogue. Also
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# re-stamps health for any YAML-curated cfg with provider==OPENROUTER
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# so a hand-picked dead OR model is gated like a dynamic one.
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await self._enrich_health_safely(
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static_configs + new_configs, log_summary=True
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)
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await self._enrich_health_safely(static_configs + new_configs, log_summary=True)
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# Rebuild the LiteLLM router so freshly fetched configs flow through
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# (dynamic OR premium entries now opt into the pool, free ones stay
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@ -415,8 +413,8 @@ class OpenRouterIntegrationService:
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# reset cached context-window profiles).
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try:
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from app.config import config as _app_config
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from app.services.llm_router_service import LLMRouterService
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from app.services.llm_router_service import (
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LLMRouterService,
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_router_instance_cache as _chat_router_cache,
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)
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@ -426,9 +424,7 @@ class OpenRouterIntegrationService:
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)
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_chat_router_cache.clear()
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except Exception as exc:
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logger.warning(
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"OpenRouter refresh: router rebuild skipped (%s)", exc
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)
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logger.warning("OpenRouter refresh: router rebuild skipped (%s)", exc)
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@staticmethod
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def _tier_counts(configs: list[dict]) -> dict[str, int]:
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@ -475,19 +471,11 @@ class OpenRouterIntegrationService:
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return
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premium_pool = sorted(
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[
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c
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for c in or_cfgs
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if str(c.get("billing_tier", "")).lower() == "premium"
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],
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[c for c in or_cfgs if str(c.get("billing_tier", "")).lower() == "premium"],
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key=lambda c: -int(c.get("quality_score_static") or 0),
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)[:_HEALTH_ENRICH_TOP_N_PREMIUM]
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free_pool = sorted(
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[
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c
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for c in or_cfgs
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if str(c.get("billing_tier", "")).lower() == "free"
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],
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[c for c in or_cfgs if str(c.get("billing_tier", "")).lower() == "free"],
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key=lambda c: -int(c.get("quality_score_static") or 0),
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)[:_HEALTH_ENRICH_TOP_N_FREE]
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# De-duplicate while preserving order: a cfg shouldn't fall in both
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@ -507,9 +495,7 @@ class OpenRouterIntegrationService:
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api_key = str(self._settings.get("api_key") or "")
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semaphore = asyncio.Semaphore(_HEALTH_ENRICH_CONCURRENCY)
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async with httpx.AsyncClient(
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timeout=_HEALTH_FETCH_TIMEOUT_SEC
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) as client:
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async with httpx.AsyncClient(timeout=_HEALTH_FETCH_TIMEOUT_SEC) as client:
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results = await asyncio.gather(
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*(
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self._fetch_endpoints(client, semaphore, api_key, cfg)
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@ -7,12 +7,12 @@ sort and a SHA256 pick.
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Score components (0-100 scale, higher is better):
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* ``static_score_or`` – derived from the bulk ``/api/v1/models`` payload
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* ``static_score_or`` - derived from the bulk ``/api/v1/models`` payload
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(provider prestige + ``created`` recency + pricing band + context window
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+ capabilities + narrow tiny/legacy slug penalty).
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* ``static_score_yaml`` – same shape for hand-curated YAML configs, plus
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* ``static_score_yaml`` - same shape for hand-curated YAML configs, plus
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an operator-trust bonus (the operator deliberately picked this model).
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* ``aggregate_health`` – run on per-model ``/api/v1/models/{id}/endpoints``
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* ``aggregate_health`` - run on per-model ``/api/v1/models/{id}/endpoints``
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responses; returns ``(gated, score_or_none)``.
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The blended ``quality_score`` (0.5 * static + 0.5 * health) is computed in
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@ -281,9 +281,7 @@ def static_score_yaml(cfg: dict) -> int:
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model_name = cfg.get("model_name") or ""
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litellm_params = cfg.get("litellm_params") or {}
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lookup_name = (
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litellm_params.get("base_model")
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or litellm_params.get("model")
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or model_name
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litellm_params.get("base_model") or litellm_params.get("model") or model_name
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)
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ctx = 0
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@ -1814,7 +1814,9 @@ async def _stream_agent_events(
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resolved_path = _extract_resolved_file_path(
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tool_name=tool_name,
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tool_output=tool_output,
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tool_input={"file_path": staged_file_path} if staged_file_path else None,
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tool_input={"file_path": staged_file_path}
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if staged_file_path
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else None,
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)
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result_text = _tool_output_to_text(tool_output)
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if _tool_output_has_error(tool_output):
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@ -2441,8 +2443,7 @@ async def stream_new_chat(
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await _preflight_llm(llm)
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mark_healthy(llm_config_id)
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_perf_log.info(
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"[stream_new_chat] auto_pin_preflight ok config_id=%s "
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"took=%.3fs",
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"[stream_new_chat] auto_pin_preflight ok config_id=%s took=%.3fs",
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llm_config_id,
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time.perf_counter() - _t_preflight,
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)
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@ -2891,7 +2892,11 @@ async def stream_new_chat(
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# Inject title update mid-stream as soon as the background
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# task finishes.
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if title_task is not None and title_task.done() and not title_emitted:
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if (
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title_task is not None
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and title_task.done()
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and not title_emitted
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):
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generated_title, title_usage = title_task.result()
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if title_usage:
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accumulator.add(**title_usage)
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@ -2944,7 +2949,9 @@ async def stream_new_chat(
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)
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).resolved_llm_config_id
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llm, agent_config, llm_load_error = await _load_llm_bundle(llm_config_id)
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llm, agent_config, llm_load_error = await _load_llm_bundle(
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llm_config_id
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)
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if llm_load_error:
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raise stream_exc
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@ -3480,8 +3487,7 @@ async def stream_resume_chat(
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await _preflight_llm(llm)
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mark_healthy(llm_config_id)
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_perf_log.info(
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"[stream_resume] auto_pin_preflight ok config_id=%s "
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"took=%.3fs",
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"[stream_resume] auto_pin_preflight ok config_id=%s took=%.3fs",
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llm_config_id,
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time.perf_counter() - _t_preflight,
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)
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@ -3684,7 +3690,9 @@ async def stream_resume_chat(
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)
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).resolved_llm_config_id
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llm, agent_config, llm_load_error = await _load_llm_bundle(llm_config_id)
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llm, agent_config, llm_load_error = await _load_llm_bundle(
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llm_config_id
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)
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if llm_load_error:
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raise stream_exc
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