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https://github.com/Routstr/routstr-core.git
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3
Commits
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e39742c429 | ||
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301dd81215 | ||
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5416cefd87 |
@@ -5,6 +5,7 @@ from pydantic.v1 import BaseModel
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from ..core import get_logger
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from ..core.db import AsyncSession
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from ..core.settings import settings
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from .price import sats_usd_price
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logger = get_logger(__name__)
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@@ -64,13 +65,62 @@ async def calculate_cost( # todo: can be sync
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)
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return cost_data
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usage_data = response_data["usage"]
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usd_cost = 0.0
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# Prioritize cost_details.upstream_inference_cost
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if "cost_details" in usage_data:
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usd_cost = float(
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usage_data["cost_details"].get("upstream_inference_cost", 0) or 0
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)
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# Fallback to cost field if upstream_inference_cost is 0
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if usd_cost == 0 and "cost" in usage_data:
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try:
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usd_cost = float(usage_data.get("cost", 0) or 0)
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except Exception:
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pass
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if usd_cost > 0:
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try:
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sats_per_usd = 1.0 / sats_usd_price()
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cost_in_sats = usd_cost * sats_per_usd
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cost_in_msats = math.ceil(cost_in_sats * 1000)
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logger.info(
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"Using cost from usage data/details",
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extra={
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"usd_cost": usd_cost,
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"cost_in_sats": cost_in_sats,
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"cost_in_msats": cost_in_msats,
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"model": response_data.get("model", "unknown"),
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},
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)
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return CostData(
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base_msats=-1,
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input_msats=-1, # Cost field doesn't break down by token type
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output_msats=-1,
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total_msats=cost_in_msats,
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)
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except Exception as e:
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logger.warning(
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"Error calculating cost from usage data",
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extra={
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"error": str(e),
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"usd_cost": usd_cost,
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"model": response_data.get("model", "unknown"),
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},
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)
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# Fall through to token-based calculation
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MSATS_PER_1K_INPUT_TOKENS: float = (
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float(settings.fixed_per_1k_input_tokens) * 1000.0
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)
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MSATS_PER_1K_OUTPUT_TOKENS: float = (
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float(settings.fixed_per_1k_output_tokens) * 1000.0
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)
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MSATS_PER_1K_IMAGE_COMPLETION_TOKENS: float = 0.0
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if not settings.fixed_pricing:
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response_model = response_data.get("model", "")
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@@ -105,13 +155,11 @@ async def calculate_cost( # todo: can be sync
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try:
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mspp = float(model_obj.sats_pricing.prompt)
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mspc = float(model_obj.sats_pricing.completion)
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mspci = float(getattr(model_obj.sats_pricing, "completion_image", 0.0))
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except Exception:
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return CostDataError(message="Invalid pricing data", code="pricing_invalid")
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MSATS_PER_1K_INPUT_TOKENS = mspp * 1_000_000.0
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MSATS_PER_1K_OUTPUT_TOKENS = mspc * 1_000_000.0
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MSATS_PER_1K_IMAGE_COMPLETION_TOKENS = mspci * 1_000_000.0
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logger.info(
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"Applied model-specific pricing",
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@@ -119,7 +167,6 @@ async def calculate_cost( # todo: can be sync
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"model": response_model,
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"input_price_msats_per_1k": MSATS_PER_1K_INPUT_TOKENS,
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"output_price_msats_per_1k": MSATS_PER_1K_OUTPUT_TOKENS,
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"image_completion_price_msats_per_1k": MSATS_PER_1K_IMAGE_COMPLETION_TOKENS,
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},
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)
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@@ -132,7 +179,7 @@ async def calculate_cost( # todo: can be sync
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},
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)
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return cost_data
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usage_data = response_data["usage"]
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input_tokens = usage_data.get("prompt_tokens", 0)
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output_tokens = usage_data.get("completion_tokens", 0)
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@@ -144,32 +191,10 @@ async def calculate_cost( # todo: can be sync
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output_tokens if output_tokens != 0 else usage_data.get("output_tokens", 0)
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)
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# Calculate image completion cost
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image_completion_msats = 0.0
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if MSATS_PER_1K_IMAGE_COMPLETION_TOKENS > 0:
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completion_details = usage_data.get("completion_tokens_details", {})
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image_tokens = completion_details.get("image_tokens", 0)
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if image_tokens > 0:
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if output_tokens >= image_tokens:
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output_tokens -= image_tokens
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image_completion_msats = round(
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image_tokens / 1000 * MSATS_PER_1K_IMAGE_COMPLETION_TOKENS, 3
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)
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logger.info(
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"Calculated image completion cost",
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extra={
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"image_tokens": image_tokens,
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"image_completion_msats": image_completion_msats,
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},
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)
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input_msats = round(input_tokens / 1000 * MSATS_PER_1K_INPUT_TOKENS, 3)
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output_msats = round(output_tokens / 1000 * MSATS_PER_1K_OUTPUT_TOKENS, 3)
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token_based_cost = math.ceil(input_msats + output_msats + image_completion_msats)
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token_based_cost = math.ceil(input_msats + output_msats)
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logger.info(
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"Calculated token-based cost",
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@@ -178,7 +203,6 @@ async def calculate_cost( # todo: can be sync
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"output_tokens": output_tokens,
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"input_cost_msats": input_msats,
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"output_cost_msats": output_msats,
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"image_completion_msats": image_completion_msats,
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"total_cost_msats": token_based_cost,
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"model": response_data.get("model", "unknown"),
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},
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@@ -31,7 +31,6 @@ class Pricing(BaseModel):
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completion: float
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request: float = 0.0
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image: float = 0.0
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completion_image: float = 0.0
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web_search: float = 0.0
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internal_reasoning: float = 0.0
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input_cache_read: float = 0.0
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@@ -41,13 +40,6 @@ class Pricing(BaseModel):
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max_cost: float = 0.0 # in sats not msats
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PRICING_OVERRIDES = {
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"gemini-3-pro-image-preview": {"completion_image": 0.00012},
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"gemini-2.5-flash-image": {"completion_image": 0.00003},
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"gemini-2.0-flash": {"completion_image": 0.00003},
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}
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class TopProvider(BaseModel):
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context_length: int | None = None
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max_completion_tokens: int | None = None
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@@ -124,16 +116,6 @@ async def async_fetch_openrouter_models(source_filter: str | None = None) -> lis
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if not _has_valid_pricing(model):
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continue
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# Apply manual pricing overrides
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if model_id in PRICING_OVERRIDES:
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pricing = model.get("pricing", {})
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if pricing:
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for k, v in PRICING_OVERRIDES[model_id].items():
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pricing[k] = str(
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v
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) # OpenRouter API returns strings for pricing
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model["pricing"] = pricing
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models_data.append(model)
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return models_data
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@@ -166,12 +148,6 @@ def _row_to_model(
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if isinstance(pricing, dict) and float(pricing.get("request", 0.0)) <= 0.0:
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pricing["request"] = max(pricing.get("request", 0.0), 0.0)
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# Apply defaults for missing fields from manual overrides
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if row.id in PRICING_OVERRIDES and isinstance(pricing, dict):
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for k, v in PRICING_OVERRIDES[row.id].items():
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if k not in pricing:
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pricing[k] = v
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parsed_pricing = Pricing.parse_obj(pricing)
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model = Model(
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id=row.id,
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@@ -531,7 +507,6 @@ def _pricing_matches(
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"completion",
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"request",
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"image",
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"completion_image",
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"web_search",
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"internal_reasoning",
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]
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