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Shroominic
2025-11-03 22:24:27 +08:00
parent 0c3beba74f
commit 1c7cbf64ef
2 changed files with 115 additions and 94 deletions
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routstr/algorithm.py
+70 -66
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@@ -13,72 +13,74 @@ logger = get_logger(__name__)
def calculate_model_cost_score(model: "Model") -> float:
"""Calculate a representative cost score for a model.
This score is used to compare models when multiple providers offer the same model.
Lower scores indicate cheaper models.
The score is calculated as a weighted average of:
- Input token cost (weighted by typical input usage)
- Output token cost (weighted by typical output usage)
- Fixed request cost
Args:
model: Model instance with pricing information
Returns:
Float representing the cost score. Lower is better.
"""
pricing = model.pricing
# Weight costs by typical usage patterns
# Assume average request: 1000 input tokens, 500 output tokens
TYPICAL_INPUT_TOKENS = 1000.0
TYPICAL_OUTPUT_TOKENS = 500.0
# Calculate weighted cost in USD
input_cost = pricing.prompt * (TYPICAL_INPUT_TOKENS / 1000.0)
output_cost = pricing.completion * (TYPICAL_OUTPUT_TOKENS / 1000.0)
request_cost = pricing.request
# Include additional costs if present
image_cost = getattr(pricing, "image", 0.0) * 0.1 # Weight lower as not every request uses images
image_cost = (
getattr(pricing, "image", 0.0) * 0.1
) # Weight lower as not every request uses images
web_search_cost = getattr(pricing, "web_search", 0.0) * 0.1
reasoning_cost = getattr(pricing, "internal_reasoning", 0.0) * 0.2
total_cost = (
input_cost +
output_cost +
request_cost +
image_cost +
web_search_cost +
reasoning_cost
input_cost
+ output_cost
+ request_cost
+ image_cost
+ web_search_cost
+ reasoning_cost
)
return total_cost
def get_provider_penalty(provider: "UpstreamProvider") -> float:
"""Calculate a penalty multiplier for certain providers.
This allows applying policy-based adjustments beyond pure cost.
For example, preferring certain providers for reliability or features.
Args:
provider: UpstreamProvider instance
Returns:
Float multiplier to apply to cost (1.0 = no penalty, >1.0 = penalize)
"""
# Default: no penalty
penalty = 1.0
# Check if this is OpenRouter (can be identified by base URL)
base_url = getattr(provider, "base_url", "")
if "openrouter.ai" in base_url.lower():
# Small penalty for OpenRouter to prefer other providers when costs are very close
# This maintains the original behavior of preferring non-OpenRouter providers
penalty = 1.001 # 0.1% penalty
return penalty
@@ -90,30 +92,30 @@ def should_prefer_model(
alias: str,
) -> bool:
"""Determine if candidate model should replace current model for an alias.
This is the core decision function for model prioritization. It considers:
1. Alias matching quality (exact match vs. canonical slug match)
2. Model cost (lower is better)
3. Provider penalties (e.g., slight preference against OpenRouter)
Args:
candidate_model: The new model being considered
candidate_provider: Provider offering the candidate model
current_model: The currently selected model for this alias
current_provider: Provider offering the current model
alias: The model alias being mapped
Returns:
True if candidate should replace current, False otherwise
"""
def get_base_model_id(model_id: str) -> str:
"""Get base model ID by removing provider prefix."""
return model_id.split("/", 1)[1] if "/" in model_id else model_id
def alias_priority(model: "Model") -> int:
"""Rank how strong the mapping of alias->model is.
Highest priority when alias exactly equals the model ID without provider prefix.
Next when alias equals canonical slug without prefix. Otherwise lowest.
"""
@@ -125,39 +127,41 @@ def should_prefer_model(
if canonical_base == alias:
return 2
return 1
candidate_alias_priority = alias_priority(candidate_model)
current_alias_priority = alias_priority(current_model)
# If candidate has better alias match, prefer it regardless of cost
if candidate_alias_priority > current_alias_priority:
return True
# If current has better alias match, keep it regardless of cost
if current_alias_priority > candidate_alias_priority:
return False
# Same alias priority - compare costs
candidate_cost = calculate_model_cost_score(candidate_model)
current_cost = calculate_model_cost_score(current_model)
# Apply provider penalties
candidate_adjusted = candidate_cost * get_provider_penalty(candidate_provider)
current_adjusted = current_cost * get_provider_penalty(current_provider)
# Prefer lower adjusted cost
should_replace = candidate_adjusted < current_adjusted
# Log provider changes when candidate wins
if should_replace:
candidate_provider_name = getattr(candidate_provider, "upstream_name", "unknown")
candidate_provider_name = getattr(
candidate_provider, "upstream_name", "unknown"
)
current_provider_name = getattr(current_provider, "upstream_name", "unknown")
logger.debug(
f"Model selection for alias '{alias}': choosing {candidate_provider_name} "
f"(cost: ${candidate_adjusted:.6f}) over {current_provider_name} "
f"(cost: ${current_adjusted:.6f})"
)
return should_replace
@@ -167,50 +171,52 @@ def create_model_mappings(
disabled_model_ids: set[str],
) -> tuple[dict[str, "Model"], dict[str, "UpstreamProvider"], dict[str, "Model"]]:
"""Create optimal model mappings based on cost and provider preferences.
This is the main entry point for the algorithm. It processes all upstream providers
and creates three mappings based on cost optimization:
1. model_instances: alias -> Model (all model aliases mapped to their Model objects)
2. provider_map: alias -> UpstreamProvider (which provider to use for each alias)
3. unique_models: base_id -> Model (unique models without provider prefixes)
The algorithm:
- Processes non-OpenRouter providers first (they're typically cheaper)
- Then processes OpenRouter models (they can still win if cheaper)
- For each model alias, uses should_prefer_model() to select the best provider
Args:
upstreams: List of all upstream provider instances
overrides_by_id: Dict of model overrides from database {model_id: (ModelRow, fee)}
disabled_model_ids: Set of model IDs that should be excluded
Returns:
Tuple of (model_instances, provider_map, unique_models)
"""
from .payment.models import _row_to_model
from .upstream import resolve_model_alias
model_instances: dict[str, "Model"] = {}
provider_map: dict[str, "UpstreamProvider"] = {}
unique_models: dict[str, "Model"] = {}
# Separate OpenRouter from other providers
openrouter: "UpstreamProvider" | None = None
other_upstreams: list["UpstreamProvider"] = []
for upstream in upstreams:
base_url = getattr(upstream, "base_url", "")
if base_url == "https://openrouter.ai/api/v1":
openrouter = upstream
else:
other_upstreams.append(upstream)
def get_base_model_id(model_id: str) -> str:
"""Get base model ID by removing provider prefix."""
return model_id.split("/", 1)[1] if "/" in model_id else model_id
def _maybe_set_alias(alias: str, model: "Model", provider: "UpstreamProvider") -> None:
def _maybe_set_alias(
alias: str, model: "Model", provider: "UpstreamProvider"
) -> None:
"""Set alias to model/provider if not set or if new model is preferred."""
existing_model = model_instances.get(alias)
if not existing_model:
@@ -220,21 +226,22 @@ def create_model_mappings(
else:
# Check if candidate should replace existing
existing_provider = provider_map[alias]
if should_prefer_model(model, provider, existing_model, existing_provider, alias):
if should_prefer_model(
model, provider, existing_model, existing_provider, alias
):
model_instances[alias] = model
provider_map[alias] = provider
def process_provider_models(
upstream: "UpstreamProvider",
is_openrouter: bool = False
upstream: "UpstreamProvider", is_openrouter: bool = False
) -> None:
"""Process all models from a given provider."""
upstream_prefix = getattr(upstream, "upstream_name", None)
for model in upstream.get_cached_models():
if not model.enabled or model.id in disabled_model_ids:
continue
# Apply overrides if present
if model.id in overrides_by_id:
override_row, provider_fee = overrides_by_id[model.id]
@@ -243,42 +250,40 @@ def create_model_mappings(
)
else:
model_to_use = model
# Add to unique models
base_id = get_base_model_id(model_to_use.id)
if not is_openrouter or base_id not in unique_models:
unique_model = model_to_use.copy(update={"id": base_id})
unique_models[base_id] = unique_model
# Get all aliases for this model
aliases = resolve_model_alias(
model_to_use.id, model_to_use.canonical_slug
)
aliases = resolve_model_alias(model_to_use.id, model_to_use.canonical_slug)
# Add prefixed alias if applicable
if upstream_prefix and "/" not in model_to_use.id:
prefixed_id = f"{upstream_prefix}/{model_to_use.id}"
if prefixed_id not in aliases:
aliases.append(prefixed_id)
# Try to set each alias
for alias in aliases:
_maybe_set_alias(alias, model_to_use, upstream)
# Process non-OpenRouter providers first (they're typically cheaper)
for upstream in other_upstreams:
process_provider_models(upstream, is_openrouter=False)
# Process OpenRouter last - models only win if they're cheaper or better matched
if openrouter:
process_provider_models(openrouter, is_openrouter=True)
# Log provider distribution
provider_counts: dict[str, int] = {}
for provider in provider_map.values():
provider_name = getattr(provider, "upstream_name", "unknown")
provider_counts[provider_name] = provider_counts.get(provider_name, 0) + 1
logger.debug(
"Created model mappings",
extra={
@@ -287,6 +292,5 @@ def create_model_mappings(
"provider_distribution": provider_counts,
},
)
return model_instances, provider_map, unique_models
return model_instances, provider_map, unique_models