Compare commits
2 Commits
| Author | SHA1 | Date | |
|---|---|---|---|
| 10d7cd7d0c | |||
| 28c285a8b6 |
@@ -1,41 +0,0 @@
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"""
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Tests for cost estimator tool (#745).
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"""
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import pytest
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from tools.cost_estimator import estimate_cost, get_pricing, CostEstimate, PRICING
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class TestCostEstimator:
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def test_estimate_cost_basic(self):
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result = estimate_cost(1000, 500, "openrouter", "claude-sonnet-4")
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assert result.input_tokens == 1000
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assert result.output_tokens == 500
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assert result.total_cost_usd > 0
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def test_local_is_free(self):
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result = estimate_cost(1000000, 1000000, "local", "llama-3")
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assert result.total_cost_usd == 0.0
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def test_get_pricing_openrouter(self):
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pricing = get_pricing("openrouter", "claude-opus-4")
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assert pricing["input"] == 15.0
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assert pricing["output"] == 75.0
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def test_get_pricing_unknown_model(self):
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pricing = get_pricing("openrouter", "unknown-model")
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assert pricing == PRICING["openrouter"]["default"]
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def test_get_pricing_unknown_provider(self):
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pricing = get_pricing("unknown-provider", "model")
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assert pricing == PRICING["openrouter"]["default"]
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def test_cost_estimate_dataclass(self):
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result = estimate_cost(1000, 500, "nous", "hermes-3-405b")
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assert isinstance(result, CostEstimate)
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assert result.provider == "nous"
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assert result.model == "hermes-3-405b"
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if __name__ == "__main__":
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pytest.main([__file__])
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55
tests/test_error_classifier.py
Normal file
55
tests/test_error_classifier.py
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@@ -0,0 +1,55 @@
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"""
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Tests for error classification (#752).
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"""
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import pytest
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from tools.error_classifier import classify_error, ErrorCategory, ErrorClassification
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class TestErrorClassification:
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def test_timeout_is_retryable(self):
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err = Exception("Connection timed out")
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result = classify_error(err)
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assert result.category == ErrorCategory.RETRYABLE
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assert result.should_retry is True
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def test_429_is_retryable(self):
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err = Exception("Rate limit exceeded")
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result = classify_error(err, response_code=429)
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assert result.category == ErrorCategory.RETRYABLE
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assert result.should_retry is True
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def test_404_is_permanent(self):
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err = Exception("Not found")
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result = classify_error(err, response_code=404)
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assert result.category == ErrorCategory.PERMANENT
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assert result.should_retry is False
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def test_403_is_permanent(self):
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err = Exception("Forbidden")
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result = classify_error(err, response_code=403)
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assert result.category == ErrorCategory.PERMANENT
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assert result.should_retry is False
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def test_500_is_retryable(self):
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err = Exception("Internal server error")
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result = classify_error(err, response_code=500)
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assert result.category == ErrorCategory.RETRYABLE
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assert result.should_retry is True
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def test_schema_error_is_permanent(self):
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err = Exception("Schema validation failed")
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result = classify_error(err)
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assert result.category == ErrorCategory.PERMANENT
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assert result.should_retry is False
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def test_unknown_is_retryable_with_caution(self):
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err = Exception("Some unknown error")
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result = classify_error(err)
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assert result.category == ErrorCategory.UNKNOWN
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assert result.should_retry is True
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assert result.max_retries == 1
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if __name__ == "__main__":
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pytest.main([__file__])
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@@ -1,192 +0,0 @@
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"""
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Provider Cost Estimator — Estimate API costs from token counts.
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Provides cost estimation for different LLM providers based on
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token counts and provider pricing.
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"""
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from typing import Dict, Optional, Tuple
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from dataclasses import dataclass
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@dataclass
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class CostEstimate:
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"""Cost estimate for a request."""
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input_tokens: int
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output_tokens: int
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input_cost_usd: float
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output_cost_usd: float
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total_cost_usd: float
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provider: str
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model: str
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# Pricing table (USD per 1M tokens) — as of April 2026
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PRICING = {
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"openrouter": {
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"claude-opus-4": {"input": 15.0, "output": 75.0},
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"claude-sonnet-4": {"input": 3.0, "output": 15.0},
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"claude-haiku-3.5": {"input": 0.80, "output": 4.0},
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"gpt-4o": {"input": 2.50, "output": 10.0},
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"gpt-4o-mini": {"input": 0.15, "output": 0.60},
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"gemini-2.5-pro": {"input": 1.25, "output": 10.0},
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"gemini-2.5-flash": {"input": 0.15, "output": 0.60},
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"llama-4-scout": {"input": 0.20, "output": 0.80},
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"llama-4-maverick": {"input": 0.50, "output": 2.0},
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"default": {"input": 1.0, "output": 3.0},
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},
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"nous": {
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"hermes-3-405b": {"input": 5.0, "output": 5.0},
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"mixtral-8x22b": {"input": 2.0, "output": 2.0},
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"hermes-2-mixtral-8x7b": {"input": 0.90, "output": 0.90},
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"default": {"input": 2.0, "output": 2.0},
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},
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"anthropic": {
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"claude-opus-4": {"input": 15.0, "output": 75.0},
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"claude-sonnet-4": {"input": 3.0, "output": 15.0},
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"claude-haiku-3.5": {"input": 0.80, "output": 4.0},
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"default": {"input": 3.0, "output": 15.0},
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},
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"local": {
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# Local models are free (electricity only)
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"default": {"input": 0.0, "output": 0.0},
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},
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}
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def get_pricing(provider: str, model: str) -> Dict[str, float]:
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"""
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Get pricing for a provider/model combination.
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Args:
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provider: Provider name (openrouter, nous, anthropic, local)
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model: Model name
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Returns:
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Dict with 'input' and 'output' prices per 1M tokens
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"""
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provider = provider.lower().strip()
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model = model.lower().strip()
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provider_pricing = PRICING.get(provider, PRICING["openrouter"])
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# Try exact match first
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if model in provider_pricing:
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return provider_pricing[model]
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# Try partial match
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for key in provider_pricing:
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if key in model or model in key:
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return provider_pricing[key]
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# Default
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return provider_pricing.get("default", {"input": 1.0, "output": 3.0})
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def estimate_cost(
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input_tokens: int,
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output_tokens: int,
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provider: str = "openrouter",
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model: str = "default"
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) -> CostEstimate:
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"""
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Estimate cost for a request.
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Args:
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input_tokens: Number of input tokens
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output_tokens: Number of output tokens
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provider: Provider name
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model: Model name
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Returns:
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CostEstimate with breakdown
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"""
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pricing = get_pricing(provider, model)
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# Calculate costs (pricing is per 1M tokens)
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input_cost = (input_tokens / 1_000_000) * pricing["input"]
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output_cost = (output_tokens / 1_000_000) * pricing["output"]
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total_cost = input_cost + output_cost
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return CostEstimate(
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input_tokens=input_tokens,
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output_tokens=output_tokens,
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input_cost_usd=input_cost,
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output_cost_usd=output_cost,
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total_cost_usd=total_cost,
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provider=provider,
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model=model,
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)
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def estimate_session_cost(messages: list, provider: str = "openrouter", model: str = "default") -> CostEstimate:
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"""
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Estimate cost for a session based on message count.
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Args:
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messages: List of messages (each with 'role' and 'content')
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provider: Provider name
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model: Model name
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Returns:
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CostEstimate for the session
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"""
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# Rough token estimation: ~4 chars per token
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input_tokens = 0
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output_tokens = 0
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for msg in messages:
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content = msg.get("content", "")
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if isinstance(content, str):
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tokens = len(content) // 4
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if msg.get("role") == "user":
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input_tokens += tokens
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elif msg.get("role") == "assistant":
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output_tokens += tokens
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return estimate_cost(input_tokens, output_tokens, provider, model)
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def format_cost_report(estimates: list) -> str:
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"""
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Format a list of cost estimates as a report.
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Args:
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estimates: List of CostEstimate objects
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Returns:
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Formatted report string
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"""
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total_cost = sum(e.total_cost_usd for e in estimates)
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total_input = sum(e.input_tokens for e in estimates)
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total_output = sum(e.output_tokens for e in estimates)
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lines = [
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"# Cost Report",
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"",
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f"**Total Cost:** ${total_cost:.4f}",
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f"**Total Tokens:** {total_input + total_output:,} (input: {total_input:,}, output: {total_output:,})",
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"",
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"| Provider | Model | Input Tokens | Output Tokens | Cost |",
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"|----------|-------|--------------|---------------|------|",
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]
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for e in estimates:
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lines.append(f"| {e.provider} | {e.model} | {e.input_tokens:,} | {e.output_tokens:,} | ${e.total_cost_usd:.4f} |")
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lines.append("")
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lines.append(f"*Generated by cost_estimator.py*")
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return "\n".join(lines)
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def get_supported_providers() -> list:
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"""Get list of supported providers."""
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return list(PRICING.keys())
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def get_provider_models(provider: str) -> list:
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"""Get list of models for a provider."""
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provider = provider.lower().strip()
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provider_pricing = PRICING.get(provider, {})
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return [k for k in provider_pricing.keys() if k != "default"]
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233
tools/error_classifier.py
Normal file
233
tools/error_classifier.py
Normal file
@@ -0,0 +1,233 @@
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"""
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Tool Error Classification — Retryable vs Permanent.
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Classifies tool errors so the agent retries transient errors
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but gives up on permanent ones immediately.
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"""
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import logging
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import re
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import time
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from dataclasses import dataclass
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from enum import Enum
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from typing import Optional, Dict, Any
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logger = logging.getLogger(__name__)
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class ErrorCategory(Enum):
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"""Error category classification."""
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RETRYABLE = "retryable"
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PERMANENT = "permanent"
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UNKNOWN = "unknown"
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@dataclass
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class ErrorClassification:
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"""Result of error classification."""
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category: ErrorCategory
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reason: str
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should_retry: bool
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max_retries: int
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backoff_seconds: float
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error_code: Optional[int] = None
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error_type: Optional[str] = None
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# Retryable error patterns
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_RETRYABLE_PATTERNS = [
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# HTTP status codes
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(r"\b429\b", "rate limit", 3, 5.0),
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(r"\b500\b", "server error", 3, 2.0),
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(r"\b502\b", "bad gateway", 3, 2.0),
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(r"\b503\b", "service unavailable", 3, 5.0),
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(r"\b504\b", "gateway timeout", 3, 5.0),
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# Timeout patterns
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(r"timeout", "timeout", 3, 2.0),
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(r"timed out", "timeout", 3, 2.0),
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(r"TimeoutExpired", "timeout", 3, 2.0),
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# Connection errors
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(r"connection refused", "connection refused", 2, 5.0),
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(r"connection reset", "connection reset", 2, 2.0),
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(r"network unreachable", "network unreachable", 2, 10.0),
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(r"DNS", "DNS error", 2, 5.0),
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# Transient errors
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(r"temporary", "temporary error", 2, 2.0),
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(r"transient", "transient error", 2, 2.0),
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(r"retry", "retryable", 2, 2.0),
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]
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# Permanent error patterns
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_PERMANENT_PATTERNS = [
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# HTTP status codes
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(r"\b400\b", "bad request", "Invalid request parameters"),
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(r"\b401\b", "unauthorized", "Authentication failed"),
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(r"\b403\b", "forbidden", "Access denied"),
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(r"\b404\b", "not found", "Resource not found"),
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(r"\b405\b", "method not allowed", "HTTP method not supported"),
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(r"\b409\b", "conflict", "Resource conflict"),
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(r"\b422\b", "unprocessable", "Validation error"),
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# Schema/validation errors
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(r"schema", "schema error", "Invalid data schema"),
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(r"validation", "validation error", "Input validation failed"),
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(r"invalid.*json", "JSON error", "Invalid JSON"),
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(r"JSONDecodeError", "JSON error", "JSON parsing failed"),
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# Authentication
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(r"api.?key", "API key error", "Invalid or missing API key"),
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(r"token.*expir", "token expired", "Authentication token expired"),
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(r"permission", "permission error", "Insufficient permissions"),
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||||||
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||||||
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# Not found patterns
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(r"not found", "not found", "Resource does not exist"),
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(r"does not exist", "not found", "Resource does not exist"),
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||||||
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(r"no such file", "file not found", "File does not exist"),
|
||||||
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||||||
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# Quota/billing
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||||||
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(r"quota", "quota exceeded", "Usage quota exceeded"),
|
||||||
|
(r"billing", "billing error", "Billing issue"),
|
||||||
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(r"insufficient.*funds", "billing error", "Insufficient funds"),
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||||||
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]
|
||||||
|
|
||||||
|
|
||||||
|
def classify_error(error: Exception, response_code: Optional[int] = None) -> ErrorClassification:
|
||||||
|
"""
|
||||||
|
Classify an error as retryable or permanent.
|
||||||
|
|
||||||
|
Args:
|
||||||
|
error: The exception that occurred
|
||||||
|
response_code: HTTP response code if available
|
||||||
|
|
||||||
|
Returns:
|
||||||
|
ErrorClassification with retry guidance
|
||||||
|
"""
|
||||||
|
error_str = str(error).lower()
|
||||||
|
error_type = type(error).__name__
|
||||||
|
|
||||||
|
# Check response code first
|
||||||
|
if response_code:
|
||||||
|
if response_code in (429, 500, 502, 503, 504):
|
||||||
|
return ErrorClassification(
|
||||||
|
category=ErrorCategory.RETRYABLE,
|
||||||
|
reason=f"HTTP {response_code} - transient server error",
|
||||||
|
should_retry=True,
|
||||||
|
max_retries=3,
|
||||||
|
backoff_seconds=5.0 if response_code == 429 else 2.0,
|
||||||
|
error_code=response_code,
|
||||||
|
error_type=error_type,
|
||||||
|
)
|
||||||
|
elif response_code in (400, 401, 403, 404, 405, 409, 422):
|
||||||
|
return ErrorClassification(
|
||||||
|
category=ErrorCategory.PERMANENT,
|
||||||
|
reason=f"HTTP {response_code} - client error",
|
||||||
|
should_retry=False,
|
||||||
|
max_retries=0,
|
||||||
|
backoff_seconds=0,
|
||||||
|
error_code=response_code,
|
||||||
|
error_type=error_type,
|
||||||
|
)
|
||||||
|
|
||||||
|
# Check retryable patterns
|
||||||
|
for pattern, reason, max_retries, backoff in _RETRYABLE_PATTERNS:
|
||||||
|
if re.search(pattern, error_str, re.IGNORECASE):
|
||||||
|
return ErrorClassification(
|
||||||
|
category=ErrorCategory.RETRYABLE,
|
||||||
|
reason=reason,
|
||||||
|
should_retry=True,
|
||||||
|
max_retries=max_retries,
|
||||||
|
backoff_seconds=backoff,
|
||||||
|
error_type=error_type,
|
||||||
|
)
|
||||||
|
|
||||||
|
# Check permanent patterns
|
||||||
|
for pattern, error_code, reason in _PERMANENT_PATTERNS:
|
||||||
|
if re.search(pattern, error_str, re.IGNORECASE):
|
||||||
|
return ErrorClassification(
|
||||||
|
category=ErrorCategory.PERMANENT,
|
||||||
|
reason=reason,
|
||||||
|
should_retry=False,
|
||||||
|
max_retries=0,
|
||||||
|
backoff_seconds=0,
|
||||||
|
error_type=error_type,
|
||||||
|
)
|
||||||
|
|
||||||
|
# Default: unknown, treat as retryable with caution
|
||||||
|
return ErrorClassification(
|
||||||
|
category=ErrorCategory.UNKNOWN,
|
||||||
|
reason=f"Unknown error type: {error_type}",
|
||||||
|
should_retry=True,
|
||||||
|
max_retries=1,
|
||||||
|
backoff_seconds=1.0,
|
||||||
|
error_type=error_type,
|
||||||
|
)
|
||||||
|
|
||||||
|
|
||||||
|
def execute_with_retry(
|
||||||
|
func,
|
||||||
|
*args,
|
||||||
|
max_retries: int = 3,
|
||||||
|
backoff_base: float = 1.0,
|
||||||
|
**kwargs,
|
||||||
|
) -> Any:
|
||||||
|
"""
|
||||||
|
Execute a function with automatic retry on retryable errors.
|
||||||
|
|
||||||
|
Args:
|
||||||
|
func: Function to execute
|
||||||
|
*args: Function arguments
|
||||||
|
max_retries: Maximum retry attempts
|
||||||
|
backoff_base: Base backoff time in seconds
|
||||||
|
**kwargs: Function keyword arguments
|
||||||
|
|
||||||
|
Returns:
|
||||||
|
Function result
|
||||||
|
|
||||||
|
Raises:
|
||||||
|
Exception: If permanent error or max retries exceeded
|
||||||
|
"""
|
||||||
|
last_error = None
|
||||||
|
|
||||||
|
for attempt in range(max_retries + 1):
|
||||||
|
try:
|
||||||
|
return func(*args, **kwargs)
|
||||||
|
except Exception as e:
|
||||||
|
last_error = e
|
||||||
|
|
||||||
|
# Classify the error
|
||||||
|
classification = classify_error(e)
|
||||||
|
|
||||||
|
logger.info(
|
||||||
|
"Attempt %d/%d failed: %s (%s, retryable: %s)",
|
||||||
|
attempt + 1, max_retries + 1,
|
||||||
|
classification.reason,
|
||||||
|
classification.category.value,
|
||||||
|
classification.should_retry,
|
||||||
|
)
|
||||||
|
|
||||||
|
# If permanent error, fail immediately
|
||||||
|
if not classification.should_retry:
|
||||||
|
logger.error("Permanent error: %s", classification.reason)
|
||||||
|
raise
|
||||||
|
|
||||||
|
# If this was the last attempt, raise
|
||||||
|
if attempt >= max_retries:
|
||||||
|
logger.error("Max retries (%d) exceeded", max_retries)
|
||||||
|
raise
|
||||||
|
|
||||||
|
# Calculate backoff with exponential increase
|
||||||
|
backoff = backoff_base * (2 ** attempt)
|
||||||
|
logger.info("Retrying in %.1fs...", backoff)
|
||||||
|
time.sleep(backoff)
|
||||||
|
|
||||||
|
# Should not reach here, but just in case
|
||||||
|
raise last_error
|
||||||
|
|
||||||
|
|
||||||
|
def format_error_report(classification: ErrorClassification) -> str:
|
||||||
|
"""Format error classification as a report string."""
|
||||||
|
icon = "🔄" if classification.should_retry else "❌"
|
||||||
|
return f"{icon} {classification.category.value}: {classification.reason}"
|
||||||
Reference in New Issue
Block a user