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style: apply Black formatting to tickerr.py
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1 changed files with 25 additions and 23 deletions
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@ -32,29 +32,29 @@ _inflight = threading.Semaphore(_MAX_INFLIGHT)
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# Map litellm custom_llm_provider → Tickerr provider slug
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_PROVIDER_MAP: Dict[str, str] = {
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"openai": "openai",
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"anthropic": "anthropic",
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"google": "google",
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"vertex_ai": "google",
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"gemini": "google",
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"cohere": "cohere",
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"mistral": "mistral",
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"groq": "groq",
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"together_ai": "together",
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"huggingface": "huggingface",
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"replicate": "replicate",
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"deepinfra": "deepinfra",
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"perplexity": "perplexity",
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"openai": "openai",
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"anthropic": "anthropic",
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"google": "google",
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"vertex_ai": "google",
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"gemini": "google",
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"cohere": "cohere",
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"mistral": "mistral",
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"groq": "groq",
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"together_ai": "together",
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"huggingface": "huggingface",
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"replicate": "replicate",
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"deepinfra": "deepinfra",
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"perplexity": "perplexity",
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"fireworks_ai": "fireworks",
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"openrouter": "openrouter",
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"azure": "azure",
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"bedrock": "aws",
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"ai21": "ai21",
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"cerebras": "cerebras",
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"xai": "xai",
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"deepseek": "deepseek",
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"ollama": "ollama",
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"nlp_cloud": "nlp_cloud",
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"openrouter": "openrouter",
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"azure": "azure",
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"bedrock": "aws",
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"ai21": "ai21",
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"cerebras": "cerebras",
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"xai": "xai",
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"deepseek": "deepseek",
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"ollama": "ollama",
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"nlp_cloud": "nlp_cloud",
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}
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# Only map codes that unambiguously indicate the specific error type.
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@ -211,7 +211,9 @@ class TickerrLogger(CustomLogger):
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provider = _normalize_provider(model, kwargs)
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status_code = _extract_status_code(exception)
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# Only set error_type for codes we can classify with confidence
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error_type: Optional[str] = _ERROR_TYPE_MAP.get(status_code) if status_code is not None else None
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error_type: Optional[str] = (
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_ERROR_TYPE_MAP.get(status_code) if status_code is not None else None
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)
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# Strip provider prefix: "anthropic/claude-3-5-haiku" → "claude-3-5-haiku"
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model_clean = model.split("/", 1)[-1] if "/" in model else model
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