Litellm clean litellm oss staging 04 01 2026

docs/my-website/docs/providers/crusoe.md

@@ -0,0 +1,196 @@
+import Tabs from '@theme/Tabs';
+import TabItem from '@theme/TabItem';
+
+# Crusoe
+
+## Overview
+
+| Property | Details |
+|-------|-------|
+| Description | Crusoe Cloud provides GPU-accelerated inference for open-source large language models, optimized for performance and cost efficiency. |
+| Provider Route on LiteLLM | `crusoe/` |
+| Link to Provider Doc | [Crusoe Managed Inference Documentation ↗](https://docs.crusoecloud.com/managed-inference/overview/index.html) |
+| Base URL | `https://managed-inference-api-proxy.crusoecloud.com/v1` |
+| Supported Operations | [`/chat/completions`](#sample-usage) |
+
+<br />
+<br />
+
+**We support ALL Crusoe models, just set `crusoe/` as a prefix when sending completion requests**
+
+## Available Models
+
+| Model | Description | Context Window |
+|-------|-------------|----------------|
+| `crusoe/deepseek-ai/DeepSeek-R1-0528` | DeepSeek R1 reasoning model (May 2025) | 163,840 tokens |
+| `crusoe/deepseek-ai/DeepSeek-V3-0324` | DeepSeek V3 chat model (March 2025) | 163,840 tokens |
+| `crusoe/google/gemma-3-12b-it` | Google Gemma 3 12B instruction-tuned | 131,072 tokens |
+| `crusoe/meta-llama/Llama-3.3-70B-Instruct` | Llama 3.3 70B instruction-tuned | 131,072 tokens |
+| `crusoe/moonshotai/Kimi-K2-Thinking` | Kimi K2 extended thinking model | 262,144 tokens |
+| `crusoe/openai/gpt-oss-120b` | OpenAI 120B open-source model | 131,072 tokens |
+| `crusoe/Qwen/Qwen3-235B-A22B-Instruct-2507` | Qwen3 235B MoE instruction-tuned | 262,144 tokens |
+
+## Required Variables
+
+```python showLineNumbers title="Environment Variables"
+os.environ["CRUSOE_API_KEY"] = ""  # your Crusoe API key
+```
+
+## Usage - LiteLLM Python SDK
+
+### Non-streaming
+
+```python showLineNumbers title="Crusoe Non-streaming Completion"
+import os
+import litellm
+from litellm import completion
+
+os.environ["CRUSOE_API_KEY"] = ""  # your Crusoe API key
+
+messages = [{"content": "Hello, how are you?", "role": "user"}]
+
+# Crusoe call
+response = completion(
+    model="crusoe/meta-llama/Llama-3.3-70B-Instruct",
+    messages=messages
+)
+
+print(response)
+```
+
+### Streaming
+
+```python showLineNumbers title="Crusoe Streaming Completion"
+import os
+import litellm
+from litellm import completion
+
+os.environ["CRUSOE_API_KEY"] = ""  # your Crusoe API key
+
+messages = [{"content": "Write a short story about AI", "role": "user"}]
+
+# Crusoe call with streaming
+response = completion(
+    model="crusoe/meta-llama/Llama-3.3-70B-Instruct",
+    messages=messages,
+    stream=True
+)
+
+for chunk in response:
+    print(chunk)
+```
+
+### Function Calling
+
+```python showLineNumbers title="Crusoe Function Calling"
+import os
+import litellm
+from litellm import completion
+
+os.environ["CRUSOE_API_KEY"] = ""  # your Crusoe API key
+
+tools = [{
+    "type": "function",
+    "function": {
+        "name": "get_weather",
+        "description": "Get the current weather in a location",
+        "parameters": {
+            "type": "object",
+            "properties": {
+                "location": {
+                    "type": "string",
+                    "description": "The city and state, e.g. San Francisco, CA"
+                }
+            },
+            "required": ["location"]
+        }
+    }
+}]
+
+messages = [{"role": "user", "content": "What's the weather in Boston?"}]
+
+response = completion(
+    model="crusoe/meta-llama/Llama-3.3-70B-Instruct",
+    messages=messages,
+    tools=tools,
+    tool_choice="auto"
+)
+
+print(response)
+```
+
+## Usage - LiteLLM Proxy Server
+
+```yaml showLineNumbers title="config.yaml"
+model_list:
+  - model_name: llama-3.3-70b
+    litellm_params:
+      model: crusoe/meta-llama/Llama-3.3-70B-Instruct
+      api_key: os.environ/CRUSOE_API_KEY
+  - model_name: deepseek-r1
+    litellm_params:
+      model: crusoe/deepseek-ai/DeepSeek-R1-0528
+      api_key: os.environ/CRUSOE_API_KEY
+  - model_name: deepseek-v3
+    litellm_params:
+      model: crusoe/deepseek-ai/DeepSeek-V3-0324
+      api_key: os.environ/CRUSOE_API_KEY
+  - model_name: qwen3-235b
+    litellm_params:
+      model: crusoe/Qwen/Qwen3-235B-A22B-Instruct-2507
+      api_key: os.environ/CRUSOE_API_KEY
+  - model_name: kimi-k2
+    litellm_params:
+      model: crusoe/moonshotai/Kimi-K2-Thinking
+      api_key: os.environ/CRUSOE_API_KEY
+```
+
+## Custom API Base
+
+**Option 1: Environment variable**
+
+```python showLineNumbers title="Custom API Base via env var"
+import os
+from litellm import completion
+
+os.environ["CRUSOE_API_BASE"] = "https://custom.crusoecloud.com/v1"
+os.environ["CRUSOE_API_KEY"] = ""  # your API key
+
+response = completion(
+    model="crusoe/meta-llama/Llama-3.3-70B-Instruct",
+    messages=[{"content": "Hello!", "role": "user"}],
+)
+```
+
+**Option 2: Pass directly**
+
+```python showLineNumbers title="Custom API Base via parameter"
+from litellm import completion
+
+response = completion(
+    model="crusoe/meta-llama/Llama-3.3-70B-Instruct",
+    messages=[{"content": "Hello!", "role": "user"}],
+    api_base="https://custom.crusoecloud.com/v1",
+    api_key="your-api-key",
+)
+```
+
+## Supported OpenAI Parameters
+
+- `temperature`
+- `max_tokens`
+- `max_completion_tokens`
+- `top_p`
+- `frequency_penalty`
+- `presence_penalty`
+- `stop`
+- `n`
+- `stream`
+- `tools`
+- `tool_choice`
+- `response_format`
+- `seed`
+- `user`
+- `logit_bias`
+- `logprobs`
+- `top_logprobs`

litellm/_logging.py

@@ -1,12 +1,12 @@
 import ast
 import logging
 import os
-import re
 import sys
 from datetime import datetime
 from logging import Formatter
-from typing import Any, Dict, List, Optional
+from typing import Any, Dict, Optional
 
+from litellm.litellm_core_utils.secret_redaction import redact_string
 from litellm.litellm_core_utils.safe_json_dumps import safe_dumps
 from litellm.litellm_core_utils.safe_json_loads import safe_json_loads
 
@@ -21,74 +21,11 @@
     os.getenv("LITELLM_DISABLE_REDACT_SECRETS", "").lower() != "true"
 )
 
-_REDACTED = "REDACTED"
-
-
-def _build_secret_patterns() -> re.Pattern:
-    patterns: List[str] = [
-        # ── PEM private key / certificate blocks ──
-        r"-----BEGIN[A-Z \-]*PRIVATE KEY-----[\s\S]*?-----END[A-Z \-]*PRIVATE KEY-----",
-        # ── GCP OAuth2 access tokens (ya29.*) ──
-        r"\bya29\.[A-Za-z0-9_.~+/-]+",
-        # ── Credential %s formatting (space separator, no key= prefix) ──
-        r"(?:client_secret|azure_password|azure_username)\s+[^\s,'\"})\]{}>]+",
-        # AWS access key IDs
-        r"(?:AKIA|ASIA)[0-9A-Z]{16}",
-        # AWS secrets / session tokens / access key IDs (key=value)
-        r"(?:aws_secret_access_key|aws_session_token|aws_access_key_id)"
-        r"\s*[:=]\s*[A-Za-z0-9/+=]{20,}",
-        # Bearer tokens (OAuth, JWT, etc.)
-        r"Bearer\s+[A-Za-z0-9\-._~+/]{10,}=*",
-        # Basic auth headers
-        r"Basic\s+[A-Za-z0-9+/]{10,}={0,2}",
-        # OpenAI / Anthropic sk- prefixed keys
-        r"sk-[A-Za-z0-9\-_]{20,}",
-        # Generic api_key / api-key / apikey (handles 'key': 'value' dict repr)
-        r"(?:api[_-]?key)['\"]?\s*[:=]\s*['\"]?[^\s,'\"})\]{}>]{8,}",
-        # x-api-key / api-key header values (handles 'key': 'value' dict repr)
-        r"(?:x-api-key|api-key)['\"]?\s*[:=]\s*['\"]?[^\s,'\"})\]{}>]+",
-        # Anthropic internal header keys
-        r"x-ak-[A-Za-z0-9\-_]{20,}",
-        # Google API keys
-        r"AIza[0-9A-Za-z\-_]{35}",
-        # Password / secret params (handles key=value and 'key': 'value')
-        # Word boundary prevents O(n^2) backtracking on long word-char runs.
-        r"(?:^|(?<=\W))\w*(?:password|passwd|client_secret|secret_key|_secret)"
-        r"['\"]?\s*[:=]\s*['\"]?[^\s,'\"})\]{}>]+",
-        # Database connection string credentials (scheme://user:pass@host)
-        r"(?<=://)[^\s'\"]*:[^\s'\"@]+(?=@)",
-        # Databricks personal access tokens
-        r"dapi[0-9a-f]{32}",
-        # ── Key-name-based redaction ──
-        # Catches secrets inside dicts/config dumps by matching on the KEY name
-        # regardless of what the value looks like.
-        # e.g. 'master_key': 'any-value-here', "database_url": "postgres://..."
-        # private_key with PEM-aware value capture
-        r"""private_key['\"]?\s*[:=]\s*['\"]?(?:-----BEGIN[A-Z \-]*PRIVATE KEY-----[\s\S]*?-----END[A-Z \-]*PRIVATE KEY-----|[^\s,'\"})\]{}>]+)""",
-        r"(?:master_key|database_url|db_url|connection_string|"
-        r"signing_key|encryption_key|"
-        r"auth_token|access_token|refresh_token|"
-        r"slack_webhook_url|webhook_url|"
-        r"database_connection_string|"
-        r"huggingface_token|jwt_secret)"
-        r"""['\"]?\s*[:=]\s*['\"]?[^\s,'\"})\]{}>]+""",
-        # ── Raw JWTs (without Bearer prefix) ──
-        r"\beyJ[A-Za-z0-9_-]{10,}\.[A-Za-z0-9_-]+\.[A-Za-z0-9_-]*",
-        # ── Azure SAS tokens in URLs ──
-        r"[?&]sig=[A-Za-z0-9%+/=]+",
-        # ── Full JSON service-account blobs (single-line and multi-line) ──
-        r'\{[^{}]*"type"\s*:\s*"service_account"[^{}]*(?:\{[^{}]*\}[^{}]*)*\}',
-    ]
-    return re.compile("|".join(patterns), re.IGNORECASE)
-
-
-_SECRET_RE = _build_secret_patterns()
-
 
 def _redact_string(value: str) -> str:
     if not _ENABLE_SECRET_REDACTION:
         return value
-    return _SECRET_RE.sub(_REDACTED, value)
+    return redact_string(value)
 
 
 def redact_secrets(value: str) -> str:

litellm/cost_calculator.py

@@ -513,7 +513,10 @@ def cost_per_token(  # noqa: PLR0915
         return fireworks_ai_cost_per_token(model=model, usage=usage_block)
     elif custom_llm_provider == "azure":
         return azure_openai_cost_per_token(
-            model=model, usage=usage_block, response_time_ms=response_time_ms
+            model=model,
+            usage=usage_block,
+            response_time_ms=response_time_ms,
+            service_tier=service_tier,
         )
     elif custom_llm_provider == "gemini":
         return gemini_cost_per_token(
@@ -539,6 +542,7 @@ def cost_per_token(  # noqa: PLR0915
             usage=usage_block,
             response_time_ms=response_time_ms,
             request_model=request_model,
+            service_tier=service_tier,
         )
     else:
         model_info = _cached_get_model_info_helper(

litellm/litellm_core_utils/exception_mapping_utils.py

@@ -6,7 +6,8 @@
 import httpx
 
 import litellm
-from litellm._logging import _redact_string, verbose_logger
+from litellm._logging import _ENABLE_SECRET_REDACTION, _redact_string, verbose_logger
+from litellm.litellm_core_utils.secret_redaction import redact_string
 from litellm.types.utils import LlmProviders
 
 from ..exceptions import (
@@ -261,10 +262,18 @@ def exception_type(  # type: ignore  # noqa: PLR0915
         original_exception=original_exception
     )
     try:
-        error_str = str(original_exception)
+        error_str = (
+            redact_string(str(original_exception))
+            if _ENABLE_SECRET_REDACTION
+            else str(original_exception)
+        )
         if model:
             if hasattr(original_exception, "message"):
-                error_str = str(original_exception.message)
+                error_str = (
+                    redact_string(str(original_exception.message))
+                    if _ENABLE_SECRET_REDACTION
+                    else str(original_exception.message)
+                )
             if isinstance(original_exception, BaseException):
                 exception_type = type(original_exception).__name__
             else:
@@ -2431,7 +2440,8 @@ def exception_type(  # type: ignore  # noqa: PLR0915
             else:
                 raise APIConnectionError(
                     message="{}\n{}".format(
-                        str(original_exception), _redact_string(traceback.format_exc())
+                        str(original_exception),
+                        _redact_string(traceback.format_exc()),
                     ),
                     llm_provider=custom_llm_provider,
                     model=model,
@@ -2461,7 +2471,8 @@ def exception_type(  # type: ignore  # noqa: PLR0915
                     raise e  # it's already mapped
             raised_exc = APIConnectionError(
                 message="{}\n{}".format(
-                    original_exception, _redact_string(traceback.format_exc())
+                    original_exception,
+                    _redact_string(traceback.format_exc()),
                 ),
                 llm_provider="",
                 model="",