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feat(providers): add Unrestricted as an OpenAI-compatible provider
Registers unrestricted in providers.json with native /v1/responses and /v1/messages, and adds qwen3.8-27b-uncensored to the cost map so spend tracking, tool calls and reasoning_effort work out of the box. The provider is also listed in the endpoint support matrix and the Add Model form
This commit is contained in:
unrestricted-dev
parent
6762d65eb8
commit
a8765bee09
9 changed files with 496 additions and 0 deletions
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@ -1029,6 +1029,7 @@ openai_compatible_endpoints: Final[list[str]] = [
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"https://api.scx.ai/v1",
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"https://api.prisminference.com/v1",
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"https://api.reka.ai/v1",
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"https://api.unrestricted.sh/v1",
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"https://gigachat.devices.sberbank.ru/api/v1",
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"https://api.openinfer.ai/v1",
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]
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@ -1109,6 +1110,7 @@ openai_compatible_providers: Final[list] = [
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"prism",
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"sail",
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"reka",
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"unrestricted",
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]
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OPENAI_AUDIO_TRANSCRIPTION_PROVIDERS: Final = frozenset({"openai"} | frozenset(openai_compatible_providers))
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@ -249,5 +249,11 @@
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"/v1/responses",
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"/v1/messages"
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]
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},
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"unrestricted": {
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"base_url": "https://api.unrestricted.sh/v1",
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"api_key_env": "UNRESTRICTED_API_KEY",
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"api_base_env": "UNRESTRICTED_API_BASE",
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"supported_endpoints": ["/v1/chat/completions", "/v1/responses", "/v1/messages"]
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}
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}
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@ -76082,5 +76082,40 @@
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"supports_response_schema": true,
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"supports_tool_choice": true,
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"supports_vision": true
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},
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"unrestricted/qwen3.8-27b-uncensored": {
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"cache_read_input_token_cost": 5e-07,
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"input_cost_per_token": 2e-06,
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"litellm_provider": "unrestricted",
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"max_input_tokens": 262144,
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"max_output_tokens": 32768,
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"max_tokens": 32768,
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"mode": "chat",
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"output_cost_per_token": 5e-06,
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"reasoning_effort_levels": [
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"none",
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"low",
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"medium",
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"xhigh"
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],
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"source": "https://unrestricted.sh/models/qwen3.8-27b-uncensored",
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"supported_endpoints": [
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"/v1/chat/completions",
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"/v1/completions",
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"/v1/responses",
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"/v1/messages"
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],
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"supported_modalities": [
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"text"
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],
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"supported_output_modalities": [
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"text"
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],
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"supports_function_calling": true,
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"supports_native_streaming": true,
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"supports_prompt_caching": true,
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"supports_reasoning": true,
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"supports_response_schema": true,
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"supports_vision": false
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}
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}
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@ -2334,6 +2334,24 @@
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"interactions": true
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}
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},
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"unrestricted": {
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"display_name": "Unrestricted (`unrestricted`)",
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"url": "https://docs.litellm.ai/docs/providers/unrestricted",
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"endpoints": {
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"chat_completions": true,
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"messages": true,
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"responses": true,
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"embeddings": false,
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"image_generations": false,
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"audio_transcriptions": false,
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"audio_speech": false,
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"moderations": false,
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"batches": false,
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"rerank": false,
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"a2a": false,
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"interactions": false
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}
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},
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"v0": {
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"display_name": "V0 (`v0`)",
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"url": "https://docs.litellm.ai/docs/providers/v0",
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@ -3639,6 +3639,34 @@
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],
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"default_model_placeholder": "typesafe/jev-latest"
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},
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{
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"provider": "UNRESTRICTED",
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"provider_display_name": "Unrestricted",
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"litellm_provider": "unrestricted",
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"credential_fields": [
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{
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"key": "api_base",
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"label": "API Base",
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"placeholder": "https://api.unrestricted.sh/v1",
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"tooltip": null,
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"required": false,
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"field_type": "text",
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"options": null,
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"default_value": null
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},
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{
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"key": "api_key",
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"label": "API Key",
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"placeholder": null,
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"tooltip": null,
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"required": true,
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"field_type": "password",
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"options": null,
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"default_value": null
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}
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],
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"default_model_placeholder": "unrestricted/qwen3.8-27b-uncensored"
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},
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{
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"provider": "V0",
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"provider_display_name": "V0",
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@ -4402,6 +4402,7 @@ class LlmProviders(str, Enum):
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META = "meta"
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SAIL = "sail"
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REKA = "reka"
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UNRESTRICTED = "unrestricted"
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LITELLM_AGENT = "litellm_agent"
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CURSOR = "cursor"
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BEDROCK_MANTLE = "bedrock_mantle"
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@ -76082,5 +76082,40 @@
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"supports_response_schema": true,
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"supports_tool_choice": true,
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"supports_vision": true
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},
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"unrestricted/qwen3.8-27b-uncensored": {
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"cache_read_input_token_cost": 5e-07,
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"input_cost_per_token": 2e-06,
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"litellm_provider": "unrestricted",
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"max_input_tokens": 262144,
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"max_output_tokens": 32768,
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"max_tokens": 32768,
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"mode": "chat",
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"output_cost_per_token": 5e-06,
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"reasoning_effort_levels": [
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"none",
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"low",
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"medium",
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"xhigh"
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],
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"source": "https://unrestricted.sh/models/qwen3.8-27b-uncensored",
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"supported_endpoints": [
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"/v1/chat/completions",
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"/v1/completions",
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"/v1/responses",
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"/v1/messages"
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],
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"supported_modalities": [
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"text"
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],
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"supported_output_modalities": [
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"text"
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],
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"supports_function_calling": true,
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"supports_native_streaming": true,
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"supports_prompt_caching": true,
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"supports_reasoning": true,
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"supports_response_schema": true,
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"supports_vision": false
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}
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}
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@ -3271,6 +3271,24 @@
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"rerank": false,
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"a2a": false
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}
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},
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"unrestricted": {
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"display_name": "Unrestricted (`unrestricted`)",
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"url": "https://docs.litellm.ai/docs/providers/unrestricted",
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"endpoints": {
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"chat_completions": true,
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"messages": true,
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"responses": true,
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"embeddings": false,
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"image_generations": false,
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"audio_transcriptions": false,
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"audio_speech": false,
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"moderations": false,
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"batches": false,
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"rerank": false,
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"a2a": false,
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"interactions": false
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}
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}
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},
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"endpoints": {
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353
tests/unit/llms/openai_like/test_unrestricted_provider.py
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353
tests/unit/llms/openai_like/test_unrestricted_provider.py
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@ -0,0 +1,353 @@
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import json
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from pathlib import Path
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from typing import Final
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import pytest
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import respx
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import litellm
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from litellm.caching.llm_caching_handler import LLMClientCache
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from litellm.cost_calculator import cost_per_token
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from litellm.litellm_core_utils.get_llm_provider_logic import get_llm_provider
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_MODEL: Final = "unrestricted/qwen3.8-27b-uncensored"
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_PROMPT_TOKENS: Final = 1_000
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_CACHED_PROMPT_TOKENS: Final = 600
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_COMPLETION_TOKENS: Final = 100
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_CHAT_COMPLETION: Final = {
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"id": "chatcmpl_unrestricted",
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"object": "chat.completion",
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"created": 1_790_000_000,
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"model": "qwen3.8-27b-uncensored",
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"choices": [
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{
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"index": 0,
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"message": {
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"role": "assistant",
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"content": "Hello from Unrestricted",
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"reasoning_content": "The user wants a greeting",
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},
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"finish_reason": "stop",
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}
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],
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"usage": {
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"prompt_tokens": _PROMPT_TOKENS,
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"completion_tokens": _COMPLETION_TOKENS,
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"total_tokens": _PROMPT_TOKENS + _COMPLETION_TOKENS,
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"prompt_tokens_details": {"cached_tokens": _CACHED_PROMPT_TOKENS},
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},
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}
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UNRESTRICTED_MODELS: Final = tuple(sorted(name for name in litellm.model_cost if name.startswith("unrestricted/")))
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def test_unrestricted_is_a_registered_provider():
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assert litellm.LlmProviders.UNRESTRICTED.value == "unrestricted"
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assert "unrestricted" in litellm.provider_list
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assert "unrestricted" in litellm.constants.openai_compatible_providers
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def test_unrestricted_provider_resolution(monkeypatch: pytest.MonkeyPatch):
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monkeypatch.setenv("UNRESTRICTED_API_KEY", "unrestricted-test-key")
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model, provider, api_key, api_base = get_llm_provider(
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model=_MODEL,
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custom_llm_provider=None,
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api_base=None,
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api_key=None,
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)
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assert model == "qwen3.8-27b-uncensored"
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assert provider == "unrestricted"
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assert api_key == "unrestricted-test-key"
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assert api_base == "https://api.unrestricted.sh/v1"
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def test_unrestricted_provider_keeps_explicit_credentials(monkeypatch: pytest.MonkeyPatch):
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monkeypatch.setenv("UNRESTRICTED_API_KEY", "unrestricted-env-key")
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monkeypatch.setenv("UNRESTRICTED_API_BASE", "https://unrestricted.env.example/v1")
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_, provider, api_key, api_base = get_llm_provider(
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model=_MODEL,
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custom_llm_provider=None,
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api_base="https://unrestricted.internal.example/v1",
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api_key="unrestricted-explicit-key",
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)
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assert provider == "unrestricted"
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assert api_key == "unrestricted-explicit-key"
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assert api_base == "https://unrestricted.internal.example/v1"
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def test_unrestricted_api_base_env_overrides_default(monkeypatch: pytest.MonkeyPatch):
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monkeypatch.setenv("UNRESTRICTED_API_KEY", "unrestricted-env-key")
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monkeypatch.setenv("UNRESTRICTED_API_BASE", "https://unrestricted.env.example/v1")
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_, provider, _, api_base = get_llm_provider(
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model=_MODEL,
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custom_llm_provider=None,
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api_base=None,
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api_key=None,
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)
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assert provider == "unrestricted"
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assert api_base == "https://unrestricted.env.example/v1"
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def test_unrestricted_api_base_autodetects_provider(monkeypatch: pytest.MonkeyPatch):
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monkeypatch.setenv("UNRESTRICTED_API_KEY", "unrestricted-env-key")
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model, provider, api_key, api_base = get_llm_provider(
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model="qwen3.8-27b-uncensored",
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custom_llm_provider=None,
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api_base="https://api.unrestricted.sh/v1",
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api_key=None,
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)
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assert model == "qwen3.8-27b-uncensored"
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assert provider == "unrestricted"
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assert api_key == "unrestricted-env-key"
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assert api_base == "https://api.unrestricted.sh/v1"
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@pytest.mark.parametrize("model", UNRESTRICTED_MODELS)
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def test_unrestricted_model_cost_and_capabilities(model: str):
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prompt_cost, completion_cost = cost_per_token(
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model=model,
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prompt_tokens=1_000_000,
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completion_tokens=1_000_000,
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custom_llm_provider="unrestricted",
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)
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model_info = litellm.get_model_info(model)
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assert prompt_cost == pytest.approx(model_info["input_cost_per_token"] * 1_000_000)
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assert completion_cost == pytest.approx(model_info["output_cost_per_token"] * 1_000_000)
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assert 0 < model_info["cache_read_input_token_cost"] < model_info["input_cost_per_token"]
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assert model_info["output_cost_per_token"] > 0
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assert model_info["max_tokens"] == model_info["max_output_tokens"] <= model_info["max_input_tokens"]
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assert model_info["litellm_provider"] == "unrestricted"
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assert model_info["mode"] == "chat"
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assert model_info["supports_function_calling"] is True
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assert model_info["supports_native_streaming"] is True
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assert model_info["supports_reasoning"] is True
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assert model_info["supports_response_schema"] is True
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assert litellm.supports_vision(model) is model_info["supports_vision"]
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def test_unrestricted_backup_registry_mirrors_cost_map():
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package_root = Path(litellm.__file__).parent
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cost_map = json.loads((package_root.parent / "model_prices_and_context_window.json").read_text())
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backup = json.loads((package_root / "model_prices_and_context_window_backup.json").read_text())
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unrestricted_entries = {name: entry for name, entry in cost_map.items() if name.startswith("unrestricted/")}
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assert tuple(sorted(unrestricted_entries)) == UNRESTRICTED_MODELS
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assert unrestricted_entries
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assert unrestricted_entries == {name: backup[name] for name in unrestricted_entries}
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def test_unrestricted_is_available_in_add_model_form():
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fields_path = Path(litellm.__file__).parent / "proxy" / "public_endpoints" / "provider_create_fields.json"
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providers = json.loads(fields_path.read_text())
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unrestricted = next(provider for provider in providers if provider["litellm_provider"] == "unrestricted")
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assert unrestricted["provider"] == "UNRESTRICTED"
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assert unrestricted["provider_display_name"] == "Unrestricted"
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assert unrestricted["default_model_placeholder"] in UNRESTRICTED_MODELS
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assert {field["key"]: field["required"] for field in unrestricted["credential_fields"]} == {
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"api_base": False,
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"api_key": True,
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}
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def test_unrestricted_supported_endpoints():
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expected: Final = {
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"chat_completions": True,
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"messages": True,
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"responses": True,
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"embeddings": False,
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"image_generations": False,
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"audio_transcriptions": False,
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"audio_speech": False,
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"moderations": False,
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"batches": False,
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"rerank": False,
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"a2a": False,
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"interactions": False,
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}
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backup_path = Path(litellm.__file__).parent / "provider_endpoints_support_backup.json"
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root_path = Path(litellm.__file__).parent.parent / "provider_endpoints_support.json"
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assert json.loads(backup_path.read_text())["providers"]["unrestricted"]["endpoints"] == expected
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assert json.loads(root_path.read_text())["providers"]["unrestricted"]["endpoints"] == expected
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def test_unrestricted_chat_completion_request():
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with respx.mock() as upstream:
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route: Final = upstream.post("https://api.unrestricted.sh/v1/chat/completions").respond(
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200, json=_CHAT_COMPLETION
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)
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response: Final = litellm.completion(
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model=_MODEL,
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messages=[{"role": "user", "content": "Say hello"}],
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api_key="unrestricted-test-key",
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)
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request: Final = route.calls.last.request
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body: Final = json.loads(request.content)
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assert route.call_count == 1
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assert str(request.url) == "https://api.unrestricted.sh/v1/chat/completions"
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assert request.headers["authorization"] == "Bearer unrestricted-test-key"
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assert body["model"] == "qwen3.8-27b-uncensored"
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assert body["messages"] == [{"role": "user", "content": "Say hello"}]
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assert response.choices[0].message.content == "Hello from Unrestricted"
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assert response.choices[0].message.reasoning_content == "The user wants a greeting"
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@pytest.mark.parametrize("reasoning_effort", litellm.model_cost[_MODEL]["reasoning_effort_levels"])
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def test_unrestricted_forwards_each_declared_reasoning_effort(reasoning_effort: str):
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with respx.mock() as upstream:
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route: Final = upstream.post("https://api.unrestricted.sh/v1/chat/completions").respond(
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200, json=_CHAT_COMPLETION
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)
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litellm.completion(
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model=_MODEL,
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messages=[{"role": "user", "content": "Say hello"}],
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reasoning_effort=reasoning_effort,
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api_key="unrestricted-test-key",
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)
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|
||||
body: Final = json.loads(route.calls.last.request.content)
|
||||
assert body["reasoning_effort"] == reasoning_effort
|
||||
|
||||
|
||||
def test_unrestricted_forwards_tools_and_json_schema_response_format():
|
||||
tools: Final = [
|
||||
{
|
||||
"type": "function",
|
||||
"function": {
|
||||
"name": "get_weather",
|
||||
"parameters": {"type": "object", "properties": {"city": {"type": "string"}}, "required": ["city"]},
|
||||
},
|
||||
}
|
||||
]
|
||||
response_format: Final = {
|
||||
"type": "json_schema",
|
||||
"json_schema": {
|
||||
"name": "weather",
|
||||
"schema": {"type": "object", "properties": {"forecast": {"type": "string"}}, "required": ["forecast"]},
|
||||
"strict": True,
|
||||
},
|
||||
}
|
||||
with respx.mock() as upstream:
|
||||
route: Final = upstream.post("https://api.unrestricted.sh/v1/chat/completions").respond(
|
||||
200, json=_CHAT_COMPLETION
|
||||
)
|
||||
litellm.completion(
|
||||
model=_MODEL,
|
||||
messages=[{"role": "user", "content": "What is the weather in Oslo?"}],
|
||||
tools=tools,
|
||||
response_format=response_format,
|
||||
api_key="unrestricted-test-key",
|
||||
)
|
||||
|
||||
body: Final = json.loads(route.calls.last.request.content)
|
||||
assert body["tools"] == tools
|
||||
assert body["response_format"] == response_format
|
||||
|
||||
|
||||
def test_unrestricted_completion_cost_bills_cached_prompt_tokens_at_the_cache_read_rate():
|
||||
with respx.mock() as upstream:
|
||||
upstream.post("https://api.unrestricted.sh/v1/chat/completions").respond(200, json=_CHAT_COMPLETION)
|
||||
response: Final = litellm.completion(
|
||||
model=_MODEL,
|
||||
messages=[{"role": "user", "content": "Say hello"}],
|
||||
api_key="unrestricted-test-key",
|
||||
)
|
||||
|
||||
model_info: Final = litellm.get_model_info(_MODEL)
|
||||
expected_cost: Final = (
|
||||
(_PROMPT_TOKENS - _CACHED_PROMPT_TOKENS) * model_info["input_cost_per_token"]
|
||||
+ _CACHED_PROMPT_TOKENS * model_info["cache_read_input_token_cost"]
|
||||
+ _COMPLETION_TOKENS * model_info["output_cost_per_token"]
|
||||
)
|
||||
assert litellm.completion_cost(completion_response=response) == pytest.approx(expected_cost)
|
||||
|
||||
|
||||
def test_unrestricted_responses_request():
|
||||
with respx.mock() as upstream:
|
||||
route: Final = upstream.post("https://api.unrestricted.sh/v1/responses").respond(
|
||||
200,
|
||||
json={
|
||||
"id": "resp_unrestricted",
|
||||
"object": "response",
|
||||
"created_at": 1_790_000_000,
|
||||
"model": "qwen3.8-27b-uncensored",
|
||||
"status": "completed",
|
||||
"output": [
|
||||
{
|
||||
"id": "msg_unrestricted",
|
||||
"type": "message",
|
||||
"role": "assistant",
|
||||
"status": "completed",
|
||||
"content": [{"type": "output_text", "text": "Hello from Unrestricted", "annotations": []}],
|
||||
}
|
||||
],
|
||||
"usage": {"input_tokens": 4, "output_tokens": 3, "total_tokens": 7},
|
||||
},
|
||||
)
|
||||
response: Final = litellm.responses(
|
||||
model=_MODEL,
|
||||
input="Say hello",
|
||||
reasoning={"effort": "low"},
|
||||
api_key="unrestricted-test-key",
|
||||
)
|
||||
|
||||
request: Final = route.calls.last.request
|
||||
body: Final = json.loads(request.content)
|
||||
assert route.call_count == 1
|
||||
assert str(request.url) == "https://api.unrestricted.sh/v1/responses"
|
||||
assert request.headers["authorization"] == "Bearer unrestricted-test-key"
|
||||
assert body["model"] == "qwen3.8-27b-uncensored"
|
||||
assert body["input"] == "Say hello"
|
||||
assert body["reasoning"] == {"effort": "low"}
|
||||
assert response.output[0].content[0].text == "Hello from Unrestricted"
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_unrestricted_anthropic_messages_request(monkeypatch: pytest.MonkeyPatch):
|
||||
monkeypatch.setattr(litellm, "disable_aiohttp_transport", True)
|
||||
monkeypatch.setattr(litellm, "in_memory_llm_clients_cache", LLMClientCache())
|
||||
thinking: Final = {"type": "enabled", "budget_tokens": 1_024}
|
||||
with respx.mock() as upstream:
|
||||
route: Final = upstream.post("https://api.unrestricted.sh/v1/messages").respond(
|
||||
200,
|
||||
json={
|
||||
"id": "msg_unrestricted",
|
||||
"type": "message",
|
||||
"role": "assistant",
|
||||
"model": "qwen3.8-27b-uncensored",
|
||||
"content": [{"type": "text", "text": "Hello from Unrestricted"}],
|
||||
"stop_reason": "end_turn",
|
||||
"stop_sequence": None,
|
||||
"usage": {"input_tokens": 4, "output_tokens": 3},
|
||||
},
|
||||
)
|
||||
response: Final = await litellm.anthropic.messages.acreate(
|
||||
model=_MODEL,
|
||||
messages=[{"role": "user", "content": "Say hello"}],
|
||||
max_tokens=2_048,
|
||||
thinking=thinking,
|
||||
api_key="unrestricted-test-key",
|
||||
)
|
||||
|
||||
request: Final = route.calls.last.request
|
||||
body: Final = json.loads(request.content)
|
||||
assert route.call_count == 1
|
||||
assert str(request.url) == "https://api.unrestricted.sh/v1/messages"
|
||||
assert request.headers["authorization"] == "Bearer unrestricted-test-key"
|
||||
assert request.headers["anthropic-version"] == "2023-06-01"
|
||||
assert body["model"] == "qwen3.8-27b-uncensored"
|
||||
assert body["messages"] == [{"role": "user", "content": "Say hello"}]
|
||||
assert body["thinking"] == thinking
|
||||
assert response["content"][0]["text"] == "Hello from Unrestricted"
|
||||
Loading…
Add table
Reference in a new issue