wassname/openrouter-python-sdk-retry-errors
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## Python SDK Changes:

Browse Source 
* `open_router.beta.responses.send()`: 
  *  `request` **Changed** **Breaking** ⚠️
  *  `response` **Changed** **Breaking** ⚠️
* `open_router.presets.create_presets_responses()`:  `request` **Changed** **Breaking** ⚠️
* `open_router.presets.create_presets_chat_completions()`:  `request` **Changed** **Breaking** ⚠️
* `open_router.chat.send()`:  `request` **Changed** **Breaking** ⚠️
* `open_router.workspaces.set_budget()`: **Added**
* `open_router.o_auth.create_auth_code()`: 
  *  `request.workspace_id` **Added**
  *  `error.status[403]` **Added**
* `open_router.files.download()`: **Added**
* `open_router.models.get()`: **Added**
* `open_router.workspaces.list_budgets()`: **Added**
* `open_router.workspaces.delete_budget()`: **Added**
* `open_router.datasets.get_benchmarks_artificial_analysis()`: **Added**
* `open_router.beta.analytics.query_analytics()`:  `response.data.warnings` **Added**
* `open_router.files.delete()`: **Added**
* `open_router.files.retrieve()`: **Added**
* `open_router.files.upload()`: **Added**
* `open_router.embeddings.list_models()`:  `response.data.[].benchmarks` **Added**
* `open_router.models.list()`: 
  *  `request` **Changed**
  *  `response.data.[].benchmarks` **Added**
* `open_router.models.list_for_user()`:  `response.data.[].benchmarks` **Added**
* `open_router.files.list()`: **Added**
* `open_router.presets.create_presets_messages()`:  `request` **Changed**
* `open_router.datasets.get_benchmarks_design_arena()`: **Added**
This commit is contained in:
speakeasybot
2026-06-17 01:01:09 +00:00
parent cdd4dc7302
commit 4e789208b4
97 changed files with 9804 additions and 391 deletions
Download Patch File Download Diff File Expand all files Collapse all files
src/openrouter/presets.py
+54
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@@ -625,6 +625,7 @@ class Presets(BaseSDK):
max_completion_tokens: OptionalNullable[int] = UNSET,
max_tokens: OptionalNullable[int] = UNSET,
metadata: Optional[Dict[str, str]] = None,
min_p: OptionalNullable[float] = UNSET,
modalities: Optional[List[components.Modality]] = None,
model: Optional[str] = None,
models: Optional[List[str]] = None,
@@ -647,6 +648,10 @@ class Presets(BaseSDK):
components.ChatRequestReasoningTypedDict,
]
] = None,
reasoning_effort: OptionalNullable[
components.ChatRequestReasoningEffort
] = UNSET,
repetition_penalty: OptionalNullable[float] = UNSET,
response_format: Optional[
Union[components.ResponseFormat, components.ResponseFormatTypedDict]
] = None,
@@ -676,6 +681,8 @@ class Presets(BaseSDK):
List[components.ChatFunctionToolTypedDict],
]
] = None,
top_a: OptionalNullable[float] = UNSET,
top_k: OptionalNullable[int] = UNSET,
top_logprobs: OptionalNullable[int] = UNSET,
top_p: OptionalNullable[float] = UNSET,
trace: Optional[
@@ -709,6 +716,7 @@ class Presets(BaseSDK):
:param max_completion_tokens: Maximum tokens in completion
:param max_tokens: Maximum tokens (deprecated, use max_completion_tokens). Note: some providers enforce a minimum of 16.
:param metadata: Key-value pairs for additional object information (max 16 pairs, 64 char keys, 512 char values)
:param min_p: Minimum probability threshold relative to the most likely token. Tokens with probability below min_p * (probability of top token) are filtered out. Not all providers support this parameter.
:param modalities: Output modalities for the response. Supported values are \"text\", \"image\", and \"audio\".
:param model: Model to use for completion
:param models: Models to use for completion
@@ -717,6 +725,8 @@ class Presets(BaseSDK):
:param presence_penalty: Presence penalty (-2.0 to 2.0)
:param provider: When multiple model providers are available, optionally indicate your routing preference.
:param reasoning: Configuration options for reasoning models
:param reasoning_effort: Shorthand for setting reasoning effort. Equivalent to setting reasoning.effort. Cannot be used simultaneously with reasoning.effort if they differ.
:param repetition_penalty: Penalizes tokens based on how much they have already appeared in the text. A value of 1.0 means no penalty. Values above 1.0 penalize repeated tokens more strongly. Not all providers support this parameter.
:param response_format: Response format configuration
:param seed: Random seed for deterministic outputs
:param service_tier: The service tier to use for processing this request.
@@ -728,6 +738,8 @@ class Presets(BaseSDK):
:param temperature: Sampling temperature (0-2)
:param tool_choice: Tool choice configuration
:param tools: Available tools for function calling
:param top_a: Consider only tokens with \"sufficiently high\" probabilities based on the probability of the most likely token. Not all providers support this parameter.
:param top_k: Limits the model to choose from the top K most likely tokens at each step. A value of 1 means the model will always pick the most likely next token. Not all providers support this parameter.
:param top_logprobs: Number of top log probabilities to return (0-20)
:param top_p: Nucleus sampling parameter (0-1)
:param trace: Metadata for observability and tracing. Known keys (trace_id, trace_name, span_name, generation_name, parent_span_id) have special handling. Additional keys are passed through as custom metadata to configured broadcast destinations.
@@ -769,6 +781,7 @@ class Presets(BaseSDK):
messages, List[components.ChatMessages]
),
metadata=metadata,
min_p=min_p,
modalities=modalities,
model=model,
models=models,
@@ -783,6 +796,8 @@ class Presets(BaseSDK):
reasoning=utils.get_pydantic_model(
reasoning, Optional[components.ChatRequestReasoning]
),
reasoning_effort=reasoning_effort,
repetition_penalty=repetition_penalty,
response_format=utils.get_pydantic_model(
response_format, Optional[components.ResponseFormat]
),
@@ -805,6 +820,8 @@ class Presets(BaseSDK):
tools=utils.get_pydantic_model(
tools, Optional[List[components.ChatFunctionTool]]
),
top_a=top_a,
top_k=top_k,
top_logprobs=top_logprobs,
top_p=top_p,
trace=utils.get_pydantic_model(trace, Optional[components.TraceConfig]),
@@ -943,6 +960,7 @@ class Presets(BaseSDK):
max_completion_tokens: OptionalNullable[int] = UNSET,
max_tokens: OptionalNullable[int] = UNSET,
metadata: Optional[Dict[str, str]] = None,
min_p: OptionalNullable[float] = UNSET,
modalities: Optional[List[components.Modality]] = None,
model: Optional[str] = None,
models: Optional[List[str]] = None,
@@ -965,6 +983,10 @@ class Presets(BaseSDK):
components.ChatRequestReasoningTypedDict,
]
] = None,
reasoning_effort: OptionalNullable[
components.ChatRequestReasoningEffort
] = UNSET,
repetition_penalty: OptionalNullable[float] = UNSET,
response_format: Optional[
Union[components.ResponseFormat, components.ResponseFormatTypedDict]
] = None,
@@ -994,6 +1016,8 @@ class Presets(BaseSDK):
List[components.ChatFunctionToolTypedDict],
]
] = None,
top_a: OptionalNullable[float] = UNSET,
top_k: OptionalNullable[int] = UNSET,
top_logprobs: OptionalNullable[int] = UNSET,
top_p: OptionalNullable[float] = UNSET,
trace: Optional[
@@ -1027,6 +1051,7 @@ class Presets(BaseSDK):
:param max_completion_tokens: Maximum tokens in completion
:param max_tokens: Maximum tokens (deprecated, use max_completion_tokens). Note: some providers enforce a minimum of 16.
:param metadata: Key-value pairs for additional object information (max 16 pairs, 64 char keys, 512 char values)
:param min_p: Minimum probability threshold relative to the most likely token. Tokens with probability below min_p * (probability of top token) are filtered out. Not all providers support this parameter.
:param modalities: Output modalities for the response. Supported values are \"text\", \"image\", and \"audio\".
:param model: Model to use for completion
:param models: Models to use for completion
@@ -1035,6 +1060,8 @@ class Presets(BaseSDK):
:param presence_penalty: Presence penalty (-2.0 to 2.0)
:param provider: When multiple model providers are available, optionally indicate your routing preference.
:param reasoning: Configuration options for reasoning models
:param reasoning_effort: Shorthand for setting reasoning effort. Equivalent to setting reasoning.effort. Cannot be used simultaneously with reasoning.effort if they differ.
:param repetition_penalty: Penalizes tokens based on how much they have already appeared in the text. A value of 1.0 means no penalty. Values above 1.0 penalize repeated tokens more strongly. Not all providers support this parameter.
:param response_format: Response format configuration
:param seed: Random seed for deterministic outputs
:param service_tier: The service tier to use for processing this request.
@@ -1046,6 +1073,8 @@ class Presets(BaseSDK):
:param temperature: Sampling temperature (0-2)
:param tool_choice: Tool choice configuration
:param tools: Available tools for function calling
:param top_a: Consider only tokens with \"sufficiently high\" probabilities based on the probability of the most likely token. Not all providers support this parameter.
:param top_k: Limits the model to choose from the top K most likely tokens at each step. A value of 1 means the model will always pick the most likely next token. Not all providers support this parameter.
:param top_logprobs: Number of top log probabilities to return (0-20)
:param top_p: Nucleus sampling parameter (0-1)
:param trace: Metadata for observability and tracing. Known keys (trace_id, trace_name, span_name, generation_name, parent_span_id) have special handling. Additional keys are passed through as custom metadata to configured broadcast destinations.
@@ -1087,6 +1116,7 @@ class Presets(BaseSDK):
messages, List[components.ChatMessages]
),
metadata=metadata,
min_p=min_p,
modalities=modalities,
model=model,
models=models,
@@ -1101,6 +1131,8 @@ class Presets(BaseSDK):
reasoning=utils.get_pydantic_model(
reasoning, Optional[components.ChatRequestReasoning]
),
reasoning_effort=reasoning_effort,
repetition_penalty=repetition_penalty,
response_format=utils.get_pydantic_model(
response_format, Optional[components.ResponseFormat]
),
@@ -1123,6 +1155,8 @@ class Presets(BaseSDK):
tools=utils.get_pydantic_model(
tools, Optional[List[components.ChatFunctionTool]]
),
top_a=top_a,
top_k=top_k,
top_logprobs=top_logprobs,
top_p=top_p,
trace=utils.get_pydantic_model(trace, Optional[components.TraceConfig]),
@@ -1253,6 +1287,12 @@ class Presets(BaseSDK):
context_management: OptionalNullable[
Union[components.ContextManagement, components.ContextManagementTypedDict]
] = UNSET,
fallbacks: OptionalNullable[
Union[
List[components.MessagesFallbackParam],
List[components.MessagesFallbackParamTypedDict],
]
] = UNSET,
max_tokens: Optional[int] = None,
metadata: Optional[
Union[components.Metadata, components.MetadataTypedDict]
@@ -1327,6 +1367,7 @@ class Presets(BaseSDK):
:param cache_control: Enable automatic prompt caching. When set at the top level, the system automatically applies cache breakpoints to the last cacheable block in the request. Currently supported for Anthropic Claude models.
:param context_management:
:param fallbacks: Fallback models to try if the primary model fails or refuses, in order. Handled by OpenRouter multi-model routing rather than Anthropic server-side fallbacks; cannot be combined with `models`. Each entry accepts only `model`. Maximum of 3 entries.
:param max_tokens:
:param metadata:
:param models:
@@ -1375,6 +1416,9 @@ class Presets(BaseSDK):
context_management=utils.get_pydantic_model(
context_management, OptionalNullable[components.ContextManagement]
),
fallbacks=utils.get_pydantic_model(
fallbacks, OptionalNullable[List[components.MessagesFallbackParam]]
),
max_tokens=max_tokens,
messages=utils.get_pydantic_model(
messages, Nullable[List[components.MessagesMessageParam]]
@@ -1547,6 +1591,12 @@ class Presets(BaseSDK):
context_management: OptionalNullable[
Union[components.ContextManagement, components.ContextManagementTypedDict]
] = UNSET,
fallbacks: OptionalNullable[
Union[
List[components.MessagesFallbackParam],
List[components.MessagesFallbackParamTypedDict],
]
] = UNSET,
max_tokens: Optional[int] = None,
metadata: Optional[
Union[components.Metadata, components.MetadataTypedDict]
@@ -1621,6 +1671,7 @@ class Presets(BaseSDK):
:param cache_control: Enable automatic prompt caching. When set at the top level, the system automatically applies cache breakpoints to the last cacheable block in the request. Currently supported for Anthropic Claude models.
:param context_management:
:param fallbacks: Fallback models to try if the primary model fails or refuses, in order. Handled by OpenRouter multi-model routing rather than Anthropic server-side fallbacks; cannot be combined with `models`. Each entry accepts only `model`. Maximum of 3 entries.
:param max_tokens:
:param metadata:
:param models:
@@ -1669,6 +1720,9 @@ class Presets(BaseSDK):
context_management=utils.get_pydantic_model(
context_management, OptionalNullable[components.ContextManagement]
),
fallbacks=utils.get_pydantic_model(
fallbacks, OptionalNullable[List[components.MessagesFallbackParam]]
),
max_tokens=max_tokens,
messages=utils.get_pydantic_model(
messages, Nullable[List[components.MessagesMessageParam]]