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blueprints
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feat/api-n
| Author | SHA1 | Date | |
|---|---|---|---|
| 8956e00c16 | |||
| 3bdf87ffa9 | |||
| 0a6e3c9d70 | |||
| 78b5dec6b6 | |||
| 72e3f6081c | |||
| 7ec7b6ffe9 | |||
| 6887165a9d | |||
| cc4d711eb1 | |||
| 626b082838 | |||
| d0328b442d |
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"label": "c",
|
||||
"localized_name": "values.c",
|
||||
"name": "values.c",
|
||||
"shape": 7,
|
||||
"type": "FLOAT,INT,BOOLEAN",
|
||||
"link": null
|
||||
},
|
||||
{
|
||||
"localized_name": "expression",
|
||||
"name": "expression",
|
||||
"type": "STRING",
|
||||
"widget": {
|
||||
"name": "expression"
|
||||
},
|
||||
"link": null
|
||||
}
|
||||
],
|
||||
"outputs": [
|
||||
{
|
||||
"localized_name": "FLOAT",
|
||||
"name": "FLOAT",
|
||||
"type": "FLOAT",
|
||||
"links": null
|
||||
},
|
||||
{
|
||||
"localized_name": "INT",
|
||||
"name": "INT",
|
||||
"type": "INT",
|
||||
"links": [
|
||||
403
|
||||
]
|
||||
},
|
||||
{
|
||||
"localized_name": "BOOL",
|
||||
"name": "BOOL",
|
||||
"type": "BOOLEAN",
|
||||
"links": null
|
||||
}
|
||||
],
|
||||
"title": "Math Expression （Width）",
|
||||
"properties": {
|
||||
"Node name for S&R": "ComfyMathExpression",
|
||||
"cnr_id": "comfy-core",
|
||||
"ver": "0.18.1",
|
||||
"enableTabs": false,
|
||||
"tabWidth": 65,
|
||||
"tabXOffset": 10,
|
||||
"hasSecondTab": false,
|
||||
"secondTabText": "Send Back",
|
||||
"secondTabOffset": 80,
|
||||
"secondTabWidth": 65,
|
||||
"ue_properties": {
|
||||
"widget_ue_connectable": {},
|
||||
"version": "7.7",
|
||||
"input_ue_unconnectable": {}
|
||||
}
|
||||
},
|
||||
"widgets_values": [
|
||||
"max(1, (int(a) + int(b) - 1) // int(b))"
|
||||
]
|
||||
},
|
||||
{
|
||||
"id": 228,
|
||||
"type": "PrimitiveInt",
|
||||
"pos": [
|
||||
-1380,
|
||||
90
|
||||
],
|
||||
"size": [
|
||||
230,
|
||||
110
|
||||
],
|
||||
"flags": {},
|
||||
"order": 1,
|
||||
"mode": 0,
|
||||
"inputs": [
|
||||
{
|
||||
"localized_name": "value",
|
||||
"name": "value",
|
||||
"type": "INT",
|
||||
"widget": {
|
||||
"name": "value"
|
||||
},
|
||||
"link": 427
|
||||
}
|
||||
],
|
||||
"outputs": [
|
||||
{
|
||||
"localized_name": "INT",
|
||||
"name": "INT",
|
||||
"type": "INT",
|
||||
"links": [
|
||||
388
|
||||
]
|
||||
}
|
||||
],
|
||||
"title": "Int (grid columns)",
|
||||
"properties": {
|
||||
"Node name for S&R": "Int (grid columns)",
|
||||
"cnr_id": "comfy-core",
|
||||
"ver": "0.18.1",
|
||||
"enableTabs": false,
|
||||
"tabWidth": 65,
|
||||
"tabXOffset": 10,
|
||||
"hasSecondTab": false,
|
||||
"secondTabText": "Send Back",
|
||||
"secondTabOffset": 80,
|
||||
"secondTabWidth": 65,
|
||||
"ue_properties": {
|
||||
"widget_ue_connectable": {},
|
||||
"version": "7.7",
|
||||
"input_ue_unconnectable": {}
|
||||
}
|
||||
},
|
||||
"widgets_values": [
|
||||
2,
|
||||
"fixed"
|
||||
]
|
||||
},
|
||||
{
|
||||
"id": 230,
|
||||
"type": "GetImageSize",
|
||||
"pos": [
|
||||
-1380,
|
||||
290
|
||||
],
|
||||
"size": [
|
||||
230,
|
||||
100
|
||||
],
|
||||
"flags": {},
|
||||
"order": 3,
|
||||
"mode": 0,
|
||||
"inputs": [
|
||||
{
|
||||
"localized_name": "image",
|
||||
"name": "image",
|
||||
"type": "IMAGE",
|
||||
"link": 389
|
||||
}
|
||||
],
|
||||
"outputs": [
|
||||
{
|
||||
"localized_name": "width",
|
||||
"name": "width",
|
||||
"type": "INT",
|
||||
"links": [
|
||||
387
|
||||
]
|
||||
},
|
||||
{
|
||||
"localized_name": "height",
|
||||
"name": "height",
|
||||
"type": "INT",
|
||||
"links": [
|
||||
390
|
||||
]
|
||||
},
|
||||
{
|
||||
"localized_name": "batch_size",
|
||||
"name": "batch_size",
|
||||
"type": "INT",
|
||||
"links": null
|
||||
}
|
||||
],
|
||||
"properties": {
|
||||
"Node name for S&R": "GetImageSize",
|
||||
"cnr_id": "comfy-core",
|
||||
"ver": "0.18.1",
|
||||
"enableTabs": false,
|
||||
"tabWidth": 65,
|
||||
"tabXOffset": 10,
|
||||
"hasSecondTab": false,
|
||||
"secondTabText": "Send Back",
|
||||
"secondTabOffset": 80,
|
||||
"secondTabWidth": 65,
|
||||
"ue_properties": {
|
||||
"widget_ue_connectable": {},
|
||||
"version": "7.7",
|
||||
"input_ue_unconnectable": {}
|
||||
}
|
||||
}
|
||||
},
|
||||
{
|
||||
"id": 252,
|
||||
"type": "PrimitiveInt",
|
||||
"pos": [
|
||||
-1380,
|
||||
470
|
||||
],
|
||||
"size": [
|
||||
230,
|
||||
110
|
||||
],
|
||||
"flags": {},
|
||||
"order": 5,
|
||||
"mode": 0,
|
||||
"inputs": [
|
||||
{
|
||||
"localized_name": "value",
|
||||
"name": "value",
|
||||
"type": "INT",
|
||||
"widget": {
|
||||
"name": "value"
|
||||
},
|
||||
"link": 428
|
||||
}
|
||||
],
|
||||
"outputs": [
|
||||
{
|
||||
"localized_name": "INT",
|
||||
"name": "INT",
|
||||
"type": "INT",
|
||||
"links": [
|
||||
429
|
||||
]
|
||||
}
|
||||
],
|
||||
"title": "Int (grid rows)",
|
||||
"properties": {
|
||||
"Node name for S&R": "Int (grid rows)",
|
||||
"cnr_id": "comfy-core",
|
||||
"ver": "0.18.1",
|
||||
"enableTabs": false,
|
||||
"tabWidth": 65,
|
||||
"tabXOffset": 10,
|
||||
"hasSecondTab": false,
|
||||
"secondTabText": "Send Back",
|
||||
"secondTabOffset": 80,
|
||||
"secondTabWidth": 65,
|
||||
"ue_properties": {
|
||||
"widget_ue_connectable": {},
|
||||
"version": "7.7",
|
||||
"input_ue_unconnectable": {}
|
||||
}
|
||||
},
|
||||
"widgets_values": [
|
||||
3,
|
||||
"fixed"
|
||||
]
|
||||
}
|
||||
],
|
||||
"groups": [],
|
||||
"links": [
|
||||
{
|
||||
"id": 403,
|
||||
"origin_id": 229,
|
||||
"origin_slot": 1,
|
||||
"target_id": 225,
|
||||
"target_slot": 1,
|
||||
"type": "INT"
|
||||
},
|
||||
{
|
||||
"id": 404,
|
||||
"origin_id": 231,
|
||||
"origin_slot": 1,
|
||||
"target_id": 225,
|
||||
"target_slot": 2,
|
||||
"type": "INT"
|
||||
},
|
||||
{
|
||||
"id": 390,
|
||||
"origin_id": 230,
|
||||
"origin_slot": 1,
|
||||
"target_id": 231,
|
||||
"target_slot": 0,
|
||||
"type": "INT"
|
||||
},
|
||||
{
|
||||
"id": 387,
|
||||
"origin_id": 230,
|
||||
"origin_slot": 0,
|
||||
"target_id": 229,
|
||||
"target_slot": 0,
|
||||
"type": "INT"
|
||||
},
|
||||
{
|
||||
"id": 388,
|
||||
"origin_id": 228,
|
||||
"origin_slot": 0,
|
||||
"target_id": 229,
|
||||
"target_slot": 1,
|
||||
"type": "INT"
|
||||
},
|
||||
{
|
||||
"id": 386,
|
||||
"origin_id": -10,
|
||||
"origin_slot": 0,
|
||||
"target_id": 225,
|
||||
"target_slot": 0,
|
||||
"type": "IMAGE"
|
||||
},
|
||||
{
|
||||
"id": 389,
|
||||
"origin_id": -10,
|
||||
"origin_slot": 0,
|
||||
"target_id": 230,
|
||||
"target_slot": 0,
|
||||
"type": "IMAGE"
|
||||
},
|
||||
{
|
||||
"id": 394,
|
||||
"origin_id": 225,
|
||||
"origin_slot": 0,
|
||||
"target_id": -20,
|
||||
"target_slot": 0,
|
||||
"type": "IMAGE"
|
||||
},
|
||||
{
|
||||
"id": 427,
|
||||
"origin_id": -10,
|
||||
"origin_slot": 1,
|
||||
"target_id": 228,
|
||||
"target_slot": 0,
|
||||
"type": "INT"
|
||||
},
|
||||
{
|
||||
"id": 428,
|
||||
"origin_id": -10,
|
||||
"origin_slot": 2,
|
||||
"target_id": 252,
|
||||
"target_slot": 0,
|
||||
"type": "INT"
|
||||
},
|
||||
{
|
||||
"id": 429,
|
||||
"origin_id": 252,
|
||||
"origin_slot": 0,
|
||||
"target_id": 231,
|
||||
"target_slot": 1,
|
||||
"type": "INT"
|
||||
}
|
||||
],
|
||||
"extra": {},
|
||||
"category": "Image Tools/Crop"
|
||||
}
|
||||
]
|
||||
},
|
||||
"extra": {}
|
||||
}
|
||||
File diff suppressed because it is too large
Load Diff
File diff suppressed because it is too large
Load Diff
@ -328,7 +328,7 @@ class CrossAttention(nn.Module):
|
||||
kv = torch.cat((k, v), dim=-1)
|
||||
split_size = kv.shape[-1] // self.num_heads // 2
|
||||
|
||||
kv = kv.view(1, -1, self.num_heads, split_size * 2)
|
||||
kv = kv.view(b, -1, self.num_heads, split_size * 2)
|
||||
k, v = torch.split(kv, split_size, dim=-1)
|
||||
|
||||
q = q.view(b, s1, self.num_heads, self.head_dim)
|
||||
@ -398,7 +398,7 @@ class Attention(nn.Module):
|
||||
qkv_combined = torch.cat((query, key, value), dim=-1)
|
||||
split_size = qkv_combined.shape[-1] // self.num_heads // 3
|
||||
|
||||
qkv = qkv_combined.view(1, -1, self.num_heads, split_size * 3)
|
||||
qkv = qkv_combined.view(B, -1, self.num_heads, split_size * 3)
|
||||
query, key, value = torch.split(qkv, split_size, dim=-1)
|
||||
|
||||
query = query.reshape(B, N, self.num_heads, self.head_dim)
|
||||
@ -607,9 +607,9 @@ class HunYuanDiTPlain(nn.Module):
|
||||
def forward(self, x, t, context, transformer_options = {}, **kwargs):
|
||||
|
||||
x = x.movedim(-1, -2)
|
||||
uncond_emb, cond_emb = context.chunk(2, dim = 0)
|
||||
|
||||
context = torch.cat([cond_emb, uncond_emb], dim = 0)
|
||||
if context.shape[0] >= 2:
|
||||
uncond_emb, cond_emb = context.chunk(2, dim = 0)
|
||||
context = torch.cat([cond_emb, uncond_emb], dim = 0)
|
||||
main_condition = context
|
||||
|
||||
t = 1.0 - t
|
||||
@ -657,5 +657,8 @@ class HunYuanDiTPlain(nn.Module):
|
||||
output = self.final_layer(combined)
|
||||
output = output.movedim(-2, -1) * (-1.0)
|
||||
|
||||
cond_emb, uncond_emb = output.chunk(2, dim = 0)
|
||||
return torch.cat([uncond_emb, cond_emb])
|
||||
if output.shape[0] >= 2:
|
||||
cond_emb, uncond_emb = output.chunk(2, dim = 0)
|
||||
return torch.cat([uncond_emb, cond_emb])
|
||||
else:
|
||||
return output
|
||||
|
||||
@ -260,7 +260,7 @@ def resolve_cast_module_with_vbar(s, dtype, device, bias_dtype, compute_dtype, w
|
||||
|
||||
|
||||
def cast_bias_weight(s, input=None, dtype=None, device=None, bias_dtype=None, offloadable=False, compute_dtype=None, want_requant=False):
|
||||
# NOTE: offloadable=False is a a legacy and if you are a custom node author reading this please pass
|
||||
# NOTE: offloadable=False is a legacy mode and if you are a custom node author reading this please pass
|
||||
# offloadable=True and call uncast_bias_weight() after your last usage of the weight/bias. This
|
||||
# will add async-offload support to your cast and improve performance.
|
||||
if input is not None:
|
||||
|
||||
@ -35,6 +35,19 @@ class AnthropicMessage(BaseModel):
|
||||
content: list[AnthropicTextContent | AnthropicImageContent] = Field(...)
|
||||
|
||||
|
||||
class AnthropicThinkingConfig(BaseModel):
|
||||
type: Literal["enabled", "disabled", "adaptive"] = Field(...)
|
||||
budget_tokens: int | None = Field(
|
||||
None, ge=1024,
|
||||
description="Reasoning budget in tokens. Used when type is 'enabled'. Must be less than max_tokens.",
|
||||
)
|
||||
|
||||
|
||||
class AnthropicOutputConfig(BaseModel):
|
||||
"""Used with `thinking.type='adaptive'` on models like Opus 4.7."""
|
||||
effort: Literal["low", "medium", "high"] | None = Field(None)
|
||||
|
||||
|
||||
class AnthropicMessagesRequest(BaseModel):
|
||||
model: str = Field(...)
|
||||
messages: list[AnthropicMessage] = Field(...)
|
||||
@ -44,6 +57,8 @@ class AnthropicMessagesRequest(BaseModel):
|
||||
top_p: float | None = Field(None, ge=0.0, le=1.0)
|
||||
top_k: int | None = Field(None, ge=0)
|
||||
stop_sequences: list[str] | None = Field(None)
|
||||
thinking: AnthropicThinkingConfig | None = Field(None)
|
||||
output_config: AnthropicOutputConfig | None = Field(None)
|
||||
|
||||
|
||||
class AnthropicResponseTextBlock(BaseModel):
|
||||
@ -51,6 +66,14 @@ class AnthropicResponseTextBlock(BaseModel):
|
||||
text: str = Field(...)
|
||||
|
||||
|
||||
class AnthropicResponseThinkingBlock(BaseModel):
|
||||
type: Literal["thinking"] = "thinking"
|
||||
thinking: str = Field(...)
|
||||
|
||||
|
||||
AnthropicResponseBlock = AnthropicResponseTextBlock | AnthropicResponseThinkingBlock
|
||||
|
||||
|
||||
class AnthropicCacheCreationUsage(BaseModel):
|
||||
ephemeral_5m_input_tokens: int | None = Field(None)
|
||||
ephemeral_1h_input_tokens: int | None = Field(None)
|
||||
@ -69,7 +92,7 @@ class AnthropicMessagesResponse(BaseModel):
|
||||
type: str | None = Field(None)
|
||||
role: str | None = Field(None)
|
||||
model: str | None = Field(None)
|
||||
content: list[AnthropicResponseTextBlock] | None = Field(None)
|
||||
content: list[AnthropicResponseBlock] | None = Field(None)
|
||||
stop_reason: str | None = Field(None)
|
||||
stop_sequence: str | None = Field(None)
|
||||
usage: AnthropicMessagesUsage | None = Field(None)
|
||||
|
||||
93
comfy_api_nodes/apis/openrouter.py
Normal file
93
comfy_api_nodes/apis/openrouter.py
Normal file
@ -0,0 +1,93 @@
|
||||
"""Pydantic models for the OpenRouter chat completions API.
|
||||
|
||||
See: https://openrouter.ai/docs/api/api-reference/chat/send-chat-completion-request
|
||||
"""
|
||||
|
||||
from typing import Literal
|
||||
|
||||
from pydantic import BaseModel, Field
|
||||
|
||||
|
||||
class OpenRouterTextContent(BaseModel):
|
||||
type: Literal["text"] = "text"
|
||||
text: str = Field(...)
|
||||
|
||||
|
||||
class OpenRouterImageUrl(BaseModel):
|
||||
url: str = Field(...)
|
||||
|
||||
|
||||
class OpenRouterImageContent(BaseModel):
|
||||
type: Literal["image_url"] = "image_url"
|
||||
image_url: OpenRouterImageUrl = Field(...)
|
||||
|
||||
|
||||
class OpenRouterVideoUrl(BaseModel):
|
||||
url: str = Field(...)
|
||||
|
||||
|
||||
class OpenRouterVideoContent(BaseModel):
|
||||
type: Literal["video_url"] = "video_url"
|
||||
video_url: OpenRouterVideoUrl = Field(...)
|
||||
|
||||
|
||||
OpenRouterContentBlock = OpenRouterTextContent | OpenRouterImageContent | OpenRouterVideoContent
|
||||
|
||||
|
||||
class OpenRouterMessage(BaseModel):
|
||||
role: Literal["system", "user", "assistant"] = Field(...)
|
||||
content: str | list[OpenRouterContentBlock] = Field(...)
|
||||
|
||||
|
||||
class OpenRouterReasoningConfig(BaseModel):
|
||||
effort: str | None = Field(None)
|
||||
exclude: bool | None = Field(None, description="If true, model reasons but reasoning is excluded from response.")
|
||||
|
||||
|
||||
class OpenRouterWebSearchOptions(BaseModel):
|
||||
search_context_size: str | None = Field(None)
|
||||
|
||||
|
||||
class OpenRouterChatRequest(BaseModel):
|
||||
model: str = Field(...)
|
||||
messages: list[OpenRouterMessage] = Field(...)
|
||||
seed: int | None = Field(None)
|
||||
reasoning: OpenRouterReasoningConfig | None = Field(None)
|
||||
web_search_options: OpenRouterWebSearchOptions | None = Field(None)
|
||||
stream: bool = Field(False)
|
||||
|
||||
|
||||
class OpenRouterUsage(BaseModel):
|
||||
prompt_tokens: int | None = Field(None)
|
||||
completion_tokens: int | None = Field(None)
|
||||
total_tokens: int | None = Field(None)
|
||||
cost: float | None = Field(None, description="Server-side authoritative USD cost of the call.")
|
||||
|
||||
|
||||
class OpenRouterResponseMessage(BaseModel):
|
||||
role: str | None = Field(None)
|
||||
content: str | None = Field(None)
|
||||
reasoning: str | None = Field(None)
|
||||
refusal: str | None = Field(None)
|
||||
|
||||
|
||||
class OpenRouterChoice(BaseModel):
|
||||
index: int | None = Field(None)
|
||||
message: OpenRouterResponseMessage | None = Field(None)
|
||||
finish_reason: str | None = Field(None)
|
||||
|
||||
|
||||
class OpenRouterError(BaseModel):
|
||||
code: int | str | None = Field(None)
|
||||
message: str | None = Field(None)
|
||||
metadata: dict | None = Field(None)
|
||||
|
||||
|
||||
class OpenRouterChatResponse(BaseModel):
|
||||
id: str | None = Field(None)
|
||||
model: str | None = Field(None)
|
||||
object: str | None = Field(None)
|
||||
provider: str | None = Field(None)
|
||||
choices: list[OpenRouterChoice] | None = Field(None)
|
||||
usage: OpenRouterUsage | None = Field(None)
|
||||
error: OpenRouterError | None = Field(None)
|
||||
@ -9,8 +9,11 @@ from comfy_api_nodes.apis.anthropic import (
|
||||
AnthropicMessage,
|
||||
AnthropicMessagesRequest,
|
||||
AnthropicMessagesResponse,
|
||||
AnthropicOutputConfig,
|
||||
AnthropicResponseTextBlock,
|
||||
AnthropicRole,
|
||||
AnthropicTextContent,
|
||||
AnthropicThinkingConfig,
|
||||
)
|
||||
from comfy_api_nodes.util import (
|
||||
ApiEndpoint,
|
||||
@ -32,15 +35,29 @@ CLAUDE_MODELS: dict[str, str] = {
|
||||
"Haiku 4.5": "claude-haiku-4-5-20251001",
|
||||
}
|
||||
|
||||
_THINKING_UNSUPPORTED = {"Haiku 4.5"}
|
||||
# Models that use the newer "adaptive" thinking mode (Opus 4.7 requires it; older models keep the explicit budget API).
|
||||
# Anthropic decides the actual budget when adaptive is used, based on the `output_config.effort` hint.
|
||||
_ADAPTIVE_THINKING_MODELS = {"Opus 4.7", "Opus 4.6", "Sonnet 4.6"}
|
||||
|
||||
def _claude_model_inputs():
|
||||
return [
|
||||
# Budget mode (Sonnet 4.5): effort -> reasoning budget in tokens. Must be < max_tokens.
|
||||
# Sized so even the "high" budget fits comfortably under the default max_tokens=32768.
|
||||
_REASONING_BUDGET: dict[str, int] = {
|
||||
"low": 2048,
|
||||
"medium": 8192,
|
||||
"high": 16384,
|
||||
}
|
||||
_REASONING_EFFORTS = ["off", "low", "medium", "high"]
|
||||
|
||||
|
||||
def _claude_model_inputs(model_label: str):
|
||||
inputs: list = [
|
||||
IO.Int.Input(
|
||||
"max_tokens",
|
||||
default=16000,
|
||||
min=32,
|
||||
max=32000,
|
||||
tooltip="Maximum number of tokens to generate before stopping.",
|
||||
default=32768,
|
||||
min=4096,
|
||||
max=64000,
|
||||
tooltip="Maximum number of tokens to generate (includes reasoning tokens when enabled).",
|
||||
advanced=True,
|
||||
),
|
||||
IO.Float.Input(
|
||||
@ -49,10 +66,24 @@ def _claude_model_inputs():
|
||||
min=0.0,
|
||||
max=1.0,
|
||||
step=0.01,
|
||||
tooltip="Controls randomness. 0.0 is deterministic, 1.0 is most random. Ignored for Opus 4.7.",
|
||||
tooltip=(
|
||||
"Controls randomness. 0.0 is deterministic, 1.0 is most random. "
|
||||
"Ignored for Opus 4.7 and any model when reasoning_effort is set."
|
||||
),
|
||||
advanced=True,
|
||||
),
|
||||
]
|
||||
if model_label not in _THINKING_UNSUPPORTED:
|
||||
inputs.append(
|
||||
IO.Combo.Input(
|
||||
"reasoning_effort",
|
||||
options=_REASONING_EFFORTS,
|
||||
default="off",
|
||||
tooltip="Extended thinking effort. 'off' disables reasoning.",
|
||||
advanced=True,
|
||||
)
|
||||
)
|
||||
return inputs
|
||||
|
||||
|
||||
def _model_price_per_million(model: str) -> tuple[float, float] | None:
|
||||
@ -95,7 +126,11 @@ def calculate_tokens_price(response: AnthropicMessagesResponse) -> float | None:
|
||||
def _get_text_from_response(response: AnthropicMessagesResponse) -> str:
|
||||
if not response.content:
|
||||
return ""
|
||||
return "\n".join(block.text for block in response.content if block.text)
|
||||
# Thinking blocks are silently dropped — we never want reasoning in the output.
|
||||
return "\n".join(
|
||||
block.text for block in response.content
|
||||
if isinstance(block, AnthropicResponseTextBlock) and block.text
|
||||
)
|
||||
|
||||
|
||||
async def _build_image_content_blocks(
|
||||
@ -133,7 +168,10 @@ class ClaudeNode(IO.ComfyNode):
|
||||
),
|
||||
IO.DynamicCombo.Input(
|
||||
"model",
|
||||
options=[IO.DynamicCombo.Option(label, _claude_model_inputs()) for label in CLAUDE_MODELS],
|
||||
options=[
|
||||
IO.DynamicCombo.Option(label, _claude_model_inputs(label))
|
||||
for label in CLAUDE_MODELS
|
||||
],
|
||||
tooltip="The Claude model used to generate the response.",
|
||||
),
|
||||
IO.Int.Input(
|
||||
@ -207,8 +245,29 @@ class ClaudeNode(IO.ComfyNode):
|
||||
) -> IO.NodeOutput:
|
||||
validate_string(prompt, strip_whitespace=True, min_length=1)
|
||||
model_label = model["model"]
|
||||
max_tokens = model["max_tokens"]
|
||||
temperature = None if model_label == "Opus 4.7" else model["temperature"]
|
||||
max_tokens = model.get("max_tokens", 32768)
|
||||
reasoning_effort = model.get("reasoning_effort", "off")
|
||||
thinking_enabled = reasoning_effort not in ("off", None) and model_label not in _THINKING_UNSUPPORTED
|
||||
|
||||
# Anthropic requires temperature to be unset (defaults to 1.0) when thinking is enabled.
|
||||
# Opus 4.7 also rejects user-supplied temperature.
|
||||
if thinking_enabled or model_label == "Opus 4.7":
|
||||
temperature = None
|
||||
else:
|
||||
temperature = model.get("temperature", 1.0)
|
||||
|
||||
thinking_cfg: AnthropicThinkingConfig | None = None
|
||||
output_cfg: AnthropicOutputConfig | None = None
|
||||
if thinking_enabled:
|
||||
if model_label in _ADAPTIVE_THINKING_MODELS:
|
||||
# Adaptive mode - Anthropic chooses the budget based on effort hint
|
||||
thinking_cfg = AnthropicThinkingConfig(type="adaptive")
|
||||
output_cfg = AnthropicOutputConfig(effort=reasoning_effort)
|
||||
else:
|
||||
# Budget mode (Sonnet 4.5). Leave at least 1024 tokens for the actual response
|
||||
budget = _REASONING_BUDGET[reasoning_effort]
|
||||
budget = min(budget, max(1024, max_tokens - 1024))
|
||||
thinking_cfg = AnthropicThinkingConfig(type="enabled", budget_tokens=budget)
|
||||
|
||||
image_tensors: list[Input.Image] = [t for t in (images or {}).values() if t is not None]
|
||||
if sum(get_number_of_images(t) for t in image_tensors) > CLAUDE_MAX_IMAGES:
|
||||
@ -229,6 +288,8 @@ class ClaudeNode(IO.ComfyNode):
|
||||
messages=[AnthropicMessage(role=AnthropicRole.user, content=content)],
|
||||
system=system_prompt or None,
|
||||
temperature=temperature,
|
||||
thinking=thinking_cfg,
|
||||
output_config=output_cfg,
|
||||
),
|
||||
price_extractor=calculate_tokens_price,
|
||||
)
|
||||
|
||||
374
comfy_api_nodes/nodes_openrouter.py
Normal file
374
comfy_api_nodes/nodes_openrouter.py
Normal file
@ -0,0 +1,374 @@
|
||||
"""API Nodes for OpenRouter LLM chat completions."""
|
||||
|
||||
from dataclasses import dataclass
|
||||
from typing import Literal
|
||||
|
||||
from typing_extensions import override
|
||||
|
||||
from comfy_api.latest import IO, ComfyExtension, Input
|
||||
from comfy_api_nodes.apis.openrouter import (
|
||||
OpenRouterChatRequest,
|
||||
OpenRouterChatResponse,
|
||||
OpenRouterContentBlock,
|
||||
OpenRouterImageContent,
|
||||
OpenRouterImageUrl,
|
||||
OpenRouterMessage,
|
||||
OpenRouterReasoningConfig,
|
||||
OpenRouterTextContent,
|
||||
OpenRouterVideoContent,
|
||||
OpenRouterVideoUrl,
|
||||
OpenRouterWebSearchOptions,
|
||||
)
|
||||
from comfy_api_nodes.util import (
|
||||
ApiEndpoint,
|
||||
get_number_of_images,
|
||||
sync_op,
|
||||
upload_images_to_comfyapi,
|
||||
upload_video_to_comfyapi,
|
||||
validate_string,
|
||||
)
|
||||
|
||||
OPENROUTER_CHAT_ENDPOINT = "/proxy/openrouter/api/v1/chat/completions"
|
||||
|
||||
|
||||
Profile = Literal["standard", "reasoning", "frontier_reasoning", "perplexity", "perplexity_reasoning"]
|
||||
|
||||
|
||||
@dataclass(frozen=True)
|
||||
class _ModelSpec:
|
||||
slug: str # exact OpenRouter model id
|
||||
profile: Profile
|
||||
price_in: float # USD per token (prompt)
|
||||
price_out: float # USD per token (completion)
|
||||
max_images: int = 0 # 0 = no image input; otherwise max URL-passed images supported
|
||||
max_videos: int = 0 # 0 = no video input; otherwise max URL-passed videos supported
|
||||
|
||||
|
||||
MODELS: list[_ModelSpec] = [
|
||||
_ModelSpec("anthropic/claude-opus-4.7", "frontier_reasoning", 0.000005, 0.000025, max_images=20),
|
||||
_ModelSpec("openai/gpt-5.5-pro", "frontier_reasoning", 0.00003, 0.00018, max_images=20),
|
||||
_ModelSpec("openai/gpt-5.5", "frontier_reasoning", 0.000005, 0.00003, max_images=20),
|
||||
_ModelSpec("google/gemini-3.5-flash", "reasoning", 0.0000015, 0.000009, max_images=20, max_videos=4),
|
||||
_ModelSpec("x-ai/grok-4.20", "reasoning", 0.00000125, 0.0000025, max_images=20),
|
||||
_ModelSpec("x-ai/grok-4.3", "reasoning", 0.00000125, 0.0000025, max_images=20),
|
||||
_ModelSpec("deepseek/deepseek-v4-pro", "reasoning", 0.000000435, 0.00000087),
|
||||
_ModelSpec("deepseek/deepseek-v4-flash", "reasoning", 0.000000112, 0.000000224),
|
||||
_ModelSpec("deepseek/deepseek-v3.2", "reasoning", 0.000000252, 0.000000378),
|
||||
_ModelSpec("qwen/qwen3.6-max-preview", "reasoning", 0.00000104, 0.00000624),
|
||||
_ModelSpec("qwen/qwen3.6-plus", "reasoning", 0.000000325, 0.00000195, max_images=10, max_videos=4),
|
||||
_ModelSpec("qwen/qwen3.6-flash", "reasoning", 0.0000001875, 0.000001125, max_images=10, max_videos=4),
|
||||
_ModelSpec("mistralai/mistral-large-2512", "standard", 0.0000005, 0.0000015, max_images=8),
|
||||
_ModelSpec("mistralai/mistral-medium-3-5", "reasoning", 0.0000015, 0.0000075, max_images=8),
|
||||
_ModelSpec("z-ai/glm-4.6", "reasoning", 0.00000043, 0.00000174),
|
||||
_ModelSpec("z-ai/glm-5", "reasoning", 0.0000006, 0.00000192),
|
||||
_ModelSpec("moonshotai/kimi-k2.6", "reasoning", 0.00000073, 0.00000349, max_images=10),
|
||||
_ModelSpec("moonshotai/kimi-k2-thinking", "reasoning", 0.0000006, 0.0000025),
|
||||
_ModelSpec("perplexity/sonar-pro", "perplexity", 0.000003, 0.000015),
|
||||
_ModelSpec("perplexity/sonar-reasoning-pro", "perplexity_reasoning", 0.000002, 0.000008),
|
||||
_ModelSpec("perplexity/sonar-deep-research", "perplexity_reasoning", 0.000002, 0.000008),
|
||||
]
|
||||
|
||||
_MODELS_BY_SLUG: dict[str, _ModelSpec] = {m.slug: m for m in MODELS}
|
||||
_REASONING_EFFORTS = ["off", "low", "medium", "high"]
|
||||
_SEARCH_CONTEXT_SIZES = ["low", "medium", "high"]
|
||||
|
||||
|
||||
def _reasoning_extra_inputs() -> list:
|
||||
return [
|
||||
IO.Combo.Input(
|
||||
"reasoning_effort",
|
||||
options=_REASONING_EFFORTS,
|
||||
default="off",
|
||||
tooltip="Reasoning effort. 'off' disables reasoning entirely.",
|
||||
advanced=True,
|
||||
),
|
||||
]
|
||||
|
||||
|
||||
def _perplexity_extra_inputs() -> list:
|
||||
return [
|
||||
IO.Combo.Input(
|
||||
"search_context_size",
|
||||
options=_SEARCH_CONTEXT_SIZES,
|
||||
default="medium",
|
||||
tooltip="How much web search context to retrieve. Larger = more grounded but slower/pricier.",
|
||||
advanced=True,
|
||||
),
|
||||
]
|
||||
|
||||
|
||||
def _profile_inputs(profile: Profile) -> list:
|
||||
if profile == "standard":
|
||||
return []
|
||||
if profile in ("reasoning", "frontier_reasoning"):
|
||||
return _reasoning_extra_inputs()
|
||||
if profile == "perplexity":
|
||||
return _perplexity_extra_inputs()
|
||||
if profile == "perplexity_reasoning":
|
||||
return _perplexity_extra_inputs() + _reasoning_extra_inputs()
|
||||
raise ValueError(f"Unknown profile: {profile}")
|
||||
|
||||
|
||||
def _media_inputs(spec: _ModelSpec) -> list:
|
||||
extras: list = []
|
||||
if spec.max_images > 0:
|
||||
extras.append(
|
||||
IO.Autogrow.Input(
|
||||
"images",
|
||||
template=IO.Autogrow.TemplateNames(
|
||||
IO.Image.Input("image"),
|
||||
names=[f"image_{i}" for i in range(1, spec.max_images + 1)],
|
||||
min=0,
|
||||
),
|
||||
tooltip=f"Optional reference image(s) — up to {spec.max_images}. Sent as URLs.",
|
||||
)
|
||||
)
|
||||
if spec.max_videos > 0:
|
||||
extras.append(
|
||||
IO.Autogrow.Input(
|
||||
"videos",
|
||||
template=IO.Autogrow.TemplateNames(
|
||||
IO.Video.Input("video"),
|
||||
names=[f"video_{i}" for i in range(1, spec.max_videos + 1)],
|
||||
min=0,
|
||||
),
|
||||
tooltip=f"Optional reference video(s) — up to {spec.max_videos}. Sent as URLs.",
|
||||
)
|
||||
)
|
||||
return extras
|
||||
|
||||
|
||||
def _inputs_for_model(spec: _ModelSpec) -> list:
|
||||
return _profile_inputs(spec.profile) + _media_inputs(spec)
|
||||
|
||||
|
||||
def _build_model_options() -> list[IO.DynamicCombo.Option]:
|
||||
return [IO.DynamicCombo.Option(spec.slug, _inputs_for_model(spec)) for spec in MODELS]
|
||||
|
||||
|
||||
def _calculate_price(response: OpenRouterChatResponse) -> float | None:
|
||||
if response.usage and response.usage.cost is not None:
|
||||
return float(response.usage.cost)
|
||||
return None
|
||||
|
||||
|
||||
def _price_badge_jsonata() -> str:
|
||||
rates_pairs = []
|
||||
for spec in MODELS:
|
||||
prompt_per_1k = spec.price_in * 1000
|
||||
completion_per_1k = spec.price_out * 1000
|
||||
rates_pairs.append(f' "{spec.slug}": [{prompt_per_1k:.8g}, {completion_per_1k:.8g}]')
|
||||
rates_block = ",\n".join(rates_pairs)
|
||||
return (
|
||||
"(\n"
|
||||
" $rates := {\n"
|
||||
f"{rates_block}\n"
|
||||
" };\n"
|
||||
" $r := $lookup($rates, widgets.model);\n"
|
||||
" $r ? {\n"
|
||||
' "type": "list_usd",\n'
|
||||
' "usd": $r,\n'
|
||||
' "format": { "approximate": true, "separator": "-", "suffix": " per 1K tokens" }\n'
|
||||
' } : {"type": "text", "text": "Token-based"}\n'
|
||||
")"
|
||||
)
|
||||
|
||||
|
||||
async def _build_image_blocks(
|
||||
cls: type[IO.ComfyNode], spec: _ModelSpec, images: list[Input.Image]
|
||||
) -> list[OpenRouterImageContent]:
|
||||
urls = await upload_images_to_comfyapi(
|
||||
cls,
|
||||
images,
|
||||
max_images=spec.max_images,
|
||||
total_pixels=2048 * 2048,
|
||||
mime_type="image/png",
|
||||
wait_label="Uploading reference images",
|
||||
)
|
||||
return [OpenRouterImageContent(image_url=OpenRouterImageUrl(url=url)) for url in urls]
|
||||
|
||||
|
||||
async def _build_video_blocks(cls: type[IO.ComfyNode], videos: list[Input.Video]) -> list[OpenRouterVideoContent]:
|
||||
blocks: list[OpenRouterVideoContent] = []
|
||||
total = len(videos)
|
||||
for idx, video in enumerate(videos):
|
||||
label = "Uploading reference video"
|
||||
if total > 1:
|
||||
label = f"{label} ({idx + 1}/{total})"
|
||||
url = await upload_video_to_comfyapi(cls, video, wait_label=label)
|
||||
blocks.append(OpenRouterVideoContent(video_url=OpenRouterVideoUrl(url=url)))
|
||||
return blocks
|
||||
|
||||
|
||||
def _user_message(prompt: str, media_blocks: list[OpenRouterContentBlock]) -> OpenRouterMessage:
|
||||
if not media_blocks:
|
||||
return OpenRouterMessage(role="user", content=prompt)
|
||||
blocks: list[OpenRouterContentBlock] = list(media_blocks)
|
||||
blocks.append(OpenRouterTextContent(text=prompt))
|
||||
return OpenRouterMessage(role="user", content=blocks)
|
||||
|
||||
|
||||
def _build_messages(
|
||||
system_prompt: str, prompt: str, media_blocks: list[OpenRouterContentBlock]
|
||||
) -> list[OpenRouterMessage]:
|
||||
messages: list[OpenRouterMessage] = []
|
||||
if system_prompt:
|
||||
messages.append(OpenRouterMessage(role="system", content=system_prompt))
|
||||
messages.append(_user_message(prompt, media_blocks))
|
||||
return messages
|
||||
|
||||
|
||||
def _build_request(
|
||||
slug: str,
|
||||
system_prompt: str,
|
||||
prompt: str,
|
||||
media_blocks: list[OpenRouterContentBlock],
|
||||
*,
|
||||
seed: int,
|
||||
reasoning_effort: str | None,
|
||||
search_context_size: str | None,
|
||||
) -> OpenRouterChatRequest:
|
||||
reasoning_cfg: OpenRouterReasoningConfig | None = None
|
||||
if reasoning_effort and reasoning_effort != "off":
|
||||
# exclude=True asks providers to reason internally but not return the trace
|
||||
reasoning_cfg = OpenRouterReasoningConfig(effort=reasoning_effort, exclude=True)
|
||||
web_search_cfg: OpenRouterWebSearchOptions | None = None
|
||||
if search_context_size:
|
||||
web_search_cfg = OpenRouterWebSearchOptions(search_context_size=search_context_size)
|
||||
return OpenRouterChatRequest(
|
||||
model=slug,
|
||||
messages=_build_messages(system_prompt, prompt, media_blocks),
|
||||
seed=seed if seed > 0 else None,
|
||||
reasoning=reasoning_cfg,
|
||||
web_search_options=web_search_cfg,
|
||||
)
|
||||
|
||||
|
||||
def _extract_text(response: OpenRouterChatResponse) -> str:
|
||||
if response.error:
|
||||
code = response.error.code if response.error.code is not None else "unknown"
|
||||
raise ValueError(f"OpenRouter error ({code}): {response.error.message or 'no message'}")
|
||||
if not response.choices:
|
||||
raise ValueError("Empty response from OpenRouter (no choices).")
|
||||
message = response.choices[0].message
|
||||
if not message:
|
||||
raise ValueError("Empty response from OpenRouter (no message).")
|
||||
if message.refusal:
|
||||
raise ValueError(f"Model refused to respond: {message.refusal}")
|
||||
return message.content or ""
|
||||
|
||||
|
||||
class OpenRouterLLMNode(IO.ComfyNode):
|
||||
|
||||
@classmethod
|
||||
def define_schema(cls):
|
||||
return IO.Schema(
|
||||
node_id="OpenRouterLLMNode",
|
||||
display_name="OpenRouter LLM",
|
||||
category="api node/text/OpenRouter",
|
||||
essentials_category="Text Generation",
|
||||
description=(
|
||||
"Generate text responses through OpenRouter. Routes to a curated set of popular "
|
||||
"models from xAI, DeepSeek, Qwen, Mistral, Z.AI (GLM), Moonshot (Kimi), and "
|
||||
"Perplexity Sonar."
|
||||
),
|
||||
inputs=[
|
||||
IO.String.Input(
|
||||
"prompt",
|
||||
multiline=True,
|
||||
default="",
|
||||
tooltip="Text input to the model.",
|
||||
),
|
||||
IO.DynamicCombo.Input(
|
||||
"model",
|
||||
options=_build_model_options(),
|
||||
tooltip="The OpenRouter model used to generate the response.",
|
||||
),
|
||||
IO.Int.Input(
|
||||
"seed",
|
||||
default=0,
|
||||
min=0,
|
||||
max=2147483647,
|
||||
control_after_generate=True,
|
||||
tooltip="Seed for sampling. Set to 0 to omit. Most models treat this as a hint only.",
|
||||
),
|
||||
IO.String.Input(
|
||||
"system_prompt",
|
||||
multiline=True,
|
||||
default="",
|
||||
optional=True,
|
||||
advanced=True,
|
||||
tooltip="Foundational instructions that dictate the model's behavior.",
|
||||
),
|
||||
],
|
||||
outputs=[IO.String.Output()],
|
||||
hidden=[
|
||||
IO.Hidden.auth_token_comfy_org,
|
||||
IO.Hidden.api_key_comfy_org,
|
||||
IO.Hidden.unique_id,
|
||||
],
|
||||
is_api_node=True,
|
||||
price_badge=IO.PriceBadge(
|
||||
depends_on=IO.PriceBadgeDepends(widgets=["model"]),
|
||||
expr=_price_badge_jsonata(),
|
||||
),
|
||||
)
|
||||
|
||||
@classmethod
|
||||
async def execute(
|
||||
cls,
|
||||
prompt: str,
|
||||
model: dict,
|
||||
seed: int,
|
||||
system_prompt: str = "",
|
||||
) -> IO.NodeOutput:
|
||||
validate_string(prompt, strip_whitespace=True, min_length=1)
|
||||
slug: str = model["model"]
|
||||
spec = _MODELS_BY_SLUG.get(slug)
|
||||
if spec is None:
|
||||
raise ValueError(f"Unknown OpenRouter model: {slug}")
|
||||
|
||||
reasoning_effort: str | None = model.get("reasoning_effort")
|
||||
search_context_size: str | None = model.get("search_context_size")
|
||||
|
||||
image_tensors: list[Input.Image] = [t for t in (model.get("images") or {}).values() if t is not None]
|
||||
if image_tensors and sum(get_number_of_images(t) for t in image_tensors) > spec.max_images:
|
||||
raise ValueError(f"Up to {spec.max_images} images are supported for {slug}.")
|
||||
video_inputs: list[Input.Video] = [v for v in (model.get("videos") or {}).values() if v is not None]
|
||||
if video_inputs and len(video_inputs) > spec.max_videos:
|
||||
raise ValueError(f"Up to {spec.max_videos} videos are supported for {slug}.")
|
||||
|
||||
media_blocks: list[OpenRouterContentBlock] = []
|
||||
if image_tensors:
|
||||
media_blocks.extend(await _build_image_blocks(cls, spec, image_tensors))
|
||||
if video_inputs:
|
||||
media_blocks.extend(await _build_video_blocks(cls, video_inputs))
|
||||
|
||||
request = _build_request(
|
||||
slug,
|
||||
system_prompt,
|
||||
prompt,
|
||||
media_blocks,
|
||||
seed=seed,
|
||||
reasoning_effort=reasoning_effort,
|
||||
search_context_size=search_context_size,
|
||||
)
|
||||
|
||||
response = await sync_op(
|
||||
cls,
|
||||
ApiEndpoint(path=OPENROUTER_CHAT_ENDPOINT, method="POST"),
|
||||
response_model=OpenRouterChatResponse,
|
||||
data=request,
|
||||
price_extractor=_calculate_price,
|
||||
)
|
||||
return IO.NodeOutput(_extract_text(response))
|
||||
|
||||
|
||||
class OpenRouterExtension(ComfyExtension):
|
||||
@override
|
||||
async def get_node_list(self) -> list[type[IO.ComfyNode]]:
|
||||
return [OpenRouterLLMNode]
|
||||
|
||||
|
||||
async def comfy_entrypoint() -> OpenRouterExtension:
|
||||
return OpenRouterExtension()
|
||||
@ -77,7 +77,7 @@ class EmptyLTXVLatentVideo(io.ComfyNode):
|
||||
@classmethod
|
||||
def execute(cls, width, height, length, batch_size=1) -> io.NodeOutput:
|
||||
latent = torch.zeros([batch_size, 128, ((length - 1) // 8) + 1, height // 32, width // 32], device=comfy.model_management.intermediate_device())
|
||||
return io.NodeOutput({"samples": latent})
|
||||
return io.NodeOutput({"samples": latent, "downscale_ratio_spacial": 32})
|
||||
|
||||
generate = execute # TODO: remove
|
||||
|
||||
|
||||
@ -1,10 +1,41 @@
|
||||
import re
|
||||
import json
|
||||
import string
|
||||
from typing_extensions import override
|
||||
|
||||
from comfy_api.latest import ComfyExtension, io
|
||||
|
||||
|
||||
class StringFormat(io.ComfyNode):
|
||||
@classmethod
|
||||
def define_schema(cls) -> io.Schema:
|
||||
autogrow = io.Autogrow.TemplateNames(
|
||||
input=io.AnyType.Input("value"),
|
||||
names=list(string.ascii_lowercase),
|
||||
min=0,
|
||||
)
|
||||
return io.Schema(
|
||||
node_id="StringFormat",
|
||||
display_name="Format Text",
|
||||
category="text",
|
||||
search_aliases=["string", "format"],
|
||||
description="Same as Python's string format method. Supports all of Python's format options and features.",
|
||||
inputs=[
|
||||
io.Autogrow.Input("values", template=autogrow),
|
||||
io.String.Input("f_string", default="{a}", multiline=True),
|
||||
],
|
||||
outputs=[
|
||||
io.String.Output(),
|
||||
],
|
||||
)
|
||||
|
||||
@classmethod
|
||||
def execute(
|
||||
cls, values: io.Autogrow.Type, f_string: str
|
||||
) -> io.NodeOutput:
|
||||
return io.NodeOutput(f_string.format(**values))
|
||||
|
||||
|
||||
class StringConcatenate(io.ComfyNode):
|
||||
@classmethod
|
||||
def define_schema(cls):
|
||||
@ -413,6 +444,7 @@ class StringExtension(ComfyExtension):
|
||||
@override
|
||||
async def get_node_list(self) -> list[type[io.ComfyNode]]:
|
||||
return [
|
||||
StringFormat,
|
||||
StringConcatenate,
|
||||
StringSubstring,
|
||||
StringLength,
|
||||
|
||||
22
openapi.yaml
22
openapi.yaml
@ -4160,6 +4160,10 @@ paths:
|
||||
name:
|
||||
type: string
|
||||
description: Display name for the API key
|
||||
description:
|
||||
type: string
|
||||
description: User-provided description of the key's purpose
|
||||
maxLength: 5000
|
||||
responses:
|
||||
"201":
|
||||
description: API key created
|
||||
@ -6351,14 +6355,6 @@ components:
|
||||
type: integer
|
||||
format: int64
|
||||
description: Size of the asset in bytes
|
||||
width:
|
||||
type: integer
|
||||
nullable: true
|
||||
description: "Original image width in pixels. Null for non-image assets or assets ingested before dimension extraction."
|
||||
height:
|
||||
type: integer
|
||||
nullable: true
|
||||
description: "Original image height in pixels. Null for non-image assets or assets ingested before dimension extraction."
|
||||
mime_type:
|
||||
type: string
|
||||
description: MIME type of the asset
|
||||
@ -7685,11 +7681,16 @@ components:
|
||||
required:
|
||||
- id
|
||||
- name
|
||||
- description
|
||||
properties:
|
||||
id:
|
||||
type: string
|
||||
name:
|
||||
type: string
|
||||
description:
|
||||
type: string
|
||||
maxLength: 5000
|
||||
description: User-provided description of the key's purpose. Always present in responses; empty string when no description was supplied on create.
|
||||
prefix:
|
||||
type: string
|
||||
description: First few characters of the key for identification
|
||||
@ -7710,12 +7711,17 @@ components:
|
||||
required:
|
||||
- id
|
||||
- name
|
||||
- description
|
||||
- key
|
||||
properties:
|
||||
id:
|
||||
type: string
|
||||
name:
|
||||
type: string
|
||||
description:
|
||||
type: string
|
||||
maxLength: 5000
|
||||
description: User-provided description of the key's purpose. Always present in responses; empty string when no description was supplied on create.
|
||||
key:
|
||||
type: string
|
||||
description: Full API key value (only returned on creation)
|
||||
|
||||
Reference in New Issue
Block a user