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Added support for Anthropic models

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This commit is contained in:
Sirshendu Ganguly
2026-05-08 15:25:45 +05:30
parent 100644fdfb
commit 4ed18c2fa0
12 changed files with 363 additions and 5 deletions
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__init__.py
+10
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@@ -53,6 +53,11 @@ from .modules.textInferenceMessages import RunwareTextInferenceMessages
from .modules.textInferenceMessage import RunwareTextInferenceMessage
from .modules.textInference import RunwareTextInference
from .modules.textInferenceSettings import RunwareTextInferenceSettings
from .modules.textInferenceToolChoice import RunwareTextInferenceToolChoice
from .modules.textInferenceSettingsCache import RunwareTextInferenceSettingsCache
from .modules.textInferenceInputs import RunwareTextInferenceInputs
from .modules.textInferenceInputsImages import RunwareTextInferenceInputsImages
from .modules.textInferenceInputsVideos import RunwareTextInferenceInputsVideos
from .modules.audioSections import RunwareAudioSections
from .modules.audioInferenceInputs import audioInferenceInputs
from .modules.audioSettings import RunwareAudioSettings
@@ -177,6 +182,11 @@ NODE_CLASS_MAPPINGS = {
"Runware Text Inference Message": RunwareTextInferenceMessage,
"Runware Text Inference": RunwareTextInference,
"Runware Text Inference Settings": RunwareTextInferenceSettings,
"Runware Text Inference Tool Choice": RunwareTextInferenceToolChoice,
"Runware Text Inference Settings Cache": RunwareTextInferenceSettingsCache,
"Runware Text Inference Inputs": RunwareTextInferenceInputs,
"Runware Text Inference Inputs Images": RunwareTextInferenceInputsImages,
"Runware Text Inference Inputs Videos": RunwareTextInferenceInputsVideos,
"Runware Audio Sections": RunwareAudioSections,
"Runware Audio Inference Inputs": audioInferenceInputs,
"Runware Audio Inference Settings": RunwareAudioSettings,
clientlibs/types.js
+25
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@@ -89,6 +89,11 @@ const RUNWARE_NODE_TYPES = {
TEXTINFERENCEMESSAGES: "Runware Text Inference Messages",
TEXTINFERENCEMESSAGE: "Runware Text Inference Message",
TEXTINFERENCESETTINGS: "Runware Text Inference Settings",
TEXTINFERENCETOOLCHOICE: "Runware Text Inference Tool Choice",
TEXTINFERENCESETTINGSCACHE: "Runware Text Inference Settings Cache",
TEXTINFERENCEINPUTS: "Runware Text Inference Inputs",
TEXTINFERENCEINPUTSIMAGES: "Runware Text Inference Inputs Images",
TEXTINFERENCEINPUTSVIDEOS: "Runware Text Inference Inputs Videos",
AUDIOSECTIONS: "Runware Audio Sections",
AUDIOINFERENCEINPUTS: "Runware Audio Inference Inputs",
AUDIOSETTINGS: "Runware Audio Inference Settings",
@@ -328,6 +333,26 @@ const RUNWARE_NODE_PROPS = {
bgColor: DEFAULT_BGCOLOR,
colorModeOnly: true,
},
[RUNWARE_NODE_TYPES.TEXTINFERENCETOOLCHOICE]: {
bgColor: DEFAULT_BGCOLOR,
colorModeOnly: true,
},
[RUNWARE_NODE_TYPES.TEXTINFERENCESETTINGSCACHE]: {
bgColor: DEFAULT_BGCOLOR,
colorModeOnly: true,
},
[RUNWARE_NODE_TYPES.TEXTINFERENCEINPUTSIMAGES]: {
bgColor: DEFAULT_BGCOLOR,
colorModeOnly: true,
},
[RUNWARE_NODE_TYPES.TEXTINFERENCEINPUTSVIDEOS]: {
bgColor: DEFAULT_BGCOLOR,
colorModeOnly: true,
},
[RUNWARE_NODE_TYPES.TEXTINFERENCEINPUTS]: {
bgColor: DEFAULT_BGCOLOR,
colorModeOnly: true,
},
[RUNWARE_NODE_TYPES.TEXTINFERENCESETTINGS]: {
bgColor: DEFAULT_BGCOLOR,
colorModeOnly: true,
clientlibs/utils.js
+5
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@@ -3275,6 +3275,11 @@ function textModelSearchFilterHandler(textModelSearchNode) {
"openai:gpt@5.4-mini (GPT-5.4 Mini)",
"openai:gpt@5.4-nano (GPT-5.4 Nano)",
],
"Anthropic": [
"anthropic:claude@opus-4.7 (Claude Opus 4.7)",
"anthropic:claude@sonnet-4.6 (Claude Sonnet 4.6)",
"anthropic:claude@haiku-4.5 (Claude Haiku 4.5)",
],
"Google": [
"google:gemini@3-flash (Gemini 3 Flash)",
],
modules/textInference.py
+15 -1
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@@ -25,6 +25,12 @@ class RunwareTextInference:
"providerSettings": ("RUNWAREPROVIDERSETTINGS", {
"tooltip": "Optional provider-specific settings (wrapped by provider prefix from the model AIR).",
}),
"toolChoice": ("RUNWARETEXTINFERENCETOOLCHOICE", {
"tooltip": "Connect Runware Text Inference Tool Choice for tool-calling strategy (auto / any / tool / none).",
}),
"inputs": ("RUNWARETEXTINFERENCEINPUTS", {
"tooltip": "Connect Runware Text Inference Inputs for inputs.images / inputs.videos (URLs or mediaUUIDs).",
}),
},
}
@@ -32,7 +38,7 @@ class RunwareTextInference:
RETURN_NAMES = ("text",)
FUNCTION = "infer_text"
CATEGORY = "Runware/Text"
DESCRIPTION = "Run text/chat inference using Runware textInference. Connect Text Model and Text Inference Messages."
DESCRIPTION = "Run text/chat inference using Runware textInference. Connect Text Model and Text Inference Messages. Optional: Settings, provider settings, tool choice, inputs (images/videos)."
@staticmethod
def _extract_text_from_data_item(item: Dict[str, Any]) -> Optional[str]:
@@ -70,6 +76,8 @@ class RunwareTextInference:
messages: List[Dict[str, str]] = kwargs.get("messages") or []
text_settings = kwargs.get("settings")
provider_settings = kwargs.get("providerSettings")
tool_choice = kwargs.get("toolChoice")
text_inputs = kwargs.get("inputs")
if not model:
raise Exception("model is empty.")
@@ -94,6 +102,12 @@ class RunwareTextInference:
provider_name = model.split(":")[0] if ":" in model else model
task["providerSettings"] = {provider_name: provider_settings}
if tool_choice is not None and isinstance(tool_choice, dict) and len(tool_choice) > 0:
task["toolChoice"] = tool_choice
if text_inputs is not None and isinstance(text_inputs, dict) and len(text_inputs) > 0:
task["inputs"] = dict(text_inputs)
gen_config = [task]
print(f"[Runware Text Inference] Request: {rwUtils.safe_json_dumps(gen_config, indent=2)}")
modules/textInferenceInputs.py
+48
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@@ -0,0 +1,48 @@
"""Runware Text Inference Inputs — merge Images + Videos blocks into task.inputs for textInference."""
from typing import Any, Dict, Tuple
class RunwareTextInferenceInputs:
"""Merge Runware Text Inference Inputs Images and/or Videos into a single inputs dict."""
@classmethod
def INPUT_TYPES(cls):
return {
"required": {},
"optional": {
"images": ("RUNWARETEXTINFERENCEINPUTSIMAGES", {
"tooltip": "Connect Runware Text Inference Inputs Images for inputs.images[].",
}),
"videos": ("RUNWARETEXTINFERENCEINPUTSVIDEOS", {
"tooltip": "Connect Runware Text Inference Inputs Videos for inputs.videos[].",
}),
},
}
RETURN_TYPES = ("RUNWARETEXTINFERENCEINPUTS",)
RETURN_NAMES = ("inputs",)
FUNCTION = "merge_inputs"
CATEGORY = "Runware/Text"
DESCRIPTION = (
"Combine Runware Text Inference Inputs Images and/or Videos into inputs for Runware Text Inference "
"(inputs.images, inputs.videos)."
)
def merge_inputs(self, **kwargs) -> Tuple[Dict[str, Any], ...]:
images_block = kwargs.get("images")
videos_block = kwargs.get("videos")
out: Dict[str, Any] = {}
if isinstance(images_block, dict) and images_block.get("images"):
imgs = images_block["images"]
if isinstance(imgs, list) and len(imgs) > 0:
out["images"] = [str(x).strip() for x in imgs if x is not None and str(x).strip()]
if isinstance(videos_block, dict) and videos_block.get("videos"):
vids = videos_block["videos"]
if isinstance(vids, list) and len(vids) > 0:
out["videos"] = [str(x).strip() for x in vids if x is not None and str(x).strip()]
return (out,)
modules/textInferenceInputsImages.py
+50
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@@ -0,0 +1,50 @@
"""Runware Text Inference Inputs Images — builds inputs.images from ComfyUI IMAGE tensors."""
from typing import Any, Dict, List, Tuple
from .utils import runwareUtils as rwUtils
class RunwareTextInferenceInputsImages:
"""Collect IMAGE tensors and convert them for textInference task.inputs.images.
Each connected IMAGE is converted via runwareUtils.convertTensor2IMG, which returns
either a cached mediaUUID (when caching is enabled) or a base64 data URI.
"""
_MAX_IMAGES = 8
@classmethod
def INPUT_TYPES(cls):
optional: Dict[str, tuple] = {}
for i in range(1, cls._MAX_IMAGES + 1):
ordinal = rwUtils.getOrdinal(i)
optional[f"Image {i}"] = ("IMAGE", {
"tooltip": (
f"{ordinal.capitalize()} image for the model. Connect a Load Image (or any IMAGE source) node. "
"Tensor is converted to base64 / mediaUUID before being sent to the API."
),
})
return {"required": {}, "optional": optional}
RETURN_TYPES = ("RUNWARETEXTINFERENCEINPUTSIMAGES",)
RETURN_NAMES = ("images",)
FUNCTION = "createImages"
CATEGORY = "Runware/Text"
DESCRIPTION = (
"Collect one or more IMAGE tensors (Load Image, generated images, etc.) for Runware Text Inference "
"inputs.images. Connect the output to Runware Text Inference Inputs."
)
def createImages(self, **kwargs) -> Tuple[Dict[str, Any], ...]:
urls: List[str] = []
for i in range(1, self._MAX_IMAGES + 1):
tensor = kwargs.get(f"Image {i}", None)
if tensor is None:
continue
urls.append(rwUtils.convertTensor2IMG(tensor))
if not urls:
return ({},)
return ({"images": urls},)
modules/textInferenceInputsVideos.py
+51
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@@ -0,0 +1,51 @@
"""Runware Text Inference Inputs Videos — builds inputs.videos (URL or mediaUUID per item)."""
from typing import Any, Dict, List, Tuple
from .utils import runwareUtils as rwUtils
class RunwareTextInferenceInputsVideos:
"""Collect video references for textInference task.inputs.videos."""
_MAX_VIDEOS = 4
@classmethod
def INPUT_TYPES(cls):
optional: Dict[str, tuple] = {
"useVideos": ("BOOLEAN", {
"default": False,
"tooltip": "Enable to include inputs.videos in the text inference request.",
}),
}
for i in range(1, cls._MAX_VIDEOS + 1):
ordinal = rwUtils.getOrdinal(i)
optional[f"Video{i}"] = ("STRING", {
"default": "",
"tooltip": f"Video URL or mediaUUID for the {ordinal} video. Only used when 'Use Videos' is enabled.",
})
return {"required": {}, "optional": optional}
RETURN_TYPES = ("RUNWARETEXTINFERENCEINPUTSVIDEOS",)
RETURN_NAMES = ("videos",)
FUNCTION = "createVideos"
CATEGORY = "Runware/Text"
DESCRIPTION = (
"Collect one or more video references (URL or mediaUUID) for Runware Text Inference "
"inputs.videos. Connect the output to Runware Text Inference Inputs."
)
def createVideos(self, **kwargs) -> Tuple[Dict[str, Any], ...]:
if not kwargs.get("useVideos", False):
return ({},)
urls: List[str] = []
for i in range(1, self._MAX_VIDEOS + 1):
raw = kwargs.get(f"Video{i}", "")
if raw is not None and str(raw).strip():
urls.append(str(raw).strip())
if not urls:
return ({},)
return ({"videos": urls},)
modules/textInferenceSettings.py
+15 -4
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@@ -70,9 +70,13 @@ class RunwareTextInferenceSettings:
"tooltip": f"Top-k sampling (1–{cls._MAX_TOP_K}).",
}),
# Keep this in the original slot to avoid shifting legacy widgets_values.
"thinkingLevel": (["none", "low", "medium", "high"], {
"thinkingLevel": (["none", "low", "medium", "high", "max", "adaptive"], {
"default": "none",
"tooltip": "Extended reasoning level: none, low, medium, high.",
"tooltip": (
"Extended reasoning level: none, low, medium, high, max, adaptive. "
"off -> disabled. low/medium/high/max -> adaptive thinking with the chosen effort. "
"adaptive -> model picks budget."
),
}),
"useStopSequences": ("BOOLEAN", {
"default": False,
@@ -123,6 +127,9 @@ class RunwareTextInferenceSettings:
"default": "{}",
"tooltip": "JSON object for toolChoice.",
}),
"cache": ("RUNWARETEXTINFERENCESETTINGSCACHE", {
"tooltip": "Connect Runware Text Inference Settings Cache for settings.cache.{scope, ttl}.",
}),
},
}
@@ -132,7 +139,7 @@ class RunwareTextInferenceSettings:
CATEGORY = "Runware/Text"
DESCRIPTION = (
"Optional text inference settings (systemPrompt, maxTokens, temperature, topP, topK, "
"stopSequences, presencePenalty, frequencyPenalty, tools, toolChoice, thinkingLevel). "
"stopSequences, presencePenalty, frequencyPenalty, tools, toolChoice, thinkingLevel, cache). "
"Connect to Runware Text Inference."
)
@@ -191,7 +198,7 @@ class RunwareTextInferenceSettings:
"minimal": "low",
}
value = aliases.get(value, value)
if value not in ("none", "low", "medium", "high"):
if value not in ("none", "low", "medium", "high", "max", "adaptive"):
return "none"
return value
@@ -242,6 +249,10 @@ class RunwareTextInferenceSettings:
if tl != "none":
out["thinkingLevel"] = tl
cache_cfg = kwargs.get("cache")
if cache_cfg is not None and isinstance(cache_cfg, dict) and len(cache_cfg) > 0:
out["cache"] = cache_cfg
if not out:
return ({},)
modules/textInferenceSettingsCache.py
+64
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@@ -0,0 +1,64 @@
"""
Runware Text Inference Settings Cache Node
Builds the cache object for Runware Text Inference (settings.cache.{scope, ttl}).
Maps cache_control placement (Anthropic):
- scope: where cache_control is attached
* system -> system block only
* system+history -> system block + last user message block (default)
- ttl: cache lifetime (5m or 1h)
"""
from typing import Dict, Any
class RunwareTextInferenceSettingsCache:
"""Runware Text Inference Settings Cache node."""
@classmethod
def INPUT_TYPES(cls):
return {
"required": {
"scope": (["system", "system+history"], {
"default": "system+history",
"tooltip": (
"Where cache_control is attached.\n"
"- system: cache the system block only.\n"
"- system+history: cache the system block and the last user message block."
),
}),
"ttl": (["5m", "1h"], {
"default": "5m",
"tooltip": "Cache lifetime: 5m (5 minutes) or 1h (1 hour).",
}),
}
}
RETURN_TYPES = ("RUNWARETEXTINFERENCESETTINGSCACHE",)
RETURN_NAMES = ("cache",)
FUNCTION = "createCache"
CATEGORY = "Runware/Text"
DESCRIPTION = (
"Build a settings.cache object (scope + ttl) and connect it to Runware Text Inference. "
"Merged into the request as settings.cache.{scope, ttl}."
)
def createCache(self, **kwargs) -> tuple[Dict[str, Any]]:
scope = (kwargs.get("scope") or "system+history").strip().lower()
if scope not in ("system", "system+history"):
scope = "system+history"
ttl = (kwargs.get("ttl") or "5m").strip().lower()
if ttl not in ("5m", "1h"):
ttl = "5m"
return ({"scope": scope, "ttl": ttl},)
NODE_CLASS_MAPPINGS = {
"RunwareTextInferenceSettingsCache": RunwareTextInferenceSettingsCache,
}
NODE_DISPLAY_NAME_MAPPINGS = {
"RunwareTextInferenceSettingsCache": "Runware Text Inference Settings Cache",
}
modules/textInferenceToolChoice.py
+73
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@@ -0,0 +1,73 @@
"""
Runware Text Inference Tool Choice Node
Builds the toolChoice object for Runware Text Inference (textInference).
Strategies (type):
- auto: model decides whether to call a tool (recommended default)
- any: model must call at least one tool but chooses which one
- tool: model must call the specific tool identified by `name`
- none: model will not call any tool
"""
from typing import Dict, Any
class RunwareTextInferenceToolChoice:
"""Runware Text Inference Tool Choice node."""
@classmethod
def INPUT_TYPES(cls):
return {
"required": {
"type": (["auto", "any", "tool", "none"], {
"default": "auto",
"tooltip": (
"Strategy the model uses to decide when and which tools to call.\n"
"- auto: model decides (recommended default).\n"
"- any: model must call at least one tool, of its choosing.\n"
"- tool: model must call the specific tool named below.\n"
"- none: model will not call any tool."
),
}),
"name": ("STRING", {
"default": "",
"tooltip": "Name of the specific tool the model must call. Required when type is 'tool'; ignored otherwise.",
}),
}
}
RETURN_TYPES = ("RUNWARETEXTINFERENCETOOLCHOICE",)
RETURN_NAMES = ("toolChoice",)
FUNCTION = "createToolChoice"
CATEGORY = "Runware/Text"
DESCRIPTION = (
"Build a toolChoice object (type + optional tool name) and connect it to "
"Runware Text Inference. Required when type is 'tool'."
)
def createToolChoice(self, **kwargs) -> tuple[Dict[str, Any]]:
choice_type = (kwargs.get("type") or "auto").strip().lower()
if choice_type not in ("auto", "any", "tool", "none"):
choice_type = "auto"
name = (kwargs.get("name") or "").strip()
result: Dict[str, Any] = {"type": choice_type}
if choice_type == "tool":
if not name:
raise Exception(
"Tool Choice: 'name' is required when type is 'tool'. "
"Provide the exact tool name the model must call."
)
result["name"] = name
return (result,)
NODE_CLASS_MAPPINGS = {
"RunwareTextInferenceToolChoice": RunwareTextInferenceToolChoice,
}
NODE_DISPLAY_NAME_MAPPINGS = {
"RunwareTextInferenceToolChoice": "Runware Text Inference Tool Choice",
}
modules/textModelSearch.py
+6
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@@ -13,6 +13,11 @@ class RunwareTextModelSearch:
"openai:gpt@5.4-mini (GPT-5.4 Mini)",
"openai:gpt@5.4-nano (GPT-5.4 Nano)",
],
"Anthropic": [
"anthropic:claude@opus-4.7 (Claude Opus 4.7)",
"anthropic:claude@sonnet-4.6 (Claude Sonnet 4.6)",
"anthropic:claude@haiku-4.5 (Claude Haiku 4.5)",
],
"Google": [
"google:gemini@3-flash (Gemini 3 Flash)",
],
@@ -23,6 +28,7 @@ class RunwareTextModelSearch:
MODEL_PROVIDERS = [
"All",
"Anthropic",
"Google",
"MiniMax",
"OpenAI",
workflows/Runware_Text_Inference_Anthropic.json
+1
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