Added support for Anthropic models
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"""
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Runware Text Inference Settings Cache Node
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Builds the cache object for Runware Text Inference (settings.cache.{scope, ttl}).
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Maps cache_control placement (Anthropic):
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- scope: where cache_control is attached
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* system -> system block only
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* system+history -> system block + last user message block (default)
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- ttl: cache lifetime (5m or 1h)
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"""
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from typing import Dict, Any
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class RunwareTextInferenceSettingsCache:
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"""Runware Text Inference Settings Cache node."""
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@classmethod
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def INPUT_TYPES(cls):
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return {
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"required": {
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"scope": (["system", "system+history"], {
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"default": "system+history",
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"tooltip": (
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"Where cache_control is attached.\n"
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"- system: cache the system block only.\n"
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"- system+history: cache the system block and the last user message block."
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),
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}),
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"ttl": (["5m", "1h"], {
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"default": "5m",
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"tooltip": "Cache lifetime: 5m (5 minutes) or 1h (1 hour).",
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}),
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}
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}
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RETURN_TYPES = ("RUNWARETEXTINFERENCESETTINGSCACHE",)
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RETURN_NAMES = ("cache",)
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FUNCTION = "createCache"
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CATEGORY = "Runware/Text"
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DESCRIPTION = (
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"Build a settings.cache object (scope + ttl) and connect it to Runware Text Inference. "
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"Merged into the request as settings.cache.{scope, ttl}."
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)
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def createCache(self, **kwargs) -> tuple[Dict[str, Any]]:
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scope = (kwargs.get("scope") or "system+history").strip().lower()
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if scope not in ("system", "system+history"):
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scope = "system+history"
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ttl = (kwargs.get("ttl") or "5m").strip().lower()
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if ttl not in ("5m", "1h"):
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ttl = "5m"
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return ({"scope": scope, "ttl": ttl},)
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NODE_CLASS_MAPPINGS = {
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"RunwareTextInferenceSettingsCache": RunwareTextInferenceSettingsCache,
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}
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NODE_DISPLAY_NAME_MAPPINGS = {
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"RunwareTextInferenceSettingsCache": "Runware Text Inference Settings Cache",
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}
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