Merge pull request #130 from Runware/feature-textInference-settings
Add Zai GLM text model and expand text inference settings
This commit is contained in:
Sirshendu Ganguly
+19
-1
@@ -1337,7 +1337,7 @@ function textInferenceSettingsToggleHandler(settingsNode) {
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if (!settingsNode?.widgets) return;
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const useSystemPromptWidget = settingsNode.widgets.find(w => w && w.name === "useSystemPrompt");
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const systemWidget = settingsNode.widgets.find(w => w && w.name === "system");
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const systemWidget = settingsNode.widgets.find(w => w && (w.name === "systemPrompt" || w.name === "system"));
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const useMaxTokensWidget = settingsNode.widgets.find(w => w && w.name === "useMaxTokens");
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const maxTokensWidget = settingsNode.widgets.find(w => w && w.name === "maxTokens");
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const useTemperatureWidget = settingsNode.widgets.find(w => w && w.name === "useTemperature");
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@@ -1346,6 +1346,16 @@ function textInferenceSettingsToggleHandler(settingsNode) {
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const topPWidget = settingsNode.widgets.find(w => w && w.name === "topP");
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const useTopKWidget = settingsNode.widgets.find(w => w && w.name === "useTopK");
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const topKWidget = settingsNode.widgets.find(w => w && w.name === "topK");
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const useStopSequencesWidget = settingsNode.widgets.find(w => w && w.name === "useStopSequences");
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const stopSequencesWidget = settingsNode.widgets.find(w => w && w.name === "stopSequences");
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const usePresencePenaltyWidget = settingsNode.widgets.find(w => w && w.name === "usePresencePenalty");
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const presencePenaltyWidget = settingsNode.widgets.find(w => w && w.name === "presencePenalty");
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const useFrequencyPenaltyWidget = settingsNode.widgets.find(w => w && w.name === "useFrequencyPenalty");
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const frequencyPenaltyWidget = settingsNode.widgets.find(w => w && w.name === "frequencyPenalty");
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const useToolsWidget = settingsNode.widgets.find(w => w && w.name === "useTools");
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const toolsWidget = settingsNode.widgets.find(w => w && w.name === "tools");
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const useToolChoiceWidget = settingsNode.widgets.find(w => w && w.name === "useToolChoice");
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const toolChoiceWidget = settingsNode.widgets.find(w => w && w.name === "toolChoice");
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function toggleWidgetState(useWidget, paramWidget) {
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if (!useWidget || !paramWidget) return;
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@@ -1368,6 +1378,11 @@ function textInferenceSettingsToggleHandler(settingsNode) {
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if (useTemperatureWidget && temperatureWidget) toggleWidgetState(useTemperatureWidget, temperatureWidget);
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if (useTopPWidget && topPWidget) toggleWidgetState(useTopPWidget, topPWidget);
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if (useTopKWidget && topKWidget) toggleWidgetState(useTopKWidget, topKWidget);
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if (useStopSequencesWidget && stopSequencesWidget) toggleWidgetState(useStopSequencesWidget, stopSequencesWidget);
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if (usePresencePenaltyWidget && presencePenaltyWidget) toggleWidgetState(usePresencePenaltyWidget, presencePenaltyWidget);
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if (useFrequencyPenaltyWidget && frequencyPenaltyWidget) toggleWidgetState(useFrequencyPenaltyWidget, frequencyPenaltyWidget);
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if (useToolsWidget && toolsWidget) toggleWidgetState(useToolsWidget, toolsWidget);
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if (useToolChoiceWidget && toolChoiceWidget) toggleWidgetState(useToolChoiceWidget, toolChoiceWidget);
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}
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function videoSettingsToggleHandler(settingsNode) {
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@@ -3047,6 +3062,9 @@ function textModelSearchFilterHandler(textModelSearchNode) {
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"Google": [
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"google:gemini@3-flash (Gemini 3 Flash)",
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],
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"Zai": [
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"zai-glm-5-1 (ZAI GLM 5.1)",
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],
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};
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function filterModelList() {
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@@ -1,11 +1,15 @@
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from typing import Any, Dict, Tuple
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import json
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from typing import Any, Dict, List, Tuple
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class RunwareTextInferenceSettings:
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"""Optional generation controls for Runware Text Inference (flat task.settings per API)."""
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_MAX_SYSTEM_CHARS = 200000
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_MAX_TOKENS_CAP = 196608
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_MAX_TOKENS_CAP = 131072
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_MAX_TOP_K = 100647
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_MAX_STOP_ITEMS = 5
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_MAX_STOP_ITEM_CHARS = 50
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@classmethod
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def INPUT_TYPES(cls):
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@@ -16,17 +20,17 @@ class RunwareTextInferenceSettings:
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"default": False,
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"tooltip": "Include systemPrompt in settings.",
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}),
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"system": ("STRING", {
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"systemPrompt": ("STRING", {
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"multiline": True,
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"default": "",
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"tooltip": "System instruction (max 200,000 characters). Sent as systemPrompt.",
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"tooltip": "System instruction (max 200,000 chars).",
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}),
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"useMaxTokens": ("BOOLEAN", {
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"default": False,
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"tooltip": "Include maxTokens in settings.",
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}),
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"maxTokens": ("INT", {
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"default": 32768,
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"default": 4096,
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"min": 1,
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"max": cls._MAX_TOKENS_CAP,
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"step": 1,
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@@ -38,21 +42,21 @@ class RunwareTextInferenceSettings:
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}),
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"temperature": ("FLOAT", {
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"default": 1.0,
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"min": 0.01,
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"min": 0.0,
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"max": 1.0,
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"step": 0.01,
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"tooltip": "Sampling temperature on (0, 1].",
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"tooltip": "Sampling temperature (0.0–1.0).",
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}),
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"useTopP": ("BOOLEAN", {
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"default": False,
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"tooltip": "Include topP in settings.",
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}),
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"topP": ("FLOAT", {
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"default": 0.95,
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"min": 0.0,
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"default": 1.0,
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"min": 0.01,
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"max": 1.0,
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"step": 0.01,
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"tooltip": "Nucleus sampling (0.0–1.0).",
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"tooltip": "Nucleus sampling (0.01–1.0).",
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}),
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"useTopK": ("BOOLEAN", {
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"default": False,
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@@ -61,13 +65,63 @@ class RunwareTextInferenceSettings:
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"topK": ("INT", {
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"default": 40,
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"min": 1,
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"max": 128,
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"max": cls._MAX_TOP_K,
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"step": 1,
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"tooltip": "Top-k sampling (1–128).",
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"tooltip": f"Top-k sampling (1–{cls._MAX_TOP_K}).",
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}),
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"thinkingLevel": (["off", "minimal", "low", "medium", "high"], {
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"default": "off",
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"tooltip": "thinkingLevel in settings (omit when off).",
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# Keep this in the original slot to avoid shifting legacy widgets_values.
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"thinkingLevel": (["none", "low", "medium", "high"], {
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"default": "none",
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"tooltip": "Extended reasoning level: none, low, medium, high.",
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}),
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"useStopSequences": ("BOOLEAN", {
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"default": False,
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"tooltip": "Include stopSequences in settings.",
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}),
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"stopSequences": ("STRING", {
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"multiline": True,
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"default": "",
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"tooltip": "Stop sequences: one per line (max 5 items, 50 chars each).",
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}),
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"usePresencePenalty": ("BOOLEAN", {
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"default": False,
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"tooltip": "Include presencePenalty in settings.",
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}),
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"presencePenalty": ("FLOAT", {
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"default": 0.0,
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"min": -2.0,
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"max": 2.0,
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"step": 0.01,
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"tooltip": "Presence penalty (-2.0 to 2.0).",
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}),
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"useFrequencyPenalty": ("BOOLEAN", {
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"default": False,
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"tooltip": "Include frequencyPenalty in settings.",
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}),
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"frequencyPenalty": ("FLOAT", {
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"default": 0.0,
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"min": -2.0,
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"max": 2.0,
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"step": 0.01,
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"tooltip": "Frequency penalty (-2.0 to 2.0).",
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}),
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"useTools": ("BOOLEAN", {
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"default": False,
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"tooltip": "Include tools in settings.",
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}),
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"tools": ("STRING", {
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"multiline": True,
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"default": "[]",
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"tooltip": "JSON array for tools.",
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}),
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"useToolChoice": ("BOOLEAN", {
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"default": False,
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"tooltip": "Include toolChoice in settings.",
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}),
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"toolChoice": ("STRING", {
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"multiline": True,
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"default": "{}",
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"tooltip": "JSON object for toolChoice.",
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}),
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},
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}
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@@ -77,34 +131,115 @@ class RunwareTextInferenceSettings:
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FUNCTION = "create_settings"
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CATEGORY = "Runware/Text"
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DESCRIPTION = (
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"Optional text inference settings (flat: systemPrompt, maxTokens, temperature, topP, topK, thinkingLevel). "
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"Optional text inference settings (systemPrompt, maxTokens, temperature, topP, topK, "
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"stopSequences, presencePenalty, frequencyPenalty, tools, toolChoice, thinkingLevel). "
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"Connect to Runware Text Inference."
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)
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@staticmethod
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def _parse_json_setting(raw: Any, expected_type: type, field_name: str) -> Any:
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if isinstance(raw, expected_type):
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return raw
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if raw is None:
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return expected_type()
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text = str(raw).strip()
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if not text:
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return expected_type()
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try:
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parsed = json.loads(text)
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except Exception as exc:
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raise Exception(f"{field_name} must be valid JSON.") from exc
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if not isinstance(parsed, expected_type):
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expected = "array" if expected_type is list else "object"
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raise Exception(f"{field_name} must be a JSON {expected}.")
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return parsed
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def _parse_stop_sequences(self, raw: Any) -> List[str]:
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if raw is None:
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return []
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items: List[str] = []
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if isinstance(raw, (list, tuple)):
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for item in raw:
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text = str(item).strip()
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if text:
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items.append(text)
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else:
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text = str(raw).strip()
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if text:
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normalized = text.replace("\r\n", "\n").replace(",", "\n")
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items = [segment.strip() for segment in normalized.split("\n") if segment.strip()]
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if len(items) > self._MAX_STOP_ITEMS:
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raise Exception(f"stopSequences supports up to {self._MAX_STOP_ITEMS} items.")
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for idx, item in enumerate(items, start=1):
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if len(item) > self._MAX_STOP_ITEM_CHARS:
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raise Exception(
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f"stopSequences item {idx} exceeds {self._MAX_STOP_ITEM_CHARS} characters."
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)
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return items
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@staticmethod
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def _normalize_thinking_level(raw: Any) -> str:
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value = str(raw or "none").strip().lower()
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# Backward compatibility with older workflows.
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aliases = {
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"off": "none",
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"minimal": "low",
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}
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value = aliases.get(value, value)
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if value not in ("none", "low", "medium", "high"):
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return "none"
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return value
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def create_settings(self, **kwargs) -> Tuple[Dict[str, Any], ...]:
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out: Dict[str, Any] = {}
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if kwargs.get("useSystemPrompt", False):
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sys_text = (kwargs.get("system") or "").strip()
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sys_text = (kwargs.get("systemPrompt") or kwargs.get("system") or "").strip()
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if sys_text:
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if len(sys_text) > self._MAX_SYSTEM_CHARS:
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sys_text = sys_text[: self._MAX_SYSTEM_CHARS]
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out["systemPrompt"] = sys_text
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if kwargs.get("useMaxTokens", False):
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out["maxTokens"] = int(kwargs.get("maxTokens", 32768))
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out["maxTokens"] = int(kwargs.get("maxTokens", 4096))
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if kwargs.get("useTemperature", False):
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out["temperature"] = float(kwargs.get("temperature", 1.0))
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if kwargs.get("useTopP", False):
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out["topP"] = float(kwargs.get("topP", 0.95))
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out["topP"] = float(kwargs.get("topP", 1.0))
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if kwargs.get("useTopK", False):
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out["topK"] = int(kwargs.get("topK", 40))
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tl = kwargs.get("thinkingLevel", "off")
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if tl != "off":
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if kwargs.get("useStopSequences", False):
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parsed_stop = self._parse_stop_sequences(kwargs.get("stopSequences", ""))
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if parsed_stop:
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out["stopSequences"] = parsed_stop
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if kwargs.get("usePresencePenalty", False):
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out["presencePenalty"] = float(kwargs.get("presencePenalty", 0.0))
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if kwargs.get("useFrequencyPenalty", False):
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out["frequencyPenalty"] = float(kwargs.get("frequencyPenalty", 0.0))
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if kwargs.get("useTools", False):
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parsed_tools = self._parse_json_setting(kwargs.get("tools"), list, "tools")
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if parsed_tools:
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out["tools"] = parsed_tools
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if kwargs.get("useToolChoice", False):
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parsed_choice = self._parse_json_setting(kwargs.get("toolChoice"), dict, "toolChoice")
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if parsed_choice:
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out["toolChoice"] = parsed_choice
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tl = self._normalize_thinking_level(kwargs.get("thinkingLevel", "none"))
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if tl != "none":
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out["thinkingLevel"] = tl
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if not out:
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@@ -16,6 +16,9 @@ class RunwareTextModelSearch:
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"Google": [
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"google:gemini@3-flash (Gemini 3 Flash)",
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],
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"Zai": [
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"zai-glm-5-1 (ZAI GLM 5.1)",
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],
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}
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MODEL_PROVIDERS = [
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@@ -23,6 +26,7 @@ class RunwareTextModelSearch:
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"Google",
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"MiniMax",
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"OpenAI",
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"Zai",
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]
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@classmethod
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