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ai: refractor api formats
This commit is contained in:
end-4
parent
27eea1c7a6
commit
c8b007631d
6 changed files with 379 additions and 280 deletions
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@ -7,6 +7,7 @@ import qs
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import Quickshell
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import Quickshell.Io
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import QtQuick
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import "./ai/"
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/**
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* Basic service to handle LLM chats. Supports Google's and OpenAI's API formats.
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@ -14,9 +15,13 @@ import QtQuick
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Singleton {
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id: root
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property Component aiMessageComponent: AiMessageData {}
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property Component aiModelComponent: AiModel {}
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property Component geminiApiStrategy: GeminiApiStrategy {}
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property Component openaiApiStrategy: OpenAiApiStrategy {}
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readonly property string interfaceRole: "interface"
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readonly property string apiKeyEnvVarName: "API_KEY"
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property Component aiMessageComponent: AiMessageData {}
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property string systemPrompt: Config.options?.ai?.systemPrompt ?? ""
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// property var messages: []
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property var messageIDs: []
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@ -126,7 +131,7 @@ Singleton {
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// - tools: List of tools that the model can use. Each tool is an object with the tool name as the key and an empty object as the value.
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// - extraParams: Extra parameters to be passed to the model. This is a JSON object.
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property var models: {
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"gemini-2.0-flash-search": {
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"gemini-2.0-flash-search": aiModelComponent.createObject(this, {
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"name": "Gemini 2.0 Flash (Search)",
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"icon": "google-gemini-symbolic",
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"description": Translation.tr("Online | Google's model\nGives up-to-date information with search."),
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@ -141,8 +146,8 @@ Singleton {
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"tools": [{
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"google_search": {}
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}]
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},
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"gemini-2.0-flash-tools": {
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}),
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"gemini-2.0-flash-tools": aiModelComponent.createObject(this, {
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"name": "Gemini 2.0 Flash (Tools)",
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"icon": "google-gemini-symbolic",
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"description": Translation.tr("Experimental | Online | Google's model\nCan do a little more but takes an extra turn to perform search"),
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@ -155,8 +160,8 @@ Singleton {
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"key_get_description": Translation.tr("**Pricing**: free. Data used for training.\n\n**Instructions**: Log into Google account, allow AI Studio to create Google Cloud project or whatever it asks, go back and click Get API key"),
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"api_format": "gemini",
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"tools": root.tools["gemini"],
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},
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"gemini-2.5-flash-search": {
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}),
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"gemini-2.5-flash-search": aiModelComponent.createObject(this, {
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"name": "Gemini 2.5 Flash (Search)",
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"icon": "google-gemini-symbolic",
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"description": Translation.tr("Online | Google's model\nGives up-to-date information with search."),
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@ -171,8 +176,8 @@ Singleton {
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"tools": [{
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"google_search": {}
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}]
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},
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"gemini-2.5-flash-tools": {
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}),
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"gemini-2.5-flash-tools": aiModelComponent.createObject(this, {
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"name": "Gemini 2.5 Flash (Tools)",
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"icon": "google-gemini-symbolic",
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"description": Translation.tr("Experimental | Online | Google's model\nCan do a little more but takes an extra turn to perform search"),
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@ -185,21 +190,8 @@ Singleton {
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"key_get_description": Translation.tr("**Pricing**: free. Data used for training.\n\n**Instructions**: Log into Google account, allow AI Studio to create Google Cloud project or whatever it asks, go back and click Get API key"),
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"api_format": "gemini",
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"tools": root.tools["gemini"],
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},
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"gemini-2.5-flash-lite": {
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"name": "Gemini 2.5 Flash-Lite",
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"icon": "google-gemini-symbolic",
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"description": Translation.tr("Experimental | Online | Google's model\nA Gemini 2.5 Flash model optimized for cost-efficiency and high throughput."),
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"homepage": "https://aistudio.google.com",
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"endpoint": "https://generativelanguage.googleapis.com/v1beta/models/gemini-2.5-flash-lite:streamGenerateContent",
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"model": "gemini-2.5-flash-lite",
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"requires_key": true,
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"key_id": "gemini",
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"key_get_link": "https://aistudio.google.com/app/apikey",
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"key_get_description": Translation.tr("**Pricing**: free. Data used for training.\n\n**Instructions**: Log into Google account, allow AI Studio to create Google Cloud project or whatever it asks, go back and click Get API key"),
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"api_format": "gemini",
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},
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"gemini-2.5-flash-lite-search": {
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}),
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"gemini-2.5-flash-lite-search": aiModelComponent.createObject(this, {
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"name": "Gemini 2.5 Flash-Lite (Search)",
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"icon": "google-gemini-symbolic",
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"description": Translation.tr("Experimental | Online | Google's model\nA Gemini 2.5 Flash model optimized for cost-efficiency and high throughput."),
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@ -214,8 +206,22 @@ Singleton {
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"tools": [{
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"google_search": {}
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}]
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},
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"openrouter-llama4-maverick": {
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}),
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"gemini-2.5-flash-lite": aiModelComponent.createObject(this, {
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"name": "Gemini 2.5 Flash-Lite",
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"icon": "google-gemini-symbolic",
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"description": Translation.tr("Experimental | Online | Google's model\nA Gemini 2.5 Flash model optimized for cost-efficiency and high throughput."),
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"homepage": "https://aistudio.google.com",
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"endpoint": "https://generativelanguage.googleapis.com/v1beta/models/gemini-2.5-flash-lite:streamGenerateContent",
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"model": "gemini-2.5-flash-lite",
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"requires_key": true,
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"key_id": "gemini",
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"key_get_link": "https://aistudio.google.com/app/apikey",
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"key_get_description": Translation.tr("**Pricing**: free. Data used for training.\n\n**Instructions**: Log into Google account, allow AI Studio to create Google Cloud project or whatever it asks, go back and click Get API key"),
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"api_format": "gemini",
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"tools": root.tools["gemini"],
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}),
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"openrouter-llama4-maverick": aiModelComponent.createObject(this, {
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"name": "Llama 4 Maverick",
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"icon": "ollama-symbolic",
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"description": Translation.tr("Online via %1 | %2's model").arg("OpenRouter").arg("Meta"),
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@ -226,8 +232,8 @@ Singleton {
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"key_id": "openrouter",
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"key_get_link": "https://openrouter.ai/settings/keys",
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"key_get_description": Translation.tr("**Pricing**: free. Data use policy varies depending on your OpenRouter account settings.\n\n**Instructions**: Log into OpenRouter account, go to Keys on the topright menu, click Create API Key"),
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},
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"openrouter-deepseek-r1": {
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}),
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"openrouter-deepseek-r1": aiModelComponent.createObject(this, {
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"name": "DeepSeek R1",
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"icon": "deepseek-symbolic",
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"description": Translation.tr("Online via %1 | %2's model").arg("OpenRouter").arg("DeepSeek"),
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@ -238,11 +244,17 @@ Singleton {
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"key_id": "openrouter",
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"key_get_link": "https://openrouter.ai/settings/keys",
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"key_get_description": Translation.tr("**Pricing**: free. Data use policy varies depending on your OpenRouter account settings.\n\n**Instructions**: Log into OpenRouter account, go to Keys on the topright menu, click Create API Key"),
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},
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}),
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}
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property var modelList: Object.keys(root.models)
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property var currentModelId: Persistent.states?.ai?.model || modelList[0]
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property var apiStrategies: {
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"openai": openaiApiStrategy.createObject(this),
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"gemini": geminiApiStrategy.createObject(this),
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}
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property ApiStrategy currentApiStrategy: apiStrategies[models[currentModelId]?.api_format || "openai"]
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Component.onCompleted: {
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setModel(currentModelId, false, false); // Do necessary setup for model
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}
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@ -280,14 +292,15 @@ Singleton {
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root.modelList = [...root.modelList, ...dataJson];
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dataJson.forEach(model => {
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const safeModelName = root.safeModelName(model);
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root.models[safeModelName] = {
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root.models[safeModelName] = aiModelComponent.createObject(this, {
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"name": guessModelName(model),
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"icon": guessModelLogo(model),
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"description": Translation.tr("Local Ollama model | %1").arg(model),
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"homepage": `https://ollama.com/library/${model}`,
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"endpoint": "http://localhost:11434/v1/chat/completions",
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"model": model,
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}
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"requires_key": false,
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})
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});
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root.modelList = Object.keys(root.models);
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@ -473,24 +486,16 @@ Singleton {
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function clearMessages() {
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root.messageIDs = [];
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root.messageByID = ({});
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root.tokenCount.input = -1;
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root.tokenCount.output = -1;
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root.tokenCount.total = -1;
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}
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Process {
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id: requester
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property var baseCommand: ["bash", "-c"]
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property var message
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property bool isReasoning
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property string apiFormat: "openai"
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property string geminiBuffer: ""
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function buildGeminiEndpoint(model) {
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// console.log("ENDPOINT: " + model.endpoint + `?key=\$\{${root.apiKeyEnvVarName}\}`)
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return model.endpoint + `?key=\$\{${root.apiKeyEnvVarName}\}`;
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}
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function buildOpenAIEndpoint(model) {
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return model.endpoint;
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}
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property AiMessageData message
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property ApiStrategy currentStrategy
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function markDone() {
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requester.message.done = true;
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@ -501,84 +506,20 @@ Singleton {
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root.saveChat("lastSession")
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}
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function buildGeminiRequestData(model, messages) {
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const tools = [
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...(model.tools ?? root.tools[model.api_format]),
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]
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// console.log("Tools", JSON.stringify(tools, null, 2));
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let baseData = {
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"contents": messages.filter(message => (message.role != Ai.interfaceRole)).map(message => {
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const geminiApiRoleName = (message.role === "assistant") ? "model" : message.role;
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const usingSearch = tools[0].google_search != undefined
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if (!usingSearch && message.functionCall != undefined && message.functionCall.length > 0) {
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return {
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"role": geminiApiRoleName,
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"parts": [{
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functionCall: {
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"name": message.functionName,
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}
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}]
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}
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}
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if (!usingSearch && message.functionResponse != undefined && message.functionResponse.length > 0) {
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return {
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"role": geminiApiRoleName,
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"parts": [{
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functionResponse: {
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"name": message.functionName,
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"response": { "content": message.functionResponse }
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}
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}]
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}
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}
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return {
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"role": geminiApiRoleName,
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"parts": [{
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text: message.rawContent,
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}]
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}
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}),
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"tools": tools,
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"system_instruction": {
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"parts": [{ text: root.systemPrompt }]
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},
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"generationConfig": {
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"temperature": root.temperature,
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},
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};
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return model.extraParams ? Object.assign({}, baseData, model.extraParams) : baseData;
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}
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function buildOpenAIRequestData(model, messages) {
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let baseData = {
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"model": model.model,
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"messages": [
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{role: "system", content: root.systemPrompt},
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...messages.filter(message => (message.role != Ai.interfaceRole)).map(message => {
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return {
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"role": message.role,
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"content": message.rawContent,
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}
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}),
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],
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"stream": true,
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"temperature": root.temperature,
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};
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return model.extraParams ? Object.assign({}, baseData, model.extraParams) : baseData;
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}
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function makeRequest() {
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const model = models[currentModelId];
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requester.apiFormat = model.api_format ?? "openai";
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requester.currentStrategy = root.currentApiStrategy;
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requester.currentStrategy.reset(); // Reset strategy state
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/* Put API key in environment variable */
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if (model.requires_key) requester.environment[`${root.apiKeyEnvVarName}`] = root.apiKeys ? (root.apiKeys[model.key_id] ?? "") : ""
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/* Build endpoint, request data */
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const endpoint = (apiFormat === "gemini") ? buildGeminiEndpoint(model) : buildOpenAIEndpoint(model);
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const endpoint = root.currentApiStrategy.buildEndpoint(model);
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const messageArray = root.messageIDs.map(id => root.messageByID[id]);
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const data = (apiFormat === "gemini") ? buildGeminiRequestData(model, messageArray) : buildOpenAIRequestData(model, messageArray);
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// console.log("REQUEST DATA: ", JSON.stringify(data, null, 2));
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const filteredMessageArray = messageArray.filter(message => message.role !== Ai.interfaceRole);
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const data = root.currentApiStrategy.buildRequestData(model, filteredMessageArray, root.systemPrompt, root.temperature);
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// console.log("[Ai] Request data: ", JSON.stringify(data, null, 2));
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let requestHeaders = {
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"Content-Type": "application/json",
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@ -606,166 +547,45 @@ Singleton {
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// console.log("Request headers: ", JSON.stringify(requestHeaders));
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// console.log("Header string: ", headerString);
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/* Get authorization header from strategy */
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const authHeader = requester.currentStrategy.buildAuthorizationHeader(root.apiKeyEnvVarName);
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/* Create command string */
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const requestCommandString = `curl --no-buffer "${endpoint}"`
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+ ` ${headerString}`
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+ ((apiFormat == "gemini") ? "" : ` -H "Authorization: Bearer \$\{${root.apiKeyEnvVarName}\}"`)
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+ (authHeader ? ` ${authHeader}` : "")
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+ ` -d '${CF.StringUtils.shellSingleQuoteEscape(JSON.stringify(data))}'`
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// console.log("Request command: ", requestCommandString);
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/* Send the request */
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requester.command = baseCommand.concat([requestCommandString]);
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/* Reset vars and make the request */
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requester.isReasoning = false
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requester.running = true
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}
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function parseGeminiBuffer() {
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// console.log("BUFFER DATA: ", requester.geminiBuffer);
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try {
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if (requester.geminiBuffer.length === 0) return;
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const dataJson = JSON.parse(requester.geminiBuffer);
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if (!dataJson.candidates) return;
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if (dataJson.candidates[0]?.finishReason) {
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requester.markDone();
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}
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// Function call handling
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if (dataJson.candidates[0]?.content?.parts[0]?.functionCall) {
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const functionCall = dataJson.candidates[0]?.content?.parts[0]?.functionCall;
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requester.message.functionName = functionCall.name;
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requester.message.functionCall = functionCall.name;
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const newContent = `\n\n[[ Function: ${functionCall.name}(${JSON.stringify(functionCall.args, null, 2)}) ]]\n`
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requester.message.rawContent += newContent;
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requester.message.content += newContent;
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root.handleGeminiFunctionCall(functionCall.name, functionCall.args);
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return
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}
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// Normal text response
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const responseContent = dataJson.candidates[0]?.content?.parts[0]?.text
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requester.message.rawContent += responseContent;
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requester.message.content += responseContent;
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const annotationSources = dataJson.candidates[0]?.groundingMetadata?.groundingChunks?.map(chunk => {
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return {
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"type": "url_citation",
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"text": chunk?.web?.title,
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"url": chunk?.web?.uri,
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}
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}) ?? [];
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// Handle annotations and search queries
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const annotations = dataJson.candidates[0]?.groundingMetadata?.groundingSupports?.map(citation => {
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return {
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"type": "url_citation",
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"start_index": citation.segment?.startIndex,
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"end_index": citation.segment?.endIndex,
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"text": citation?.segment.text,
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"url": annotationSources[citation.groundingChunkIndices[0]]?.url,
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"sources": citation.groundingChunkIndices
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}
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});
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requester.message.annotationSources = annotationSources;
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requester.message.annotations = annotations;
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requester.message.searchQueries = dataJson.candidates[0]?.groundingMetadata?.webSearchQueries ?? [];
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// console.log("[AI] Gemini: Search queries: ", JSON.stringify(requester.message.searchQueries, null, 2));
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// Usage
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root.tokenCount.input = dataJson.usageMetadata?.promptTokenCount ?? -1;
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root.tokenCount.output = dataJson.usageMetadata?.candidatesTokenCount ?? -1;
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root.tokenCount.total = dataJson.usageMetadata?.totalTokenCount ?? -1;
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// console.log("[AI] Gemini: Token count: ", root.tokenCount);
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// Last logging
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// console.log(JSON.stringify(requester.message, null, 2));
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} catch (e) {
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console.log("[AI] Gemini: Could not parse buffer: ", e);
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requester.message.rawContent += requester.geminiBuffer;
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requester.message.content += requester.geminiBuffer
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} finally {
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requester.geminiBuffer = "";
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}
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}
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function handleGeminiResponseLine(line) {
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if (line.startsWith("[")) {
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requester.geminiBuffer += line.slice(1).trim();
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} else if (line == "]") {
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requester.geminiBuffer += line.slice(0, -1).trim();
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parseGeminiBuffer();
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} else if (line.startsWith(",")) { // end of one entry
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parseGeminiBuffer();
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} else {
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requester.geminiBuffer += line.trim();
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}
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}
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function handleOpenAIResponseLine(line) {
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// Remove 'data: ' prefix if present and trim whitespace
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let cleanData = line.trim();
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if (cleanData.startsWith("data:")) {
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cleanData = cleanData.slice(5).trim();
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}
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// console.log("Clean data: ", cleanData);
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if (!cleanData || cleanData.startsWith(":")) return;
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if (cleanData === "[DONE]") {
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requester.markDone();
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return;
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}
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const dataJson = JSON.parse(cleanData);
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let newContent = "";
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const responseContent = dataJson.choices[0]?.delta?.content || dataJson.message?.content;
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const responseReasoning = dataJson.choices[0]?.delta?.reasoning || dataJson.choices[0]?.delta?.reasoning_content;
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if (responseContent && responseContent.length > 0) {
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if (requester.isReasoning) {
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requester.isReasoning = false;
|
||||
const endBlock = "\n\n</think>\n\n";
|
||||
requester.message.content += endBlock;
|
||||
requester.message.rawContent += endBlock;
|
||||
}
|
||||
newContent = dataJson.choices[0]?.delta?.content || dataJson.message.content;
|
||||
} else if (responseReasoning && responseReasoning.length > 0) {
|
||||
// console.log("Reasoning content: ", dataJson.choices[0].delta.reasoning);
|
||||
if (!requester.isReasoning) {
|
||||
requester.isReasoning = true;
|
||||
const startBlock = "\n\n<think>\n\n";
|
||||
requester.message.rawContent += startBlock;
|
||||
requester.message.content += startBlock;
|
||||
}
|
||||
newContent = dataJson.choices[0].delta.reasoning || dataJson.choices[0].delta.reasoning_content;
|
||||
}
|
||||
|
||||
requester.message.content += newContent;
|
||||
requester.message.rawContent += newContent;
|
||||
|
||||
if (dataJson.done) {
|
||||
requester.markDone();
|
||||
}
|
||||
}
|
||||
|
||||
stdout: SplitParser {
|
||||
onRead: data => {
|
||||
// console.log("RAW DATA: ", data);
|
||||
// console.log("[Ai] Raw response line: ", data);
|
||||
if (data.length === 0) return;
|
||||
if (requester.message.thinking) requester.message.thinking = false;
|
||||
|
||||
// Handle response line
|
||||
if (requester.message.thinking) requester.message.thinking = false;
|
||||
try {
|
||||
if (requester.apiFormat === "gemini") {
|
||||
requester.handleGeminiResponseLine(data);
|
||||
const result = requester.currentStrategy.parseResponseLine(data, requester.message);
|
||||
// console.log("[Ai] Parsed response result: ", JSON.stringify(result, null, 2));
|
||||
|
||||
if (result.functionCall) {
|
||||
root.handleFunctionCall(result.functionCall.name, result.functionCall.args);
|
||||
}
|
||||
else if (requester.apiFormat === "openai") {
|
||||
requester.handleOpenAIResponseLine(data);
|
||||
if (result.tokenUsage) {
|
||||
root.tokenCount.input = result.tokenUsage.input;
|
||||
root.tokenCount.output = result.tokenUsage.output;
|
||||
root.tokenCount.total = result.tokenUsage.total;
|
||||
}
|
||||
else {
|
||||
console.log("Unknown API format: ", requester.apiFormat);
|
||||
requester.message.rawContent += data;
|
||||
requester.message.content += data;
|
||||
if (result.finished) {
|
||||
requester.markDone();
|
||||
}
|
||||
|
||||
} catch (e) {
|
||||
console.log("[AI] Could not parse response from stream: ", e);
|
||||
console.log("[AI] Could not parse response: ", e);
|
||||
requester.message.rawContent += data;
|
||||
requester.message.content += data;
|
||||
}
|
||||
|
|
@ -773,18 +593,15 @@ Singleton {
|
|||
}
|
||||
|
||||
onExited: (exitCode, exitStatus) => {
|
||||
if (requester.apiFormat == "gemini") requester.parseGeminiBuffer();
|
||||
else requester.markDone();
|
||||
|
||||
try { // to parse full response into json for error handling
|
||||
// console.log("Full response: ", requester.message.content + "]");
|
||||
const parsedResponse = JSON.parse(requester.message.rawContent + "]");
|
||||
requester.message.rawContent = `\`\`\`json\n${JSON.stringify(parsedResponse, null, 2)}\n\`\`\``;
|
||||
requester.message.content = requester.message.rawContent;
|
||||
} catch (e) {
|
||||
// console.log("[AI] Could not parse response on exit: ", e);
|
||||
const result = requester.currentStrategy.onRequestFinished(requester.message);
|
||||
|
||||
if (result.finished) {
|
||||
requester.markDone();
|
||||
} else if (!requester.message.done) {
|
||||
requester.markDone();
|
||||
}
|
||||
|
||||
// Handle error responses
|
||||
if (requester.message.content.includes("API key not valid")) {
|
||||
root.addApiKeyAdvice(models[requester.message.model]);
|
||||
}
|
||||
|
|
@ -814,20 +631,7 @@ Singleton {
|
|||
root.messageByID[id] = aiMessage;
|
||||
}
|
||||
|
||||
function buildGeminiFunctionOutput(name, output) {
|
||||
const functionResponsePart = {
|
||||
"name": name,
|
||||
"response": { "content": output }
|
||||
}
|
||||
return {
|
||||
"role": "user",
|
||||
"parts": [{
|
||||
functionResponse: functionResponsePart,
|
||||
}]
|
||||
}
|
||||
}
|
||||
|
||||
function handleGeminiFunctionCall(name, args) {
|
||||
function handleFunctionCall(name, args) {
|
||||
if (name === "switch_to_search_mode") {
|
||||
const modelId = root.currentModelId;
|
||||
if (modelId.endsWith("-tools")) {
|
||||
|
|
|
|||
|
|
@ -1,4 +1,3 @@
|
|||
import qs.modules.common
|
||||
import QtQuick;
|
||||
|
||||
/**
|
||||
33
.config/quickshell/ii/services/ai/AiModel.qml
Normal file
33
.config/quickshell/ii/services/ai/AiModel.qml
Normal file
|
|
@ -0,0 +1,33 @@
|
|||
import QtQuick;
|
||||
|
||||
/**
|
||||
* An AI model representation.
|
||||
* - name: Friendly name of the model
|
||||
* - icon: Icon name of the model
|
||||
* - description: Description of the model
|
||||
* - endpoint: Endpoint of the model
|
||||
* - model: Model code (like gpt-4.1 or gemini-2.5-flash)
|
||||
* - requires_key: Whether the model requires an API key
|
||||
* - key_id: The identifier of the API key. Use the same identifier for models that can be accessed with the same key.
|
||||
* - key_get_link: Link to get an API key
|
||||
* - key_get_description: Description of pricing and how to get an API key
|
||||
* - api_format: The API format of the model. Can be "openai" or "gemini". Default is "openai".
|
||||
* - tools: List of tools that the model can use.
|
||||
* - extraParams: Extra parameters to be passed to the model. This is a JSON object.
|
||||
*/
|
||||
|
||||
QtObject {
|
||||
property string name
|
||||
property string icon
|
||||
property string description
|
||||
property string homepage
|
||||
property string endpoint
|
||||
property string model
|
||||
property bool requires_key: true
|
||||
property string key_id
|
||||
property string key_get_link
|
||||
property string key_get_description
|
||||
property string api_format: "openai"
|
||||
property var tools
|
||||
property var extraParams: ({})
|
||||
}
|
||||
10
.config/quickshell/ii/services/ai/ApiStrategy.qml
Normal file
10
.config/quickshell/ii/services/ai/ApiStrategy.qml
Normal file
|
|
@ -0,0 +1,10 @@
|
|||
import QtQuick
|
||||
|
||||
QtObject {
|
||||
function buildEndpoint(model: AiModel): string { throw new Error("Not implemented") }
|
||||
function buildRequestData(model: AiModel, messages, systemPrompt: string, temperature: real) { throw new Error("Not implemented") }
|
||||
function buildAuthorizationHeader(apiKeyEnvVarName: string): string { throw new Error("Not implemented") }
|
||||
function parseResponseLine(line: string, message: AiMessageData) { throw new Error("Not implemented") }
|
||||
function onRequestFinished(message: AiMessageData): var { return {} } // Default: no special handling
|
||||
function reset() { } // Reset any internal state if needed
|
||||
}
|
||||
156
.config/quickshell/ii/services/ai/GeminiApiStrategy.qml
Normal file
156
.config/quickshell/ii/services/ai/GeminiApiStrategy.qml
Normal file
|
|
@ -0,0 +1,156 @@
|
|||
import QtQuick
|
||||
|
||||
ApiStrategy {
|
||||
property string buffer: ""
|
||||
|
||||
function buildEndpoint(model: AiModel): string {
|
||||
const result = model.endpoint + `?key=\$\{${root.apiKeyEnvVarName}\}`
|
||||
console.log("[AI] Endpoint: " + result);
|
||||
return result;
|
||||
}
|
||||
|
||||
function buildRequestData(model: AiModel, messages, systemPrompt: string, temperature: real) {
|
||||
const tools = model.tools ?? [];
|
||||
let baseData = {
|
||||
"contents": messages.map(message => {
|
||||
const geminiApiRoleName = (message.role === "assistant") ? "model" : message.role;
|
||||
const usingSearch = tools[0].google_search != undefined
|
||||
if (!usingSearch && message.functionCall != undefined && message.functionCall.length > 0) {
|
||||
return {
|
||||
"role": geminiApiRoleName,
|
||||
"parts": [{
|
||||
functionCall: {
|
||||
"name": message.functionName,
|
||||
}
|
||||
}]
|
||||
}
|
||||
}
|
||||
if (!usingSearch && message.functionResponse != undefined && message.functionResponse.length > 0) {
|
||||
return {
|
||||
"role": geminiApiRoleName,
|
||||
"parts": [{
|
||||
functionResponse: {
|
||||
"name": message.functionName,
|
||||
"response": { "content": message.functionResponse }
|
||||
}
|
||||
}]
|
||||
}
|
||||
}
|
||||
return {
|
||||
"role": geminiApiRoleName,
|
||||
"parts": [{
|
||||
text: message.rawContent,
|
||||
}]
|
||||
}
|
||||
}),
|
||||
"tools": tools,
|
||||
"system_instruction": {
|
||||
"parts": [{ text: systemPrompt }]
|
||||
},
|
||||
"generationConfig": {
|
||||
"temperature": temperature,
|
||||
},
|
||||
};
|
||||
return model.extraParams ? Object.assign({}, baseData, model.extraParams) : baseData;
|
||||
}
|
||||
|
||||
function buildAuthorizationHeader(apiKeyEnvVarName: string): string {
|
||||
// Gemini doesn't use Authorization header, key is in URL
|
||||
return "";
|
||||
}
|
||||
|
||||
function parseResponseLine(line, message) {
|
||||
if (line.startsWith("[")) {
|
||||
buffer += line.slice(1).trim();
|
||||
} else if (line === "]") {
|
||||
buffer += line.slice(0, -1).trim();
|
||||
return parseBuffer(message);
|
||||
} else if (line.startsWith(",")) {
|
||||
return parseBuffer(message);
|
||||
} else {
|
||||
buffer += line.trim();
|
||||
}
|
||||
return {};
|
||||
}
|
||||
|
||||
function parseBuffer(message) {
|
||||
// console.log("[Ai] Gemini buffer: ", buffer);
|
||||
let finished = false;
|
||||
try {
|
||||
if (buffer.length === 0) return {};
|
||||
const dataJson = JSON.parse(buffer);
|
||||
if (!dataJson.candidates) return {};
|
||||
|
||||
if (dataJson.candidates[0]?.finishReason) {
|
||||
finished = true;
|
||||
}
|
||||
|
||||
// Function call handling
|
||||
if (dataJson.candidates[0]?.content?.parts[0]?.functionCall) {
|
||||
const functionCall = dataJson.candidates[0]?.content?.parts[0]?.functionCall;
|
||||
message.functionName = functionCall.name;
|
||||
message.functionCall = functionCall.name;
|
||||
const newContent = `\n\n[[ Function: ${functionCall.name}(${JSON.stringify(functionCall.args, null, 2)}) ]]\n`
|
||||
message.rawContent += newContent;
|
||||
message.content += newContent;
|
||||
return { functionCall: { name: functionCall.name, args: functionCall.args }, finished: finished };
|
||||
}
|
||||
|
||||
// Normal text response
|
||||
const responseContent = dataJson.candidates[0]?.content?.parts[0]?.text
|
||||
message.rawContent += responseContent;
|
||||
message.content += responseContent;
|
||||
|
||||
// Handle annotations and metadata
|
||||
const annotationSources = dataJson.candidates[0]?.groundingMetadata?.groundingChunks?.map(chunk => {
|
||||
return {
|
||||
"type": "url_citation",
|
||||
"text": chunk?.web?.title,
|
||||
"url": chunk?.web?.uri,
|
||||
}
|
||||
}) ?? [];
|
||||
|
||||
const annotations = dataJson.candidates[0]?.groundingMetadata?.groundingSupports?.map(citation => {
|
||||
return {
|
||||
"type": "url_citation",
|
||||
"start_index": citation.segment?.startIndex,
|
||||
"end_index": citation.segment?.endIndex,
|
||||
"text": citation?.segment.text,
|
||||
"url": annotationSources[citation.groundingChunkIndices[0]]?.url,
|
||||
"sources": citation.groundingChunkIndices
|
||||
}
|
||||
});
|
||||
message.annotationSources = annotationSources;
|
||||
message.annotations = annotations;
|
||||
message.searchQueries = dataJson.candidates[0]?.groundingMetadata?.webSearchQueries ?? [];
|
||||
|
||||
// Usage metadata
|
||||
if (dataJson.usageMetadata) {
|
||||
return {
|
||||
tokenUsage: {
|
||||
input: dataJson.usageMetadata.promptTokenCount ?? -1,
|
||||
output: dataJson.usageMetadata.candidatesTokenCount ?? -1,
|
||||
total: dataJson.usageMetadata.totalTokenCount ?? -1
|
||||
},
|
||||
finished: finished
|
||||
};
|
||||
}
|
||||
|
||||
} catch (e) {
|
||||
console.log("[AI] Gemini: Could not parse buffer: ", e);
|
||||
message.rawContent += buffer;
|
||||
message.content += buffer;
|
||||
} finally {
|
||||
buffer = "";
|
||||
}
|
||||
return { finished: finished };
|
||||
}
|
||||
|
||||
function onRequestFinished(message) {
|
||||
return parseBuffer(message);
|
||||
}
|
||||
|
||||
function reset() {
|
||||
buffer = "";
|
||||
}
|
||||
}
|
||||
97
.config/quickshell/ii/services/ai/OpenAiApiStrategy.qml
Normal file
97
.config/quickshell/ii/services/ai/OpenAiApiStrategy.qml
Normal file
|
|
@ -0,0 +1,97 @@
|
|||
import QtQuick
|
||||
|
||||
ApiStrategy {
|
||||
property bool isReasoning: false
|
||||
|
||||
function buildEndpoint(model: AiModel): string {
|
||||
console.log("[AI] Endpoint: " + model.endpoint);
|
||||
return model.endpoint;
|
||||
}
|
||||
|
||||
function buildRequestData(model: AiModel, messages, systemPrompt: string, temperature: real) {
|
||||
let baseData = {
|
||||
"model": model.model,
|
||||
"messages": [
|
||||
{role: "system", content: systemPrompt},
|
||||
...messages.map(message => {
|
||||
return {
|
||||
"role": message.role,
|
||||
"content": message.rawContent,
|
||||
}
|
||||
}),
|
||||
],
|
||||
"stream": true,
|
||||
"temperature": temperature,
|
||||
};
|
||||
return model.extraParams ? Object.assign({}, baseData, model.extraParams) : baseData;
|
||||
}
|
||||
|
||||
function buildAuthorizationHeader(apiKeyEnvVarName: string): string {
|
||||
return `-H "Authorization: Bearer \$\{${apiKeyEnvVarName}\}"`;
|
||||
}
|
||||
|
||||
function parseResponseLine(line, message) {
|
||||
// Remove 'data: ' prefix if present and trim whitespace
|
||||
let cleanData = line.trim();
|
||||
if (cleanData.startsWith("data:")) {
|
||||
cleanData = cleanData.slice(5).trim();
|
||||
}
|
||||
|
||||
// Handle special cases
|
||||
if (!cleanData || cleanData.startsWith(":")) return {};
|
||||
if (cleanData === "[DONE]") {
|
||||
return { finished: true };
|
||||
}
|
||||
|
||||
// Real stuff
|
||||
try {
|
||||
const dataJson = JSON.parse(cleanData);
|
||||
let newContent = "";
|
||||
|
||||
const responseContent = dataJson.choices[0]?.delta?.content || dataJson.message?.content;
|
||||
const responseReasoning = dataJson.choices[0]?.delta?.reasoning || dataJson.choices[0]?.delta?.reasoning_content;
|
||||
|
||||
if (responseContent && responseContent.length > 0) {
|
||||
if (isReasoning) {
|
||||
isReasoning = false;
|
||||
const endBlock = "\n\n</think>\n\n";
|
||||
message.content += endBlock;
|
||||
message.rawContent += endBlock;
|
||||
}
|
||||
newContent = responseContent;
|
||||
} else if (responseReasoning && responseReasoning.length > 0) {
|
||||
if (!isReasoning) {
|
||||
isReasoning = true;
|
||||
const startBlock = "\n\n<think>\n\n";
|
||||
message.rawContent += startBlock;
|
||||
message.content += startBlock;
|
||||
}
|
||||
newContent = responseReasoning;
|
||||
}
|
||||
|
||||
message.content += newContent;
|
||||
message.rawContent += newContent;
|
||||
|
||||
if (dataJson.done) {
|
||||
return { finished: true };
|
||||
}
|
||||
|
||||
} catch (e) {
|
||||
console.log("[AI] OpenAI: Could not parse line: ", e);
|
||||
message.rawContent += line;
|
||||
message.content += line;
|
||||
}
|
||||
|
||||
return {};
|
||||
}
|
||||
|
||||
function onRequestFinished(message) {
|
||||
// OpenAI format doesn't need special finish handling
|
||||
return {};
|
||||
}
|
||||
|
||||
function reset() {
|
||||
isReasoning = false;
|
||||
}
|
||||
|
||||
}
|
||||
Loading…
Reference in a new issue