@robinpath/ai - npm Package Compare versions

Comparing version 0.1.2 to 0.3.0

dist/ai.d.ts

+/**
+ * RobinPath AI Module (Node port).
+ *
+ * A thin, provider-agnostic LLM wrapper. Every handler takes a saved
+ * credential slug (type `ai_provider`) as its first argument. The slug
+ * encapsulates `{ provider, api_key, base_url?, default_model? }` so the
+ * same script works against OpenAI, Anthropic, or any OpenAI-compatible
+ * endpoint just by swapping the credential.
+ *
+ * This module is intentionally higher-level than the `openai` and
+ * `anthropic` modules — it exposes generic primitives (`chat`, `complete`,
+ * `summarize`, `extract`, `classify`, `translate`, `sentiment`,
+ * `generateJson`, `embedding`) that are useful in automations without
+ * forcing the author to commit to a specific vendor.
+ *
+ * Credential type:
+ *   - ai_provider : { provider, api_key, base_url?, default_model?, default_max_tokens? }
+ */
+import type { BuiltinHandler, CredentialTypeSchema, FunctionMetadata, ModuleHost, ModuleMetadata } from "@robinpath/core";
+export declare function configureAi(h: ModuleHost): void;
+export declare const AiFunctions: Record<string, BuiltinHandler>;
+export declare const AiCredentialTypes: CredentialTypeSchema[];
+export declare const AiFunctionMetadata: Record<string, FunctionMetadata>;
+export declare const AiModuleMetadata: ModuleMetadata;
+//# sourceMappingURL=ai.d.ts.map

dist/ai.d.ts.map

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dist/ai.js

+/**
+ * RobinPath AI Module (Node port).
+ *
+ * A thin, provider-agnostic LLM wrapper. Every handler takes a saved
+ * credential slug (type `ai_provider`) as its first argument. The slug
+ * encapsulates `{ provider, api_key, base_url?, default_model? }` so the
+ * same script works against OpenAI, Anthropic, or any OpenAI-compatible
+ * endpoint just by swapping the credential.
+ *
+ * This module is intentionally higher-level than the `openai` and
+ * `anthropic` modules — it exposes generic primitives (`chat`, `complete`,
+ * `summarize`, `extract`, `classify`, `translate`, `sentiment`,
+ * `generateJson`, `embedding`) that are useful in automations without
+ * forcing the author to commit to a specific vendor.
+ *
+ * Credential type:
+ *   - ai_provider : { provider, api_key, base_url?, default_model?, default_max_tokens? }
+ */
+// ── Module state ────────────────────────────────────────────────────────
+const state = {};
+export function configureAi(h) { state.host = h; }
+function host() {
+    if (!state.host)
+        throw new Error("AI module not initialized — use rp.installModule().");
+    return state.host;
+}
+const CREDENTIAL_TYPE = "ai_provider";
+const PROVIDER_DEFAULTS = {
+    openai: { baseUrl: "https://api.openai.com/v1", model: "gpt-4o-mini" },
+    anthropic: { baseUrl: "https://api.anthropic.com/v1", model: "claude-sonnet-4-5" },
+    openrouter: { baseUrl: "https://openrouter.ai/api/v1", model: "openai/gpt-4o-mini" },
+};
+const errorReturn = (error, code, extra = {}) => ({ error, code, ...extra });
+async function resolveProvider(slug) {
+    if (!slug)
+        return errorReturn("Credential slug is required.", "credential_not_found");
+    const fields = await host().credentials.get(slug);
+    if (!fields)
+        return errorReturn(`Credential '${slug}' not found.`, "credential_not_found");
+    const apiKey = String(fields.api_key ?? "");
+    if (!apiKey)
+        return errorReturn("Credential has no `api_key` field.", "api_key_missing");
+    const providerRaw = String(fields.provider ?? "openai").toLowerCase();
+    const provider = providerRaw === "anthropic" ? "anthropic" :
+        providerRaw === "openai" || providerRaw === "openrouter" ? "openai" :
+            "custom";
+    const defaults = PROVIDER_DEFAULTS[providerRaw] ?? { baseUrl: "", model: "" };
+    const baseUrl = String(fields.base_url ?? defaults.baseUrl).replace(/\/+$/, "");
+    if (!baseUrl)
+        return errorReturn("Credential has no `base_url` and provider is unrecognized.", "base_url_missing");
+    return {
+        provider,
+        apiKey,
+        baseUrl,
+        defaultModel: String(fields.default_model ?? defaults.model),
+        defaultMaxTokens: Number(fields.default_max_tokens ?? 1024),
+    };
+}
+async function callOpenAI(cfg, messages, model, maxTokens, temperature, system) {
+    const allMessages = system ? [{ role: "system", content: system }, ...messages] : messages;
+    const body = { model, messages: allMessages, max_tokens: maxTokens };
+    if (temperature !== undefined)
+        body.temperature = temperature;
+    let response;
+    try {
+        response = await fetch(`${cfg.baseUrl}/chat/completions`, {
+            method: "POST",
+            headers: { "Content-Type": "application/json", Authorization: `Bearer ${cfg.apiKey}` },
+            body: JSON.stringify(body),
+        });
+    }
+    catch (e) {
+        return errorReturn(e instanceof Error ? e.message : String(e), "transport");
+    }
+    const raw = await response.text();
+    let data;
+    try {
+        data = raw ? JSON.parse(raw) : {};
+    }
+    catch {
+        data = { raw };
+    }
+    if (!response.ok) {
+        return errorReturn(`AI provider returned HTTP ${response.status}.`, response.status === 429 ? "rate_limited" : "provider_error", { status: response.status, provider_error: data.error ?? data });
+    }
+    const choices = data.choices;
+    const usage = data.usage;
+    return {
+        content: choices?.[0]?.message?.content ?? "",
+        role: "assistant",
+        model: data.model,
+        usage: usage ? {
+            promptTokens: usage.prompt_tokens ?? 0,
+            completionTokens: usage.completion_tokens ?? 0,
+            totalTokens: usage.total_tokens ?? 0,
+        } : undefined,
+    };
+}
+async function callAnthropic(cfg, messages, model, maxTokens, temperature, system) {
+    const body = { model, messages, max_tokens: maxTokens };
+    if (system)
+        body.system = system;
+    if (temperature !== undefined)
+        body.temperature = temperature;
+    let response;
+    try {
+        response = await fetch(`${cfg.baseUrl}/messages`, {
+            method: "POST",
+            headers: {
+                "Content-Type": "application/json",
+                "x-api-key": cfg.apiKey,
+                "anthropic-version": "2023-06-01",
+            },
+            body: JSON.stringify(body),
+        });
+    }
+    catch (e) {
+        return errorReturn(e instanceof Error ? e.message : String(e), "transport");
+    }
+    const raw = await response.text();
+    let data;
+    try {
+        data = raw ? JSON.parse(raw) : {};
+    }
+    catch {
+        data = { raw };
+    }
+    if (!response.ok) {
+        return errorReturn(`AI provider returned HTTP ${response.status}.`, response.status === 429 ? "rate_limited" : "provider_error", { status: response.status, provider_error: data.error ?? data });
+    }
+    const content = data.content?.[0]?.text ?? "";
+    const usage = data.usage;
+    return {
+        content,
+        role: "assistant",
+        model: data.model,
+        usage: usage ? {
+            promptTokens: usage.input_tokens ?? 0,
+            completionTokens: usage.output_tokens ?? 0,
+            totalTokens: (usage.input_tokens ?? 0) + (usage.output_tokens ?? 0),
+        } : undefined,
+        stopReason: data.stop_reason,
+    };
+}
+async function doChat(slug, messagesInput, opts) {
+    const cfg = await resolveProvider(slug);
+    if ("error" in cfg)
+        return cfg;
+    const model = String(opts.model ?? cfg.defaultModel);
+    const maxTokens = opts.maxTokens != null ? Number(opts.maxTokens) : cfg.defaultMaxTokens;
+    const temperature = opts.temperature != null ? Number(opts.temperature) : undefined;
+    const system = opts.system != null ? String(opts.system) : undefined;
+    let msgs;
+    if (typeof messagesInput === "string") {
+        msgs = [{ role: "user", content: messagesInput }];
+    }
+    else if (Array.isArray(messagesInput)) {
+        msgs = messagesInput;
+    }
+    else {
+        msgs = [{ role: "user", content: String(messagesInput) }];
+    }
+    if (cfg.provider === "anthropic") {
+        return callAnthropic(cfg, msgs, model, maxTokens, temperature, system);
+    }
+    return callOpenAI(cfg, msgs, model, maxTokens, temperature, system);
+}
+// ── Handlers ────────────────────────────────────────────────────────────
+const configure = async (args) => {
+    // `configure` validates that a given credential slug exists and echoes the
+    // resolved provider/model. It is NOT required to call this before chat —
+    // handlers resolve per-call — but it gives scripts a cheap sanity check.
+    const slug = String(args[0] ?? "");
+    const cfg = await resolveProvider(slug);
+    if ("error" in cfg)
+        return cfg;
+    return {
+        credential: slug,
+        provider: cfg.provider,
+        baseUrl: cfg.baseUrl,
+        defaultModel: cfg.defaultModel,
+        defaultMaxTokens: cfg.defaultMaxTokens,
+    };
+};
+const chat = async (args) => {
+    const slug = String(args[0] ?? "");
+    const messagesInput = args[1];
+    const opts = (args[2] && typeof args[2] === "object" ? args[2] : {});
+    return (await doChat(slug, messagesInput, opts));
+};
+const complete = async (args) => {
+    const slug = String(args[0] ?? "");
+    const prompt = String(args[1] ?? "");
+    const opts = (args[2] && typeof args[2] === "object" ? args[2] : {});
+    const result = await doChat(slug, prompt, opts);
+    if ("error" in result)
+        return result;
+    return result.content ?? "";
+};
+const summarize = async (args) => {
+    const slug = String(args[0] ?? "");
+    const text = String(args[1] ?? "");
+    const opts = (args[2] && typeof args[2] === "object" ? args[2] : {});
+    const hint = opts.maxLength ? `in ${Number(opts.maxLength)} words or less` : "concisely";
+    const prompt = `Summarize the following text ${hint}:\n\n${text}`;
+    return (await complete([slug, prompt, opts]));
+};
+const extract = async (args) => {
+    const slug = String(args[0] ?? "");
+    const text = String(args[1] ?? "");
+    const fields = Array.isArray(args[2])
+        ? args[2].map(String)
+        : String(args[2] ?? "").split(",").map((s) => s.trim()).filter(Boolean);
+    const opts = (args[3] && typeof args[3] === "object" ? args[3] : {});
+    if (fields.length === 0)
+        return errorReturn("`fields` is required.", "fields_missing");
+    const prompt = `Extract the following fields from the text below and return ONLY a valid JSON object with these keys: ${fields.join(", ")}.\n\nText:\n${text}\n\nJSON:`;
+    const result = await complete([slug, prompt, { ...opts, temperature: 0 }]);
+    if (typeof result !== "string")
+        return result;
+    try {
+        const match = result.match(/\{[\s\S]*\}/);
+        return match ? JSON.parse(match[0]) : result;
+    }
+    catch {
+        return result;
+    }
+};
+const classify = async (args) => {
+    const slug = String(args[0] ?? "");
+    const text = String(args[1] ?? "");
+    const categories = Array.isArray(args[2])
+        ? args[2].map(String)
+        : String(args[2] ?? "").split(",").map((s) => s.trim()).filter(Boolean);
+    const opts = (args[3] && typeof args[3] === "object" ? args[3] : {});
+    if (categories.length < 2)
+        return errorReturn("At least 2 categories are required.", "categories_missing");
+    const prompt = `Classify the following text into exactly one of these categories: ${categories.join(", ")}.\n\nText: ${text}\n\nRespond with ONLY the category name, nothing else.`;
+    const result = await complete([slug, prompt, { ...opts, temperature: 0 }]);
+    if (typeof result !== "string")
+        return result;
+    return result.trim();
+};
+const translate = async (args) => {
+    const slug = String(args[0] ?? "");
+    const text = String(args[1] ?? "");
+    const targetLang = String(args[2] ?? "English");
+    const opts = (args[3] && typeof args[3] === "object" ? args[3] : {});
+    const prompt = `Translate the following text to ${targetLang}. Return ONLY the translation, nothing else.\n\n${text}`;
+    return (await complete([slug, prompt, opts]));
+};
+const sentiment = async (args) => {
+    const slug = String(args[0] ?? "");
+    const text = String(args[1] ?? "");
+    const opts = (args[2] && typeof args[2] === "object" ? args[2] : {});
+    const prompt = `Analyze the sentiment of the following text. Respond with ONLY a JSON object: {"sentiment": "positive"|"negative"|"neutral", "score": 0.0-1.0, "confidence": 0.0-1.0}\n\nText: ${text}\n\nJSON:`;
+    const result = await complete([slug, prompt, { ...opts, temperature: 0 }]);
+    if (typeof result !== "string")
+        return result;
+    try {
+        const match = result.match(/\{[\s\S]*\}/);
+        return match ? JSON.parse(match[0]) : { sentiment: "neutral", score: 0.5 };
+    }
+    catch {
+        return { sentiment: "neutral", score: 0.5, raw: result };
+    }
+};
+const generateJson = async (args) => {
+    const slug = String(args[0] ?? "");
+    const prompt = String(args[1] ?? "");
+    const schema = args[2];
+    const opts = (args[3] && typeof args[3] === "object" ? args[3] : {});
+    let fullPrompt = `${prompt}\n\nRespond with ONLY a valid JSON object`;
+    if (schema)
+        fullPrompt += ` matching this structure: ${JSON.stringify(schema)}`;
+    fullPrompt += ". No explanations, no markdown, just JSON.";
+    const result = await complete([slug, fullPrompt, { ...opts, temperature: 0 }]);
+    if (typeof result !== "string")
+        return result;
+    try {
+        const match = result.match(/\{[\s\S]*\}|\[[\s\S]*\]/);
+        return match ? JSON.parse(match[0]) : result;
+    }
+    catch {
+        return result;
+    }
+};
+const embedding = async (args) => {
+    const slug = String(args[0] ?? "");
+    const input = args[1];
+    const opts = (args[2] && typeof args[2] === "object" ? args[2] : {});
+    const cfg = await resolveProvider(slug);
+    if ("error" in cfg)
+        return cfg;
+    const model = String(opts.model ?? "text-embedding-3-small");
+    const texts = Array.isArray(input) ? input.map(String) : [String(input)];
+    let response;
+    try {
+        response = await fetch(`${cfg.baseUrl}/embeddings`, {
+            method: "POST",
+            headers: { "Content-Type": "application/json", Authorization: `Bearer ${cfg.apiKey}` },
+            body: JSON.stringify({ model, input: texts }),
+        });
+    }
+    catch (e) {
+        return errorReturn(e instanceof Error ? e.message : String(e), "transport");
+    }
+    const raw = await response.text();
+    let data;
+    try {
+        data = raw ? JSON.parse(raw) : {};
+    }
+    catch {
+        data = { raw };
+    }
+    if (!response.ok) {
+        return errorReturn(`Embeddings provider returned HTTP ${response.status}.`, response.status === 429 ? "rate_limited" : "provider_error", { status: response.status, provider_error: data.error ?? data });
+    }
+    const embeds = data.data?.map((d) => d.embedding) ?? [];
+    return texts.length === 1 ? (embeds[0] ?? []) : embeds;
+};
+// ── Exports ─────────────────────────────────────────────────────────────
+export const AiFunctions = {
+    configure, chat, complete, summarize, extract, classify, translate, sentiment, generateJson, embedding,
+};
+// ── Credential types ────────────────────────────────────────────────────
+export const AiCredentialTypes = [
+    {
+        slug: CREDENTIAL_TYPE,
+        title: "AI Provider (generic)",
+        icon: "sparkles",
+        fields: [
+            {
+                name: "provider",
+                title: "Provider",
+                type: "text",
+                required: true,
+                placeholder: "openai",
+                description: "One of: `openai`, `anthropic`, `openrouter`, or a custom name. Determines the wire protocol.",
+            },
+            {
+                name: "api_key",
+                title: "API Key",
+                type: "password",
+                required: true,
+                description: "Provider API key. Stored encrypted.",
+            },
+            {
+                name: "base_url",
+                title: "Base URL",
+                type: "text",
+                required: false,
+                placeholder: "https://api.openai.com/v1",
+                description: "Override the provider endpoint. Required for custom / self-hosted OpenAI-compatible servers.",
+            },
+            {
+                name: "default_model",
+                title: "Default model",
+                type: "text",
+                required: false,
+                placeholder: "gpt-4o-mini",
+                description: "Used when a handler is called without an explicit `model`.",
+            },
+            {
+                name: "default_max_tokens",
+                title: "Default max tokens",
+                type: "number",
+                required: false,
+                description: "Default completion length. Default: 1024.",
+            },
+        ],
+    },
+];
+// ── Function metadata ───────────────────────────────────────────────────
+const credentialParam = {
+    name: "credential",
+    title: "Credential",
+    description: "Slug of a saved `ai_provider` credential.",
+    dataType: "string",
+    formInputType: "resource",
+    required: true,
+    allowExpression: true,
+    placeholder: "my_ai_provider",
+    resource: {
+        type: "credential",
+        listFn: "credential.list",
+        modes: ["list", "expression"],
+        searchable: true,
+        filter: { type: CREDENTIAL_TYPE },
+    },
+};
+const commonErrors = {
+    credential_not_found: "No credential with that slug exists in the vault.",
+    api_key_missing: "The credential exists but has no `api_key` field.",
+    base_url_missing: "The credential has no `base_url` and the provider is unrecognized.",
+    transport: "Network failure calling the AI provider.",
+    provider_error: "The provider returned an error — see `provider_error` for details.",
+    rate_limited: "You hit a rate limit. Slow down or upgrade your plan.",
+};
+const optionsParam = {
+    name: "options",
+    title: "Options",
+    description: "Recognized keys:\n  model       : default from credential\n  maxTokens   : default from credential (1024)\n  temperature : 0–1\n  system      : system prompt string",
+    dataType: "object",
+    formInputType: "json",
+    required: false,
+    allowExpression: true,
+    language: "json",
+    rows: 4,
+    advanced: true,
+};
+export const AiFunctionMetadata = {
+    configure: {
+        title: "Validate AI credential",
+        summary: "Resolve a credential slug and echo its provider / defaults",
+        description: "Returns the resolved provider, base URL, default model, and default max tokens for a credential. Does not make a network call. Useful as a sanity check at the top of a script.",
+        group: "setup",
+        action: "read",
+        icon: "settings",
+        capability: "manage_options",
+        sideEffects: [],
+        idempotent: true,
+        since: "1.0.0",
+        tags: ["ai", "configure", "credential"],
+        parameters: [credentialParam],
+        returnType: "object",
+        returnDescription: "{ credential, provider, baseUrl, defaultModel, defaultMaxTokens }",
+        errors: commonErrors,
+        example: 'ai.configure "my_ai"',
+    },
+    chat: {
+        title: "Chat completion",
+        summary: "Send a chat message and get a structured response",
+        description: "Sends `messages` to the credential's provider. Returns `{content, role, model, usage}`. Pass either a string (wrapped as a single user message) or an array of `{role, content}` objects.",
+        group: "chat",
+        action: "write",
+        icon: "message-square",
+        capability: "manage_options",
+        sideEffects: ["makes_http_call", "charges_money"],
+        idempotent: false,
+        since: "1.0.0",
+        tags: ["ai", "chat", "llm", "completion"],
+        parameters: [
+            credentialParam,
+            {
+                name: "messages",
+                title: "Messages",
+                description: "String (single user prompt) or array of {role, content}.",
+                dataType: "any",
+                formInputType: "json",
+                required: true,
+                allowExpression: true,
+                language: "json",
+                rows: 6,
+            },
+            optionsParam,
+        ],
+        returnType: "object",
+        returnDescription: "{ content, role, model, usage?: {promptTokens, completionTokens, totalTokens} }",
+        errors: commonErrors,
+        examples: [
+            {
+                title: "Ask a quick question",
+                code: 'ai.chat "my_ai" "Explain quantum computing in one line."',
+            },
+            {
+                title: "With a system prompt",
+                code: 'ai.chat "my_ai" [{role: "user", content: "Summarize {{ post.content }}"}] {system: "You are concise.", maxTokens: 80}',
+            },
+        ],
+        example: 'ai.chat "my_ai" "Hi"',
+    },
+    complete: {
+        title: "Text completion",
+        summary: "Run a chat request and return just the text",
+        description: "Same as `chat` but unwraps the response and returns the plain text `content`.",
+        group: "chat",
+        action: "write",
+        icon: "type",
+        capability: "manage_options",
+        sideEffects: ["makes_http_call", "charges_money"],
+        idempotent: false,
+        since: "1.0.0",
+        tags: ["ai", "complete", "text"],
+        parameters: [
+            credentialParam,
+            {
+                name: "prompt",
+                title: "Prompt",
+                description: "The user prompt to send.",
+                dataType: "string",
+                formInputType: "textarea",
+                required: true,
+                allowExpression: true,
+                rows: 4,
+            },
+            optionsParam,
+        ],
+        returnType: "string",
+        returnDescription: "The generated text (or error object on failure).",
+        errors: commonErrors,
+        example: 'ai.complete "my_ai" "Write a haiku about automation."',
+    },
+    summarize: {
+        title: "Summarize text",
+        summary: "Produce a concise summary of a piece of text",
+        description: "Wraps `complete` with a summarization prompt. Pass `maxLength` (in words) via options.",
+        group: "helpers",
+        action: "write",
+        icon: "list",
+        capability: "manage_options",
+        sideEffects: ["makes_http_call", "charges_money"],
+        idempotent: false,
+        since: "1.0.0",
+        tags: ["ai", "summarize"],
+        parameters: [
+            credentialParam,
+            {
+                name: "text",
+                title: "Text",
+                description: "The source text to summarize.",
+                dataType: "string",
+                formInputType: "textarea",
+                required: true,
+                allowExpression: true,
+                rows: 6,
+            },
+            {
+                name: "options",
+                title: "Options",
+                description: "Recognized keys:\n  maxLength  : target word count\n  model / maxTokens / temperature",
+                dataType: "object",
+                formInputType: "json",
+                required: false,
+                allowExpression: true,
+                language: "json",
+                rows: 3,
+                advanced: true,
+            },
+        ],
+        returnType: "string",
+        returnDescription: "The summary text.",
+        errors: commonErrors,
+        example: 'ai.summarize "my_ai" {{ post.content }} {maxLength: 50}',
+    },
+    extract: {
+        title: "Extract structured fields",
+        summary: "Pull named fields out of text as a JSON object",
+        description: "Asks the model to return a JSON object with the given keys. Temperature is forced to 0.",
+        group: "helpers",
+        action: "write",
+        icon: "box-select",
+        capability: "manage_options",
+        sideEffects: ["makes_http_call", "charges_money"],
+        idempotent: true,
+        since: "1.0.0",
+        tags: ["ai", "extract", "json"],
+        parameters: [
+            credentialParam,
+            {
+                name: "text",
+                title: "Text",
+                description: "Unstructured source text.",
+                dataType: "string",
+                formInputType: "textarea",
+                required: true,
+                allowExpression: true,
+                rows: 6,
+            },
+            {
+                name: "fields",
+                title: "Fields",
+                description: "Array of field names (or comma-separated string) to extract.",
+                dataType: "array",
+                formInputType: "json",
+                required: true,
+                allowExpression: true,
+                language: "json",
+                rows: 2,
+                placeholder: '["name", "email", "company"]',
+            },
+            optionsParam,
+        ],
+        returnType: "object",
+        returnDescription: "Parsed JSON object with the requested keys, or raw text on parse failure.",
+        errors: { ...commonErrors, fields_missing: "You must pass at least one field name." },
+        example: 'ai.extract "my_ai" "John Smith, 30, NYC" ["name","age","city"]',
+    },
+    classify: {
+        title: "Classify into categories",
+        summary: "Pick exactly one category for a piece of text",
+        description: "Returns the category label chosen by the model. Temperature is forced to 0.",
+        group: "helpers",
+        action: "write",
+        icon: "tag",
+        capability: "manage_options",
+        sideEffects: ["makes_http_call", "charges_money"],
+        idempotent: true,
+        since: "1.0.0",
+        tags: ["ai", "classify"],
+        parameters: [
+            credentialParam,
+            {
+                name: "text",
+                title: "Text",
+                description: "Text to classify.",
+                dataType: "string",
+                formInputType: "textarea",
+                required: true,
+                allowExpression: true,
+                rows: 4,
+            },
+            {
+                name: "categories",
+                title: "Categories",
+                description: "Array (at least 2) of category labels to choose from.",
+                dataType: "array",
+                formInputType: "json",
+                required: true,
+                allowExpression: true,
+                language: "json",
+                rows: 2,
+                placeholder: '["billing","support","sales","spam"]',
+            },
+            optionsParam,
+        ],
+        returnType: "string",
+        returnDescription: "The selected category label.",
+        errors: { ...commonErrors, categories_missing: "At least 2 categories are required." },
+        example: 'ai.classify "my_ai" "Love this product!" ["positive","negative","neutral"]',
+    },
+    translate: {
+        title: "Translate text",
+        summary: "Translate a string to a target language",
+        description: "Wraps `complete` with a translation prompt. Pass the language name (e.g. 'Spanish') as the third arg.",
+        group: "helpers",
+        action: "write",
+        icon: "languages",
+        capability: "manage_options",
+        sideEffects: ["makes_http_call", "charges_money"],
+        idempotent: true,
+        since: "1.0.0",
+        tags: ["ai", "translate"],
+        parameters: [
+            credentialParam,
+            {
+                name: "text",
+                title: "Text",
+                description: "Text to translate.",
+                dataType: "string",
+                formInputType: "textarea",
+                required: true,
+                allowExpression: true,
+                rows: 4,
+            },
+            {
+                name: "targetLang",
+                title: "Target language",
+                description: "Human-readable target language (e.g. 'Spanish', 'French').",
+                dataType: "string",
+                formInputType: "text",
+                required: true,
+                allowExpression: true,
+                placeholder: "Spanish",
+            },
+            optionsParam,
+        ],
+        returnType: "string",
+        returnDescription: "The translated text.",
+        errors: commonErrors,
+        example: 'ai.translate "my_ai" "Hello world" "French"',
+    },
+    sentiment: {
+        title: "Analyze sentiment",
+        summary: "Classify text as positive / negative / neutral with a score",
+        description: "Returns `{sentiment, score, confidence}`. Temperature is forced to 0.",
+        group: "helpers",
+        action: "write",
+        icon: "smile",
+        capability: "manage_options",
+        sideEffects: ["makes_http_call", "charges_money"],
+        idempotent: true,
+        since: "1.0.0",
+        tags: ["ai", "sentiment"],
+        parameters: [
+            credentialParam,
+            {
+                name: "text",
+                title: "Text",
+                description: "Text to analyze.",
+                dataType: "string",
+                formInputType: "textarea",
+                required: true,
+                allowExpression: true,
+                rows: 4,
+            },
+            optionsParam,
+        ],
+        returnType: "object",
+        returnDescription: "{ sentiment: 'positive'|'negative'|'neutral', score: 0..1, confidence: 0..1 }",
+        errors: commonErrors,
+        example: 'ai.sentiment "my_ai" "This is amazing!"',
+    },
+    generateJson: {
+        title: "Generate structured JSON",
+        summary: "Ask the model to produce JSON matching an optional schema",
+        description: "Returns the parsed JSON object (or raw text on parse failure). Temperature is forced to 0.",
+        group: "helpers",
+        action: "write",
+        icon: "braces",
+        capability: "manage_options",
+        sideEffects: ["makes_http_call", "charges_money"],
+        idempotent: true,
+        since: "1.0.0",
+        tags: ["ai", "json", "schema"],
+        parameters: [
+            credentialParam,
+            {
+                name: "prompt",
+                title: "Prompt",
+                description: "Describe what JSON you want.",
+                dataType: "string",
+                formInputType: "textarea",
+                required: true,
+                allowExpression: true,
+                rows: 4,
+            },
+            {
+                name: "schema",
+                title: "Schema",
+                description: "Optional example object that the output should mirror.",
+                dataType: "object",
+                formInputType: "json",
+                required: false,
+                allowExpression: true,
+                language: "json",
+                rows: 4,
+            },
+            optionsParam,
+        ],
+        returnType: "object",
+        returnDescription: "Parsed JSON (or raw text on parse failure).",
+        errors: commonErrors,
+        example: 'ai.generateJson "my_ai" "Make a fake user" {name: "string", email: "string"}',
+    },
+    embedding: {
+        title: "Create embedding",
+        summary: "Get a vector embedding for text(s)",
+        description: "Calls `/embeddings` against the credential's provider. Expects an OpenAI-style embeddings endpoint — works for OpenAI, OpenRouter, and most compatible APIs. Anthropic currently has no hosted embeddings endpoint.",
+        group: "chat",
+        action: "write",
+        icon: "binary",
+        capability: "manage_options",
+        sideEffects: ["makes_http_call", "charges_money"],
+        idempotent: true,
+        since: "1.0.0",
+        tags: ["ai", "embedding", "vector"],
+        parameters: [
+            credentialParam,
+            {
+                name: "input",
+                title: "Input",
+                description: "A string or array of strings to embed.",
+                dataType: "any",
+                formInputType: "json",
+                required: true,
+                allowExpression: true,
+                language: "json",
+                rows: 3,
+            },
+            {
+                name: "options",
+                title: "Options",
+                description: "Recognized keys:\n  model : default 'text-embedding-3-small'",
+                dataType: "object",
+                formInputType: "json",
+                required: false,
+                allowExpression: true,
+                language: "json",
+                rows: 3,
+                advanced: true,
+            },
+        ],
+        returnType: "any",
+        returnDescription: "A vector (for a single string) or array of vectors (for multiple inputs).",
+        errors: commonErrors,
+        example: 'ai.embedding "my_ai" "Hello world"',
+    },
+};
+export const AiModuleMetadata = {
+    slug: "ai",
+    title: "AI (generic LLM)",
+    summary: "Provider-agnostic LLM helpers: chat, complete, summarize, extract, classify, translate, sentiment, JSON, embeddings",
+    description: "A thin provider-agnostic wrapper. Point a single `ai_provider` credential at OpenAI, Anthropic, OpenRouter, or any OpenAI-compatible endpoint and every handler just works. Use the dedicated `openai` / `anthropic` modules when you need vendor-specific features (images, audio, vision, tool use).",
+    category: "ai",
+    icon: "icon.svg",
+    color: "#7C3AED",
+    version: "0.2.0",
+    docsUrl: "https://docs.robinpath.com/modules/ai",
+    status: "stable",
+    requires: [],
+    minNodeVersion: "18.0.0",
+    credentialsType: CREDENTIAL_TYPE,
+    operationGroups: {
+        setup: { title: "Setup", description: "Credential validation.", order: 1 },
+        chat: { title: "Chat & Embeddings", description: "Core LLM calls.", order: 2 },
+        helpers: { title: "Helpers", description: "Sugar for common tasks.", order: 3 },
+    },
+    methods: Object.keys(AiFunctions),
+};
+//# sourceMappingURL=ai.js.map

dist/ai.js.map

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dist/index.d.ts

+import type { ModuleAdapter } from "@robinpath/core";
+declare const AiModule: ModuleAdapter;
+export default AiModule;
+export { AiModule };
+export { AiFunctions, AiFunctionMetadata, AiModuleMetadata, AiCredentialTypes, configureAi, } from "./ai.js";
+//# sourceMappingURL=index.d.ts.map

dist/index.d.ts.map

+{"version":3,"file":"index.d.ts","sourceRoot":"","sources":["../src/index.ts"],"names":[],"mappings":"AAAA,OAAO,KAAK,EAAE,aAAa,EAAE,MAAM,iBAAiB,CAAC;AASrD,QAAA,MAAM,QAAQ,EAAE,aAQf,CAAC;AAEF,eAAe,QAAQ,CAAC;AACxB,OAAO,EAAE,QAAQ,EAAE,CAAC;AACpB,OAAO,EACL,WAAW,EACX,kBAAkB,EAClB,gBAAgB,EAChB,iBAAiB,EACjB,WAAW,GACZ,MAAM,SAAS,CAAC"}

dist/index.js

+import { AiFunctions, AiFunctionMetadata, AiModuleMetadata, AiCredentialTypes, configureAi, } from "./ai.js";
+const AiModule = {
+    name: "ai",
+    functions: AiFunctions,
+    functionMetadata: AiFunctionMetadata,
+    moduleMetadata: AiModuleMetadata,
+    credentialTypes: AiCredentialTypes,
+    configure: configureAi,
+    global: false,
+};
+export default AiModule;
+export { AiModule };
+export { AiFunctions, AiFunctionMetadata, AiModuleMetadata, AiCredentialTypes, configureAi, } from "./ai.js";
+//# sourceMappingURL=index.js.map

dist/index.js.map

+{"version":3,"file":"index.js","sourceRoot":"","sources":["../src/index.ts"],"names":[],"mappings":"AACA,OAAO,EACL,WAAW,EACX,kBAAkB,EAClB,gBAAgB,EAChB,iBAAiB,EACjB,WAAW,GACZ,MAAM,SAAS,CAAC;AAEjB,MAAM,QAAQ,GAAkB;IAC9B,IAAI,EAAE,IAAI;IACV,SAAS,EAAE,WAAW;IACtB,gBAAgB,EAAE,kBAAkB;IACpC,cAAc,EAAE,gBAAgB;IAChC,eAAe,EAAE,iBAAiB;IAClC,SAAS,EAAE,WAAW;IACtB,MAAM,EAAE,KAAK;CACd,CAAC;AAEF,eAAe,QAAQ,CAAC;AACxB,OAAO,EAAE,QAAQ,EAAE,CAAC;AACpB,OAAO,EACL,WAAW,EACX,kBAAkB,EAClB,gBAAgB,EAChB,iBAAiB,EACjB,WAAW,GACZ,MAAM,SAAS,CAAC"}

package.json

 {
   "name": "@robinpath/ai",
-  "version": "0.1.2",
-  "description": "LLM integration for OpenAI, Anthropic, and compatible APIs",
+  "version": "0.3.0",
+  "description": "Provider-agnostic LLM helpers (OpenAI, Anthropic, OpenRouter, or any OpenAI-compatible endpoint). Uses the encrypted credential vault.",
   "publishConfig": {
@@ -25,6 +25,6 @@ "access": "public"
   "peerDependencies": {
-    "@robinpath/core": ">=0.20.0"
+    "@robinpath/core": ">=0.40.0"
   },
   "devDependencies": {
-    "@robinpath/core": "^0.30.1",
+    "@robinpath/core": "^0.40.0",
     "tsx": "^4.19.0",
@@ -34,3 +34,6 @@ "typescript": "^5.6.0"
   "keywords": [
-    "ai"
+    "ai",
+    "llm",
+    "openai",
+    "anthropic"
   ],
@@ -41,5 +44,12 @@ "license": "MIT",
     "type": "integration",
-    "auth": "api-key",
-    "functionCount": 10
+    "auth": "credential-vault",
+    "credentialType": "ai_provider",
+    "functionCount": 10,
+    "language": "nodejs",
+    "platforms": [
+      "cloud",
+      "cli",
+      "desktop"
+    ]
   }
 }

README.md

@@ -22,3 +22,3 @@ # @robinpath/ai
 ```bash
-npm install @robinpath/ai
+robinpath add @robinpath/ai
 ```
@@ -25,0 +25,0 @@

New alerts

Major refactor

Supply chain risk

Package has recently undergone a major refactor. It may be unstable or indicate significant internal changes. Use caution when updating to versions that include significant changes.

Found 1 instance in 1 package

Network access

Supply chain risk

This module accesses the network.

Found 1 instance in 1 package

URL strings

Supply chain risk

Package contains fragments of external URLs or IP addresses, which the package may be accessing at runtime.

Found 1 instance in 1 package

Fixed alerts

Empty package

Supply chain risk

Package does not contain any code. It may be removed, is name squatting, or the result of a faulty package publish.

Found 1 instance in 1 package

Major refactor

Supply chain risk

Package has recently undergone a major refactor. It may be unstable or indicate significant internal changes. Use caution when updating to versions that include significant changes.

Found 1 instance in 1 package

Improved metrics

Total package byte prevSize

65681

1485.73%

Number of package files

10

400%

Lines of code

853

Infinity%

Worsened metrics

Number of low supply chain risk alerts

2

100%

Number of medium supply chain risk alerts

4

100%

No dependency changes