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-rw-r--r--config/pi/extensions/parallel-extract.ts277
-rw-r--r--config/pi/extensions/parallel-search.ts401
-rw-r--r--config/pi/extensions/provider-discovery.ts.disabled108
-rw-r--r--config/pi/models.json20
-rw-r--r--config/pi/settings.json11
5 files changed, 817 insertions, 0 deletions
diff --git a/config/pi/extensions/parallel-extract.ts b/config/pi/extensions/parallel-extract.ts
new file mode 100644
index 0000000..2ab7a87
--- /dev/null
+++ b/config/pi/extensions/parallel-extract.ts
@@ -0,0 +1,277 @@
+/**
+ * Parallel Extract Extension - Content extraction via Parallel.ai
+ *
+ * Provides the extract tool for extracting content from URLs.
+ *
+ * Requires PARALLEL_API_KEY environment variable.
+ *
+ * https://docs.parallel.ai
+ */
+
+import {
+ DEFAULT_MAX_BYTES,
+ DEFAULT_MAX_LINES,
+ type ExtensionAPI,
+ formatSize,
+ getMarkdownTheme,
+ keyHint,
+ type Theme,
+ truncateHead,
+} from "@mariozechner/pi-coding-agent";
+import { Container, Markdown, Spacer, Text } from "@mariozechner/pi-tui";
+import { Type } from "typebox";
+
+const API_BASE = "https://api.parallel.ai";
+const BETA_HEADER = "search-extract-2025-10-10";
+
+function getApiKey(): string {
+ const key = process.env.PARALLEL_API_KEY;
+ if (!key) {
+ throw new Error(
+ "PARALLEL_API_KEY environment variable is not set. " +
+ "Get your API key at https://platform.parallel.ai",
+ );
+ }
+ return key;
+}
+
+// ── API types ──────────────────────────────────────────────────────────────
+
+interface ExtractResult {
+ url: string;
+ title?: string | null;
+ publish_date?: string | null;
+ excerpts?: string[] | null;
+ full_content?: string | null;
+}
+
+interface ExtractError {
+ url: string;
+ error_type: string;
+ http_status_code?: number | null;
+ content?: string | null;
+}
+
+interface ExtractResponse {
+ extract_id: string;
+ results: ExtractResult[];
+ errors: ExtractError[];
+}
+
+// ── API helper ─────────────────────────────────────────────────────────────
+
+async function parallelExtract(
+ params: {
+ url: string;
+ objective?: string;
+ },
+ signal?: AbortSignal,
+): Promise<ExtractResponse> {
+ const body: Record<string, unknown> = {
+ urls: [params.url],
+ excerpts: false,
+ full_content: true,
+ };
+ if (params.objective) body.objective = params.objective;
+
+ const resp = await fetch(`${API_BASE}/v1beta/extract`, {
+ method: "POST",
+ headers: {
+ "Content-Type": "application/json",
+ "x-api-key": getApiKey(),
+ "parallel-beta": BETA_HEADER,
+ },
+ body: JSON.stringify(body),
+ signal,
+ });
+
+ if (!resp.ok) {
+ const text = await resp.text().catch(() => "");
+ throw new Error(`Extract API error ${resp.status}: ${text}`);
+ }
+
+ return (await resp.json()) as ExtractResponse;
+}
+
+// ── Formatting helper ──────────────────────────────────────────────────────
+
+function formatExtractResult(result?: ExtractResult, error?: ExtractError): string {
+ if (error) {
+ return (
+ `## Error: ${error.url}\nType: ${error.error_type}` +
+ (error.http_status_code ? ` (HTTP ${error.http_status_code})` : "") +
+ (error.content ? `\n${error.content}` : "")
+ );
+ }
+
+ if (!result) return "No content extracted.";
+
+ return "\n" + (result.full_content ?? "");
+}
+
+// ── Tool details type ──────────────────────────────────────────────────────
+
+interface ExtractDetails {
+ url: string;
+ error: boolean;
+ extractId: string;
+ truncated?: boolean;
+ spinnerFrame?: number;
+}
+
+// ── Spinner ─────────────────────────────────────────────────────────────────
+
+const SPINNER_FRAMES = ["⠋", "⠙", "⠹", "⠸", "⠼", "⠴", "⠦", "⠧", "⠇", "⠏"];
+
+type SpinnerUpdate = (partial: {
+ content: { type: "text"; text: string }[];
+ details?: ExtractDetails;
+}) => void;
+
+function startSpinner(
+ onUpdate: SpinnerUpdate | undefined,
+ baseDetails: ExtractDetails,
+ signal?: AbortSignal,
+): () => void {
+ if (!onUpdate) return () => {};
+ let frame = 0;
+ const interval = setInterval(() => {
+ if (signal?.aborted) {
+ clearInterval(interval);
+ return;
+ }
+ onUpdate({
+ content: [{ type: "text", text: "Running..." }],
+ details: { ...baseDetails, spinnerFrame: frame },
+ });
+ frame = (frame + 1) % SPINNER_FRAMES.length;
+ }, 80);
+ return () => clearInterval(interval);
+}
+
+function renderSpinner(details: ExtractDetails | undefined, theme: Theme, label: string): Text {
+ const frame = details?.spinnerFrame ?? 0;
+ const spinner = SPINNER_FRAMES[frame % SPINNER_FRAMES.length];
+ return new Text(`\n${theme.fg("dim", `${spinner} ${label} (escape/ctrl+c to cancel)`)}`, 0, 0);
+}
+
+// ── Extension entry point ──────────────────────────────────────────────────
+
+export default function (pi: ExtensionAPI) {
+ if (!process.env.PARALLEL_API_KEY) return;
+
+ pi.registerTool({
+ name: "extract",
+ label: "Extract",
+ description:
+ `Extract content from a URL. Returns page title and full content. ` +
+ `Optionally provide an objective to focus extraction on specific information. ` +
+ `Output truncated to ${DEFAULT_MAX_LINES} lines or ${formatSize(DEFAULT_MAX_BYTES)}.`,
+ promptSnippet: "Extract full content from a URL via Parallel.ai",
+ parameters: Type.Object({
+ url: Type.String({
+ description: "URL to extract content from",
+ }),
+ objective: Type.Optional(
+ Type.String({
+ description: "Focus extraction on this objective (e.g. 'find the pricing information')",
+ }),
+ ),
+ }),
+
+ async execute(_toolCallId, params, signal, onUpdate) {
+ const { url, objective } = params;
+
+ const baseDetails: ExtractDetails = { url, error: false, extractId: "" };
+ const stopSpinner = startSpinner(onUpdate as SpinnerUpdate | undefined, baseDetails, signal);
+
+ let response: ExtractResponse;
+ try {
+ response = await parallelExtract({ url, objective }, signal);
+ } finally {
+ stopSpinner();
+ }
+
+ const hasError = response.errors.length > 0;
+ let resultText = formatExtractResult(response.results[0], response.errors[0]);
+
+ const truncation = truncateHead(resultText, {
+ maxLines: DEFAULT_MAX_LINES,
+ maxBytes: DEFAULT_MAX_BYTES,
+ });
+
+ resultText = truncation.content;
+ const truncated = truncation.truncated;
+ if (truncated) {
+ resultText += `\n\n[Output truncated: showing ${truncation.outputLines} of ${truncation.totalLines} lines `;
+ resultText += `(${formatSize(truncation.outputBytes)} of ${formatSize(truncation.totalBytes)}). `;
+ resultText += `Try a more specific objective to reduce content size.]`;
+ }
+
+ const details: ExtractDetails = {
+ url,
+ error: hasError,
+ extractId: response.extract_id,
+ truncated,
+ };
+
+ return {
+ content: [{ type: "text", text: resultText }],
+ details,
+ };
+ },
+
+ renderCall(args, theme) {
+ let text = theme.fg("toolTitle", theme.bold("extract "));
+ text += theme.fg("accent", args.url.replace(/^https?:\/\//, ""));
+ return new Text(text, 0, 0);
+ },
+
+ renderResult(result, { expanded, isPartial }, theme) {
+ const details = result.details as ExtractDetails | undefined;
+
+ if (isPartial) {
+ return renderSpinner(details, theme, "Extracting...");
+ }
+
+ if (!details || !details.extractId) {
+ const content = result.content[0];
+ const msg = content?.type === "text" ? content.text : "No content";
+ return new Text(theme.fg("dim", msg), 0, 0);
+ }
+
+ if (!expanded) {
+ let text = "";
+ if (details.error) {
+ text += "\n" + theme.fg("error", "error");
+ }
+ text += `\n(${keyHint("app.tools.expand", "to expand")})`;
+ return new Text(text, 0, 0);
+ }
+
+ const content = result.content[0];
+ if (content?.type === "text" && content.text) {
+ const container = new Container();
+ if (details.error) {
+ container.addChild(new Text(theme.fg("error", "error"), 0, 0));
+ }
+ const mdTheme = getMarkdownTheme();
+ container.addChild(
+ new Markdown(content.text, 1, 0, mdTheme, { color: (t) => theme.fg("dim", t) }),
+ );
+ if (details.truncated) {
+ container.addChild(new Text(theme.fg("warning", "[truncated]"), 1, 0));
+ }
+ container.addChild(new Spacer(1));
+ container.addChild(new Text(`(${keyHint("app.tools.expand", "to collapse")})`, 0, 0));
+ return container;
+ }
+
+ let text = "";
+ if (details.error) {
+ text += theme.fg("error", "error");
+ }
+ return new Text(text, 0, 0);
+ },
+ });
+}
diff --git a/config/pi/extensions/parallel-search.ts b/config/pi/extensions/parallel-search.ts
new file mode 100644
index 0000000..3bca820
--- /dev/null
+++ b/config/pi/extensions/parallel-search.ts
@@ -0,0 +1,401 @@
+/**
+ * Parallel Search Extension - Web search via Parallel.ai
+ *
+ * Provides the search tool for searching the web using natural language objectives or keyword queries.
+ *
+ * Requires PARALLEL_API_KEY environment variable.
+ *
+ * https://docs.parallel.ai
+ */
+
+import {
+ DEFAULT_MAX_BYTES,
+ DEFAULT_MAX_LINES,
+ type ExtensionAPI,
+ formatSize,
+ getMarkdownTheme,
+ keyHint,
+ type Theme,
+ truncateHead,
+} from "@mariozechner/pi-coding-agent";
+import { Container, Markdown, Spacer, Text } from "@mariozechner/pi-tui";
+import { Type } from "typebox";
+
+const API_BASE = "https://api.parallel.ai";
+const BETA_HEADER = "search-extract-2025-10-10";
+
+function getApiKey(): string {
+ const key = process.env.PARALLEL_API_KEY;
+ if (!key) {
+ throw new Error(
+ "PARALLEL_API_KEY environment variable is not set. " +
+ "Get your API key at https://platform.parallel.ai",
+ );
+ }
+ return key;
+}
+
+// ── API types ──────────────────────────────────────────────────────────────
+
+interface SearchResult {
+ url: string;
+ title?: string | null;
+ publish_date?: string | null;
+ excerpts?: string[] | null;
+}
+
+interface SearchResponse {
+ search_id: string;
+ results: SearchResult[];
+}
+
+// ── API helper ─────────────────────────────────────────────────────────────
+
+async function parallelSearch(
+ params: {
+ objective?: string;
+ search_queries?: string[];
+ max_results?: number;
+ mode?: string;
+ include_domains?: string[];
+ exclude_domains?: string[];
+ after_date?: string;
+ max_chars_per_result?: number;
+ max_chars_total?: number;
+ },
+ signal?: AbortSignal,
+): Promise<SearchResponse> {
+ const body: Record<string, unknown> = {
+ mode: params.mode ?? "agentic",
+ };
+ if (params.objective) body.objective = params.objective;
+ if (params.search_queries) body.search_queries = params.search_queries;
+ if (params.max_results) body.max_results = params.max_results;
+
+ if (params.max_chars_per_result || params.max_chars_total) {
+ const excerpts: Record<string, unknown> = {};
+ if (params.max_chars_per_result) excerpts.max_chars_per_result = params.max_chars_per_result;
+ if (params.max_chars_total) excerpts.max_chars_total = params.max_chars_total;
+ body.excerpts = excerpts;
+ }
+
+ if (params.include_domains || params.exclude_domains || params.after_date) {
+ const sourcePolicy: Record<string, unknown> = {};
+ if (params.include_domains) sourcePolicy.include_domains = params.include_domains;
+ if (params.exclude_domains) sourcePolicy.exclude_domains = params.exclude_domains;
+ if (params.after_date) sourcePolicy.after_date = params.after_date;
+ body.source_policy = sourcePolicy;
+ }
+
+ const resp = await fetch(`${API_BASE}/v1beta/search`, {
+ method: "POST",
+ headers: {
+ "Content-Type": "application/json",
+ "x-api-key": getApiKey(),
+ "parallel-beta": BETA_HEADER,
+ },
+ body: JSON.stringify(body),
+ signal,
+ });
+
+ if (!resp.ok) {
+ const text = await resp.text().catch(() => "");
+ throw new Error(`Parallel search API error ${resp.status}: ${text}`);
+ }
+
+ return (await resp.json()) as SearchResponse;
+}
+
+// ── Formatting helper ──────────────────────────────────────────────────────
+
+function formatSearchResults(results: SearchResult[]): string {
+ if (results.length === 0) return "No results found.";
+
+ const parts: string[] = [];
+ for (let i = 0; i < results.length; i++) {
+ const r = results[i];
+ let entry = `[${i + 1}] ${r.title ?? "(no title)"}\n ${r.url}`;
+ if (r.publish_date) entry += `\n Published: ${r.publish_date}`;
+ if (r.excerpts?.length) {
+ entry += "\n" + r.excerpts.map((e) => ` ${e}`).join("\n");
+ }
+ parts.push(entry);
+ }
+ return parts.join("\n\n");
+}
+
+// ── Tool details types ─────────────────────────────────────────────────────
+
+interface SearchResultDetail {
+ url: string;
+ title?: string | null;
+ publish_date?: string | null;
+ excerpts?: string[] | null;
+}
+
+interface SearchDetails {
+ objective?: string;
+ search_queries?: string[];
+ resultCount: number;
+ searchId: string;
+ results?: SearchResultDetail[];
+ spinnerFrame?: number;
+}
+
+// ── Spinner ─────────────────────────────────────────────────────────────────
+
+const SPINNER_FRAMES = ["⠋", "⠙", "⠹", "⠸", "⠼", "⠴", "⠦", "⠧", "⠇", "⠏"];
+
+type SpinnerUpdate = (partial: {
+ content: { type: "text"; text: string }[];
+ details?: SearchDetails;
+}) => void;
+
+function startSpinner(
+ onUpdate: SpinnerUpdate | undefined,
+ baseDetails: SearchDetails,
+ signal?: AbortSignal,
+): () => void {
+ if (!onUpdate) return () => {};
+ let frame = 0;
+ const interval = setInterval(() => {
+ if (signal?.aborted) {
+ clearInterval(interval);
+ return;
+ }
+ onUpdate({
+ content: [{ type: "text", text: "Running..." }],
+ details: { ...baseDetails, spinnerFrame: frame },
+ });
+ frame = (frame + 1) % SPINNER_FRAMES.length;
+ }, 80);
+ return () => clearInterval(interval);
+}
+
+function renderSpinner(details: SearchDetails | undefined, theme: Theme, label: string): Text {
+ const frame = details?.spinnerFrame ?? 0;
+ const spinner = SPINNER_FRAMES[frame % SPINNER_FRAMES.length];
+ return new Text(`\n${theme.fg("dim", `${spinner} ${label} (escape/ctrl+c to cancel)`)}`, 0, 0);
+}
+
+// ── Extension entry point ──────────────────────────────────────────────────
+
+export default function (pi: ExtensionAPI) {
+ if (!process.env.PARALLEL_API_KEY) return;
+
+ const searchCountCache = new Map<string, number>();
+ function searchCacheKey(objective?: string, search_queries?: string[]): string {
+ return JSON.stringify({ objective, search_queries });
+ }
+
+ pi.registerTool({
+ name: "search",
+ label: "Search",
+ description:
+ `Search the web. Provide a natural language objective describing what you're looking for, ` +
+ `and/or keyword search queries. Returns relevant results with titles, URLs, and excerpts. ` +
+ `Output truncated to ${DEFAULT_MAX_LINES} lines or ${formatSize(DEFAULT_MAX_BYTES)}.`,
+ promptSnippet: "Search the web via Parallel.ai (objective and/or keyword queries)",
+ parameters: Type.Object({
+ objective: Type.Optional(
+ Type.String({
+ description:
+ "Natural language description of what to find. At least one of objective or search_queries is required.",
+ }),
+ ),
+ search_queries: Type.Optional(
+ Type.Array(Type.String(), {
+ description:
+ "Keyword search queries. May contain search operators. At least one of objective or search_queries is required.",
+ }),
+ ),
+ max_results: Type.Optional(
+ Type.Number({
+ description: "Max results to return (default: 5)",
+ }),
+ ),
+ mode: Type.Optional(
+ Type.String({
+ description:
+ 'Search mode: "agentic" (default, concise), "one-shot" (comprehensive), or "fast" (lower latency)',
+ }),
+ ),
+ include_domains: Type.Optional(
+ Type.Array(Type.String(), {
+ description: 'Restrict results to these domains (e.g. ["wikipedia.org", ".gov"])',
+ }),
+ ),
+ exclude_domains: Type.Optional(
+ Type.Array(Type.String(), {
+ description: 'Exclude results from these domains (e.g. ["reddit.com"])',
+ }),
+ ),
+ after_date: Type.Optional(
+ Type.String({
+ description: "Only return results published on or after this date (YYYY-MM-DD)",
+ }),
+ ),
+ max_chars_per_result: Type.Optional(
+ Type.Number({
+ description: "Max characters of excerpts per result (min 1000)",
+ }),
+ ),
+ max_chars_total: Type.Optional(
+ Type.Number({
+ description: "Max total characters of excerpts across all results (min 1000)",
+ }),
+ ),
+ }),
+
+ async execute(_toolCallId, params, signal, onUpdate) {
+ const {
+ objective,
+ search_queries,
+ max_results,
+ mode,
+ include_domains,
+ exclude_domains,
+ after_date,
+ max_chars_per_result,
+ max_chars_total,
+ } = params;
+
+ if (!objective && (!search_queries || search_queries.length === 0)) {
+ throw new Error("at least one of objective or search_queries must be provided.");
+ }
+
+ const baseDetails: SearchDetails = {
+ objective,
+ search_queries,
+ resultCount: 0,
+ searchId: "",
+ };
+ const stopSpinner = startSpinner(onUpdate as SpinnerUpdate | undefined, baseDetails, signal);
+
+ let response: SearchResponse;
+ try {
+ response = await parallelSearch(
+ {
+ objective,
+ search_queries,
+ max_results: max_results ?? 5,
+ mode,
+ include_domains,
+ exclude_domains,
+ after_date,
+ max_chars_per_result: max_chars_per_result ?? 500,
+ max_chars_total: max_chars_total ?? 2500,
+ },
+ signal,
+ );
+ } finally {
+ stopSpinner();
+ }
+
+ let resultText = formatSearchResults(response.results);
+
+ const truncation = truncateHead(resultText, {
+ maxLines: DEFAULT_MAX_LINES,
+ maxBytes: DEFAULT_MAX_BYTES,
+ });
+
+ resultText = truncation.content;
+ if (truncation.truncated) {
+ resultText += `\n\n[Output truncated: showing ${truncation.outputLines} of ${truncation.totalLines} lines `;
+ resultText += `(${formatSize(truncation.outputBytes)} of ${formatSize(truncation.totalBytes)})]`;
+ }
+
+ searchCountCache.set(searchCacheKey(objective, search_queries), response.results.length);
+
+ const details: SearchDetails = {
+ objective,
+ search_queries,
+ resultCount: response.results.length,
+ searchId: response.search_id,
+ results: response.results.map((r) => ({
+ url: r.url,
+ title: r.title,
+ publish_date: r.publish_date,
+ excerpts: r.excerpts,
+ })),
+ };
+
+ return {
+ content: [{ type: "text", text: resultText }],
+ details,
+ };
+ },
+
+ renderCall(args, theme) {
+ let text = theme.fg("toolTitle", theme.bold("search "));
+ if (args.objective) {
+ text += theme.fg("accent", `${args.objective}`);
+ } else if (args.search_queries?.length) {
+ text += theme.fg("accent", args.search_queries.join(", "));
+ }
+ if (args.include_domains?.length) {
+ text += theme.fg("muted", ` site:${args.include_domains.join(",")}`);
+ }
+ const count = searchCountCache.get(searchCacheKey(args.objective, args.search_queries));
+ if (count !== undefined) {
+ text += theme.fg("dim", ` [${count} results]`);
+ }
+ return new Text(text, 0, 0);
+ },
+
+ renderResult(result, { expanded, isPartial }, theme) {
+ const details = result.details as SearchDetails | undefined;
+
+ if (isPartial) {
+ return renderSpinner(details, theme, "Searching...");
+ }
+
+ if (!details || !details.resultCount) {
+ const content = result.content[0];
+ const msg = content?.type === "text" ? content.text : "No results found";
+ return new Text(theme.fg("warning", msg), 0, 0);
+ }
+
+ if (!expanded) {
+ let text = "\n";
+ if (details.results?.length) {
+ for (let i = 0; i < details.results.length; i++) {
+ const r = details.results[i];
+ if (i > 0) text += "\n";
+ const url = r.url.replace(/^https?:\/\//, "");
+ text += `${theme.fg("dim", `${i + 1}.`)} ${theme.fg("accent", url)}`;
+ }
+ }
+ text += `\n\n(${keyHint("app.tools.expand", "to expand")})`;
+ return new Text(text, 0, 0);
+ }
+
+ const container = new Container();
+ container.addChild(new Spacer(1));
+
+ if (details.results?.length) {
+ const mdTheme = getMarkdownTheme();
+ for (let i = 0; i < details.results.length; i++) {
+ if (i > 0) {
+ container.addChild(new Spacer(1));
+ }
+ const r = details.results[i];
+ const url = r.url.replace(/^https?:\/\//, "");
+ const header = `${theme.fg("dim", `${i + 1}.`)} ${theme.fg("accent", url)}`;
+ container.addChild(new Text(header, 0, 0));
+
+ if (r.excerpts?.length) {
+ const excerptMd = r.excerpts.join("\n\n---\n\n");
+ container.addChild(
+ new Markdown(excerptMd, 3, 0, mdTheme, { color: (t) => theme.fg("dim", t) }),
+ );
+ }
+ }
+ }
+
+ container.addChild(new Spacer(1));
+ container.addChild(new Text(`(${keyHint("app.tools.expand", "to collapse")})`, 0, 0));
+ return container;
+ },
+ });
+}
diff --git a/config/pi/extensions/provider-discovery.ts.disabled b/config/pi/extensions/provider-discovery.ts.disabled
new file mode 100644
index 0000000..759a2fb
--- /dev/null
+++ b/config/pi/extensions/provider-discovery.ts.disabled
@@ -0,0 +1,108 @@
+import type { ExtensionAPI } from "@mariozechner/pi-coding-agent";
+
+interface ProviderConfig {
+ id: string;
+ baseUrl: string;
+ envKey: string;
+ suffix: string;
+}
+
+const PROVIDERS: ProviderConfig[] = [
+ {
+ id: "siliconflow",
+ baseUrl: "https://api.siliconflow.com/v1",
+ envKey: "SILICONFLOW_API_KEY",
+ suffix: "SF"
+ },
+ {
+ id: "deepinfra",
+ baseUrl: "https://api.deepinfra.com/v1/openai",
+ envKey: "DEEPINFRA_API_KEY",
+ suffix: "DI"
+ }
+];
+
+// Patterns matched in order; first match wins.
+const CONTEXT_OVERRIDES: Array<[RegExp, number]> = [
+ [/qwen3.*coder/i, 262144],
+ [/qwen3.*next/i, 262144],
+ [/qwen3-235b|qwen3-32b|qwen3-14b|qwen3-8b|qwen3-30b/i, 131072],
+ [/qwq-32b/i, 131072],
+ [/qwen2\.5-.*-128k/i, 131072],
+ [/qwen2\.5/i, 32768],
+ [/deepseek-v3|deepseek-r1/i, 131072],
+ [/kimi-k2/i, 131072],
+ [/glm-4\.[567]|glm-5/i, 131072],
+ [/gpt-oss/i, 131072],
+ [/minimax/i, 245760],
+ [/hunyuan/i, 32768],
+];
+
+function resolveContextWindow(modelId: string): number {
+ for (const [pattern, ctx] of CONTEXT_OVERRIDES) {
+ if (pattern.test(modelId)) return ctx;
+ }
+ return 32768; // conservative fallback
+}
+
+export default async function (pi: ExtensionAPI) {
+ console.log("Provider discovery: Starting...");
+
+ await Promise.all(PROVIDERS.map(async (config) => {
+ const apiKey = process.env[config.envKey];
+ if (!apiKey) {
+ console.warn(`Provider discovery: ${config.envKey} not found. Skipping ${config.id}.`);
+ return;
+ }
+
+ try {
+ const response = await fetch(`${config.baseUrl}/models`, {
+ headers: { "Authorization": `Bearer ${apiKey}` }
+ });
+
+ if (!response.ok) {
+ throw new Error(`API error ${response.status}`);
+ }
+
+ const payload = await response.json();
+ const models = payload.data
+ .filter((model: any) => {
+ // Heuristic to filter for chat/text models
+ const id = model.id.toLowerCase();
+ return id.includes("/") || model.type === "text-generation" || id.includes("gpt") || id.includes("llama") || id.includes("claude");
+ })
+ .map((model: any) => {
+ const id = model.id;
+ const isReasoning = id.toLowerCase().includes("r1") ||
+ id.toLowerCase().includes("thinking") ||
+ id.toLowerCase().includes("reasoning") ||
+ id.toLowerCase().includes("qwq");
+
+ return {
+ id: id,
+ name: `${id.split('/').pop()} (${config.suffix})`,
+ reasoning: isReasoning,
+ input: ["text"],
+ contextWindow: model.context_window ?? resolveContextWindow(id),
+ maxTokens: 4096
+ };
+ });
+
+ pi.registerProvider(config.id, {
+ baseUrl: config.baseUrl,
+ apiKey: config.envKey,
+ api: "openai-completions",
+ models: models,
+ compat: {
+ supportsDeveloperRole: false,
+ supportsStrictMode: false,
+ requiresToolResultName: true
+ },
+ });
+
+ console.log(`Provider discovery: Registered ${models.length} models for ${config.id}.`);
+ } catch (error) {
+ console.error(`Provider discovery: Failed to fetch models for ${config.id}:`, error);
+ }
+ }));
+}
diff --git a/config/pi/models.json b/config/pi/models.json
new file mode 100644
index 0000000..9dd0617
--- /dev/null
+++ b/config/pi/models.json
@@ -0,0 +1,20 @@
+{
+ "providers": {
+ "siliconflow-anthropic": {
+ "baseUrl": "https://api.siliconflow.com/anthropic",
+ "api": "anthropic-messages",
+ "apiKey": "SILICONFLOW_API_KEY",
+ "authHeader": true,
+ "models": [
+ {
+ "id": "Qwen/Qwen3-Coder-480B-A35B-Instruct",
+ "name": "Qwen3 Coder 480B (SiliconFlow Anthropic)",
+ "reasoning": false,
+ "input": ["text"],
+ "contextWindow": 262144,
+ "maxTokens": 16384
+ }
+ ]
+ }
+ }
+}
diff --git a/config/pi/settings.json b/config/pi/settings.json
new file mode 100644
index 0000000..c1a47c4
--- /dev/null
+++ b/config/pi/settings.json
@@ -0,0 +1,11 @@
+{
+ "defaultProvider": "openrouter",
+ "defaultModel": "z-ai/glm-5.3",
+ "defaultThinkingLevel": "high",
+ "hideThinkingBlock": true,
+ "theme": "dark",
+ "packages": [
+ "npm:@narumitw/pi-goal",
+ "npm:pi-mcp-adapter@2.33.0"
+ ]
+}
generated by cgit v1.2.3 (git 2.39.1) at 2026-11-07 06:00:24 +0000