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The first public release of LLeMbas CLI: a terminal coding agent and project manager for any LLM API, with permission modes, git snapshots, memory and skills, knowledge bases, MCP, voice, and a link to a LLeMbas instance whose web UI can work its sessions too. Signed Linux binaries for x64 and arm64. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
90 lines
3.2 KiB
TypeScript
90 lines
3.2 KiB
TypeScript
import type { Connection, Effort, ModelSpec } from "../config/schema.ts"
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// Provider-neutral conversation model. Every dialect converts to and from this.
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export type TextPart = { type: "text"; text: string }
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export type ImagePart = { type: "image"; mime: string; data: string /* base64 */ }
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/** `signature` / `opaque` carry what a provider needs echoed back on the next turn
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* (Anthropic thinking signatures, Gemini thought signatures, Responses encrypted reasoning). */
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export type ReasoningPart = { type: "reasoning"; text: string; signature?: string; opaque?: unknown }
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/** `signature`: Gemini's thought signature, which must travel back with the call. */
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export type ToolCallPart = { type: "tool_call"; id: string; name: string; args: string /* raw JSON */; signature?: string }
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export type Message =
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/** `turnId`: the turn a prompt started, kept with it in the store for
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* `_lembas/session/history`; never sent to a model. */
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| { role: "user"; parts: (TextPart | ImagePart)[]; turnId?: string }
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| { role: "assistant"; parts: (TextPart | ReasoningPart | ToolCallPart)[] }
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| { role: "tool"; callId: string; name: string; content: string; isError?: boolean }
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export interface ToolSpec {
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name: string
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description: string
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/** JSON Schema for the arguments object. */
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parameters: Record<string, unknown>
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}
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export interface Usage {
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input: number
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output: number
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reasoning?: number
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cached?: number
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/** True when the endpoint reported nothing and these are estimates. */
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estimated?: boolean
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}
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export type StreamEvent =
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| { type: "text"; text: string }
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| { type: "reasoning"; text: string }
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/** Partial tool-call progress, for the UI. */
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| { type: "tool_call_delta"; index: number; name?: string; argsDelta: string }
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| { type: "usage"; usage: Usage }
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/** How far the server is through reading the prompt, before the reply starts (llama.cpp's
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* return_progress): tokens in all, taken from its cache, and read so far; ms spent reading. */
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| { type: "progress"; total: number; cache: number; processed: number; ms: number }
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| { type: "finish"; reason: string; message: Extract<Message, { role: "assistant" }> }
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/** Something worth telling the user that is not an error, e.g. a retry. */
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| { type: "notice"; message: string }
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export interface ChatRequest {
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system: string
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messages: Message[]
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tools: ToolSpec[]
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/** null = off */
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effort?: Effort | null
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signal?: AbortSignal
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}
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export interface ResolvedModel {
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/** `connection/model` */
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ref: string
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connectionName: string
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connection: Connection
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id: string
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spec: ModelSpec
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}
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export interface DiscoveredModel {
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id: string
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context?: number
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}
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export interface Client {
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stream(req: ChatRequest): AsyncGenerator<StreamEvent>
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listModels(): Promise<DiscoveredModel[]>
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}
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export class ProviderError extends Error {
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constructor(
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message: string,
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readonly status?: number,
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readonly body?: string,
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/** Nothing of the model's reply had been passed on yet, so a retry cannot duplicate output. */
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readonly beforeOutput = status !== undefined,
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/** The server could not be reached at all (refused, no route, no answer): another may be. */
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readonly unreachable = false,
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) {
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super(message)
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}
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}
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