feat: adapt pullfrog for gitea + ollama
This commit is contained in:
+1
-216
@@ -6,17 +6,8 @@ import type { ResolvedInstructions } from "../utils/instructions.ts";
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import type { ResolvedPayload } from "../utils/payload.ts";
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import type { TodoTracker } from "../utils/todoTracking.ts";
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// maximum number of stderr lines to keep in the rolling buffer during agent execution
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export const MAX_STDERR_LINES = 20;
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// ── post-run retry loop ────────────────────────────────────────────────────────
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/**
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* how many times the post-run loop may resume the agent to fix a dirty tree
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* or a failing stop hook before giving up.
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*/
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export const MAX_POST_RUN_RETRIES = 3;
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export function getGitStatus(): string {
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try {
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return execFileSync("git", ["status", "--porcelain"], {
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@@ -28,146 +19,33 @@ export function getGitStatus(): string {
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}
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}
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export function buildCommitPrompt(status: string): string {
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return [
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`UNCOMMITTED CHANGES — the working tree is dirty. push all changes to a pull request (new or existing). \`git status\` must be clean before you finish.`,
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"",
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"```",
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status,
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"```",
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].join("\n");
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}
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export interface StopHookFailure {
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exitCode: number;
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output: string;
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}
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export interface SummaryStale {
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/** absolute path to the seeded snapshot file the agent was meant to edit. */
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filePath: string;
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}
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export interface PostRunIssues {
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stopHook?: StopHookFailure;
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dirtyTree?: string;
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/** populated when the rolling PR summary file is byte-identical to its
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* seed, i.e. the agent never touched it. soft gate — nudges once via a
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* resume turn but never fails the run, parallel to dirtyTree semantics. */
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summaryStale?: SummaryStale;
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/**
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* populated when the agent selected a review mode but the post-run check
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* over toolState shows neither a `create_pull_request_review` submission
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* nor a final `report_progress` write happened. derived inline from
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* `toolState.selectedMode` + `toolState.review` + `toolState.finalSummaryWritten`
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* via {@link getUnsubmittedReview} — no parallel toolState flag is stored.
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* carries the mode name so the resume prompt can reference it. handled like
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* `stopHook`: nudge via resume, hard-fail if still unsatisfied after
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* `MAX_POST_RUN_RETRIES`.
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*/
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unsubmittedReview?: "Review" | "IncrementalReview";
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}
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export function hasPostRunIssues(issues: PostRunIssues): boolean {
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return (
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issues.stopHook !== undefined ||
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issues.dirtyTree !== undefined ||
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issues.summaryStale !== undefined ||
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issues.unsubmittedReview !== undefined
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);
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}
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/**
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* token/cost usage data from a single agent run.
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*
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* NOTE on semantics: `inputTokens` here is the *total* billable input for the
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* run — non-cached input + cache read + cache write — matching the per-agent
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* SDK conventions. This is what gets persisted to `WorkflowRun.inputTokens`.
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*
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* The stdout token table and markdown step summary display a different "Input"
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* column that shows only the non-cached portion (derivable as
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* `inputTokens - cacheReadTokens - cacheWriteTokens`) so humans can see the
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* cache hit ratio at a glance. Dashboards that query `WorkflowRun.inputTokens`
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* directly are seeing the full total, not the log column.
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*/
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export interface AgentUsage {
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agent: string;
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/** full billable input: non-cached + cache read + cache write */
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inputTokens: number;
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outputTokens: number;
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cacheReadTokens?: number | undefined;
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cacheWriteTokens?: number | undefined;
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costUsd?: number | undefined;
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}
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export interface AgentToolUseEvent {
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toolName: string;
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input: unknown;
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}
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/**
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* Result returned by agent execution
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*/
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export interface AgentResult {
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success: boolean;
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output?: string | undefined;
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error?: string | undefined;
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metadata?: Record<string, unknown>;
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usage?: AgentUsage | undefined;
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}
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/**
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* Context passed to agent.run() and threaded through the post-run loop.
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*
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* design rule: this is the single object that flows through the harness and
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* downstream utilities by reference. derived predicates (e.g.
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* `getUnsubmittedReview`), tmpfile paths, and seed bytes live on
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* `toolState` — read them at the call site, do not duplicate them onto this
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* interface. utilities that need run state should accept `ctx` whole, not
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* destructure a narrow subset.
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*/
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export interface AgentRunContext {
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payload: ResolvedPayload;
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resolvedModel?: string | undefined;
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model?: string | undefined;
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mcpServerUrl: string;
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tmpdir: string;
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/** harness-owned secret paths that agent filesystem tools must never read. */
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secretDenyPaths?: string[] | undefined;
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instructions: ResolvedInstructions;
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todoTracker?: TodoTracker | undefined;
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/**
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* user-configured stop hook script. runs after the agent finishes each
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* attempt; non-zero exit resumes the agent with the hook output as
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* guidance. null when the repo has no stop hook configured.
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*/
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stopScript?: string | null | undefined;
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/**
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* mutable per-run state shared with the MCP server (by reference). post-run
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* gates read fresh values from it after each agent attempt — `summaryFilePath`,
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* `summarySeed`, `selectedMode`, `review`, `finalSummaryWritten`,
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* `hadProgressComment` are all consulted by `collectPostRunIssues`. see
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* `action/toolState.ts` for the literal-state design rule.
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*/
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toolState: ToolState;
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/**
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* called synchronously when the agent subprocess is killed for inner
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* activity timeout. lets main.ts tear down shared resources (MCP HTTP
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* server) so lingering SSE reconnects don't keep the outer timer alive.
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*/
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onActivityTimeout?: (() => void) | undefined;
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onToolUse?: ((event: AgentToolUseEvent) => void) | undefined;
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/**
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* Pullfrog API JWT scoped to this run. agents only need this when they
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* have to write state back to Pullfrog mid-run (today: opencode.ts uses
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* it to seed the post-hook's writeback envelope for Codex auth refresh).
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* empty string when the run wasn't context-resolved (e.g. local dry-runs).
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*/
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apiToken: string;
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}
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export interface Agent {
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name: AgentId;
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install: (token?: string) => Promise<string>;
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run: (ctx: AgentRunContext) => Promise<AgentResult>;
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}
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@@ -180,96 +58,3 @@ export const agent = (input: Agent): Agent => {
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},
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};
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};
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/** format a USD cost to 4 decimal places, always showing the leading zero */
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export function formatCostUsd(costUsd: number): string {
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return costUsd.toFixed(4);
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}
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/**
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* merge two AgentUsage snapshots into one running total.
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*
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* both agent harnesses invoke their runner multiple times per `run()` when the
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* post-run retry loop kicks in (MAX_POST_RUN_RETRIES). each invocation
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* produces its own AgentUsage; we sum them so downstream callers (usage
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* summary, WorkflowRun persistence) see the whole session — not just the
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* final retry's slice.
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*
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* returns `undefined` when both sides are empty so callers can short-circuit
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* without a special case. zero-valued cache / cost fields are dropped to
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* `undefined` for symmetry with each harness's `buildUsage`.
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*/
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export function mergeAgentUsage(
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a: AgentUsage | undefined,
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b: AgentUsage | undefined
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): AgentUsage | undefined {
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// always return a fresh object — callers treat AgentUsage as immutable, and
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// returning `a` / `b` directly would leak that invariant to future callers
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if (!a && !b) return undefined;
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if (!a) return { ...(b as AgentUsage) };
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if (!b) return { ...a };
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const cacheRead = (a.cacheReadTokens ?? 0) + (b.cacheReadTokens ?? 0);
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const cacheWrite = (a.cacheWriteTokens ?? 0) + (b.cacheWriteTokens ?? 0);
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const cost = (a.costUsd ?? 0) + (b.costUsd ?? 0);
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return {
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agent: a.agent,
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inputTokens: a.inputTokens + b.inputTokens,
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outputTokens: a.outputTokens + b.outputTokens,
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cacheReadTokens: cacheRead > 0 ? cacheRead : undefined,
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cacheWriteTokens: cacheWrite > 0 ? cacheWrite : undefined,
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costUsd: cost > 0 ? cost : undefined,
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};
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}
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/**
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* unified per-run token table used by every agent harness.
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*
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* columns are kept stable across agents and models so downstream log parsers
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* (scripts/token-usage.ts, cost dashboards) only have to understand one format:
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*
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* Input non-cached input tokens sent this run
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* Cache Read input tokens served from prompt cache (Anthropic, etc.)
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* Cache Write input tokens written to prompt cache this run
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* Output assistant output tokens
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* Total sum of the four columns — the real billable quantity
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* Cost ($) USD cost reported by the provider (only rendered when known)
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*
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* models that don't report prompt caching leave Cache Read / Write at 0.
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* OpenCode emits per-step `part.cost` sourced from models.dev (works across
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* Anthropic, OpenAI, Google, xAI, DeepSeek, Moonshot, OpenRouter, etc.);
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* Claude CLI emits `total_cost_usd` on its final `result` event. pass the
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* accumulated value via `costUsd` to render the Cost column.
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*/
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export function logTokenTable(t: {
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input: number;
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cacheRead: number;
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cacheWrite: number;
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output: number;
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costUsd?: number | undefined;
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}): void {
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const total = t.input + t.cacheRead + t.cacheWrite + t.output;
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// narrow costUsd to a concrete number so the render path doesn't need a cast
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const costUsd = typeof t.costUsd === "number" && t.costUsd > 0 ? t.costUsd : undefined;
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const headerRow: Array<{ data: string; header: true }> = [
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{ data: "Input", header: true },
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{ data: "Cache Read", header: true },
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{ data: "Cache Write", header: true },
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{ data: "Output", header: true },
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{ data: "Total", header: true },
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];
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const dataRow: string[] = [
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String(t.input),
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String(t.cacheRead),
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String(t.cacheWrite),
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String(t.output),
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String(total),
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];
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if (costUsd !== undefined) {
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headerRow.push({ data: "Cost ($)", header: true });
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dataRow.push(formatCostUsd(costUsd));
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}
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log.table([headerRow, dataRow]);
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}
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