Darochin's picture
Mirror OpenSkyNet workspace snapshot from Git HEAD
fc93158 verified
import type { AgentMessage } from "@mariozechner/pi-agent-core";
import type { ExtensionContext } from "@mariozechner/pi-coding-agent";
import { describe, expect, it } from "vitest";
import { pruneContextMessages } from "./pruner.js";
import { DEFAULT_CONTEXT_PRUNING_SETTINGS } from "./settings.js";
type AssistantMessage = Extract<AgentMessage, { role: "assistant" }>;
type AssistantContentBlock = AssistantMessage["content"][number];
const CONTEXT_WINDOW_1M = {
model: { contextWindow: 1_000_000 },
} as unknown as ExtensionContext;
function makeUser(text: string): AgentMessage {
return {
role: "user",
content: text,
timestamp: Date.now(),
};
}
function makeAssistant(content: AssistantMessage["content"]): AgentMessage {
return {
role: "assistant",
content,
api: "openai-responses",
provider: "openai",
model: "test-model",
usage: {
input: 1,
output: 1,
cacheRead: 0,
cacheWrite: 0,
totalTokens: 2,
cost: {
input: 0,
output: 0,
cacheRead: 0,
cacheWrite: 0,
total: 0,
},
},
stopReason: "stop",
timestamp: Date.now(),
};
}
function makeToolResult(
content: Array<
{ type: "text"; text: string } | { type: "image"; data: string; mimeType: string }
>,
): AgentMessage {
return {
role: "toolResult",
toolName: "read",
content,
timestamp: Date.now(),
} as AgentMessage;
}
describe("pruneContextMessages", () => {
it("does not crash on assistant message with malformed thinking block (missing thinking string)", () => {
const messages: AgentMessage[] = [
makeUser("hello"),
makeAssistant([
{ type: "thinking" } as unknown as AssistantContentBlock,
{ type: "text", text: "ok" },
]),
];
expect(() =>
pruneContextMessages({
messages,
settings: DEFAULT_CONTEXT_PRUNING_SETTINGS,
ctx: CONTEXT_WINDOW_1M,
}),
).not.toThrow();
});
it("does not crash on assistant message with null content entries", () => {
const messages: AgentMessage[] = [
makeUser("hello"),
makeAssistant([null as unknown as AssistantContentBlock, { type: "text", text: "world" }]),
];
expect(() =>
pruneContextMessages({
messages,
settings: DEFAULT_CONTEXT_PRUNING_SETTINGS,
ctx: CONTEXT_WINDOW_1M,
}),
).not.toThrow();
});
it("does not crash on assistant message with malformed text block (missing text string)", () => {
const messages: AgentMessage[] = [
makeUser("hello"),
makeAssistant([
{ type: "text" } as unknown as AssistantContentBlock,
{ type: "thinking", thinking: "still fine" },
]),
];
expect(() =>
pruneContextMessages({
messages,
settings: DEFAULT_CONTEXT_PRUNING_SETTINGS,
ctx: CONTEXT_WINDOW_1M,
}),
).not.toThrow();
});
it("handles well-formed thinking blocks correctly", () => {
const messages: AgentMessage[] = [
makeUser("hello"),
makeAssistant([
{ type: "thinking", thinking: "let me think" },
{ type: "text", text: "here is the answer" },
]),
];
const result = pruneContextMessages({
messages,
settings: DEFAULT_CONTEXT_PRUNING_SETTINGS,
ctx: CONTEXT_WINDOW_1M,
});
expect(result).toHaveLength(2);
});
it("soft-trims image-containing tool results by replacing image blocks with placeholders", () => {
const messages: AgentMessage[] = [
makeUser("summarize this"),
makeToolResult([
{ type: "text", text: "A".repeat(120) },
{ type: "image", data: "img", mimeType: "image/png" },
{ type: "text", text: "B".repeat(120) },
]),
makeAssistant([{ type: "text", text: "done" }]),
];
const result = pruneContextMessages({
messages,
settings: {
...DEFAULT_CONTEXT_PRUNING_SETTINGS,
keepLastAssistants: 1,
softTrimRatio: 0,
hardClear: {
...DEFAULT_CONTEXT_PRUNING_SETTINGS.hardClear,
enabled: false,
},
softTrim: {
maxChars: 200,
headChars: 170,
tailChars: 30,
},
},
ctx: CONTEXT_WINDOW_1M,
isToolPrunable: () => true,
contextWindowTokensOverride: 16,
});
const toolResult = result[1] as Extract<AgentMessage, { role: "toolResult" }>;
expect(toolResult.content).toHaveLength(1);
expect(toolResult.content[0]).toMatchObject({ type: "text" });
const textBlock = toolResult.content[0] as { type: "text"; text: string };
expect(textBlock.text).toContain("[image removed during context pruning]");
expect(textBlock.text).toContain(
"[Tool result trimmed: kept first 170 chars and last 30 chars",
);
});
it("replaces image-only tool results with placeholders even when text trimming is not needed", () => {
const messages: AgentMessage[] = [
makeUser("summarize this"),
makeToolResult([{ type: "image", data: "img", mimeType: "image/png" }]),
makeAssistant([{ type: "text", text: "done" }]),
];
const result = pruneContextMessages({
messages,
settings: {
...DEFAULT_CONTEXT_PRUNING_SETTINGS,
keepLastAssistants: 1,
softTrimRatio: 0,
hardClearRatio: 10,
hardClear: {
...DEFAULT_CONTEXT_PRUNING_SETTINGS.hardClear,
enabled: false,
},
softTrim: {
maxChars: 5_000,
headChars: 2_000,
tailChars: 2_000,
},
},
ctx: CONTEXT_WINDOW_1M,
isToolPrunable: () => true,
contextWindowTokensOverride: 1,
});
const toolResult = result[1] as Extract<AgentMessage, { role: "toolResult" }>;
expect(toolResult.content).toEqual([
{ type: "text", text: "[image removed during context pruning]" },
]);
});
it("hard-clears image-containing tool results once ratios require clearing", () => {
const messages: AgentMessage[] = [
makeUser("summarize this"),
makeToolResult([
{ type: "text", text: "small text" },
{ type: "image", data: "img", mimeType: "image/png" },
]),
makeAssistant([{ type: "text", text: "done" }]),
];
const placeholder = "[hard cleared test placeholder]";
const result = pruneContextMessages({
messages,
settings: {
...DEFAULT_CONTEXT_PRUNING_SETTINGS,
keepLastAssistants: 1,
softTrimRatio: 0,
hardClearRatio: 0,
minPrunableToolChars: 1,
softTrim: {
maxChars: 5_000,
headChars: 2_000,
tailChars: 2_000,
},
hardClear: {
enabled: true,
placeholder,
},
},
ctx: CONTEXT_WINDOW_1M,
isToolPrunable: () => true,
contextWindowTokensOverride: 8,
});
const toolResult = result[1] as Extract<AgentMessage, { role: "toolResult" }>;
expect(toolResult.content).toEqual([{ type: "text", text: placeholder }]);
});
});