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# Catty prompt cache repair and verification
## Scope and issue history
- Original report: [#3545](https://github.com/binaricat/Netcatty/issues/3545), duplicate [#3546](https://github.com/binaricat/Netcatty/issues/3546).
- [#3547](https://github.com/binaricat/Netcatty/pull/3547) moved static guidelines before scope/session details. That repair remains valid, but its closing comment did not claim a measured DeepSeek result.
- This change starts from main `b5fee9632ea012e5c15fbdae454dec2aa7d32572` and repairs additional cache invalidation and usage-reporting paths.
## Confirmed defects and changes
1. Completed terminal results were rewritten when the next user turn rebuilt history. Keep the already bounded result, with secret redaction, and let context budgeting own necessary reductions.
2. Live SDK results use JSON while saved history uses text. Apply the same bounded compression to both before sending them, avoiding a second, different representation on the next turn.
3. Routine output cleanup inserted the latest goal and pending handles at the start of otherwise intact history. Reserve that reinjection for actual budget pressure or summarization.
4. Large-output handle notices were replaced at the front on every step. Results already containing a handle need no duplicate notice. Announce missing handles once at the tail and preserve prior notices; continue to reserve their budget if older results are pruned.
5. DeepSeek's documented `prompt_cache_hit_tokens` was lost when the OpenAI-compatible SDK parsed responses. Normalize it to the standard cached-token field before parsing, preserving an existing standard value, including zero. Cover streaming and non-streaming responses.
6. Catty omitted cache counts from its usage events and saved assistant messages. Preserve provider counts and attach aggregate usage after the final assistant message has been created.
7. Native Anthropic requests lacked cache breakpoints. Cache the static system block and a bounded conversation tail; leave implicit-cache OpenAI/Google requests untouched and preserve signed reasoning content. Enable these vendor fields only for the official HTTPS Anthropic endpoint (including the SDK's default endpoint), not third-party Messages-compatible gateways. Use the shared resolved SDK address, including OpenRouter/Ollama fallbacks when a stored URL is empty. Review follow-ups add endpoint gating and full-driver gateway/fallback regressions; they do not change the measured DeepSeek path.
## Comparison with mature agents and official guidance
- [Codex prompt-caching tests](https://github.com/openai/codex/blob/8c076942cb70fba8e5c4732c23f1faabc4aed484/codex-rs/core/tests/suite/prompt_caching.rs): exercise stable tools and append-only request prefixes. The new tests compare the actual serialized requests produced by Catty's driver, SDK and bridge adapter across consecutive turns.
- [OpenCode cache policy](https://github.com/anomalyco/opencode/blob/c38d83c0c4f92466ff9c8e12b8a741698e811012/packages/ai/src/cache-policy.ts): use provider-specific explicit cache boundaries where required and leave implicit-cache protocols alone.
- [DeepSeek context caching](https://api-docs.deepseek.com/guides/kv_cache/): exact shared prefixes, asynchronous/best-effort cache persistence and provider-reported hit/miss counts. Live probes wait between turns and use the official endpoint.
- [Anthropic prompt caching](https://platform.claude.com/docs/en/build-with-claude/prompt-caching): explicit boundaries, tool/system/message ordering and a limit of four breakpoints. Catty uses at most three automatic markers.
- [OpenAI prompt caching](https://developers.openai.com/api/docs/guides/prompt-caching): stable shared prefixes. No additional explicit cache-control fields are sent on this path.
## Live verification
The final fixed Catty driver was bundled from the isolated worktree and executed inside the running Electron renderer, using the app's existing IPC and configured `https://api.deepseek.com` service, model `deepseek-v4-flash`. The API key stayed inside the app's credential handling.
Each run contains six consecutive turns for each of three scenarios: plain chat, one command per turn, and a command producing 14,000 synthetic log lines followed by a bounded saved-output read. Model requests and usage are real. Tool execution uses an in-memory fixture; no command is sent to the user's connected SSH hosts. The prompts contain only synthetic session/host information.
The results file records every provider-reported input/cache/output count, per-step counts and errors. The rate is total cached input divided by total input, including all model calls in a turn. It is not an average of rounded percentages.
Two complete runs of the final source produced 36 turns / 72 real model requests, with zero errors:
| Scenario | Turns | Weighted cache hit rate | Per-turn range |
| --- | ---: | ---: | ---: |
| Plain chat | 12 | 98.55% | 98.19%-98.92% |
| Command execution | 12 | 98.59% | 98.12%-99.03% |
| Large command output + saved-output read | 12 | 97.80% | 97.30%-98.32% |
Raw per-turn and per-step counters are in [the JSON evidence file](./catty-prompt-cache-live-2026-10-18.json). These are warm-cache measurements; an earlier probe's first request correctly reported zero cached input before subsequent requests reached about 98%. The earlier probe is excluded from the final-source totals.
The production chat-message component was rendered with the live conversation in Electron. Its usage footer showed input, output, cache and reasoning counts; opening the command entry showed the expected fixture result. No product UI layout was changed.
Limits: live provider evidence covers the configured DeepSeek model. Native Anthropic request formatting and usage preservation are verified with the real SDK and a protocol fixture, not a paid Claude session. Cache hits remain provider-managed; a new prefix, necessary compaction or expired cache can legitimately miss.
## Automated verification
- Full AI/history/UI-related suite after the endpoint review follow-ups: 600 tests passed.
- New regression coverage includes six consecutive plain-chat turns, six command turns, six large-file turns, six large-terminal-output turns, long-output handles, streaming/non-streaming DeepSeek usage, aggregate multi-step usage and native Anthropic boundaries.
- Production build passed.
- Full lint passed with eight existing warnings; final changed-file lint passed without warnings.
- Type checking matches the untouched main baseline: 758 existing errors, zero additional errors after normalizing checkout paths and line numbers.
Full-repository verification also found setup and unrelated timing limits:
- The first run passed 13,968 tests and skipped 36, with one failed file caused by the fresh worktree missing the nested `plugin-cli/node_modules/yauzl` dependency. Linking the existing dependency directory repaired the setup; all 29 CLI tests then passed.
- A repeat full run hit the unchanged `large directory progress coalesces synchronous persistence work` timing assertion (2,638,624 characters persisted against a 588,644-character snapshot). That assertion passed in the prior full run. All 102 tests in its file passed on isolated rerun; the same assertion also passed on untouched main. This is an observed full-run timing fluctuation, not a claimed baseline reproduction or an SFTP repair.
- The Homebrew Node 22 binary is broken locally (missing shared library); verification uses an isolated official npm Node 22 runtime. `TMPDIR=/tmp` selects Netcatty's shorter private per-user temporary directory for Unix-socket tests. The default macOS path exceeded the FIDO test socket limit; no product source was changed to accommodate this environment.
The full suite is therefore not reported as unconditionally green. No Catty/cache test failed in the final implementation.
@@ -0,0 +1,955 @@
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},
{
"kind": "large-output",
"round": 1,
"promptTokens": 14550,
"cachedTokens": 14336,
"completionTokens": 4
},
{
"kind": "large-output",
"round": 2,
"promptTokens": 14637,
"cachedTokens": 14464,
"completionTokens": 63
},
{
"kind": "large-output",
"round": 2,
"promptTokens": 15293,
"cachedTokens": 14592,
"completionTokens": 97
},
{
"kind": "large-output",
"round": 2,
"promptTokens": 15517,
"cachedTokens": 15360,
"completionTokens": 4
},
{
"kind": "large-output",
"round": 3,
"promptTokens": 15604,
"cachedTokens": 15360,
"completionTokens": 63
},
{
"kind": "large-output",
"round": 3,
"promptTokens": 16262,
"cachedTokens": 15616,
"completionTokens": 99
},
{
"kind": "large-output",
"round": 3,
"promptTokens": 16490,
"cachedTokens": 16256,
"completionTokens": 4
},
{
"kind": "large-output",
"round": 4,
"promptTokens": 16577,
"cachedTokens": 16384,
"completionTokens": 63
},
{
"kind": "large-output",
"round": 4,
"promptTokens": 17236,
"cachedTokens": 16512,
"completionTokens": 100
},
{
"kind": "large-output",
"round": 4,
"promptTokens": 17466,
"cachedTokens": 17280,
"completionTokens": 4
},
{
"kind": "large-output",
"round": 5,
"promptTokens": 17553,
"cachedTokens": 17408,
"completionTokens": 63
},
{
"kind": "large-output",
"round": 5,
"promptTokens": 18209,
"cachedTokens": 17536,
"completionTokens": 97
},
{
"kind": "large-output",
"round": 5,
"promptTokens": 18433,
"cachedTokens": 18176,
"completionTokens": 4
},
{
"kind": "large-output",
"round": 6,
"promptTokens": 18520,
"cachedTokens": 18304,
"completionTokens": 63
},
{
"kind": "large-output",
"round": 6,
"promptTokens": 19174,
"cachedTokens": 18432,
"completionTokens": 95
},
{
"kind": "large-output",
"round": 6,
"promptTokens": 19394,
"cachedTokens": 19200,
"completionTokens": 4
}
],
"errors": []
}
]
}
@@ -30,7 +30,7 @@ export interface CattyStreamChunk {
stepNumber?: number;
}
const STEP_HANDLE_NOTICE_RE = /^\[step \d+\] Tool output handles available:/;
const STEP_HANDLE_NOTICE_RE = /^(?:\[step \d+\] Tool output handles available:|\[Tool output handles available:)/;
function isStepHandleNoticeMessage(content: unknown): boolean {
return typeof content === 'string' && STEP_HANDLE_NOTICE_RE.test(content);
@@ -0,0 +1,251 @@
import assert from 'node:assert/strict';
import test from 'node:test';
import { CattyTurnDriver } from './turnDrivers/cattyTurnDriver';
import { ToolOutputStore } from './toolOutputStore';
import { ToolResultDedup } from './toolResultDedup';
import { SessionStateStore } from './sessionState';
import type { CattyTurnInput, TurnDriverContext } from './turnDrivers/types';
import type { AgentEvent } from './types';
import type { AISession, ChatMessage, ProviderConfig } from '../types';
interface WireMessage {
role: string;
content: unknown;
}
interface WireRequest {
messages: WireMessage[];
tools?: unknown[];
system?: Array<{ type: string; text: string; cache_control?: unknown }>;
}
type Reply = { tool: 'terminal_execute' | 'sftp_read_file' } | { text: string };
function fixture(t: test.TestContext, replies: Reply[], style: 'openai' | 'anthropic' = 'openai', terminalOutput = 'small output') {
const originalWindow = globalThis.window;
const originalRaf = globalThis.requestAnimationFrame;
const originalCancelRaf = globalThis.cancelAnimationFrame;
t.after(() => {
globalThis.window = originalWindow;
globalThis.requestAnimationFrame = originalRaf;
globalThis.cancelAnimationFrame = originalCancelRaf;
});
globalThis.requestAnimationFrame = callback => setTimeout(() => callback(0), 0) as unknown as number;
globalThis.cancelAnimationFrame = id => clearTimeout(id);
const requests: WireRequest[] = [];
const urls: string[] = [];
const events: AgentEvent[] = [];
const messages: ChatMessage[] = [];
const data = new Map<string, (value: string) => void>();
const end = new Map<string, () => void>();
const bridge = {
aiSetChatSessionCancelled: async () => ({ ok: true }),
aiMcpUpdateSessions: async () => undefined,
aiExec: async () => ({ ok: true, stdout: terminalOutput, stderr: '', exitCode: 0 }),
aiCapability: async (_method: string, params: Record<string, unknown>) => ({
ok: true,
path: params.path,
content: Array.from({ length: 2000 }, (_, i) => `log ${i}: synthetic ${String(params.path)}`).join('\n'),
}),
onAiStreamData: (id: string, callback: (value: string) => void) => {
data.set(id, callback);
return () => { data.delete(id); };
},
onAiStreamEnd: (id: string, callback: () => void) => {
end.set(id, callback);
return () => { end.delete(id); };
},
onAiStreamError: () => () => undefined,
aiChatCancel: async () => true,
aiChatStream: async (id: string, url: string, _headers: Record<string, string>, body: string) => {
urls.push(url);
requests.push(JSON.parse(body) as WireRequest);
const reply = replies[requests.length - 1];
assert.ok(reply, 'unexpected model request');
const send = (chunk: unknown) => data.get(id)?.(JSON.stringify(chunk));
if (style === 'anthropic') {
send({ type: 'message_start', message: {
id: `response-${requests.length}`, type: 'message', role: 'assistant', model: 'claude-sonnet-4-5',
content: [], stop_reason: null, stop_sequence: null,
usage: { input_tokens: 100, output_tokens: 0, cache_read_input_tokens: 900, cache_creation_input_tokens: 0 },
} });
send({ type: 'content_block_start', index: 0, content_block: { type: 'text', text: '' } });
send({ type: 'content_block_delta', index: 0, delta: { type: 'text_delta', text: 'OK' } });
send({ type: 'content_block_stop', index: 0 });
send({ type: 'message_delta', delta: { stop_reason: 'end_turn', stop_sequence: null }, usage: { output_tokens: 1 } });
send({ type: 'message_stop' });
} else {
const toolReply = 'tool' in reply;
const delta = toolReply ? {
role: 'assistant',
tool_calls: [{ index: 0, id: `call-${requests.length}`, type: 'function', function: {
name: reply.tool,
arguments: JSON.stringify(reply.tool === 'terminal_execute'
? { sessionId: 'terminal-1', command: `printf audit-${requests.length}` }
: { sessionId: 'terminal-1', path: `/fixture/log-${requests.length}` }),
} }],
} : { role: 'assistant', content: reply.text };
send({ id: 'response', object: 'chat.completion.chunk', created: 0, model: 'test-model',
choices: [{ index: 0, delta, finish_reason: null }] });
send({ id: 'response', object: 'chat.completion.chunk', created: 0, model: 'test-model',
choices: [{ index: 0, delta: {}, finish_reason: toolReply ? 'tool_calls' : 'stop' }] });
send({ id: 'response', object: 'chat.completion.chunk', created: 0, model: 'test-model', choices: [],
usage: { prompt_tokens: 1000, completion_tokens: 1, total_tokens: 1001,
prompt_cache_hit_tokens: 900, prompt_cache_miss_tokens: 100 } });
data.get(id)?.('[DONE]');
}
end.get(id)?.();
return { ok: true, statusCode: 200 };
},
};
globalThis.window = { netcatty: bridge } as unknown as Window & typeof globalThis;
const store = new ToolOutputStore();
const dedup = new ToolResultDedup();
const state = new SessionStateStore();
const provider: ProviderConfig = {
id: 'fixture', providerId: 'custom', name: 'Fixture', enabled: true, style,
defaultModel: style === 'anthropic' ? 'claude-sonnet-4-5' : 'test-model',
baseURL: style === 'anthropic' ? 'https://api.anthropic.com' : 'https://provider.example.test/v1', apiKey: 'not-a-real-key',
};
let turnNumber = 0;
return {
requests, urls, events, messages, provider,
async turn(maxIterations = 1) {
turnNumber += 1;
const history = structuredClone(messages);
const userText = `Audit round ${turnNumber}`;
const assistantId = `assistant-${turnNumber}`;
messages.push({ id: `user-${turnNumber}`, role: 'user', content: userText, timestamp: turnNumber },
{ id: assistantId, role: 'assistant', content: '', timestamp: turnNumber });
const currentSession: AISession = {
id: 'chat-1', title: 'Fixture', agentId: 'catty', scope: { type: 'terminal', targetId: 'terminal-1' },
createdAt: 0, updatedAt: turnNumber, messages: history,
};
const signal = new AbortController().signal;
const input: CattyTurnInput = {
backend: 'catty', chatSessionId: 'chat-1', sendScopeKey: 'chat-1', userText, signal,
currentSession, assistantMsgId: assistantId, maxIterations, bridge,
context: {
activeProvider: provider, activeModelId: provider.defaultModel!, scopeType: 'terminal', scopeLabel: 'Fixture',
globalPermissionMode: 'auto', commandBlocklist: [], autoTitleSession: () => undefined,
terminalSessions: [{ sessionId: 'terminal-1', hostname: 'fixture.example.test', label: 'Fixture', connected: true }],
},
ui: {
addMessageToSession: (_session, message) => { messages.push(message); },
updateMessageById: (_session, id, update) => {
const index = messages.findIndex(message => message.id === id);
if (index >= 0) messages[index] = update(messages[index]);
},
updateLastMessage: () => undefined,
reportStreamError: (_session, _signal, error) => { throw error; },
setStreamingForScope: () => undefined,
},
};
const context: TurnDriverContext = {
turnId: `turn-${turnNumber}`, chatSessionId: 'chat-1', sessionId: 'chat-1', backend: 'catty', signal,
emit: event => { events.push({
...event, sessionId: 'chat-1', chatSessionId: 'chat-1', backend: 'catty', timestamp: Date.now(),
} as AgentEvent); }, toolOutputStore: store, toolResultDedup: dedup, sessionStateStore: state,
};
dedup.beginTurn();
await new CattyTurnDriver().run(input, context);
},
};
}
function assertRequestPrefix(previous: WireRequest, next: WireRequest) {
assert.deepEqual(next.messages.slice(0, previous.messages.length), previous.messages,
'already-sent conversation must remain an exact prefix');
assert.deepEqual(next.tools, previous.tools);
}
test('Catty preserves the request prefix across six ordinary turns', async t => {
const f = fixture(t, Array.from({ length: 6 }, () => ({ text: 'OK' })));
for (let i = 0; i < 6; i += 1) await f.turn();
assert.equal(f.requests.length, 6);
for (let i = 1; i < f.requests.length; i += 1) assertRequestPrefix(f.requests[i - 1], f.requests[i]);
});
test('Catty replays completed small commands without rewriting their results', async t => {
const f = fixture(t, Array.from({ length: 6 }, () => [
{ tool: 'terminal_execute' as const }, { text: 'OK' },
]).flat());
for (let i = 0; i < 6; i += 1) await f.turn(2);
assert.equal(f.requests.length, 12);
for (let i = 1; i < f.requests.length; i += 1) assertRequestPrefix(f.requests[i - 1], f.requests[i]);
assert.equal(f.messages.at(-1)?.usage?.cachedInputTokens, 1800, 'usage includes both model steps');
assert.doesNotMatch(JSON.stringify(f.requests), /cache_control/, 'OpenAI-compatible requests use implicit caching');
});
test('Catty keeps large-output handles without replacing the conversation prefix', async t => {
const f = fixture(t, [{ tool: 'sftp_read_file' }, { tool: 'sftp_read_file' }, { text: 'OK' }]);
await f.turn(3);
assert.equal(f.requests.length, 3);
for (let i = 1; i < f.requests.length; i += 1) assertRequestPrefix(f.requests[i - 1], f.requests[i]);
assert.match(JSON.stringify(f.requests.at(-1)), /tool output handle:/);
assert.doesNotMatch(JSON.stringify(f.requests.at(-1)), /Tool output handles available/);
});
test('Catty preserves large-output history across consecutive user turns', async t => {
const f = fixture(t, Array.from({ length: 6 }, () => [
{ tool: 'sftp_read_file' as const }, { text: 'OK' },
]).flat());
for (let i = 0; i < 6; i += 1) await f.turn(2);
assert.equal(f.requests.length, 12);
for (let i = 1; i < f.requests.length; i += 1) assertRequestPrefix(f.requests[i - 1], f.requests[i]);
});
test('Catty preserves large terminal results across consecutive user turns', async t => {
const f = fixture(t, Array.from({ length: 6 }, () => [
{ tool: 'terminal_execute' as const }, { text: 'OK' },
]).flat(), 'openai', Array.from({ length: 14000 }, (_, i) => `synthetic log record ${i}`).join('\n'));
for (let i = 0; i < 6; i += 1) await f.turn(2);
assert.equal(f.requests.length, 12);
for (let i = 1; i < f.requests.length; i += 1) assertRequestPrefix(f.requests[i - 1], f.requests[i]);
});
test('Catty keeps DeepSeek cache reads in trace and persisted assistant usage', async t => {
const f = fixture(t, [{ text: 'OK' }]);
await f.turn();
const event = f.events.find(event => event.type === 'usage');
assert.ok(event?.type === 'usage');
assert.equal(event.cachedPromptTokens, 900);
assert.equal(f.messages.at(-1)?.usage?.cachedInputTokens, 900);
});
test('Catty marks a stable Claude system block and the conversation tail for caching', async t => {
const f = fixture(t, [{ text: 'OK' }], 'anthropic');
await f.turn();
const system = f.requests[0].system!;
assert.ok(system.length >= 2, 'static and dynamic system context need separate boundaries');
assert.deepEqual(system[0].cache_control, { type: 'ephemeral' });
assert.doesNotMatch(system[0].text, /## Current Scope/);
assert.match(system[1].text, /## Current Scope/);
assert.match(JSON.stringify(f.requests[0].messages.at(-1)), /cache_control/);
const event = f.events.find(event => event.type === 'usage');
assert.ok(event?.type === 'usage');
assert.equal(event.cachedPromptTokens, 900);
assert.equal(f.messages.at(-1)?.usage?.cachedInputTokens, 900);
});
test('Catty does not send vendor cache extensions to an Anthropic-compatible gateway', async t => {
const f = fixture(t, [{ text: 'OK' }], 'anthropic');
f.provider.baseURL = 'https://gateway.example.test/anthropic';
await f.turn();
assert.equal(f.requests.length, 1);
assert.doesNotMatch(JSON.stringify(f.requests), /cache_control/);
assert.equal(f.messages.at(-1)?.content, 'OK');
});
for (const providerId of ['openrouter', 'ollama'] as const) {
test(`Catty respects the ${providerId} endpoint fallback with Anthropic format`, async t => {
const f = fixture(t, [{ text: 'OK' }], 'anthropic');
f.provider.providerId = providerId;
f.provider.baseURL = '';
await f.turn();
assert.match(f.urls[0], providerId === 'openrouter' ? /^https:\/\/openrouter\.ai\// : /^http:\/\/localhost:11434\//);
assert.doesNotMatch(JSON.stringify(f.requests), /cache_control/);
assert.equal(f.messages.at(-1)?.content, 'OK');
});
}
@@ -0,0 +1,56 @@
import type { ModelMessage, SystemModelMessage } from 'ai';
import type { ProviderConfig } from '../types';
const CACHE_CONTROL = { type: 'ephemeral' } as const;
/** Native Anthropic needs explicit breakpoints; implicit-cache protocols stay untouched. */
export function createCattyPromptCache(
systemPrompt: string,
provider: string,
endpoint?: Pick<ProviderConfig, 'baseURL'>,
) {
let officialEndpoint = false;
if (endpoint) {
try {
// This must be the resolved SDK address, including vendor fallbacks.
// Only an unresolved URL after that step uses the SDK's native default.
officialEndpoint = new URL(endpoint.baseURL || 'https://api.anthropic.com').origin === 'https://api.anthropic.com';
} catch { /* An unknown endpoint must not receive vendor extensions. */ }
}
const enabled = /^anthropic(?:\.|$)/.test(provider) && officialEndpoint;
const boundary = systemPrompt.indexOf('\n\n## Current Scope');
const instructions: string | SystemModelMessage[] = enabled
? [{
role: 'system',
content: boundary < 0 ? systemPrompt : systemPrompt.slice(0, boundary),
providerOptions: { anthropic: { cacheControl: CACHE_CONTROL } },
}, ...(boundary < 0 ? [] : [{
role: 'system' as const,
content: systemPrompt.slice(boundary),
}])]
: systemPrompt;
return {
enabled,
instructions,
prepareMessages(messages: ModelMessage[]): ModelMessage[] {
if (!enabled) return messages;
// Keep at most two moving conversation breakpoints, plus the static
// system boundary. Remove our prior message-level markers as v7 carries
// prepared messages forward; never alter signed reasoning content.
const targets = new Set<number>();
for (let index = messages.length - 1; index >= 0 && targets.size < 2; index -= 1) {
if (messages[index].role === 'user' || messages[index].role === 'tool') targets.add(index);
}
return messages.map((message, index) => {
const existing = message.providerOptions?.anthropic;
if (!targets.has(index) && !existing?.cacheControl && !existing?.cache_control) return message;
const anthropic = { ...existing };
delete anthropic.cacheControl;
delete anthropic.cache_control;
if (targets.has(index)) anthropic.cacheControl = CACHE_CONTROL;
return { ...message, providerOptions: { ...message.providerOptions, anthropic } };
});
},
};
}
@@ -0,0 +1,42 @@
import assert from 'node:assert/strict';
import test from 'node:test';
import type { ModelMessage } from 'ai';
import { createCattyPromptCache } from './cattyPromptCache';
test('leaves implicit-cache protocols unchanged', () => {
for (const provider of ['openai.chat', 'openai.responses', 'google.generative-ai']) {
const cache = createCattyPromptCache('instructions', provider);
const messages: ModelMessage[] = [{ role: 'user', content: 'hello' }];
assert.equal(cache.instructions, 'instructions');
assert.equal(cache.prepareMessages(messages), messages);
}
});
test('Claude markers stay bounded across tool steps without changing signed reasoning', () => {
const cache = createCattyPromptCache('static\n\n## Current Scope\nvolatile', 'anthropic.messages', { baseURL: 'https://api.anthropic.com' });
const reasoning = { type: 'reasoning' as const, text: 'thinking',
providerOptions: { anthropic: { signature: 'signed-value' } } };
let messages: ModelMessage[] = [{ role: 'user', content: 'hello' }];
for (let step = 0; step < 30; step += 1) {
messages = cache.prepareMessages(messages);
const marked = messages.filter(message => message.providerOptions?.anthropic?.cacheControl);
assert.ok(marked.length <= 2);
messages.push({ role: 'assistant', content: [reasoning, { type: 'text', text: 'result' }] });
messages.push({ role: 'user', content: `next-${step}` });
}
for (const message of messages) {
if (message.role === 'assistant') assert.equal(message.content[0], reasoning);
}
assert.ok(Array.isArray(cache.instructions));
assert.deepEqual(cache.instructions[0].providerOptions?.anthropic?.cacheControl, { type: 'ephemeral' });
});
test('only the official HTTPS Anthropic endpoint enables vendor cache markers', () => {
for (const baseURL of ['https://proxy.example.test/v1', 'http://api.anthropic.com', 'https://api.anthropic.com.example.test', 'invalid']) {
const cache = createCattyPromptCache('instructions', 'anthropic.messages', { baseURL });
assert.equal(cache.enabled, false);
}
assert.equal(createCattyPromptCache('instructions', 'anthropic.messages').enabled, false);
assert.equal(createCattyPromptCache('instructions', 'anthropic.messages', {}).enabled, true);
assert.equal(createCattyPromptCache('instructions', 'anthropic.messages', { baseURL: 'https://api.anthropic.com/v1' }).enabled, true);
});
@@ -78,7 +78,7 @@ test('prepareTurnContext applies typed compression before LLM summarize threshol
assert.ok(prepared.messages.length >= messages.length);
const serialized = JSON.stringify(prepared.messages);
assert.match(serialized, /Fix only the upstream timeout issue/);
assert.match(serialized, /Permission mode: confirm/);
assert.doesNotMatch(serialized, /Netcatty session context/);
assert.ok(serialized.length < JSON.stringify(messages).length);
});
@@ -163,7 +163,7 @@ test('TraceStore bounds compaction history independently from events', () => {
assert.equal(store.getCompactions('chat-bounded-compactions').length, 3);
});
test('prepareStepContext replaces prior step handle notices under v7 carry-forward semantics', async () => {
test('prepareStepContext preserves prior notices and appends only newly available handles', async () => {
const store = new ToolOutputStore();
store.store({
chatSessionId: 'chat-4',
@@ -194,9 +194,22 @@ test('prepareStepContext replaces prior step handle notices under v7 carry-forwa
&& typeof message.content === 'string'
&& message.content.includes('Tool output handles available'),
);
assert.equal(notices.length, 1);
assert.match(String(notices[0]?.content), /\[step 2\]/);
assert.doesNotMatch(String(notices[0]?.content), /tool-output-old/);
assert.equal(notices.length, 2);
assert.deepEqual(prepared.messages.slice(0, 2), [priorNotice, { role: 'user', content: 'continue' }]);
assert.equal(notices[0], priorNotice);
assert.match(String(notices[1]?.content), /^\[Tool output handles available:/);
assert.doesNotMatch(String(notices[1]?.content), /tool-output-old|\[step/);
assert.equal(prepared.messages.at(-1), notices[1]);
const next = await prepareStepContext({
messages: prepared.messages,
stepNumber: 3,
sessionId: 'chat-4',
chatSessionId: 'chat-4',
toolOutputStore: store,
runtimeContext,
});
assert.deepEqual(next.messages, prepared.messages, 'unchanged handles need no per-step rewrite');
});
test('prepareStepContext emits step compaction trace when over budget', async () => {
@@ -266,7 +279,8 @@ test('prepareStepContext retains handle notice after step budget guard', async (
&& message.content.includes('Tool output handles available'),
);
assert.equal(notices.length, 1);
assert.match(String(notices[0]?.content), /\[step 2\]/);
assert.match(String(notices[0]?.content), /^\[Tool output handles available:/);
assert.equal(prepared.messages.at(-1), notices[0]);
});
test('prepareStepContext never leaves orphan results from a parallel tool batch', async () => {
+30 -39
View File
@@ -1,6 +1,5 @@
import type { ModelMessage } from 'ai';
import type { ChatMessage, AIPermissionMode } from '../types';
import { isStepHandleNoticeMessage } from './agentEventAdapter';
import {
DEFAULT_CONTEXT_WINDOW_TOKENS,
DEFAULT_PROTECT_RECENT_MESSAGES,
@@ -265,7 +264,9 @@ export async function prepareTurnContext(
}
const reinjection = buildReinjectionMessages(input.reinjection);
if (reinjection.length > 0 && didAdjust) {
// Routine output cleanup does not discard the conversation or its goals.
// Reinserting the latest goal at the front would invalidate every turn.
if (reinjection.length > 0 && didAdjust && (underBudgetPressure || didLlmSummarize)) {
const reinjectionTokens = estimateModelMessagesTokensWithKind({
messages: reinjection,
providerId: input.providerId,
@@ -414,22 +415,6 @@ export async function prepareStepContext(
const typed = compressMessagesForRequestTooLargeRetry(working);
working = typed.messages;
const pendingHandles = input.toolOutputStore?.listPendingHandles(input.chatSessionId ?? input.sessionId) ?? [];
let didHandleNotice = false;
if (pendingHandles.length > 0 && input.stepNumber > 0) {
working = working.filter((message) => {
if (message.role !== 'user') return true;
const content = typeof message.content === 'string' ? message.content : '';
return !isStepHandleNoticeMessage(content);
});
const notice: ModelMessage = {
role: 'user',
content: `[step ${input.stepNumber}] Tool output handles available: ${pendingHandles.map(h => h.id).join(', ')}`,
};
working = [notice, ...working];
didHandleNotice = true;
}
const budgetGuard = applyStepBudgetGuard(working, {
contextWindow,
reservedTokens: input.reservedTokens ?? 0,
@@ -438,36 +423,42 @@ export async function prepareStepContext(
protectRecentMessages: protectRecent,
});
working = budgetGuard.messages;
if (didHandleNotice && pendingHandles.length > 0) {
const hasHandleNotice = working.some(
(message) => message.role === 'user' && isStepHandleNoticeMessage(message.content),
);
if (!hasHandleNotice) {
working = [{
role: 'user',
content: `[step ${input.stepNumber}] Tool output handles available: ${pendingHandles.map(h => h.id).join(', ')}`,
}, ...working];
}
}
if (didHandleNotice) {
const notices = working.filter(
message => message.role === 'user' && isStepHandleNoticeMessage(message.content),
);
const body = working.filter(
message => !(message.role === 'user' && isStepHandleNoticeMessage(message.content)),
);
const pendingHandles = input.stepNumber > 0
? input.toolOutputStore?.listPendingHandles(input.chatSessionId ?? input.sessionId) ?? []
: [];
const unannouncedHandles = () => {
// Bounded tool results already carry their read handles. Announce only
// handles whose result was pruned, so normal history needs no transient
// user message that would disappear when the next turn is rebuilt.
const visibleContent = working.map(message => typeof message.content === 'string'
? message.content : JSON.stringify(message.content));
return pendingHandles.filter(handle => !visibleContent.some(content => content.includes(handle.id)));
};
let didHandleNotice = false;
if (unannouncedHandles().length > 0) {
// Reserve the complete list: the guard may remove an older announcement.
// New notices belong at the tail; replacing a step-numbered prefix would
// invalidate the entire cached conversation on every model call.
const noticeTokens = estimateModelMessagesTokensWithKind({
messages: notices,
messages: [{ role: 'user', content: `[Tool output handles available: ${pendingHandles.map(h => h.id).join(', ')}]` }],
providerId: input.providerId,
}).tokens;
const finalGuard = applyStepBudgetGuard(body, {
const finalGuard = applyStepBudgetGuard(working, {
contextWindow,
reservedTokens: (input.reservedTokens ?? 0) + noticeTokens,
maxOutputTokens,
providerId: input.providerId,
protectRecentMessages: protectRecent,
});
working = [...notices, ...finalGuard.messages];
working = finalGuard.messages;
const handles = unannouncedHandles();
if (handles.length > 0) {
working = [...working, {
role: 'user',
content: `[Tool output handles available: ${handles.map(h => h.id).join(', ')}]`,
}];
didHandleNotice = true;
}
budgetGuard.didAdjust = budgetGuard.didAdjust || finalGuard.didAdjust;
}
const didBudgetAdjust = integrity.didAdjust || stale.didAdjust || typed.didAdjust || budgetGuard.didAdjust;
@@ -27,7 +27,7 @@ import {
type AssistantContentPart,
type CattyProviderContinuationContext,
} from '../../aiChatStreamingSupport';
import { redactSecretsInValueForModel } from '../modelSecretRedaction';
import { redactSecretsForModel, redactSecretsInValueForModel } from '../modelSecretRedaction';
import { fitLargeUserInputForModel } from '../largeUserInput';
import type { ToolOutputStore } from '../toolOutputStore';
@@ -198,7 +198,6 @@ export interface BuildCattySdkMessagesInput {
trimmed: string;
attachments?: ChatMessageAttachment[];
continuationContext: CattyProviderContinuationContext;
preserveTerminalToolResults?: ReadonlySet<ToolResult>;
chatSessionId: string;
toolOutputStore: ToolOutputStore;
fieldsByMessage: Map<ModelMessage, OpenAIChatAssistantFields | undefined>;
@@ -212,7 +211,6 @@ export function buildCattySdkMessages(input: BuildCattySdkMessagesInput): ModelM
trimmed,
attachments,
continuationContext,
preserveTerminalToolResults = new Set<ToolResult>(),
chatSessionId,
toolOutputStore,
fieldsByMessage,
@@ -394,9 +392,12 @@ export function buildCattySdkMessages(input: BuildCattySdkMessagesInput): ModelM
toolName: toolCall?.name ?? 'unknown',
output: {
type: 'text' as const,
value: buildHistoricalToolResultReplayText(tr, toolCall, {
preserveTerminalOutput: preserveTerminalToolResults.has(tr),
}),
// Live results are already bounded. Reformatting them merely
// because another user turn arrived breaks the cached prefix.
// Context-budget pruning still owns necessary reductions.
value: redactSecretsForModel(buildHistoricalToolResultReplayText(tr, toolCall, {
preserveTerminalOutput: true,
})),
},
};
}),
@@ -8,13 +8,14 @@ import {
} from '../../cattyRequestTooLargeRetry';
import { mapCattyStreamChunkToAgentEvents } from '../agentEventAdapter';
import type { AgentEvent } from '../types';
import type { ProviderAdvancedParams } from '../../types';
import { resolveProviderStyle, type ProviderAdvancedParams } from '../../types';
import type { CattyReasoningProviderOptions } from '../../cattyReasoning';
import { createModelFromConfig } from '../../sdk/providers';
import { createModelFromConfig, resolveProviderEndpoint } from '../../sdk/providers';
import type { CattyToolsBundle } from '../capabilityTools';
import { buildCattyToolApproval } from '../cattyToolApproval';
import type { CattyRuntimeContext } from '../cattyRuntimeContext';
import { buildCattyStreamTimeouts } from '../streamTimeouts';
import { createCattyPromptCache } from '../cattyPromptCache';
import {
extractProviderContinuationFromRawChunk,
mergeProviderContinuation,
@@ -39,7 +40,7 @@ import {
type ToolOutputDeniedChunk,
type ToolResultChunk,
} from '../../aiChatStreamingSupport';
import type { ChatMessage } from '../../types';
import type { ChatMessage, ProviderConfig } from '../../types';
export type CattyModel = ReturnType<typeof createModelFromConfig>;
@@ -51,6 +52,7 @@ export interface CattyStreamUiSink {
export interface ProcessCattyStreamInput {
streamSessionId: string;
model: CattyModel;
providerConfig?: ProviderConfig;
systemPrompt: string;
toolsBundle: CattyToolsBundle;
sdkMessages: ModelMessage[];
@@ -76,6 +78,7 @@ export interface ProcessCattyStreamInput {
export interface ProcessCattyStreamResult {
usage?: {
promptTokens?: number;
cachedPromptTokens?: number;
completionTokens?: number;
totalTokens?: number;
};
@@ -129,11 +132,15 @@ export async function processCattyStream(input: ProcessCattyStreamInput): Promis
let runtimeContext = initialRuntimeContext;
const { tools, toolsContext } = toolsBundle;
const endpoint = input.providerConfig
? resolveProviderEndpoint(input.providerConfig, resolveProviderStyle(input.providerConfig), undefined)
: undefined;
const promptCache = createCattyPromptCache(systemPrompt, model.provider, endpoint);
const result = streamText({
model,
messages: sdkMessages,
instructions: systemPrompt,
messages: promptCache.prepareMessages(sdkMessages),
instructions: promptCache.instructions,
tools,
toolsContext,
runtimeContext,
@@ -186,6 +193,7 @@ export async function processCattyStream(input: ProcessCattyStreamInput): Promis
modelId: step.model.modelId,
finishReason: step.finishReason,
promptTokens: usage.inputTokens ?? 0,
cachedPromptTokens: usage.inputTokenDetails?.cacheReadTokens,
completionTokens: usage.outputTokens ?? 0,
totalTokens: (usage.inputTokens ?? 0) + (usage.outputTokens ?? 0),
} as AgentEvent);
@@ -201,15 +209,17 @@ export async function processCattyStream(input: ProcessCattyStreamInput): Promis
timestamp: Date.now(),
turnId,
promptTokens: usage.inputTokens ?? 0,
cachedPromptTokens: usage.inputTokenDetails?.cacheReadTokens,
completionTokens: usage.outputTokens ?? 0,
reasoningTokens: usage.outputTokenDetails?.reasoningTokens,
totalTokens: (usage.inputTokens ?? 0) + (usage.outputTokens ?? 0),
estimated: false,
} as AgentEvent);
}
},
...(prepareStep ? {
...(prepareStep || promptCache.enabled ? {
prepareStep: async ({ stepNumber, messages, runtimeContext: stepRuntimeContext }) => {
const prepared = await prepareStep({
const prepared = await prepareStep?.({
stepNumber,
messages,
runtimeContext: stepRuntimeContext as CattyRuntimeContext,
@@ -217,7 +227,7 @@ export async function processCattyStream(input: ProcessCattyStreamInput): Promis
if (prepared?.runtimeContext) {
runtimeContext = prepared.runtimeContext;
}
return prepared ?? { messages };
return { ...prepared, messages: promptCache.prepareMessages(prepared?.messages ?? messages) };
},
} : {}),
...(advancedParams?.maxTokens != null && { maxOutputTokens: advancedParams.maxTokens }),
@@ -552,6 +562,21 @@ export async function processCattyStream(input: ProcessCattyStreamInput): Promis
const usage = await result.usage;
const finalStep = await result.finalStep;
const performance = finalStep?.performance;
// onEnd can run before this consumer flushes its final text and creates the
// post-tool assistant message. Attach turn totals only after that flush.
if (usage) {
ui.updateMessageById(streamSessionId, activeMsgId, message => ({
...message,
usage: {
inputTokens: usage.inputTokens ?? 0,
cachedInputTokens: usage.inputTokenDetails?.cacheReadTokens,
outputTokens: usage.outputTokens ?? 0,
reasoningTokens: usage.outputTokenDetails?.reasoningTokens,
totalTokens: (usage.inputTokens ?? 0) + (usage.outputTokens ?? 0),
estimated: false,
},
}));
}
if (performance) {
onAgentEvent?.({
@@ -571,6 +596,7 @@ export async function processCattyStream(input: ProcessCattyStreamInput): Promis
return {
usage: usage ? {
promptTokens: usage.inputTokens,
cachedPromptTokens: usage.inputTokenDetails?.cacheReadTokens,
completionTokens: usage.outputTokens,
totalTokens: (usage.inputTokens ?? 0) + (usage.outputTokens ?? 0),
} : undefined,
@@ -37,7 +37,6 @@ import {
buildCattySdkMessages,
collectOpenAIChatAssistantFieldsForMessages,
collectPreservedTerminalWriteFingerprints,
collectToolResultsAfterMessage,
createContinuationContext,
} from './cattyMessageBuilder';
import { hadToolProgressBeforeRequestTooLarge, processCattyStream } from './cattyStreamProcessor';
@@ -218,7 +217,6 @@ async function runCattyTurn(input: CattyTurnInput, ctx: TurnDriverContext): Prom
const buildSdkMessages = (
allMessages: import('../../types').ChatMessage[],
includeCurrentUserMessage: boolean,
options: { preserveTerminalToolResults?: ReadonlySet<import('../../types').ToolResult> } = {},
sessionContextCompaction = currentSession?.contextCompaction,
) => buildCattySdkMessages({
allMessages,
@@ -227,7 +225,6 @@ async function runCattyTurn(input: CattyTurnInput, ctx: TurnDriverContext): Prom
trimmed: modelUserText,
attachments: includeCurrentUserMessage ? attachments : undefined,
continuationContext,
preserveTerminalToolResults: options.preserveTerminalToolResults,
chatSessionId: sessionId,
toolOutputStore: ctx.toolOutputStore,
fieldsByMessage: openAIChatAssistantFieldsByMessage,
@@ -399,7 +396,6 @@ async function runCattyTurn(input: CattyTurnInput, ctx: TurnDriverContext): Prom
const headSdkMessages = buildSdkMessages(
uiMessages.slice(0, compactedMessageCount),
false,
{},
undefined,
);
const compacted = await compactMessages(headSdkMessages, {
@@ -414,7 +410,7 @@ async function runCattyTurn(input: CattyTurnInput, ctx: TurnDriverContext): Prom
};
ui.persistContextCompaction?.(sessionId, nextCompaction);
emitContextSnapshot(prepareMessagesForStream(
buildSdkMessages(uiMessages, false, {}, nextCompaction),
buildSdkMessages(uiMessages, false, nextCompaction),
));
} else {
// Non-durable outcome: keep the meter honest (full current context).
@@ -452,6 +448,7 @@ async function runCattyTurn(input: CattyTurnInput, ctx: TurnDriverContext): Prom
await processCattyStream({
streamSessionId: sessionId,
model,
providerConfig: context.activeProvider,
systemPrompt,
toolsBundle,
sdkMessages: streamMessages,
@@ -514,12 +511,7 @@ async function runCattyTurn(input: CattyTurnInput, ctx: TurnDriverContext): Prom
assistantMsgId,
sessionId,
);
retryBaseMessages = buildSdkMessages(latestSession.messages, false, {
preserveTerminalToolResults: collectToolResultsAfterMessage(
latestSession.messages,
assistantMsgId,
),
}, latestSession.contextCompaction);
retryBaseMessages = buildSdkMessages(latestSession.messages, false, latestSession.contextCompaction);
}
retryAssistantMsgId = generateId();
ui.addMessageToSession(sessionId, {
+1
View File
@@ -180,6 +180,7 @@ export interface StepEndEvent extends AgentEventBase {
modelId?: string;
finishReason?: string;
promptTokens: number;
cachedPromptTokens?: number;
completionTokens: number;
totalTokens: number;
}
@@ -0,0 +1,28 @@
import assert from 'node:assert/strict';
import test from 'node:test';
import { normalizeOpenAIChatCacheUsage } from './openAIChatCacheUsage';
test('adapts documented DeepSeek cache usage while preserving the rest of the response', () => {
const response = { choices: [], usage: {
prompt_tokens: 1000, prompt_cache_hit_tokens: 900, prompt_cache_miss_tokens: 100,
prompt_tokens_details: { other: 1 }, completion_tokens: 5,
} };
const parsed = JSON.parse(normalizeOpenAIChatCacheUsage(JSON.stringify(response)));
assert.deepEqual(parsed, {
...response, usage: { ...response.usage, prompt_tokens_details: { other: 1, cached_tokens: 900 } },
});
});
test('preserves standard usage and rejects invalid cache counts without breaking stream data', () => {
for (const hit of [-1, 1.5, '900', 1001, null]) {
const data = JSON.stringify({ usage: { prompt_tokens: 1000, prompt_cache_hit_tokens: hit } });
assert.equal(normalizeOpenAIChatCacheUsage(data), data);
}
for (const data of ['[DONE]', 'not JSON', '{"usage":null}', '{"type":"message_start"}']) {
assert.equal(normalizeOpenAIChatCacheUsage(data), data);
}
const data = JSON.stringify({ usage: {
prompt_tokens: 1000, prompt_cache_hit_tokens: 900, prompt_tokens_details: { cached_tokens: 0 },
} });
assert.equal(normalizeOpenAIChatCacheUsage(data), data);
});
+17
View File
@@ -0,0 +1,17 @@
/** Adapt DeepSeek's documented usage fields before the OpenAI SDK validates them. */
export function normalizeOpenAIChatCacheUsage(data: string): string {
if (!data.includes('prompt_cache_hit_tokens')) return data;
try {
const body = JSON.parse(data);
const usage = body?.usage;
const hit = usage?.prompt_cache_hit_tokens;
if (!Number.isSafeInteger(hit) || hit < 0) return data;
if (Number.isFinite(usage.prompt_tokens) && hit > usage.prompt_tokens) return data;
// Preserve a provider's standard field, including an explicit zero.
if (usage.prompt_tokens_details?.cached_tokens != null) return data;
usage.prompt_tokens_details = { ...usage.prompt_tokens_details, cached_tokens: hit };
return JSON.stringify(body);
} catch {
return data;
}
}
+23 -1
View File
@@ -1,6 +1,6 @@
import assert from 'node:assert/strict';
import test from 'node:test';
import { isStepCount, streamText, tool } from 'ai';
import { generateText, isStepCount, streamText, tool } from 'ai';
import { z } from 'zod';
import { createBridgeFetchForSDK, createModelFromConfig } from './sdk/providers';
import type { OpenAIChatAssistantFields } from './providerContinuation';
@@ -1305,3 +1305,25 @@ for (const indexes of [[0], [1], [1, 4], [4, 1]]) {
indexes.map(index => `call_${index}`).sort());
});
}
test('non-streaming DeepSeek usage reaches the SDK as cached input', async t => {
const originalWindow = globalThis.window;
t.after(() => { globalThis.window = originalWindow; });
globalThis.window = { netcatty: {
aiFetch: async () => ({ ok: true, status: 200, data: JSON.stringify({
id: 'response', object: 'chat.completion', created: 0, model: 'deepseek-chat',
choices: [{ index: 0, message: { role: 'assistant', content: 'OK' }, finish_reason: 'stop' }],
usage: { prompt_tokens: 1000, completion_tokens: 1, total_tokens: 1001,
prompt_cache_hit_tokens: 900, prompt_cache_miss_tokens: 100 },
}) }),
} } as unknown as Window & typeof globalThis;
const result = await generateText({
model: createModelFromConfig({
id: 'fixture', providerId: 'custom', name: 'Fixture', enabled: true,
baseURL: 'https://provider.example.test/v1', apiKey: 'fixture', defaultModel: 'deepseek-chat',
}),
prompt: 'hello',
});
assert.equal(result.usage.inputTokenDetails.cacheReadTokens, 900);
assert.equal(result.usage.inputTokenDetails.noCacheTokens, 100);
});
@@ -158,13 +158,19 @@ function compressContentPartForRequestRetry(part: unknown): unknown {
const output = record.output;
if (output && typeof output === "object") {
const outputRecord = output as Record<string, unknown>;
if (outputRecord.type === "text" && typeof outputRecord.value === "string") {
const value = compressAndTruncateText(outputRecord.value, RETRY_MAX_TOOL_RESULT_CHARS);
if (value === outputRecord.value) return part;
const text = outputRecord.type === "text" && typeof outputRecord.value === "string"
? outputRecord.value
: outputRecord.type === "json" ? JSON.stringify(outputRecord.value) : undefined;
if (text !== undefined) {
// Live SDK tool results are JSON, while persisted results replay as
// text. Apply the same reduction before their first model request.
const value = compressAndTruncateText(text, RETRY_MAX_TOOL_RESULT_CHARS);
if (value === text) return part;
return {
...record,
output: {
...outputRecord,
type: "text",
value,
},
};
+3 -2
View File
@@ -6,6 +6,7 @@ import { resolveOpenAIApi, resolveProviderStyle } from '../types';
import { normalizeAnthropicSdkBaseURL } from '../anthropicCompatBaseUrl';
import { buildSdkRequestHeaders } from '../providerRequestHeaders';
import { normalizeOllamaSdkBaseURL } from '../ollamaCompatBaseUrl';
import { normalizeOpenAIChatCacheUsage } from '../openAIChatCacheUsage';
export { normalizeOllamaSdkBaseURL };
import {
@@ -529,7 +530,7 @@ export function createBridgeFetchForSDK(
};
const unsubData = bridge.onAiStreamData(requestId, (data: string) => {
const normalizedData = normalizeOpenAIChatToolCalls(data);
const normalizedData = normalizeOpenAIChatCacheUsage(normalizeOpenAIChatToolCalls(data));
captureOpenAIChatFields(normalizedData);
// Re-wrap as SSE so the SDK can parse it
enqueueChunk(encoder.encode(`data: ${normalizedData}\n\n`));
@@ -627,7 +628,7 @@ export function createBridgeFetchForSDK(
// Non-streaming path
const result = await bridge.aiFetch(url, method, headers, requestBody, providerId);
return new Response(result.data, {
return new Response(normalizeOpenAIChatCacheUsage(result.data), {
status: result.status,
statusText: result.ok ? 'OK' : 'Error',
headers: { 'content-type': 'application/json' },