Files
OmniRoute/open-sse/translator/index.ts
tombii 0bc557fb8b feat(sse): preserve client cache_control for Claude Code with deterministic routing
Adds intelligent cache control preservation for Claude Code clients:

- New cacheControlPolicy.ts module with detection logic:
  - isClaudeCodeClient(): Detects Claude Code via User-Agent
  - providerSupportsCaching(): Checks provider (claude, anthropic, zai, qwen)
  - isDeterministicStrategy(): Identifies priority/cost-optimized strategies
  - shouldPreserveCacheControl(): Main policy decision

- Cache control is preserved when:
  1. Client is Claude Code (detected via User-Agent)
  2. Provider supports prompt caching
  3. Request routing is deterministic:
     - Single model requests (always)
     - Combo with priority or cost-optimized strategy only

- Updated translator to accept preserveCacheControl option
- Updated chatCore and chat handler to propagate combo strategy
- Added comprehensive unit tests (24 tests)

Non-deterministic combo strategies (weighted, round-robin, random, etc.)
continue to use OmniRoute's managed caching strategy.

Refs: #cache-control-preservation
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-03-29 12:24:44 +02:00

338 lines
11 KiB
TypeScript

import { FORMATS } from "./formats.ts";
import { ensureToolCallIds, fixMissingToolResponses } from "./helpers/toolCallHelper.ts";
import { prepareClaudeRequest } from "./helpers/claudeHelper.ts";
import { filterToOpenAIFormat } from "./helpers/openaiHelper.ts";
import {
coerceToolSchemas,
injectEmptyReasoningContentForToolCalls,
sanitizeToolDescriptions,
} from "./helpers/schemaCoercion.ts";
import { getRequestTranslator, getResponseTranslator } from "./registry.ts";
import { bootstrapTranslatorRegistry } from "./bootstrap.ts";
import { normalizeThinkingConfig } from "../services/provider.ts";
import { applyThinkingBudget } from "../services/thinkingBudget.ts";
import { normalizeRoles } from "../services/roleNormalizer.ts";
bootstrapTranslatorRegistry();
export { register } from "./registry.ts";
function normalizeResponsesInputItem(item) {
if (typeof item === "string") {
return {
type: "message",
role: "user",
content: [{ type: "input_text", text: item }],
};
}
if (!item || typeof item !== "object") return item;
if (item.type || item.role) {
return item.type ? item : { type: "message", ...item };
}
if (typeof item.text === "string") {
return {
type: "message",
role: "user",
content: [{ type: "input_text", text: item.text }],
};
}
return item;
}
function normalizeOpenAIResponsesRequest(body) {
if (!body || typeof body !== "object") return body;
const normalized = { ...body };
if (typeof normalized.input === "string") {
normalized.input = [
{
type: "message",
role: "user",
content: [{ type: "input_text", text: normalized.input }],
},
];
return normalized;
}
if (Array.isArray(normalized.input)) {
normalized.input = normalized.input.map(normalizeResponsesInputItem);
return normalized;
}
if (normalized.input && typeof normalized.input === "object") {
normalized.input = [normalizeResponsesInputItem(normalized.input)];
return normalized;
}
return normalized;
}
/** @param options.normalizeToolCallId - When true, use 9-char tool call ids (e.g. Mistral); when false, leave ids as-is */
/** @param options.preserveDeveloperRole - undefined/true: keep developer for OpenAI format (default); false: map to system */
/** @param options.preserveCacheControl - When true, preserve client-side cache_control markers (for Claude Code, etc.) */
// Translate request: source -> openai -> target
export function translateRequest(
sourceFormat,
targetFormat,
model,
body,
stream = true,
credentials = null,
provider = null,
reqLogger = null,
options?: { normalizeToolCallId?: boolean; preserveDeveloperRole?: boolean; preserveCacheControl?: boolean }
) {
let result = body;
const use9CharId = options?.normalizeToolCallId === true;
const preserveDeveloperRole = options?.preserveDeveloperRole;
// Phase 2: Apply thinking budget control before normalization
result = applyThinkingBudget(result);
// Normalize thinking config: remove if lastMessage is not user
normalizeThinkingConfig(result);
// Ensure tool_calls have id; optionally normalize to 9-char for providers like Mistral
ensureToolCallIds(result, { use9CharId });
// Fix missing tool responses (insert empty tool_result if needed)
fixMissingToolResponses(result);
// Normalize roles: developer→system unless preserved, system→user for incompatible models.
// This handles (1) sourceFormat openai with messages containing developer → non-openai target
// or preserveDeveloperRole=false, and (2) all other paths where result.messages already exists.
if (result.messages && Array.isArray(result.messages)) {
result.messages = normalizeRoles(
result.messages,
provider || "",
model || "",
targetFormat,
preserveDeveloperRole
);
}
// If same format, skip translation steps
if (sourceFormat !== targetFormat) {
// Check for direct translation path first (e.g., Claude → Gemini)
const directTranslator = getRequestTranslator(sourceFormat, targetFormat);
if (directTranslator && sourceFormat !== FORMATS.OPENAI && targetFormat !== FORMATS.OPENAI) {
result = directTranslator(model, result, stream, credentials);
} else {
// Fallback: hub-and-spoke via OpenAI
// Step 1: source -> openai (if source is not openai)
if (sourceFormat !== FORMATS.OPENAI) {
const toOpenAI = getRequestTranslator(sourceFormat, FORMATS.OPENAI);
if (toOpenAI) {
result = toOpenAI(model, result, stream, credentials);
// Log OpenAI intermediate format
reqLogger?.logOpenAIRequest?.(result);
}
}
// Step 2: openai -> target (if target is not openai)
if (targetFormat !== FORMATS.OPENAI) {
const fromOpenAI = getRequestTranslator(FORMATS.OPENAI, targetFormat);
if (fromOpenAI) {
result = fromOpenAI(model, result, stream, credentials);
}
}
}
}
// Always normalize to clean OpenAI format when target is OpenAI
// This handles hybrid requests (e.g., OpenAI messages + Claude tools)
if (targetFormat === FORMATS.OPENAI) {
result = filterToOpenAIFormat(result);
}
// Final step: prepare request for Claude format endpoints
// Preserve cache_control when:
// 1. Claude passthrough mode (Claude → Claude), OR
// 2. Explicitly requested via options (for caching-aware clients like Claude Code)
if (targetFormat === FORMATS.CLAUDE) {
const isClaudePassthrough = sourceFormat === FORMATS.CLAUDE;
const preserveCache = isClaudePassthrough || options?.preserveCacheControl === true;
result = prepareClaudeRequest(result, provider, preserveCache);
}
// Normalize openai-responses input shape for providers that require list input.
if (targetFormat === FORMATS.OPENAI_RESPONSES) {
result = normalizeOpenAIResponsesRequest(result);
}
// Second role normalization: only for OPENAI_RESPONSES. Here messages are built from input
// after the translation step, so the first normalizeRoles (above) did not see them. For
// sourceFormat openai with messages already on the body, the first block handles developer
// → system (non-openai target or preserveDeveloperRole=false); no second pass needed.
if (
sourceFormat === FORMATS.OPENAI_RESPONSES &&
result.messages &&
Array.isArray(result.messages)
) {
result.messages = normalizeRoles(
result.messages,
provider || "",
model || "",
targetFormat,
preserveDeveloperRole
);
}
if (result.tools !== undefined) {
result.tools = coerceToolSchemas(result.tools);
result.tools = sanitizeToolDescriptions(result.tools);
}
if (targetFormat === FORMATS.OPENAI && result.messages && Array.isArray(result.messages)) {
result.messages = injectEmptyReasoningContentForToolCalls(result.messages, provider);
}
// Ensure unique tool_call ids on final payload (translators may have introduced duplicates)
ensureToolCallIds(result, { use9CharId });
fixMissingToolResponses(result);
if (result.tools) {
result.tools = coerceToolSchemas(result.tools);
result.tools = sanitizeToolDescriptions(result.tools);
}
// Inject reasoning_content = "" for DeepSeek/Reasoning models assistant messages with tool_calls
// if omitted by the client, to avoid upstream 400 errors (e.g. "Messages with role 'assistant' that contain tool_calls must also include reasoning_content")
const isReasoner =
provider === "deepseek" || (typeof model === "string" && /r1|reason/i.test(model));
if (isReasoner && result.messages && Array.isArray(result.messages)) {
for (const msg of result.messages) {
if (
msg.role === "assistant" &&
Array.isArray(msg.tool_calls) &&
msg.tool_calls.length > 0 &&
msg.reasoning_content === undefined
) {
msg.reasoning_content = "";
}
}
}
return result;
}
// Translate response chunk: target -> openai -> source
export function translateResponse(targetFormat, sourceFormat, chunk, state) {
// If same format, return as-is
if (sourceFormat === targetFormat) {
return [chunk];
}
let results = [chunk];
let openaiResults = null; // Store OpenAI intermediate results
// Check for direct translation path first (e.g., Gemini → Claude)
const directTranslator = getResponseTranslator(targetFormat, sourceFormat);
if (directTranslator && targetFormat !== FORMATS.OPENAI && sourceFormat !== FORMATS.OPENAI) {
const converted = directTranslator(chunk, state);
if (converted) {
results = Array.isArray(converted) ? converted : [converted];
} else {
results = [];
}
return results;
}
// Fallback: hub-and-spoke via OpenAI
// Step 1: target -> openai (if target is not openai)
if (targetFormat !== FORMATS.OPENAI) {
const toOpenAI = getResponseTranslator(targetFormat, FORMATS.OPENAI);
if (toOpenAI) {
results = [];
const converted = toOpenAI(chunk, state);
if (converted) {
results = Array.isArray(converted) ? converted : [converted];
openaiResults = results; // Store OpenAI intermediate
}
}
}
// Step 2: openai -> source (if source is not openai)
if (sourceFormat !== FORMATS.OPENAI) {
const fromOpenAI = getResponseTranslator(FORMATS.OPENAI, sourceFormat);
if (fromOpenAI) {
const finalResults = [];
for (const r of results) {
const converted = fromOpenAI(r, state);
if (converted) {
finalResults.push(...(Array.isArray(converted) ? converted : [converted]));
}
}
results = finalResults;
}
}
// Attach OpenAI intermediate results for logging
if (openaiResults && sourceFormat !== FORMATS.OPENAI && targetFormat !== FORMATS.OPENAI) {
(results as { _openaiIntermediate?: unknown })._openaiIntermediate = openaiResults;
}
return results;
}
// Check if translation needed
export function needsTranslation(sourceFormat, targetFormat) {
return sourceFormat !== targetFormat;
}
// Initialize state for streaming response based on format
export function initState(sourceFormat) {
// Base state for all formats
const base = {
messageId: null,
model: null,
textBlockStarted: false,
thinkingBlockStarted: false,
inThinkingBlock: false,
currentBlockIndex: null,
toolCalls: new Map(),
finishReason: null,
finishReasonSent: false,
usage: null,
contentBlockIndex: -1,
};
// Add openai-responses specific fields
if (sourceFormat === FORMATS.OPENAI_RESPONSES) {
return {
...base,
seq: 0,
responseId: `resp_${Date.now()}`,
created: Math.floor(Date.now() / 1000),
started: false,
msgTextBuf: {},
msgItemAdded: {},
msgContentAdded: {},
msgItemDone: {},
reasoningId: "",
reasoningIndex: -1,
reasoningBuf: "",
reasoningPartAdded: false,
reasoningDone: false,
inThinking: false,
funcArgsBuf: {},
funcNames: {},
funcCallIds: {},
funcArgsDone: {},
funcItemDone: {},
completedSent: false,
};
}
return base;
}
// Initialize all translators (no-op, kept for backward compatibility)
export function initTranslators() {
bootstrapTranslatorRegistry();
}