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cline-openai-cache-key

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Cline OpenAI native provider sends no prompt_cache_key. Add a stable per-task key so cached_tokens stops being zero.

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Cline: add prompt_cache_key to OpenAI native provider

Target

src/core/api/providers/openai-native.ts in cline/cline.

Permalink: https://github.com/cline/cline/blob/65e9727c/src/core/api/providers/openai-native.ts

Symptom

Cline's OpenAI native provider only READS cache stats from responses, it never enables caching:

const cacheReadTokens = usage?.prompt_tokens_details?.cached_tokens || 0
const cacheWriteTokens = 0  // ← always 0

No prompt_cache_key set on the Responses API call, no work done to verify prefix stability. OpenAI's automatic prefix caching may still fire if the prefix happens to be byte-stable, but routing is random across pods so hit rates are low and unpredictable.

Open issue #554 ("OpenAI Prompt Caching appears not enabled?") tracks user-side confusion. PR #1156 attempted a partial fix but was closed without merging.

Fix

Set a stable prompt_cache_key derived from the task ID (or a hash of the system instructions if no task ID is available). NEVER use a per-request UUID — that's worse than no key.

--- a/src/core/api/providers/openai-native.ts
+++ b/src/core/api/providers/openai-native.ts
@@
-  const response = await client.responses.create({
+  // Stable cache key: same task = same pod = warm cache.
+  // NEVER use uuid() — random keys force random pod routing and
+  // kill cache hits.
+  const cacheKey = this.options.taskId
+    || this.options.ulid
+    || crypto.createHash("sha256")
+         .update(systemPrompt)
+         .digest("hex")
+         .slice(0, 16)
+
+  const response = await client.responses.create({
     model: modelId,
     input: messages,
+    prompt_cache_key: `cline:${modelId}:${cacheKey}`,
     ...
   })

If the harness uses the legacy Chat Completions endpoint (client.chat.completions.create), prompt_cache_key isn't a valid field there. In that case the only knob is prefix stability — make sure the system prompt has no per-request timestamps, session IDs, or randomized content.

Verify

  1. Start mitmproxy capture as before.
  2. Configure Cline with an OpenAI model (gpt-5.4, gpt-5-codex, etc.).
  3. Send two identical prompts in the same task.
  4. Inspect captured requests:
    • prompt_cache_key field present and identical across both
    • System prompt bytes identical
  5. Inspect responses:
    • Turn 2 usage.prompt_tokens_details.cached_tokens > 0
    • Ratio cached_tokens / prompt_tokens ≥ 0.5 on a steady-state turn

Background

OpenAI's Responses API uses prompt_cache_key as a pod-routing hint. Stable key = same pod = warm cache. Per-request UUIDs are the #1 silent killer of OpenAI cache hits.

See docs/gotchas.md #9b for the full explanation, and docs/concepts/openai.md "The prompt_cache_key trick".

Reference implementation: Codex CLI uses session thread_id as the cache key and preserves it across compaction and sub-agents — see audits/codex-cli.md.

Full audit: audits/cline.md.