chore(llm): make cache: 'auto' the default (#26798)

packages/llm/test/provider/anthropic-messages-cache.recorded.test.ts

@@ -20,6 +20,9 @@ const cacheRequest = LLM.request({
   model,
   system: [{ type: "text", text: LARGE_CACHEABLE_SYSTEM, cache: new CacheHint({ type: "ephemeral" }) }],
   prompt: "Say hi.",
+  // Manual hint on the system part is the only marker we want here — skip the
+  // auto-policy's latest-user-message breakpoint so the cassette body matches.
+  cache: "none",
   generation: { maxTokens: 16, temperature: 0 },
 })
 

packages/llm/test/provider/anthropic-messages.test.ts

@@ -18,6 +18,9 @@ const request = LLM.request({
   model,
   system: { type: "text", text: "You are concise.", cache: new CacheHint({ type: "ephemeral" }) },
   prompt: "Say hello.",
+  // This fixture predates the `cache: "auto"` default; pin the policy off so
+  // existing wire-shape assertions only see the manual hint on the system part.
+  cache: "none",
   generation: { maxTokens: 20, temperature: 0 },
 })
 
@@ -48,6 +51,7 @@ describe("Anthropic Messages route", () => {
             LLM.assistant([LLM.toolCall({ id: "call_1", name: "lookup", input: { query: "weather" } })]),
             LLM.toolMessage({ id: "call_1", name: "lookup", result: { forecast: "sunny" } }),
           ],
+          cache: "none",
         }),
       )
 

packages/llm/test/provider/bedrock-converse-cache.recorded.test.ts

@@ -27,6 +27,9 @@ const cacheRequest = LLM.request({
   model,
   system: [{ type: "text", text: LARGE_CACHEABLE_SYSTEM, cache: new CacheHint({ type: "ephemeral" }) }],
   prompt: "Say hi.",
+  // Manual hint on the system part is the only marker we want here — skip the
+  // auto-policy's latest-user-message breakpoint so the cassette body matches.
+  cache: "none",
   generation: { maxTokens: 16, temperature: 0 },
 })
 

packages/llm/test/provider/bedrock-converse.test.ts

@@ -63,6 +63,9 @@ const baseRequest = LLM.request({
   model,
   system: "You are concise.",
   prompt: "Say hello.",
+  // Wire-shape assertions in this file predate the `cache: "auto"` default;
+  // pin the policy off so they only exercise the lowering path itself.
+  cache: "none",
   generation: { maxTokens: 64, temperature: 0 },
 })
 
@@ -125,6 +128,7 @@ describe("Bedrock Converse route", () => {
             LLM.assistant([LLM.toolCall({ id: "tool_1", name: "lookup", input: { query: "weather" } })]),
             LLM.toolMessage({ id: "tool_1", name: "lookup", result: { forecast: "sunny" } }),
           ],
+          cache: "none",
         }),
       )
 
@@ -339,6 +343,7 @@ describe("Bedrock Converse route", () => {
               { type: "media", mediaType: "image/webp", data: "DDDD" },
             ]),
           ],
+          cache: "none",
         }),
       )
 
@@ -470,6 +475,7 @@ describe("Bedrock Converse route", () => {
             LLM.assistant([LLM.toolCall({ id: "call_1", name: "lookup", input: {} })]),
             LLM.toolMessage({ id: "call_1", name: "lookup", result: { temp: 72 }, cache }),
           ],
+          cache: "none",
         }),
       )
 
@@ -555,6 +561,7 @@ describe("Bedrock Converse recorded", () => {
           model: recordedModel(),
           system: "Reply with the single word 'Hello'.",
           prompt: "Say hello.",
+          cache: "none",
           generation: { maxTokens: 16, temperature: 0 },
         }),
       )
@@ -577,6 +584,7 @@ describe("Bedrock Converse recorded", () => {
           prompt: "Call get_weather with city exactly Paris.",
           tools: [weatherTool],
           toolChoice: LLM.toolChoice(weatherTool),
+          cache: "none",
           generation: { maxTokens: 80, temperature: 0 },
         }),
       )