From 2acf08cca055f6bac41da762fefa08dc053a3a1a Mon Sep 17 00:00:00 2001
From: Aiden Cline <aidenpcline@gmail.com>
Date: Mon, 6 Jul 2026 18:41:04 -0500
Subject: [PATCH] fix(core): harden semantic context estimation

---
 packages/core/src/session/compaction.ts       | 43 +++++++++++++++++--
 packages/core/test/session-compaction.test.ts | 28 ++++++++++--
 2 files changed, 63 insertions(+), 8 deletions(-)

diff --git a/packages/core/src/session/compaction.ts b/packages/core/src/session/compaction.ts
index ce4e84e91f..d3bb0a5cc6 100644
--- a/packages/core/src/session/compaction.ts
+++ b/packages/core/src/session/compaction.ts
@@ -80,22 +80,57 @@ export interface Interface {
 
 export class Service extends Context.Service<Service, Interface>()("@opencode/v2/SessionCompaction") {}
 
-const stringify = (value: unknown) => (typeof value === "string" ? value : (JSON.stringify(value) ?? String(value)))
+const serializeString = (value: unknown) => {
+  try {
+    return String(value)
+  } catch {
+    return "[unserializable]"
+  }
+}
+
+const serializeJson = (value: unknown) => {
+  try {
+    return JSON.stringify(value) ?? serializeString(value)
+  } catch {
+    return serializeString(value)
+  }
+}
+
+const serializeError = (value: unknown) => {
+  try {
+    const prototype =
+      typeof value === "object" && value !== null && !Array.isArray(value) && Object.getPrototypeOf(value)
+    const structured = Array.isArray(value) || prototype === Object.prototype || prototype === null
+    return structured ? serializeJson(value) : serializeString(value)
+  } catch {
+    return serializeString(value)
+  }
+}
 
 const serializeContent = (part: LLMRequest["messages"][number]["content"][number]) => {
   if (part.type === "text" || part.type === "reasoning") return part.text
   if (part.type === "media") return ""
-  if (part.type === "tool-call") return `${part.name}\n${stringify(part.input)}`
+  if (part.type === "tool-call") return `${part.name}\n${serializeJson(part.input)}`
+  // OpenAI replays hosted image generations by item reference; the opaque JSON result contains the image bytes.
+  if (
+    part.providerExecuted &&
+    part.name === "image_generation" &&
+    part.result.type === "json" &&
+    typeof part.providerMetadata?.openai?.itemId === "string"
+  )
+    return part.name
   if (part.result.type === "content")
     return [part.name, ...part.result.value.flatMap((item) => (item.type === "text" ? [item.text] : []))].join("\n")
-  return `${part.name}\n${stringify(part.result.value)}`
+  if (part.result.type === "text") return `${part.name}\n${serializeString(part.result.value)}`
+  if (part.result.type === "error") return `${part.name}\n${serializeError(part.result.value)}`
+  return `${part.name}\n${serializeJson(part.result.value)}`
 }
 
 const estimate = (request: LLMRequest) =>
   Token.estimate(
     [
       ...request.system.map((part) => part.text),
-      JSON.stringify(request.tools),
+      serializeJson(request.tools),
       ...request.messages.flatMap((message) => message.content.map(serializeContent).filter(Boolean)),
     ].join("\n"),
   )
diff --git a/packages/core/test/session-compaction.test.ts b/packages/core/test/session-compaction.test.ts
index ae6c1c70a8..47f5608cbf 100644
--- a/packages/core/test/session-compaction.test.ts
+++ b/packages/core/test/session-compaction.test.ts
@@ -1,6 +1,15 @@
 import { expect, test } from "bun:test"
-import { LLM, LLMClient, LLMEvent, Message, Model, ToolCallPart, type LLMRequest } from "@opencode-ai/llm"
-import { OpenAIChat } from "@opencode-ai/llm/protocols"
+import {
+  LLM,
+  LLMClient,
+  LLMEvent,
+  Message,
+  Model,
+  ToolCallPart,
+  ToolResultPart,
+  type LLMRequest,
+} from "@opencode-ai/llm"
+import { OpenAIChat, OpenAIResponses } from "@opencode-ai/llm/protocols"
 import { Base64, FileAttachment } from "@opencode-ai/schema/prompt"
 import { Config } from "@opencode-ai/core/config"
 import { Database } from "@opencode-ai/core/database/database"
@@ -87,7 +96,7 @@ it.effect("does not count image attachments as text context", () =>
     const inputModel = Model.make({
       id: "media-model",
       provider: "test",
-      route: OpenAIChat.route.with({ limits: { context: 30_000, output: 1_000 } }),
+      route: OpenAIResponses.route.with({ limits: { context: 30_000, output: 1_000 } }),
     })
     const inputModelRef = ModelV2.Ref.make({
       id: ModelV2.ID.make(inputModel.id),
@@ -110,7 +119,18 @@ it.effect("does not count image attachments as text context", () =>
     ]
     const request = LLM.request({
       model: inputModel,
-      messages: toLLMMessages(messages, inputModelRef),
+      messages: [
+        ...toLLMMessages(messages, inputModelRef),
+        Message.assistant(
+          ToolResultPart.make({
+            id: "image_generation_1",
+            name: "image_generation",
+            result: { type: "image_generation_call", output: Buffer.alloc(64 * 1024).toString("base64") },
+            providerExecuted: true,
+            providerMetadata: { openai: { itemId: "image_generation_1" } },
+          }),
+        ),
+      ],
     })
 
     expect(request.messages.flatMap((message) => message.content)).toContainEqual({