Summarize chat trigger (#1890)

<!-- CURSOR_SUMMARY -->
> [!NOTE]
> Adds a context-limit banner with one-click “summarize into new chat,”
refactors token counting with react-query, and persists per-message max
token usage.
> 
> - **Chat UX**
> - **Context limit banner** (`ContextLimitBanner.tsx`,
`MessagesList.tsx`): shows when within 40k tokens of `contextWindow`,
with tooltip and action to summarize into a new chat.
> - **Summarize flow**: extracted to `useSummarizeInNewChat` and used in
chat input and banner; new summarize system prompt
(`summarize_chat_system_prompt.ts`).
> - **Token usage & counting**
> - **Persist max tokens used per assistant message**: DB migration
(`messages.max_tokens_used`), schema updates, and saving usage during
streaming (`chat_stream_handlers.ts`).
> - **Token counting refactor** (`useCountTokens.ts`): react-query with
debounce; returns `estimatedTotalTokens` and `actualMaxTokens`;
invalidated on model change and stream end; `TokenBar` updated.
> - **Surfacing usage**: tooltip on latest assistant message shows total
tokens (`ChatMessage.tsx`).
> - **Model/config tweaks**
> - Set `auto` model `contextWindow` to `200_000`
(`language_model_constants.ts`).
>   - Improve chat auto-scroll dependency (`ChatPanel.tsx`).
>   - Fix app path validation regex (`app_handlers.ts`).
> - **Testing & dev server**
> - E2E tests for banner and summarize
(`e2e-tests/context_limit_banner.spec.ts` + fixtures/snapshot).
> - Fake LLM server streams usage to simulate high token scenarios
(`testing/fake-llm-server/*`).
> 
> <sup>Written by [Cursor
Bugbot](https://cursor.com/dashboard?tab=bugbot) for commit
2ae16a14d50699cc772407426419192c2fdf2ec3. This will update automatically
on new commits. Configure
[here](https://cursor.com/dashboard?tab=bugbot).</sup>
<!-- /CURSOR_SUMMARY -->













<!-- This is an auto-generated description by cubic. -->
---
## Summary by cubic
Adds a “Summarize into new chat” trigger and a context limit banner to
help keep conversations focused and avoid hitting model limits. Also
tracks and surfaces actual token usage per assistant message, with a
token counting refactor for reliability.

- **New Features**
- Summarize into new chat from the input or banner; improved system
prompt with clear output format.
- Context limit banner shows when within 40k tokens of the model’s
context window and offers a one-click summarize action.
  - Tooltip on the latest assistant message shows total tokens used.

- **Refactors**
- Token counting now uses react-query and returns estimatedTotalTokens
and actualMaxTokens; counts are invalidated on model change and when
streaming settles.
- Persist per-message max_tokens_used in the messages table; backend
aggregates model usage during streaming and saves it.
- Adjusted default “Auto” model contextWindow to 200k for more realistic
limits.
- Improved chat scrolling while streaming; fixed app path validation
regex.

<sup>Written for commit 2ae16a14d50699cc772407426419192c2fdf2ec3.
Summary will update automatically on new commits.</sup>

<!-- End of auto-generated description by cubic. -->

testing/fake-llm-server/chatCompletionHandler.ts

@@ -371,6 +371,15 @@ export default Index;
       return;
     }
 
+    // Check for high token usage marker to simulate near context limit
+    const highTokensMatch =
+      typeof lastMessage?.content === "string" &&
+      !lastMessage?.content.startsWith("Summarize the following chat:") &&
+      lastMessage?.content?.match?.(/\[high-tokens=(\d+)\]/);
+    const highTokensValue = highTokensMatch
+      ? parseInt(highTokensMatch[1], 10)
+      : null;
+
     // Split the message into characters to simulate streaming
     const messageChars = messageContent.split("");
 
@@ -388,8 +397,15 @@ export default Index;
         res.write(createStreamChunk(batch));
         index += batchSize;
       } else {
-        // Send the final chunk
-        res.write(createStreamChunk("", "assistant", true));
+        // Send the final chunk with optional usage info for high token simulation
+        const usage = highTokensValue
+          ? {
+              prompt_tokens: highTokensValue - 100,
+              completion_tokens: 100,
+              total_tokens: highTokensValue,
+            }
+          : undefined;
+        res.write(createStreamChunk("", "assistant", true, usage));
         clearInterval(interval);
         res.end();
       }