diff --git a/packages/playwright-core/src/utils/isomorphic/llm.ts b/packages/playwright-core/src/utils/isomorphic/llm.ts
deleted file mode 100644
index 0a5647f4cb..0000000000
--- a/packages/playwright-core/src/utils/isomorphic/llm.ts
+++ /dev/null
@@ -1,195 +0,0 @@
-/**
- * Copyright (c) Microsoft Corporation.
- *
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at
- *
- * http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- */
-
-import { EventEmitter } from '@testIsomorphic/events';
-
-export type LLMMessage = {
-  role: 'user' | 'assistant' | 'developer';
-  content: string;
-  displayContent?: string;
-};
-
-export interface LLM {
-  chatCompletion(messages: LLMMessage[], signal: AbortSignal): AsyncGenerator<string>;
-}
-
-// https://html.spec.whatwg.org/multipage/server-sent-events.html#parsing-an-event-stream
-async function *parseSSE(body: NonNullable<Response['body']>): AsyncGenerator<{ type: string, data: string, id: string }> {
-  const reader = body.pipeThrough(new TextDecoderStream()).getReader();
-  let buffer = '';
-
-  let lastEventId = '';
-  let type: string = '';
-  let data = '';
-
-  while (true) {
-    const { value, done } = await reader.read();
-    if (done)
-      break;
-    buffer += value;
-    const lines = buffer.split('\n');
-    buffer = lines.pop()!; // last line is either empty or incomplete
-
-    for (const line of lines) {
-      if (line.length === 0) {
-        if (data === '') {
-          data = '';
-          type = '';
-          continue;
-        }
-
-        if (data[data.length - 1] === '\n')
-          data = data.substring(0, data.length - 1);
-
-        const event = { type: type || 'message', data, id: lastEventId };
-        type = '';
-        data = '';
-
-        yield event;
-      }
-      if (line[0] === ':')
-        continue;
-
-      let name = '';
-      let value = '';
-      const colon = line.indexOf(':');
-      if (colon === -1) {
-        name = line;
-      } else {
-        name = line.substring(0, colon);
-        value = line[colon + 1] === ' ' ? line.substring(colon + 2) : line.substring(colon + 1);
-      }
-
-      switch (name) {
-        case 'event':
-          type = value;
-          break;
-        case 'data':
-          data += value + '\n';
-          break;
-        case 'id':
-          lastEventId = value;
-          break;
-        case 'retry':
-        default:
-          // not implemented
-          break;
-      }
-    }
-  }
-}
-
-export class OpenAI implements LLM {
-
-  constructor(private apiKey: string, private baseURL = 'https://api.openai.com') {}
-
-  async *chatCompletion(messages: LLMMessage[])  {
-    const url = new URL('./v1/chat/completions', this.baseURL);
-    const response = await fetch(url, {
-      method: 'POST',
-      headers: {
-        'Content-Type': 'application/json',
-        'Authorization': `Bearer ${this.apiKey}`,
-        'x-pw-serviceworker': 'forward',
-      },
-      body: JSON.stringify({
-        model: 'gpt-4o',
-        messages: messages.map(({ role, content }) => ({ role, content })),
-        stream: true,
-      }),
-    });
-
-    if (response.status !== 200 || !response.body)
-      throw new Error('Failed to chat with OpenAI, unexpected status: ' + response.status + await response.text());
-
-    for await (const sseEvent of parseSSE(response.body)) {
-      const event = JSON.parse(sseEvent.data);
-      if (event.object === 'chat.completion.chunk') {
-        if (event.choices[0].finish_reason)
-          break;
-        yield event.choices[0].delta.content;
-      }
-    }
-  }
-}
-
-export class Anthropic implements LLM {
-  constructor(private apiKey: string, private baseURL = 'https://api.anthropic.com') {}
-  async *chatCompletion(messages: LLMMessage[]): AsyncGenerator<string> {
-    const response = await fetch(new URL('./v1/messages', this.baseURL), {
-      method: 'POST',
-      headers: {
-        'Content-Type': 'application/json',
-        'x-api-key': this.apiKey,
-        'anthropic-version': '2023-06-01',
-        'x-pw-serviceworker': 'forward',
-      },
-      body: JSON.stringify({
-        model: 'claude-3-5-sonnet-20241022',
-        messages: messages.filter(({ role }) => role !== 'developer').map(({ role, content }) => ({ role, content })),
-        system: messages.find(({ role }) => role === 'developer')?.content,
-        max_tokens: 1024,
-        stream: true,
-      })
-    });
-
-    if (response.status !== 200 || !response.body)
-      throw new Error('Failed to chat with Anthropic, unexpected status: ' + response.status + await response.text());
-
-    for await (const sseEvent of parseSSE(response.body)) {
-      const event = JSON.parse(sseEvent.data);
-      if (event.type  === 'content_block_delta')
-        yield event.delta.text;
-    }
-  }
-}
-
-export class LLMChat {
-  conversations = new Map<string, Conversation>();
-
-  constructor(readonly api: LLM) {}
-
-  getConversation(id: string, systemPrompt: string) {
-    if (!this.conversations.has(id)) {
-      const conversation = new Conversation(this, systemPrompt);
-      this.conversations.set(id, conversation);
-    }
-    return this.conversations.get(id)!;
-  }
-}
-
-export class Conversation {
-  history: LLMMessage[];
-  onChange = new EventEmitter<void>();
-
-  constructor(private chat: LLMChat, systemPrompt: string) {
-    this.history = [{ role: 'developer', content: systemPrompt }];
-  }
-
-  async send(content: string, displayContent: string | undefined, signal: AbortSignal) {
-    const response: LLMMessage = { role: 'assistant', content: '' };
-    this.history.push({ role: 'user', content, displayContent }, response);
-    this.onChange.fire();
-    for await (const chunk of this.chat.api.chatCompletion(this.history, signal)) {
-      response.content += chunk;
-      this.onChange.fire();
-    }
-  }
-
-  isEmpty() {
-    return this.history.length === 1;
-  }
-}
diff --git a/packages/trace-viewer/src/ui/llm.tsx b/packages/trace-viewer/src/ui/llm.tsx
index 9bfced6008..10a095bd28 100644
--- a/packages/trace-viewer/src/ui/llm.tsx
+++ b/packages/trace-viewer/src/ui/llm.tsx
@@ -1,5 +1,200 @@
+/**
+ * Copyright (c) Microsoft Corporation.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
 import * as React from 'react';
-import { LLMChat, LLM, OpenAI, Anthropic } from '@isomorphic/llm';
+import { EventEmitter } from '@testIsomorphic/events';
+
+export type LLMMessage = {
+  role: 'user' | 'assistant' | 'developer';
+  content: string;
+  displayContent?: string;
+};
+
+interface LLM {
+  chatCompletion(messages: LLMMessage[], signal: AbortSignal): AsyncGenerator<string>;
+}
+
+// https://html.spec.whatwg.org/multipage/server-sent-events.html#parsing-an-event-stream
+async function *parseSSE(body: NonNullable<Response['body']>): AsyncGenerator<{ type: string, data: string, id: string }> {
+  const reader = body.pipeThrough(new TextDecoderStream()).getReader();
+  let buffer = '';
+
+  let lastEventId = '';
+  let type: string = '';
+  let data = '';
+
+  while (true) {
+    const { value, done } = await reader.read();
+    if (done)
+      break;
+    buffer += value;
+    const lines = buffer.split('\n');
+    buffer = lines.pop()!; // last line is either empty or incomplete
+
+    for (const line of lines) {
+      if (line.length === 0) {
+        if (data === '') {
+          data = '';
+          type = '';
+          continue;
+        }
+
+        if (data[data.length - 1] === '\n')
+          data = data.substring(0, data.length - 1);
+
+        const event = { type: type || 'message', data, id: lastEventId };
+        type = '';
+        data = '';
+
+        yield event;
+      }
+      if (line[0] === ':')
+        continue;
+
+      let name = '';
+      let value = '';
+      const colon = line.indexOf(':');
+      if (colon === -1) {
+        name = line;
+      } else {
+        name = line.substring(0, colon);
+        value = line[colon + 1] === ' ' ? line.substring(colon + 2) : line.substring(colon + 1);
+      }
+
+      switch (name) {
+        case 'event':
+          type = value;
+          break;
+        case 'data':
+          data += value + '\n';
+          break;
+        case 'id':
+          lastEventId = value;
+          break;
+        case 'retry':
+        default:
+          // not implemented
+          break;
+      }
+    }
+  }
+}
+
+class OpenAI implements LLM {
+
+  constructor(private apiKey: string, private baseURL = 'https://api.openai.com') {}
+
+  async *chatCompletion(messages: LLMMessage[])  {
+    const url = new URL('./v1/chat/completions', this.baseURL);
+    const response = await fetch(url, {
+      method: 'POST',
+      headers: {
+        'Content-Type': 'application/json',
+        'Authorization': `Bearer ${this.apiKey}`,
+        'x-pw-serviceworker': 'forward',
+      },
+      body: JSON.stringify({
+        model: 'gpt-4o',
+        messages: messages.map(({ role, content }) => ({ role, content })),
+        stream: true,
+      }),
+    });
+
+    if (response.status !== 200 || !response.body)
+      throw new Error('Failed to chat with OpenAI, unexpected status: ' + response.status + await response.text());
+
+    for await (const sseEvent of parseSSE(response.body)) {
+      const event = JSON.parse(sseEvent.data);
+      if (event.object === 'chat.completion.chunk') {
+        if (event.choices[0].finish_reason)
+          break;
+        yield event.choices[0].delta.content;
+      }
+    }
+  }
+}
+
+class Anthropic implements LLM {
+  constructor(private apiKey: string, private baseURL = 'https://api.anthropic.com') {}
+  async *chatCompletion(messages: LLMMessage[]): AsyncGenerator<string> {
+    const response = await fetch(new URL('./v1/messages', this.baseURL), {
+      method: 'POST',
+      headers: {
+        'Content-Type': 'application/json',
+        'x-api-key': this.apiKey,
+        'anthropic-version': '2023-06-01',
+        'x-pw-serviceworker': 'forward',
+      },
+      body: JSON.stringify({
+        model: 'claude-3-5-sonnet-20241022',
+        messages: messages.filter(({ role }) => role !== 'developer').map(({ role, content }) => ({ role, content })),
+        system: messages.find(({ role }) => role === 'developer')?.content,
+        max_tokens: 1024,
+        stream: true,
+      })
+    });
+
+    if (response.status !== 200 || !response.body)
+      throw new Error('Failed to chat with Anthropic, unexpected status: ' + response.status + await response.text());
+
+    for await (const sseEvent of parseSSE(response.body)) {
+      const event = JSON.parse(sseEvent.data);
+      if (event.type  === 'content_block_delta')
+        yield event.delta.text;
+    }
+  }
+}
+
+class LLMChat {
+  conversations = new Map<string, Conversation>();
+
+  constructor(readonly api: LLM) {}
+
+  getConversation(id: string, systemPrompt: string) {
+    if (!this.conversations.has(id)) {
+      const conversation = new Conversation(this, systemPrompt);
+      this.conversations.set(id, conversation);
+    }
+    return this.conversations.get(id)!;
+  }
+}
+
+class Conversation {
+  history: LLMMessage[];
+  onChange = new EventEmitter<void>();
+
+  constructor(private chat: LLMChat, systemPrompt: string) {
+    this.history = [{ role: 'developer', content: systemPrompt }];
+  }
+
+  async send(content: string, displayContent: string | undefined, signal: AbortSignal) {
+    const response: LLMMessage = { role: 'assistant', content: '' };
+    this.history.push({ role: 'user', content, displayContent }, response);
+    this.onChange.fire();
+    for await (const chunk of this.chat.api.chatCompletion(this.history, signal)) {
+      response.content += chunk;
+      this.onChange.fire();
+    }
+  }
+
+  isEmpty() {
+    return this.history.length < 2;
+  }
+}
+
 
 const llmContext = React.createContext<LLMChat | undefined>(undefined);