Trying to get UI working with vector stores in a

app.ipynb

@@ -192,6 +192,135 @@
     "chain.run({'question': query})"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# UI\n",
+    "https://medium.com/@gabriel_renno/how-to-build-a-gpt3-5-powered-chatbot-for-your-landing-page-with-langchain-and-gradio-1236ddfb0cf1"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 40,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Running on local URL:  http://127.0.0.1:7862\n",
+      "\n",
+      "To create a public link, set `share=True` in `launch()`.\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div><iframe src=\"http://127.0.0.1:7862/\" width=\"100%\" height=\"500\" allow=\"autoplay; camera; microphone; clipboard-read; clipboard-write;\" frameborder=\"0\" allowfullscreen></iframe></div>"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/plain": []
+     },
+     "execution_count": 40,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "c:\\sc\\ai\\rag-demo-1\\.venv\\lib\\site-packages\\gradio\\components\\button.py:89: UserWarning: Using the update method is deprecated. Simply return a new object instead, e.g. `return gr.Button(...)` instead of `return gr.Button.update(...)`.\n",
+      "  warnings.warn(\n",
+      "Traceback (most recent call last):\n",
+      "  File \"c:\\sc\\ai\\rag-demo-1\\.venv\\lib\\site-packages\\gradio\\queueing.py\", line 406, in call_prediction\n",
+      "    output = await route_utils.call_process_api(\n",
+      "  File \"c:\\sc\\ai\\rag-demo-1\\.venv\\lib\\site-packages\\gradio\\route_utils.py\", line 226, in call_process_api\n",
+      "    output = await app.get_blocks().process_api(\n",
+      "  File \"c:\\sc\\ai\\rag-demo-1\\.venv\\lib\\site-packages\\gradio\\blocks.py\", line 1554, in process_api\n",
+      "    result = await self.call_function(\n",
+      "  File \"c:\\sc\\ai\\rag-demo-1\\.venv\\lib\\site-packages\\gradio\\blocks.py\", line 1206, in call_function\n",
+      "    prediction = await utils.async_iteration(iterator)\n",
+      "  File \"c:\\sc\\ai\\rag-demo-1\\.venv\\lib\\site-packages\\gradio\\utils.py\", line 517, in async_iteration\n",
+      "    return await iterator.__anext__()\n",
+      "  File \"c:\\sc\\ai\\rag-demo-1\\.venv\\lib\\site-packages\\gradio\\utils.py\", line 621, in asyncgen_wrapper\n",
+      "    async for response in f(*args, **kwargs):\n",
+      "  File \"c:\\sc\\ai\\rag-demo-1\\.venv\\lib\\site-packages\\gradio\\chat_interface.py\", line 424, in _stream_fn\n",
+      "    first_response = await async_iteration(generator)\n",
+      "  File \"c:\\sc\\ai\\rag-demo-1\\.venv\\lib\\site-packages\\gradio\\utils.py\", line 517, in async_iteration\n",
+      "    return await iterator.__anext__()\n",
+      "  File \"c:\\sc\\ai\\rag-demo-1\\.venv\\lib\\site-packages\\gradio\\utils.py\", line 510, in __anext__\n",
+      "    return await anyio.to_thread.run_sync(\n",
+      "  File \"c:\\sc\\ai\\rag-demo-1\\.venv\\lib\\site-packages\\anyio\\to_thread.py\", line 33, in run_sync\n",
+      "    return await get_asynclib().run_sync_in_worker_thread(\n",
+      "  File \"c:\\sc\\ai\\rag-demo-1\\.venv\\lib\\site-packages\\anyio\\_backends\\_asyncio.py\", line 877, in run_sync_in_worker_thread\n",
+      "    return await future\n",
+      "  File \"c:\\sc\\ai\\rag-demo-1\\.venv\\lib\\site-packages\\anyio\\_backends\\_asyncio.py\", line 807, in run\n",
+      "    result = context.run(func, *args)\n",
+      "  File \"c:\\sc\\ai\\rag-demo-1\\.venv\\lib\\site-packages\\gradio\\utils.py\", line 493, in run_sync_iterator_async\n",
+      "    return next(iterator)\n",
+      "  File \"C:\\Users\\Garth Raulstone\\AppData\\Local\\Temp\\ipykernel_23576\\3750532605.py\", line 13, in predict\n",
+      "    response = openai.ChatCompletion.create(\n",
+      "  File \"c:\\sc\\ai\\rag-demo-1\\.venv\\lib\\site-packages\\openai\\api_resources\\chat_completion.py\", line 25, in create\n",
+      "    return super().create(*args, **kwargs)\n",
+      "  File \"c:\\sc\\ai\\rag-demo-1\\.venv\\lib\\site-packages\\openai\\api_resources\\abstract\\engine_api_resource.py\", line 155, in create\n",
+      "    response, _, api_key = requestor.request(\n",
+      "  File \"c:\\sc\\ai\\rag-demo-1\\.venv\\lib\\site-packages\\openai\\api_requestor.py\", line 289, in request\n",
+      "    result = self.request_raw(\n",
+      "  File \"c:\\sc\\ai\\rag-demo-1\\.venv\\lib\\site-packages\\openai\\api_requestor.py\", line 591, in request_raw\n",
+      "    abs_url, headers, data = self._prepare_request_raw(\n",
+      "  File \"c:\\sc\\ai\\rag-demo-1\\.venv\\lib\\site-packages\\openai\\api_requestor.py\", line 563, in _prepare_request_raw\n",
+      "    data = json.dumps(params).encode()\n",
+      "  File \"C:\\Users\\Garth Raulstone\\AppData\\Local\\Programs\\Python\\Python310\\lib\\json\\__init__.py\", line 231, in dumps\n",
+      "    return _default_encoder.encode(obj)\n",
+      "  File \"C:\\Users\\Garth Raulstone\\AppData\\Local\\Programs\\Python\\Python310\\lib\\json\\encoder.py\", line 199, in encode\n",
+      "    chunks = self.iterencode(o, _one_shot=True)\n",
+      "  File \"C:\\Users\\Garth Raulstone\\AppData\\Local\\Programs\\Python\\Python310\\lib\\json\\encoder.py\", line 257, in iterencode\n",
+      "    return _iterencode(o, 0)\n",
+      "  File \"C:\\Users\\Garth Raulstone\\AppData\\Local\\Programs\\Python\\Python310\\lib\\json\\encoder.py\", line 179, in default\n",
+      "    raise TypeError(f'Object of type {o.__class__.__name__} '\n",
+      "TypeError: Object of type Pinecone is not JSON serializable\n"
+     ]
+    }
+   ],
+   "source": [
+    "import openai\n",
+    "import gradio as gr\n",
+    "\n",
+    "openai.api_key = os.environ['OPENAI_API_KEY']\n",
+    "\n",
+    "def predict(message, history):\n",
+    "    history_openai_format = []\n",
+    "    for human, assistant in history:\n",
+    "        history_openai_format.append({\"role\": \"user\", \"content\": human })\n",
+    "        history_openai_format.append({\"role\": \"assistant\", \"content\":assistant})\n",
+    "    history_openai_format.append({\"role\": \"user\", \"content\": message})\n",
+    "\n",
+    "    response = openai.ChatCompletion.create(\n",
+    "        model='gpt-3.5-turbo',\n",
+    "        messages= history_openai_format,\n",
+    "        temperature=1.0,\n",
+    "        stream=True,\n",
+    "        vector_store=vector_store\n",
+    "    )\n",
+    "\n",
+    "    partial_message = \"\"\n",
+    "    for chunk in response:\n",
+    "        if len(chunk['choices'][0]['delta']) != 0:\n",
+    "            partial_message = partial_message + chunk['choices'][0]['delta']['content']\n",
+    "            yield partial_message\n",
+    "\n",
+    "gr.ChatInterface(predict).queue().launch()"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": 3,
@@ -241,6 +370,11 @@
     "\n",
     "iface.launch()"
    ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": []
   }
  ],
  "metadata": {