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     "output_type": "stream",
     "text": [
      "Answer: How can I assist you today?\n"
     ]
    }
   ],
   "source": [
    "# from langchain.llms import openai\n",
    "import openai\n",
    "from dotenv import load_dotenv\n",
    "import os\n",
    "load_dotenv()\n",
    "\n",
    "import streamlit as st\n",
    "\n",
    "openai.api_key = os.environ[\"OPEN_API_KEY\"]\n",
    "\n",
    "# def get_openai_response(question):\n",
    "#     llm = openai()\n",
    "\n",
    "# Function to ask a question using the ChatGPT model\n",
    "def ask_question(question):\n",
    "    try:\n",
    "        response = openai.ChatCompletion.create(\n",
    "            model=\"ft:gpt-3.5-turbo-0125:shubham-gupta::AqKlxnFo\",  # Replace with your fine-tuned chat model if applicable\n",
    "            messages=[\n",
    "                {\"role\": \"system\", \"content\": \"You are a helpful assistant.\"},\n",
    "                {\"role\": \"user\", \"content\": question}],\n",
    "            max_tokens=100,\n",
    "            temperature=0.5\n",
    "        )\n",
    "        # Extract assistant's response and add to chat history\n",
    "        assistant_message = response[\"choices\"][0][\"message\"][\"content\"]\n",
    "        return assistant_message\n",
    "    except openai.OpenAIError as e:  # Handle API-related errors\n",
    "        return f\"An OpenAI API error occurred: {e}\"\n",
    "    except Exception as e:  # Handle other unexpected errors\n",
    "        return f\"An unexpected error occurred: {e}\"\n",
    "\n",
    "# Example usage\n",
    "if __name__ == \"__main__\":\n",
    "    user_question = input(\"Ask a question: \")\n",
    "    answer = ask_question(user_question)\n",
    "    print(f\"Answer: {answer}\")\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 3\n",
    "\n",
    "# Instead of downgrading pydantic, consider upgrading langchain or llama-index. For example, the error in the title doesn't occur with pydantic==2.8.2 and llama_index.core==0.10.67. Similar errors involving langchain also doesn't occur for newer versions of langchain, e.g. langchain>=0.3.0 and langchain-core>=0.3.0.1\n",
    "\n",
    "# So pip install langchain langchain-core -U should really solve the issue."
   ]
  }
 ],
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