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    "# Streaming with LLMs\n",
    "\n",
    "LangChain provides streaming support for LLMs. Currently, we only support streaming for the `OpenAI` LLM implementation, but streaming support for other LLM implementations is on the roadmap. To utilize streaming, use a [`CallbackHandler`](https://github.com/hwchase17/langchain/blob/master/langchain/callbacks/base.py) that implements `on_llm_new_token`. In this example, we are using [`StreamingStdOutCallbackHandler`]()."
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     "name": "stdout",
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     "text": [
      "\n",
      "\n",
      "Verse 1\n",
      "I'm sippin' on sparkling water,\n",
      "It's so refreshing and light,\n",
      "It's the perfect way to quench my thirst,\n",
      "On a hot summer night.\n",
      "\n",
      "Chorus\n",
      "Sparkling water, sparkling water,\n",
      "It's the best way to stay hydrated,\n",
      "It's so refreshing and light,\n",
      "It's the perfect way to stay alive.\n",
      "\n",
      "Verse 2\n",
      "I'm sippin' on sparkling water,\n",
      "It's so bubbly and bright,\n",
      "It's the perfect way to cool me down,\n",
      "On a hot summer night.\n",
      "\n",
      "Chorus\n",
      "Sparkling water, sparkling water,\n",
      "It's the best way to stay hydrated,\n",
      "It's so refreshing and light,\n",
      "It's the perfect way to stay alive.\n",
      "\n",
      "Verse 3\n",
      "I'm sippin' on sparkling water,\n",
      "It's so crisp and clean,\n",
      "It's the perfect way to keep me going,\n",
      "On a hot summer day.\n",
      "\n",
      "Chorus\n",
      "Sparkling water, sparkling water,\n",
      "It's the best way to stay hydrated,\n",
      "It's so refreshing and light,\n",
      "It's the perfect way to stay alive."
     ]
    }
   ],
   "source": [
    "from langchain.llms import OpenAI\n",
    "from langchain.callbacks.base import CallbackManager\n",
    "from langchain.callbacks.streaming_stdout import StreamingStdOutCallbackHandler\n",
    "\n",
    "\n",
    "llm = OpenAI(streaming=True, callback_manager=CallbackManager([StreamingStdOutCallbackHandler()]), verbose=True, temperature=0)\n",
    "resp = llm(\"Write me a song about sparkling water.\")"
   ]
  },
  {
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   "id": "61fb6de7-c6c8-48d0-a48e-1204c027a23c",
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   "source": [
    "We still have access to the end `LLMResult` if using `generate`. However, `token_usage` is not currently supported for streaming."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "a35373f1-9ee6-4753-a343-5aee749b8527",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\n",
      "Q: What did the fish say when it hit the wall?\n",
      "A: Dam!"
     ]
    },
    {
     "data": {
      "text/plain": [
       "LLMResult(generations=[[Generation(text='\\n\\nQ: What did the fish say when it hit the wall?\\nA: Dam!', generation_info={'finish_reason': 'stop', 'logprobs': None})]], llm_output={'token_usage': {}})"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "llm.generate([\"Tell me a joke.\"])"
   ]
  }
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