run-llama--llama_index/docs/examples/embeddings/together.ipynb

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   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a href=\"https://colab.research.google.com/github/run-llama/llama_index/blob/main/docs/examples/embeddings/together.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Together AI Embeddings\n",
    "\n",
    "This notebook shows how to use `Together AI` for embeddings. Together AI provides access to many state-of-the-art embedding models.\n",
    "\n",
    "Visit https://together.ai and sign up to get an API key."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Setup"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "If you're opening this Notebook on colab, you will probably need to install LlamaIndex 🦙."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "%pip install llama-index-embeddings-together"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "!pip install llama-index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# You can set the API key in the embeddings or env\n",
    "# import os\n",
    "# os.environ[\"TOEGETHER_API_KEY\"] = \"your-api-key\"\n",
    "\n",
    "from llama_index.embeddings.together import TogetherEmbedding\n",
    "\n",
    "embed_model = TogetherEmbedding(\n",
    "    model_name=\"togethercomputer/m2-bert-80M-8k-retrieval\", api_key=\"...\"\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Get Embeddings"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "embeddings = embed_model.get_text_embedding(\"hello world\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "768\n"
     ]
    }
   ],
   "source": [
    "print(len(embeddings))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[-0.11657876, -0.012690996, 0.24342081, 0.32781482, 0.022501636]\n"
     ]
    }
   ],
   "source": [
    "print(embeddings[:5])"
   ]
  }
 ],
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