comet-ml--opik/apps/opik-documentation/documentation/docs/cookbook/dspy.ipynb

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    "# Using Opik with DSPy\n",
    "\n",
    "[DSPy](https://dspy.ai/) is the framework for programming—rather than prompting—language models.\n",
    "\n",
    "In this guide, we will showcase how to integrate Opik with DSPy so that all the DSPy calls are logged as traces in Opik."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Creating an account on Comet.com\n",
    "\n",
    "[Comet](https://www.comet.com/site?from=llm&utm_source=opik&utm_medium=colab&utm_content=dspy&utm_campaign=opik) provides a hosted version of the Opik platform, [simply create an account](https://www.comet.com/signup?from=llm&utm_source=opik&utm_medium=colab&utm_content=dspy&utm_campaign=opik) and grab your API Key.\n",
    "\n",
    "> You can also run the Opik platform locally, see the [installation guide](https://www.comet.com/docs/opik/self-host/overview/?from=llm&utm_source=opik&utm_medium=colab&utm_content=dspy&utm_campaign=opik) for more information."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "%pip install --upgrade opik dspy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import opik\n",
    "\n",
    "opik.configure(use_local=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "import getpass\n",
    "\n",
    "if \"OPENAI_API_KEY\" not in os.environ:\n",
    "    os.environ[\"OPENAI_API_KEY\"] = getpass.getpass(\"Enter your OpenAI API key: \")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Logging traces\n",
    "\n",
    "In order to log traces to Opik, you will need to set the `opik` callback:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import dspy\n",
    "from opik.integrations.dspy.callback import OpikCallback\n",
    "\n",
    "lm = dspy.LM(\"openai/gpt-4o-mini\")\n",
    "\n",
    "project_name = \"DSPY\"\n",
    "opik_callback = OpikCallback(project_name=project_name, log_graph=True)\n",
    "\n",
    "dspy.configure(lm=lm, callbacks=[opik_callback])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "cot = dspy.ChainOfThought(\"question -> answer\")\n",
    "cot(question=\"What is the meaning of life?\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The trace is now logged to the Opik platform:\n",
    "\n",
    "![DSPy trace](https://raw.githubusercontent.com/comet-ml/opik/main/apps/opik-documentation/documentation/fern/img/cookbook/dspy_trace_cookbook.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "If you set `log_graph` to `True` in the `OpikCallback`, then each module graph is also displayed in the \"Agent graph\" tab:\n",
    "\n",
    "![DSPy trace with graph](https://raw.githubusercontent.com/comet-ml/opik/main/apps/opik-documentation/documentation/fern/img/cookbook/dspy_trace_cookbook_with_agent_graph.png)"
   ]
  }
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