From 5242a048afa1a83e3fb0495cab0a798ab4c99b91 Mon Sep 17 00:00:00 2001
From: Syeed-MD-Talha <syeedmdtalha@gmail.com>
Date: Tue, 5 Aug 2025 11:14:37 +0600
Subject: [PATCH] docs: Add Groq API integration to models tutorial notebook

- Add Groq section with OpenAI-compatible client setup
- Include basic usage example and AgentChat integration
- Add feature compatibility list and API key setup instructions
- Follow existing documentation patterns for external providers
---
 .../tutorial/models.ipynb                     | 62 ++++++++++++++++++-
 1 file changed, 60 insertions(+), 2 deletions(-)

diff --git a/python/docs/src/user-guide/agentchat-user-guide/tutorial/models.ipynb b/python/docs/src/user-guide/agentchat-user-guide/tutorial/models.ipynb
index 0d1bdf26ba80..a54af20b13d1 100644
--- a/python/docs/src/user-guide/agentchat-user-guide/tutorial/models.ipynb
+++ b/python/docs/src/user-guide/agentchat-user-guide/tutorial/models.ipynb
@@ -576,11 +576,69 @@
    "source": [
     "Read more about the [Semantic Kernel Adapter](../../../reference/python/autogen_ext.models.semantic_kernel.rst)."
    ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Groq (experimental)\n",
+    "\n",
+    "[Groq](https://groq.com/) provides ultra-fast inference for open-source LLMs through their cloud API. Groq offers an [OpenAI-compatible API](https://console.groq.com/docs/quickstart), so you can use the {py:class}`~autogen_ext.models.openai.OpenAIChatCompletionClient` with Groq's endpoints.\n",
+    "\n",
+    "You will need to obtain an [API key](https://console.groq.com/keys) from Groq.\n",
+    "\n",
+    "This endpoint supports the following OpenAI client library features:\n",
+    "* Chat completions\n",
+    "* Model selection\n",
+    "* Temperature/sampling\n",
+    "* Streaming\n",
+    "* JSON mode\n",
+    "* Function calling (tools)\n",
+    "\n",
+    "**Note**: While some model providers may offer OpenAI-compatible APIs, they may still have minor differences. For example, the `finish_reason` field may be different in the response."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "finish_reason='stop' content='The capital of France is Paris.' usage=RequestUsage(prompt_tokens=17, completion_tokens=8) cached=False logprobs=None thought=None\n"
+     ]
+    }
+   ],
+   "source": [
+    "import os\n",
+    "from autogen_core.models import UserMessage\n",
+    "from autogen_ext.models.openai import OpenAIChatCompletionClient\n",
+    "\n",
+    "# Create Groq model client\n",
+    "model_client = OpenAIChatCompletionClient(\n",
+    "    model=\"llama3-8b-8192\",  # or other Groq models like \"mixtral-8x7b-32768\"\n",
+    "    base_url=\"https://api.groq.com/openai/v1\",\n",
+    "    # api_key=\"GROQ_API_KEY\",  \n",
+    "    model_info={\n",
+    "        \"vision\": False,\n",
+    "        \"function_calling\": True,\n",
+    "        \"json_output\": True,\n",
+    "        \"family\": \"unknown\",\n",
+    "        \"structured_output\": True,\n",
+    "    },\n",
+    ")\n",
+    "\n",
+    "response = await model_client.create([UserMessage(content=\"What is the capital of France?\", source=\"user\")])\n",
+    "print(response)\n",
+    "await model_client.close()"
+   ]
   }
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": ".venv",
+   "display_name": "autogen",
    "language": "python",
    "name": "python3"
   },
@@ -594,7 +652,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.9"
+   "version": "3.10.0"
   }
  },
  "nbformat": 4,