added kisski endpoint

ScaDS · Oct 11, 2024 · 0e79bdc · 0e79bdc
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diff --git a/docs/15_endpoint_apis/06_kisski_endpoint.ipynb b/docs/15_endpoint_apis/06_kisski_endpoint.ipynb
@@ -0,0 +1,168 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "87404224-b84b-409f-8683-c4a243d29722",
+   "metadata": {},
+   "source": [
+    "# KISSKI / GWDG endpoint\n",
+    "In this notebook we will use the [KISSKI LLM service](https://kisski.gwdg.de/leistungen/2-02-llm-service/) infrastructure. KISSKI is the German AI Service Center for Sensible and Critical Infrastructure. Before you can access it, you need to create an API key by filling out [this form](https://services.kisski.de/services/en/service/?service=2-02-llm-service.json); make sure to check the box \"API access to our chat service\". You will see that also this method uses the OpenAI API and we change the `base_url`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "752e974d-9aaf-44aa-80fb-01a042cf5774",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'1.43.0'"
+      ]
+     },
+     "execution_count": 1,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "import os\n",
+    "import openai\n",
+    "openai.__version__"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "915d61b5-efe2-4efa-88ac-2ae1866d32e7",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "ab55e229-93b9-4e9b-974d-037002690bf0",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "def prompt_kisski(message:str, model=\"meta-llama-3.1-70b-instruct\"):\n",
+    "    \"\"\"A prompt helper function that sends a message to KISSKI Chat AI API\n",
+    "    and returns only the text response.\n",
+    "    \"\"\"\n",
+    "    import os\n",
+    "    \n",
+    "    # convert message in the right format if necessary\n",
+    "    if isinstance(message, str):\n",
+    "        message = [{\"role\": \"user\", \"content\": message}]\n",
+    "    \n",
+    "    # setup connection to the LLM\n",
+    "    client = openai.OpenAI()\n",
+    "    client.base_url = \"https://chat-ai.academiccloud.de/v1\"\n",
+    "    client.api_key = os.environ.get('KISSKI_API_KEY')\n",
+    "    \n",
+    "    response = client.chat.completions.create(\n",
+    "        model=model,\n",
+    "        messages=message\n",
+    "    )\n",
+    "    \n",
+    "    # extract answer\n",
+    "    return response.choices[0].message.content"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "a7654a20-a307-4b26-8d25-bef20b70224e",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "\"How's it going? Is there something I can help you with or would you like to chat?\""
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "prompt_kisski(\"Hi!\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "578e9edd-b58f-4fd0-a56d-1966105221dc",
+   "metadata": {},
+   "source": [
+    "## Exercise\n",
+    "List the models available in the blablador endpoint and try them out by specifying them when calling `prompt_blablador()`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "05171ba7-a775-41c5-954d-7d4fc2b5b625",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "meta-llama-3.1-8b-instruct\n",
+      "meta-llama-3.1-70b-instruct\n",
+      "mistral-large-instruct\n",
+      "llama-3.1-sauerkrautlm-70b-instruct\n",
+      "qwen2.5-72b-instruct\n",
+      "codestral-22b\n",
+      "occiglot-7b-eu5-instruct\n"
+     ]
+    }
+   ],
+   "source": [
+    "client = openai.OpenAI()\n",
+    "client.base_url = \"https://chat-ai.academiccloud.de/v1\"\n",
+    "client.api_key = os.environ.get('KISSKI_API_KEY')\n",
+    "\n",
+    "print(\"\\n\".join([model.id for model in client.models.list().data]))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "7e810ee2-4d22-42f6-add5-532cf95b4b9c",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.9"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/docs/_toc.yml b/docs/_toc.yml
@@ -24,6 +24,7 @@ parts:
       - file: 15_endpoint_apis/01_openai_api.ipynb
       - file: 15_endpoint_apis/02_ollama_endpoint.ipynb
       - file: 15_endpoint_apis/04_scadsai_llm_endpoint.ipynb
+      - file: 15_endpoint_apis/06_kisski_endpoint.ipynb
       - file: 15_endpoint_apis/03_blablador_endpoint.ipynb
       - file: 15_endpoint_apis/05_azure_endpoints.ipynb
       - file: 15_endpoint_apis/10_anthropic_api.ipynb