ibm watsonxai code

3p-integrations/ibm/Get Started with watsonx.ai & Llama.ipynb

@@ -65,14 +65,6 @@
    ]
   },
   {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "d5d854f2-a6f9-4107-a687-492d6eba2003",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
    "cell_type": "markdown",
    "id": "8f8d6bb9-96cb-44ea-b39c-1c957c7b1963",
    "metadata": {},
@@ -131,7 +123,7 @@
     "    project_id = os.getenv(\"PROJECT_ID\")\n",
     "except KeyError:\n",
     "    project_id = input(\"Please enter your project_id (hit enter): \")\n",
-    "    \n",
+    "\n",
     "print(\"Credentials configured successfully!\")"
    ]
   },
@@ -331,7 +323,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": null,
    "id": "199d4189-dc80-49db-a901-ebe7e82437de",
    "metadata": {},
    "outputs": [],
@@ -339,8 +331,8 @@
     "from ibm_watsonx_ai.foundation_models import ModelInference\n",
     "\n",
     "model = ModelInference(\n",
-    "    model_id=model_id, \n",
-    "    params=params, \n",
+    "    model_id=model_id,\n",
+    "    params=params,\n",
     "    credentials=credentials,\n",
     "    project_id=project_id)"
    ]
@@ -511,14 +503,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": null,
    "id": "1c6f1a12-6943-428d-833a-46aaac498cb3",
    "metadata": {},
    "outputs": [],
    "source": [
     "def email_assistant(context, tone=\"professional\"):\n",
     "    \"\"\"Generate email responses based on context and tone\"\"\"\n",
-    "    \n",
+    "\n",
     "    messages = [\n",
     "    {\"role\": \"system\", \"content\": \"You are a helpful assistant.\"},\n",
     "    {\"role\": \"user\", \"content\": f\"\"\"\n",
@@ -526,7 +518,7 @@
     "    Context: {context}\n",
     "    Email Response:\"\"\"}\n",
     "     ]\n",
-    "    \n",
+    "\n",
     "    params = TextChatParameters(\n",
     "        temperature=0.5,\n",
     "        max_tokens=250\n",
@@ -538,10 +530,10 @@
     "        credentials=credentials,\n",
     "        project_id=project_id\n",
     "    )\n",
-    "    \n",
+    "\n",
     "    response = model.chat(messages=messages)\n",
     "    clean_response = response[\"choices\"][0][\"message\"][\"content\"]\n",
-    "    \n",
+    "\n",
     "    return clean_response\n"
    ]
   },
@@ -588,34 +580,34 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 20,
+   "execution_count": null,
    "id": "856c6538-28fb-41f8-81f9-df0b38e47ce7",
    "metadata": {},
    "outputs": [],
    "source": [
     "def generate_docstring(code):\n",
     "    \"\"\"Generate documentation for code snippets\"\"\"\n",
-    "    \n",
+    "\n",
     "    messages = [\n",
     "    {\"role\": \"system\", \"content\": \"You are a helpful assistant.\"},\n",
     "    {\"role\": \"user\", \"content\": f\"\"\"\n",
     "    Generate a comprehensive docstring for this Python function:\n",
     "    {code}\n",
-    "    \n",
+    "\n",
     "    Include:\n",
     "    - Description\n",
     "    - Parameters\n",
     "    - Returns\n",
     "    - Example usage\n",
-    "    \n",
+    "\n",
     "    Docstring:\"\"\"}\n",
     "    ]\n",
-    "   \n",
+    "\n",
     "    params = TextChatParameters(\n",
     "        temperature=0.5,\n",
     "        max_tokens=1000\n",
     "    )\n",
-    "    \n",
+    "\n",
     "    model = ModelInference(\n",
     "        model_id=model_id,\n",
     "        params=params,\n",
@@ -625,9 +617,8 @@
     "\n",
     "    response = model.chat(messages=messages)\n",
     "    clean_response = response[\"choices\"][0][\"message\"][\"content\"]\n",
-    "    \n",
-    "    return clean_response\n",
-    "\n"
+    "\n",
+    "    return clean_response\n"
    ]
   },
   {