wip: debug and fix thanks to @JasonWeill in jupyterlab/jupyter-ai#746

notebooks/getting-started.ipynb

@@ -65,7 +65,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 3,
    "id": "42d67f40-462b-43ba-a63f-fdd9e126a423",
    "metadata": {},
    "outputs": [],
@@ -78,51 +78,149 @@
    "id": "b93d0cb3-9844-4b3d-8778-360ec07b20ac",
    "metadata": {},
    "source": [
-    "# 3. Recreate example from Readme\n",
-    "\n",
-    "https://github.com/jupyterlab/jupyter-ai shows this example: https://github.com/jupyterlab/jupyter-ai/blob/main/docs/source/_static/sample-html-math.png"
+    "# 3. Test the models"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
-   "id": "9ae14480-b195-4686-9c80-70654bccfd24",
+   "execution_count": 8,
+   "id": "af16e864-8beb-4ea2-93d0-c74b6b595f85",
    "metadata": {},
    "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/Users/me/jaanli/language-model-notebooks/.venv/lib/python3.12/site-packages/langchain_anthropic/llms.py:164: UserWarning: This Anthropic LLM is deprecated. Please use `from langchain_anthropic import ChatAnthropic` instead\n",
-      "  warnings.warn(\n"
-     ]
-    },
     {
      "data": {
       "text/html": [
-       "<svg xmlns=\"http://www.w3.org/2000/svg\" width=\"100\" height=\"100\"> \n",
-       "  <rect x=\"0\" y=\"0\" width=\"100\" height=\"100\" style=\"stroke:black;fill:white;\"/> \n",
-       "</svg>"
+       "AI generated code inserted below &#11015;&#65039;"
       ],
       "text/plain": [
        "<IPython.core.display.HTML object>"
       ]
      },
-     "execution_count": 7,
+     "execution_count": 8,
      "metadata": {
       "text/html": {
        "jupyter_ai": {
-        "model_id": "claude-v1.2",
-        "provider_id": "anthropic"
+        "model_id": "claude-3-opus-20240229",
+        "provider_id": "anthropic-chat"
        }
       }
      },
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "%%ai anthropic:claude-v1.2 -f html\n",
-    "Create a square using SVG with a black border and white fill."
+    "%%ai anthropic-chat:claude-3-opus-20240229 --format code \n",
+    "Create and visualize an interactive plot of the world's population using python and the altair library."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "a5320525-d508-4de0-abce-e4c776db0d54",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "\n",
+       "<style>\n",
+       "  #altair-viz-3c2dc2fe93674313bc7b8a770e6ca792.vega-embed {\n",
+       "    width: 100%;\n",
+       "    display: flex;\n",
+       "  }\n",
+       "\n",
+       "  #altair-viz-3c2dc2fe93674313bc7b8a770e6ca792.vega-embed details,\n",
+       "  #altair-viz-3c2dc2fe93674313bc7b8a770e6ca792.vega-embed details summary {\n",
+       "    position: relative;\n",
+       "  }\n",
+       "</style>\n",
+       "<div id=\"altair-viz-3c2dc2fe93674313bc7b8a770e6ca792\"></div>\n",
+       "<script type=\"text/javascript\">\n",
+       "  var VEGA_DEBUG = (typeof VEGA_DEBUG == \"undefined\") ? {} : VEGA_DEBUG;\n",
+       "  (function(spec, embedOpt){\n",
+       "    let outputDiv = document.currentScript.previousElementSibling;\n",
+       "    if (outputDiv.id !== \"altair-viz-3c2dc2fe93674313bc7b8a770e6ca792\") {\n",
+       "      outputDiv = document.getElementById(\"altair-viz-3c2dc2fe93674313bc7b8a770e6ca792\");\n",
+       "    }\n",
+       "    const paths = {\n",
+       "      \"vega\": \"https://cdn.jsdelivr.net/npm/vega@5?noext\",\n",
+       "      \"vega-lib\": \"https://cdn.jsdelivr.net/npm/vega-lib?noext\",\n",
+       "      \"vega-lite\": \"https://cdn.jsdelivr.net/npm/[email protected]?noext\",\n",
+       "      \"vega-embed\": \"https://cdn.jsdelivr.net/npm/vega-embed@6?noext\",\n",
+       "    };\n",
+       "\n",
+       "    function maybeLoadScript(lib, version) {\n",
+       "      var key = `${lib.replace(\"-\", \"\")}_version`;\n",
+       "      return (VEGA_DEBUG[key] == version) ?\n",
+       "        Promise.resolve(paths[lib]) :\n",
+       "        new Promise(function(resolve, reject) {\n",
+       "          var s = document.createElement('script');\n",
+       "          document.getElementsByTagName(\"head\")[0].appendChild(s);\n",
+       "          s.async = true;\n",
+       "          s.onload = () => {\n",
+       "            VEGA_DEBUG[key] = version;\n",
+       "            return resolve(paths[lib]);\n",
+       "          };\n",
+       "          s.onerror = () => reject(`Error loading script: ${paths[lib]}`);\n",
+       "          s.src = paths[lib];\n",
+       "        });\n",
+       "    }\n",
+       "\n",
+       "    function showError(err) {\n",
+       "      outputDiv.innerHTML = `<div class=\"error\" style=\"color:red;\">${err}</div>`;\n",
+       "      throw err;\n",
+       "    }\n",
+       "\n",
+       "    function displayChart(vegaEmbed) {\n",
+       "      vegaEmbed(outputDiv, spec, embedOpt)\n",
+       "        .catch(err => showError(`Javascript Error: ${err.message}<br>This usually means there's a typo in your chart specification. See the javascript console for the full traceback.`));\n",
+       "    }\n",
+       "\n",
+       "    if(typeof define === \"function\" && define.amd) {\n",
+       "      requirejs.config({paths});\n",
+       "      require([\"vega-embed\"], displayChart, err => showError(`Error loading script: ${err.message}`));\n",
+       "    } else {\n",
+       "      maybeLoadScript(\"vega\", \"5\")\n",
+       "        .then(() => maybeLoadScript(\"vega-lite\", \"5.17.0\"))\n",
+       "        .then(() => maybeLoadScript(\"vega-embed\", \"6\"))\n",
+       "        .catch(showError)\n",
+       "        .then(() => displayChart(vegaEmbed));\n",
+       "    }\n",
+       "  })({\"config\": {\"view\": {\"continuousWidth\": 300, \"continuousHeight\": 300}}, \"data\": {\"url\": \"https://cdn.jsdelivr.net/npm/[email protected]/data/population.json\"}, \"mark\": {\"type\": \"line\"}, \"encoding\": {\"color\": {\"field\": \"age\", \"type\": \"nominal\"}, \"tooltip\": [{\"field\": \"year\", \"type\": \"ordinal\"}, {\"aggregate\": \"sum\", \"field\": \"people\", \"type\": \"quantitative\"}, {\"field\": \"age\", \"type\": \"nominal\"}], \"x\": {\"field\": \"year\", \"type\": \"ordinal\"}, \"y\": {\"aggregate\": \"sum\", \"field\": \"people\", \"type\": \"quantitative\"}}, \"height\": 400, \"params\": [{\"name\": \"param_2\", \"select\": {\"type\": \"interval\", \"encodings\": [\"x\", \"y\"]}, \"bind\": \"scales\"}], \"title\": \"World Population by Age Group\", \"transform\": [{\"filter\": \"(datum.year >= 1850)\"}], \"width\": 600, \"$schema\": \"https://vega.github.io/schema/vega-lite/v5.17.0.json\"}, {\"mode\": \"vega-lite\"});\n",
+       "</script>"
+      ],
+      "text/plain": [
+       "alt.Chart(...)"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "import altair as alt\n",
+    "from vega_datasets import data\n",
+    "\n",
+    "# Load the population data\n",
+    "pop_data = data.population.url\n",
+    "\n",
+    "# Create the interactive plot\n",
+    "plot = alt.Chart(pop_data).mark_line().encode(\n",
+    "    x='year:O',\n",
+    "    y='sum(people):Q',\n",
+    "    color='age:N',\n",
+    "    tooltip=['year:O', 'sum(people):Q', 'age:N']\n",
+    ").properties(\n",
+    "    width=600,\n",
+    "    height=400,\n",
+    "    title='World Population by Age Group'\n",
+    ").transform_filter(\n",
+    "    alt.datum.year >= 1850\n",
+    ").interactive()\n",
+    "\n",
+    "# Display the plot\n",
+    "plot"
    ]
   }
  ],

requirements.in

@@ -1,4 +1,10 @@
 jupyter-ai
 jupyterlab
 python-dotenv
-langchain-anthropic
+langchain-anthropic
+pandas
+ipywidgets
+numpy
+matplotlib
+altair
+vega_datasets