Add add_example method to all ExampleSelector classes, with tests (#178)

Also updated docs, and noticed an issue with the add_texts method on
VectorStores that I had missed before -- the metadatas arg should be
required to match the classmethod which initializes the VectorStores
(the add_example methods break otherwise in the ExampleSelectors)

docs/examples/prompts/prompt_management.ipynb

@@ -310,7 +310,7 @@
     "    example_prompt=example_prompt, \n",
     "    # This is the maximum length that the formatted examples should be.\n",
     "    # Length is measured by the get_text_length function below.\n",
-    "    max_length=18,\n",
+    "    max_length=25,\n",
     "    # This is the function used to get the length of a string, which is used\n",
     "    # to determine which examples to include. It is commented out because\n",
     "    # it is provided as a default value if none is specified.\n",
@@ -378,17 +378,59 @@
       "Input: happy\n",
       "Output: sad\n",
       "\n",
-      "Input: big and huge and massive and large and gigantic and tall and bigger than everything else\n",
+      "Input: big and huge and massive and large and gigantic and tall and much much much much much bigger than everything else\n",
       "Output:\n"
      ]
     }
    ],
    "source": [
     "# An example with long input, so it selects only one example.\n",
-    "long_string = \"big and huge and massive and large and gigantic and tall and bigger than everything else\"\n",
+    "long_string = \"big and huge and massive and large and gigantic and tall and much much much much much bigger than everything else\"\n",
     "print(dynamic_prompt.format(adjective=long_string))"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "id": "e4bebcd9",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Give the antonym of every input\n",
+      "\n",
+      "Input: happy\n",
+      "Output: sad\n",
+      "\n",
+      "Input: tall\n",
+      "Output: short\n",
+      "\n",
+      "Input: energetic\n",
+      "Output: lethargic\n",
+      "\n",
+      "Input: sunny\n",
+      "Output: gloomy\n",
+      "\n",
+      "Input: windy\n",
+      "Output: calm\n",
+      "\n",
+      "Input: big\n",
+      "Output: small\n",
+      "\n",
+      "Input: enthusiastic\n",
+      "Output:\n"
+     ]
+    }
+   ],
+   "source": [
+    "# You can add an example to an example selector as well.\n",
+    "new_example = {\"input\": \"big\", \"output\": \"small\"}\n",
+    "dynamic_prompt.example_selector.add_example(new_example)\n",
+    "print(dynamic_prompt.format(adjective=\"enthusiastic\"))"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "2d007b0a",
@@ -401,7 +443,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 14,
    "id": "241bfe80",
    "metadata": {},
    "outputs": [],
@@ -413,7 +455,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 15,
    "id": "50d0a701",
    "metadata": {},
    "outputs": [],
@@ -440,7 +482,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 16,
    "id": "4c8fdf45",
    "metadata": {},
    "outputs": [
@@ -465,9 +507,11 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 17,
    "id": "829af21a",
-   "metadata": {},
+   "metadata": {
+    "scrolled": true
+   },
    "outputs": [
     {
      "name": "stdout",
@@ -484,10 +528,36 @@
     }
    ],
    "source": [
-    "# Input is a measurment, so should select the tall/short example\n",
+    "# Input is a measurement, so should select the tall/short example\n",
     "print(similar_prompt.format(adjective=\"fat\"))"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "id": "3c16fe23",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Give the antonym of every input\n",
+      "\n",
+      "Input: enthusiastic\n",
+      "Output: apathetic\n",
+      "\n",
+      "Input: joyful\n",
+      "Output:\n"
+     ]
+    }
+   ],
+   "source": [
+    "# You can add new examples to the SemanticSimilarityExampleSelector as well\n",
+    "similar_prompt.example_selector.add_example({\"input\": \"enthusiastic\", \"output\": \"apathetic\"})\n",
+    "print(similar_prompt.format(adjective=\"joyful\"))"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "dbc32551",
@@ -532,7 +602,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.6"
+   "version": "3.10.4"
   }
  },
  "nbformat": 4,