Fix wrong class instantiation in docs MMR example (#5501)

# Fix wrong class instantiation in docs MMR example

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When looking at the Maximal Marginal Relevance ExampleSelector example
at
https://python.langchain.com/en/latest/modules/prompts/example_selectors/examples/mmr.html,
I noticed that there seems to be an error. Initially, the
`MaxMarginalRelevanceExampleSelector` class is used as an
`example_selector` argument to the `FewShotPromptTemplate` class. Then,
according to the text, a comparison is made to regular similarity
search. However, the `FewShotPromptTemplate` still uses the
`MaxMarginalRelevanceExampleSelector` class, so the output is the same.

To fix it, I added an instantiation of the
`SemanticSimilarityExampleSelector` class, because this seems to be what
is intended.


## Who can review?

@hwchase17

docs/modules/prompts/example_selectors/examples/mmr.ipynb

@@ -12,12 +12,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 1,
    "id": "ac95c968",
    "metadata": {},
    "outputs": [],
    "source": [
-    "from langchain.prompts.example_selector import MaxMarginalRelevanceExampleSelector\n",
+    "from langchain.prompts.example_selector import MaxMarginalRelevanceExampleSelector, SemanticSimilarityExampleSelector\n",
     "from langchain.vectorstores import FAISS\n",
     "from langchain.embeddings import OpenAIEmbeddings\n",
     "from langchain.prompts import FewShotPromptTemplate, PromptTemplate\n",
@@ -39,7 +39,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 2,
    "id": "db579bea",
    "metadata": {},
    "outputs": [],
@@ -66,7 +66,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 3,
    "id": "cd76e344",
    "metadata": {},
    "outputs": [
@@ -94,7 +94,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 4,
    "id": "cf82956b",
    "metadata": {},
    "outputs": [
@@ -107,8 +107,8 @@
       "Input: happy\n",
       "Output: sad\n",
       "\n",
-      "Input: windy\n",
-      "Output: calm\n",
+      "Input: sunny\n",
+      "Output: gloomy\n",
       "\n",
       "Input: worried\n",
       "Output:\n"
@@ -116,7 +116,18 @@
     }
    ],
    "source": [
-    "# Let's compare this to what we would just get if we went solely off of similarity\n",
+    "# Let's compare this to what we would just get if we went solely off of similarity,\n",
+    "# by using SemanticSimilarityExampleSelector instead of MaxMarginalRelevanceExampleSelector.\n",
+    "example_selector = SemanticSimilarityExampleSelector.from_examples(\n",
+    "    # This is the list of examples available to select from.\n",
+    "    examples, \n",
+    "    # This is the embedding class used to produce embeddings which are used to measure semantic similarity.\n",
+    "    OpenAIEmbeddings(), \n",
+    "    # This is the VectorStore class that is used to store the embeddings and do a similarity search over.\n",
+    "    FAISS, \n",
+    "    # This is the number of examples to produce.\n",
+    "    k=2\n",
+    ")\n",
     "similar_prompt = FewShotPromptTemplate(\n",
     "    # We provide an ExampleSelector instead of examples.\n",
     "    example_selector=example_selector,\n",
@@ -125,7 +136,6 @@
     "    suffix=\"Input: {adjective}\\nOutput:\", \n",
     "    input_variables=[\"adjective\"],\n",
     ")\n",
-    "similar_prompt.example_selector.k = 2\n",
     "print(similar_prompt.format(adjective=\"worried\"))"
    ]
   },
@@ -154,7 +164,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.1"
+   "version": "3.9.16"
   }
  },
  "nbformat": 4,