Making it possible to use "certainty" as a parameter for the weaviate similarity_search (#1218)

Checking if weaviate similarity_search kwargs contains "certainty" and
use it accordingly. The minimal level of certainty must be a float, and
it is computed by normalized distance.

docs/modules/indexes/chain_examples/chat_vector_db.ipynb

@@ -268,12 +268,48 @@
   },
   {
    "cell_type": "markdown",
-   "id": "7fb44daa",
-   "metadata": {},
+   "source": [
+    "## Chat Vector DB with `search_distance`\n",
+    "If you are using a vector store that supports filtering by search distance, you can add a threshold value parameter."
+   ],
+   "metadata": {
+    "collapsed": false
+   }
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "outputs": [],
+   "source": [
+    "vectordbkwargs = {\"search_distance\": 0.9}"
+   ],
+   "metadata": {
+    "collapsed": false
+   }
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "outputs": [],
+   "source": [
+    "qa = ChatVectorDBChain.from_llm(OpenAI(temperature=0), vectorstore, return_source_documents=True)\n",
+    "chat_history = []\n",
+    "query = \"What did the president say about Ketanji Brown Jackson\"\n",
+    "result = qa({\"question\": query, \"chat_history\": chat_history, \"vectordbkwargs\": vectordbkwargs})"
+   ],
+   "metadata": {
+    "collapsed": false
+   }
+  },
+  {
+   "cell_type": "markdown",
    "source": [
     "## Chat Vector DB with `map_reduce`\n",
     "We can also use different types of combine document chains with the Chat Vector DB chain."
-   ]
+   ],
+   "metadata": {
+    "collapsed": false
+   }
   },
   {
    "cell_type": "code",
@@ -486,7 +522,7 @@
    "source": [
     "chat_history = [(query, result[\"answer\"])]\n",
     "query = \"Did he mention who she suceeded\"\n",
-    "result = qa({\"question\": query, \"chat_history\": chat_history})"
+    "result = qa({\"question\": query, \"chat_history\": chat_history})\n"
    ]
   }
  ],