chroma docs (#1012)

docs/use_cases/evaluation/data_augmented_question_answering.ipynb

@@ -21,25 +21,35 @@
    "outputs": [],
    "source": [
     "from langchain.embeddings.openai import OpenAIEmbeddings\n",
-    "from langchain.vectorstores.faiss import FAISS\n",
+    "from langchain.vectorstores import Chroma\n",
     "from langchain.text_splitter import CharacterTextSplitter\n",
     "from langchain import OpenAI, VectorDBQA"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 3,
    "id": "4fdc211d",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Running Chroma using direct local API.\n",
+      "Using DuckDB in-memory for database. Data will be transient.\n"
+     ]
+    }
+   ],
    "source": [
-    "with open('../../modules/state_of_the_union.txt') as f:\n",
-    "    state_of_the_union = f.read()\n",
+    "from langchain.document_loaders import TextLoader\n",
+    "loader = TextLoader('../../modules/state_of_the_union.txt')\n",
+    "documents = loader.load()\n",
     "text_splitter = CharacterTextSplitter(chunk_size=1000, chunk_overlap=0)\n",
-    "texts = text_splitter.split_text(state_of_the_union)\n",
+    "texts = text_splitter.split_documents(documents)\n",
     "\n",
     "embeddings = OpenAIEmbeddings()\n",
-    "docsearch = FAISS.from_texts(texts, embeddings)\n",
+    "docsearch = Chroma.from_documents(texts, embeddings)\n",
     "qa = VectorDBQA.from_llm(llm=OpenAI(), vectorstore=docsearch)"
    ]
   },
@@ -57,7 +67,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 4,
    "id": "3459b001",
    "metadata": {},
    "outputs": [],
@@ -77,7 +87,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 5,
    "id": "b9c3fa75",
    "metadata": {},
    "outputs": [],
@@ -89,7 +99,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 6,
    "id": "c24543a9",
    "metadata": {},
    "outputs": [],
@@ -279,7 +289,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.9"
+   "version": "3.9.1"
   }
  },
  "nbformat": 4,