add documentation on how to load different chain types (#595)

docs/modules/chains/combine_docs_examples/vector_db_qa.ipynb

@@ -46,7 +46,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "qa = VectorDBQA.from_llm(llm=OpenAI(), vectorstore=docsearch)"
+    "qa = VectorDBQA.from_chain_type(llm=OpenAI(), chain_type=\"stuff\", vectorstore=docsearch)"
    ]
   },
   {
@@ -58,7 +58,7 @@
     {
      "data": {
       "text/plain": [
-       "' The president said that Ketanji Brown Jackson is one of the nation’s top legal minds and that she will continue Justice Breyer’s legacy of excellence.'"
+       "\" The president said that Ketanji Brown Jackson is one of the nation's top legal minds, a former top litigator in private practice, a former federal public defender, from a family of public school educators and police officers, a consensus builder, and has received a broad range of support from the Fraternal Order of Police to former judges appointed by Democrats and Republicans.\""
       ]
      },
      "execution_count": 4,
@@ -71,6 +71,91 @@
     "qa.run(query)"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "c28f1f64",
+   "metadata": {},
+   "source": [
+    "## Chain Type\n",
+    "You can easily specify different chain types to load and use in the VectorDBQA chain. For a more detailed walkthrough of these types, please see [this notebook](question_answering.ipynb).\n",
+    "\n",
+    "There are two ways to load different chain types. First, you can specify the chain type argument in the `from_chain_type` method. This allows you to pass in the name of the chain type you want to use. For example, in the below we change the chain type to `map_reduce`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "22d2417d",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "qa = VectorDBQA.from_chain_type(llm=OpenAI(), chain_type=\"map_reduce\", vectorstore=docsearch)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "43204ad1",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "\" The president said that Ketanji Brown Jackson is one of the nation's top legal minds, a former top litigator in private practice, a former federal public defender, from a family of public school educators and police officers, a consensus builder, and has received a broad range of support from the Fraternal Order of Police to former judges appointed by Democrats and Republicans.\""
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "query = \"What did the president say about Ketanji Brown Jackson\"\n",
+    "qa.run(query)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "60368f38",
+   "metadata": {},
+   "source": [
+    "The above way allows you to really simply change the chain_type, but it does provide a ton of flexibility over parameters to that chain type. If you want to control those parameters, you can load the chain directly (as you did in [this notebook](question_answering.ipynb)) and then pass that directly to the the VectorDBQA chain with the `combine_documents_chain` parameter. For example:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "id": "7b403f0d",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from langchain.chains.question_answering import load_qa_chain\n",
+    "qa_chain = load_qa_chain(OpenAI(temperature=0), chain_type=\"stuff\")\n",
+    "qa = VectorDBQA(combine_documents_chain=qa_chain, vectorstore=docsearch)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "id": "9e04a9ac",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "\" The president said that Ketanji Brown Jackson is one of the nation's top legal minds, a former top litigator in private practice, a former federal public defender, and from a family of public school educators and police officers. He also said that she is a consensus builder and has received a broad range of support from the Fraternal Order of Police to former judges appointed by Democrats and Republicans.\""
+      ]
+     },
+     "execution_count": 19,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "query = \"What did the president say about Ketanji Brown Jackson\"\n",
+    "qa.run(query)"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "0b8c37f7",
@@ -87,7 +172,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "qa = VectorDBQA.from_llm(llm=OpenAI(), vectorstore=docsearch, return_source_documents=True)"
+    "qa = VectorDBQA.from_chain_type(llm=OpenAI(), chain_type=\"stuff\", return_source_documents=True)"
    ]
   },
   {

docs/modules/chains/combine_docs_examples/vector_db_qa_with_sources.ipynb

@@ -26,7 +26,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 2,
    "id": "17d1306e",
    "metadata": {},
    "outputs": [],
@@ -41,7 +41,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 3,
    "id": "0e745d99",
    "metadata": {},
    "outputs": [],
@@ -51,7 +51,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 4,
    "id": "f42d79dc",
    "metadata": {},
    "outputs": [],
@@ -63,7 +63,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 5,
    "id": "8aa571ae",
    "metadata": {},
    "outputs": [],
@@ -73,26 +73,69 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 6,
    "id": "aa859d4c",
    "metadata": {},
    "outputs": [],
    "source": [
     "from langchain import OpenAI\n",
     "\n",
-    "chain = VectorDBQAWithSourcesChain.from_llm(OpenAI(temperature=0), vectorstore=docsearch)"
+    "chain = VectorDBQAWithSourcesChain.from_chain_type(OpenAI(temperature=0), chain_type=\"stuff\", vectorstore=docsearch)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 7,
    "id": "8ba36fa7",
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "{'answer': ' The president thanked Justice Breyer for his service.',\n",
+       "{'answer': ' The president thanked Justice Breyer for his service.\\n',\n",
+       " 'sources': '30-pl'}"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "chain({\"question\": \"What did the president say about Justice Breyer\"}, return_only_outputs=True)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "718ecbda",
+   "metadata": {},
+   "source": [
+    "## Chain Type\n",
+    "You can easily specify different chain types to load and use in the VectorDBQAWithSourcesChain chain. For a more detailed walkthrough of these types, please see [this notebook](qa_with_sources.ipynb).\n",
+    "\n",
+    "There are two ways to load different chain types. First, you can specify the chain type argument in the `from_chain_type` method. This allows you to pass in the name of the chain type you want to use. For example, in the below we change the chain type to `map_reduce`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "8b35b30a",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "chain = VectorDBQAWithSourcesChain.from_chain_type(OpenAI(temperature=0), chain_type=\"map_reduce\", vectorstore=docsearch)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "58bd424f",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'answer': ' The president honored Justice Stephen Breyer for his service.\\n',\n",
        " 'sources': '30-pl'}"
       ]
      },
@@ -104,11 +147,53 @@
    "source": [
     "chain({\"question\": \"What did the president say about Justice Breyer\"}, return_only_outputs=True)"
    ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "21e14eed",
+   "metadata": {},
+   "source": [
+    "The above way allows you to really simply change the chain_type, but it does provide a ton of flexibility over parameters to that chain type. If you want to control those parameters, you can load the chain directly (as you did in [this notebook](qa_with_sources.ipynb)) and then pass that directly to the the VectorDBQA chain with the `combine_documents_chain` parameter. For example:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "af35f0c6",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from langchain.chains.qa_with_sources import load_qa_with_sources_chain\n",
+    "qa_chain = load_qa_with_sources_chain(OpenAI(temperature=0), chain_type=\"stuff\")\n",
+    "qa = VectorDBQAWithSourcesChain(combine_document_chain=qa_chain, vectorstore=docsearch)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "c91fdc8a",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'answer': ' The president honored Justice Stephen Breyer for his service.\\n',\n",
+       " 'sources': '30-pl'}"
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "chain({\"question\": \"What did the president say about Justice Breyer\"}, return_only_outputs=True)"
+   ]
   }
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3.9.0 64-bit ('llm-env')",
+   "display_name": "Python 3 (ipykernel)",
    "language": "python",
    "name": "python3"
   },
@@ -122,7 +207,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.0"
+   "version": "3.10.9"
   },
   "vscode": {
    "interpreter": {