mv popular and additional chains to use cases (#8242)

docs/docs_skeleton/docs/guides/safety/index.mdx

@@ -0,0 +1,6 @@
+# Preventing harmful outputs
+
+One of the key concerns with using LLMs is that they may generate harmful or unethical text. This is an area of active research in the field. Here we present some built-in chains inspired by this research, which are intended to make the outputs of LLMs safer.
+
+- [Moderation chain](/docs/use_cases/safety/moderation): Explicitly check if any output text is harmful and flag it.
+- [Constitutional chain](/docs/use_cases/safety/constitutional_chain): Prompt the model with a set of principles which should guide it's behavior.

docs/docs_skeleton/docs/modules/chains/additional/index.mdx

@@ -1,8 +0,0 @@
----
-sidebar_position: 4
----
-# Additional
-
-import DocCardList from "@theme/DocCardList";
-
-<DocCardList />

docs/docs_skeleton/docs/modules/chains/additional/multi_prompt_router.mdx

@@ -1,7 +0,0 @@
-# Dynamically selecting from multiple prompts
-
-This notebook demonstrates how to use the `RouterChain` paradigm to create a chain that dynamically selects the prompt to use for a given input. Specifically we show how to use the `MultiPromptChain` to create a question-answering chain that selects the prompt which is most relevant for a given question, and then answers the question using that prompt.
-
-import Example from "@snippets/modules/chains/additional/multi_prompt_router.mdx"
-
-<Example/>

docs/docs_skeleton/docs/modules/chains/popular/index.mdx

@@ -1,8 +0,0 @@
----
-sidebar_position: 3
----
-# Popular
-
-import DocCardList from "@theme/DocCardList";
-
-<DocCardList />

docs/docs_skeleton/docs/modules/data_connection/retrievers/integrations/_category_.yml

@@ -1 +0,0 @@
-label: 'Integrations'

docs/docs_skeleton/docs/use_cases/question_answering/how_to/_category_.yml

@@ -0,0 +1 @@
+label: 'How to'

docs/docs_skeleton/docs/use_cases/question_answering/how_to/chat_vector_db.mdx

@@ -2,7 +2,7 @@
 sidebar_position: 2
 ---
 
-# Conversational Retrieval QA
+# Store and reference chat history
 The ConversationalRetrievalQA chain builds on RetrievalQAChain to provide a chat history component.
 
 It first combines the chat history (either explicitly passed in or retrieved from the provided memory) and the question into a standalone question, then looks up relevant documents from the retriever, and finally passes those documents and the question to a question answering chain to return a response.

docs/docs_skeleton/docs/use_cases/question_answering/how_to/multi_retrieval_qa_router.mdx

@@ -1,4 +1,4 @@
-# Dynamically selecting from multiple retrievers
+# Dynamically select from multiple retrievers
 
 This notebook demonstrates how to use the `RouterChain` paradigm to create a chain that dynamically selects which Retrieval system to use. Specifically we show how to use the `MultiRetrievalQAChain` to create a question-answering chain that selects the retrieval QA chain which is most relevant for a given question, and then answers the question using it.
 

docs/docs_skeleton/docs/use_cases/question_answering/how_to/question_answering.mdx

@@ -1,4 +1,4 @@
-# Document QA
+# QA over in-memory documents
 
 Here we walk through how to use LangChain for question answering over a list of documents. Under the hood we'll be using our [Document chains](/docs/modules/chains/document/).
 

docs/docs_skeleton/docs/use_cases/question_answering/how_to/vector_db_qa.mdx

@@ -1,7 +1,7 @@
 ---
 sidebar_position: 1
 ---
-# Retrieval QA
+# QA using a Retriever
 
 This example showcases question answering over an index.
 

docs/docs_skeleton/vercel.json

@@ -1610,59 +1610,59 @@
     },
     {
       "source": "/en/latest/modules/chains/examples/flare.html",
-      "destination": "/docs/modules/chains/additional/flare"
+      "destination": "/docs/use_cases/question_answering/how_to/flare"
     },
     {
       "source": "/en/latest/modules/chains/examples/graph_cypher_qa.html",
-      "destination": "/docs/modules/chains/additional/graph_cypher_qa"
+      "destination": "/docs/use_cases/graph/graph_cypher_qa"
     },
     {
       "source": "/en/latest/modules/chains/examples/graph_nebula_qa.html",
-      "destination": "/docs/modules/chains/additional/graph_nebula_qa"
+      "destination": "/docs/use_cases/graph/graph_nebula_qa"
     },
     {
       "source": "/en/latest/modules/chains/index_examples/graph_qa.html",
-      "destination": "/docs/modules/chains/additional/graph_qa"
+      "destination": "/docs/use_cases/graph/graph_qa"
     },
     {
       "source": "/en/latest/modules/chains/index_examples/hyde.html",
-      "destination": "/docs/modules/chains/additional/hyde"
+      "destination": "/docs/use_cases/question_answering/how_to/hyde"
     },
     {
       "source": "/en/latest/modules/chains/examples/llm_bash.html",
-      "destination": "/docs/modules/chains/additional/llm_bash"
+      "destination": "/docs/use_cases/code_writing/llm_bash"
     },
     {
       "source": "/en/latest/modules/chains/examples/llm_checker.html",
-      "destination": "/docs/modules/chains/additional/llm_checker"
+      "destination": "/docs/use_cases/self_check/llm_checker"
     },
     {
       "source": "/en/latest/modules/chains/examples/llm_math.html",
-      "destination": "/docs/modules/chains/additional/llm_math"
+      "destination": "/docs/use_cases/code_writing/llm_math"
     },
     {
       "source": "/en/latest/modules/chains/examples/llm_requests.html",
-      "destination": "/docs/modules/chains/additional/llm_requests"
+      "destination": "/docs/use_cases/apis/llm_requests"
     },
     {
       "source": "/en/latest/modules/chains/examples/llm_summarization_checker.html",
-      "destination": "/docs/modules/chains/additional/llm_summarization_checker"
+      "destination": "/docs/use_cases/self_check/llm_summarization_checker"
     },
     {
       "source": "/en/latest/modules/chains/examples/openapi.html",
-      "destination": "/docs/modules/chains/additional/openapi"
+      "destination": "/docs/use_cases/apis/openapi"
     },
     {
       "source": "/en/latest/modules/chains/examples/pal.html",
-      "destination": "/docs/modules/chains/additional/pal"
+      "destination": "/docs/use_cases/code_writing/pal"
     },
     {
       "source": "/en/latest/modules/chains/examples/tagging.html",
-      "destination": "/docs/modules/chains/additional/tagging"
+      "destination": "/docs/use_cases/tagging"
     },
     {
       "source": "/en/latest/modules/chains/index_examples/vector_db_text_generation.html",
-      "destination": "/docs/modules/chains/additional/vector_db_text_generation"
+      "destination": "/docs/use_cases/question_answering/how_to/vector_db_text_generation"
     },
     {
       "source": "/en/latest/modules/chains/generic/router.html",
@@ -3771,6 +3771,170 @@
     {
       "source": "/en/latest/:path*",
       "destination": "/docs/:path*"
+    },
+    {
+      "source": "/docs/modules/chains/additional/constitutional_chain",
+      "destination": "/docs/guides/safety/constitutional_chain"
+    },
+    {
+      "source": "/docs/modules/chains/additional/moderation",
+      "destination": "/docs/guides/safety/moderation"
+    },
+    {
+      "source": "/docs/modules/chains/popular/api",
+      "destination": "/docs/use_cases/apis/api"
+    },
+    {
+      "source": "/docs/modules/chains/additional/analyze_document",
+      "destination": "/docs/use_cases/question_answering/how_to/analyze_document"
+    },
+    {
+      "source": "/docs/modules/chains/popular/chat_vector_db",
+      "destination": "/docs/use_cases/question_answering/how_to/chat_vector_db"
+    },
+    {
+      "source": "/docs/modules/chains/additional/multi_retrieval_qa_router",
+      "destination": "/docs/use_cases/question_answering/how_to/multi_retrieval_qa_router"
+    },
+    {
+      "source": "/docs/modules/chains/additional/question_answering",
+      "destination": "/docs/use_cases/question_answering/how_to/question_answering"
+    },
+    {
+      "source": "/docs/modules/chains/popular/vector_db_qa",
+      "destination": "/docs/use_cases/question_answering/how_to/vector_db_qa"
+    },
+    {
+      "source": "/docs/modules/chains/popular/summarize",
+      "destination": "/docs/use_cases/summarization/summarize"
+    },
+    {
+      "source": "/docs/modules/chains/popular/sqlite",
+      "destination": "/docs/use_cases/tabular/sqlite"
+    },
+    {
+      "source": "/docs/modules/chains/popular/openai_functions",
+      "destination": "/docs/modules/chains/how_to/openai_functions"
+    },
+    {
+      "source": "/docs/modules/chains/additional/llm_requests",
+      "destination": "/docs/use_cases/apis/llm_requests"
+    },
+    {
+      "source": "/docs/modules/chains/additional/openai_openapi",
+      "destination": "/docs/use_cases/apis/openai_openapi"
+    },
+    {
+      "source": "/docs/modules/chains/additional/openapi",
+      "destination": "/docs/use_cases/apis/openapi"
+    },
+    {
+      "source": "/docs/modules/chains/additional/openapi_openai",
+      "destination": "/docs/use_cases/apis/openapi_openai"
+    },
+    {
+      "source": "/docs/modules/chains/additional/cpal",
+      "destination": "/docs/use_cases/code_writing/cpal"
+    },
+    {
+      "source": "/docs/modules/chains/additional/llm_bash",
+      "destination": "/docs/use_cases/code_writing/llm_bash"
+    },
+    {
+      "source": "/docs/modules/chains/additional/llm_math",
+      "destination": "/docs/use_cases/code_writing/llm_math"
+    },
+    {
+      "source": "/docs/modules/chains/additional/llm_symbolic_math",
+      "destination": "/docs/use_cases/code_writing/llm_symbolic_math"
+    },
+    {
+      "source": "/docs/modules/chains/additional/pal",
+      "destination": "/docs/use_cases/code_writing/pal"
+    },
+    {
+      "source": "/docs/modules/chains/additional/graph_arangodb_qa",
+      "destination": "/docs/use_cases/graph/graph_arangodb_qa"
+    },
+    {
+      "source": "/docs/modules/chains/additional/graph_cypher_qa",
+      "destination": "/docs/use_cases/graph/graph_cypher_qa"
+    },
+    {
+      "source": "/docs/modules/chains/additional/graph_hugegraph_qa",
+      "destination": "/docs/use_cases/graph/graph_hugegraph_qa"
+    },
+    {
+      "source": "/docs/modules/chains/additional/graph_kuzu_qa",
+      "destination": "/docs/use_cases/graph/graph_kuzu_qa"
+    },
+    {
+      "source": "/docs/modules/chains/additional/graph_nebula_qa",
+      "destination": "/docs/use_cases/graph/graph_nebula_qa"
+    },
+    {
+      "source": "/docs/modules/chains/additional/graph_qa",
+      "destination": "/docs/use_cases/graph/graph_qa"
+    },
+    {
+      "source": "/docs/modules/chains/additional/graph_sparql_qa",
+      "destination": "/docs/use_cases/graph/graph_sparql_qa"
+    },
+    {
+      "source": "/docs/modules/chains/additional/neptune_cypher_qa",
+      "destination": "/docs/use_cases/graph/neptune_cypher_qa"
+    },
+    {
+      "source": "/docs/modules/chains/additional/tot",
+      "destination": "/docs/use_cases/graph/tot"
+    },
+    {
+      "source": "/docs/use_cases/question_answering//document-context-aware-QA",
+      "destination": "/docs/use_cases/question_answering/how_to/document-context-aware-QA"
+    },
+    {
+      "source": "/docs/modules/chains/additional/flare",
+      "destination": "/docs/use_cases/question_answering/how_to/flare"
+    },
+    {
+      "source": "/docs/modules/chains/additional/hyde",
+      "destination": "/docs/use_cases/question_answering/how_to/hyde"
+    },
+    {
+      "source": "/docs/use_cases/question_answering//local_retrieval_qa",
+      "destination": "/docs/use_cases/question_answering/how_to/local_retrieval_qa"
+    },
+    {
+      "source": "/docs/modules/chains/additional/qa_citations",
+      "destination": "/docs/use_cases/question_answering/how_to/qa_citations"
+    },
+    {
+      "source": "/docs/modules/chains/additional/vector_db_text_generation",
+      "destination": "/docs/use_cases/question_answering/how_to/vector_db_text_generation"
+    },
+    {
+      "source": "/docs/modules/chains/additional/openai_functions_retrieval_qa",
+      "destination": "/docs/use_cases/question_answering/integrations/openai_functions_retrieval_qa"
+    },
+    {
+      "source": "/docs/use_cases/question_answering//semantic-search-over-chat",
+      "destination": "/docs/use_cases/question_answering/integrations/semantic-search-over-chat"
+    },
+    {
+      "source": "/docs/modules/chains/additional/llm_checker",
+      "destination": "/docs/use_cases/self_check/llm_checker"
+    },
+    {
+      "source": "/docs/modules/chains/additional/llm_summarization_checker",
+      "destination": "/docs/use_cases/self_check/llm_summarization_checker"
+    },
+    {
+      "source": "/docs/modules/chains/additional/elasticsearch_database",
+      "destination": "/docs/use_cases/tabular/elasticsearch_database"
+    },
+    {
+      "source": "/docs/modules/chains/additional/tagging",
+      "destination": "/docs/use_cases/tagging"
     }
   ]
 }