docs: remove warnings/update diagrams (#1746)

* remove warnings/udpate diagrams

* replace get_relevant_documents with invoke

docs/docs/tutorials/rag/langgraph_adaptive_rag_local.ipynb

@@ -110,7 +110,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 4,
    "id": "af8379bd-7eae-4ba6-b632-12e89eab9920",
    "metadata": {},
    "outputs": [],
@@ -129,19 +129,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 2,
    "id": "f9ff6b99-080d-4827-b2cb-f775543d76f5",
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "Downloading: 100%|██████████| 274M/274M [00:43<00:00, 6.38MiB/s] \n",
-      "Verifying: 100%|██████████| 274M/274M [00:00<00:00, 618MiB/s] \n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "from langchain.text_splitter import RecursiveCharacterTextSplitter\n",
     "from langchain_community.document_loaders import WebBaseLoader\n",
@@ -183,18 +174,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 5,
    "id": "7045e064-e666-4aea-9111-6e9d2007f27e",
    "metadata": {},
    "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/var/folders/td/vzm913rx77x21csd90g63_7c0000gn/T/ipykernel_7200/1754575056.py:22: LangChainDeprecationWarning: The method `BaseRetriever.get_relevant_documents` was deprecated in langchain-core 0.1.46 and will be removed in 1.0. Use invoke instead.\n",
-      "  docs = retriever.get_relevant_documents(question)\n"
-     ]
-    },
     {
      "name": "stdout",
      "output_type": "stream",
@@ -225,14 +208,14 @@
     "\n",
     "question_router = prompt | llm | JsonOutputParser()\n",
     "question = \"llm agent memory\"\n",
-    "docs = retriever.get_relevant_documents(question)\n",
+    "docs = retriever.invoke(question)\n",
     "doc_txt = docs[1].page_content\n",
     "print(question_router.invoke({\"question\": question}))"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 7,
    "id": "813cdcef-8b75-4214-a2ed-b89077b3d287",
    "metadata": {},
    "outputs": [
@@ -267,25 +250,17 @@
     "\n",
     "retrieval_grader = prompt | llm | JsonOutputParser()\n",
     "question = \"agent memory\"\n",
-    "docs = retriever.get_relevant_documents(question)\n",
+    "docs = retriever.invoke(question)\n",
     "doc_txt = docs[1].page_content\n",
     "print(retrieval_grader.invoke({\"question\": question, \"document\": doc_txt}))"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 9,
    "id": "aeb8b373-0289-4dec-bd4b-8b2701200301",
    "metadata": {},
    "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/Users/isaachershenson/.pyenv/versions/3.11.9/lib/python3.11/site-packages/langsmith/client.py:5301: LangChainBetaWarning: The function `loads` is in beta. It is actively being worked on, so the API may change.\n",
-      "  prompt = loads(json.dumps(prompt_object.manifest))\n"
-     ]
-    },
     {
      "name": "stdout",
      "output_type": "stream",
@@ -526,7 +501,7 @@
     "    question = state[\"question\"]\n",
     "\n",
     "    # Retrieval\n",
-    "    documents = retriever.get_relevant_documents(question)\n",
+    "    documents = retriever.invoke(question)\n",
     "    return {\"documents\": documents, \"question\": question}\n",
     "\n",
     "\n",

docs/docs/tutorials/rag/langgraph_crag.ipynb

@@ -360,7 +360,7 @@
     "    question = state[\"question\"]\n",
     "\n",
     "    # Retrieval\n",
-    "    documents = retriever.get_relevant_documents(question)\n",
+    "    documents = retriever.invoke(question)\n",
     "    return {\"documents\": documents, \"question\": question}\n",
     "\n",
     "\n",

docs/docs/tutorials/rag/langgraph_self_rag.ipynb

@@ -445,7 +445,7 @@
     "    question = state[\"question\"]\n",
     "\n",
     "    # Retrieval\n",
-    "    documents = retriever.get_relevant_documents(question)\n",
+    "    documents = retriever.invoke(question)\n",
     "    return {\"documents\": documents, \"question\": question}\n",
     "\n",
     "\n",

docs/docs/tutorials/rag/langgraph_self_rag_local.ipynb

@@ -446,7 +446,7 @@
     "    question = state[\"question\"]\n",
     "\n",
     "    # Retrieval\n",
-    "    documents = retriever.get_relevant_documents(question)\n",
+    "    documents = retriever.invoke(question)\n",
     "    return {\"documents\": documents, \"question\": question}\n",
     "\n",
     "\n",