Update: addressing comments + fixing hugging face import

3p-integrations/langchain/langgraph_rag_agent_local.ipynb

@@ -15,7 +15,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "! pip install -U langchain-ollama langchain_community tiktoken langchainhub chromadb langchain langgraph tavily-python sentence-transformers"
+    "! pip install -U langchain-huggingface langchain_community langchain-ollama tiktoken langchainhub chromadb langchain langgraph tavily-python"
    ]
   },
   {
@@ -99,7 +99,8 @@
     "os.environ['LANGCHAIN_ENDPOINT'] = 'https://api.smith.langchain.com'\n",
     "os.environ['LANGCHAIN_API_KEY'] = 'LANGCHAIN_API_KEY'\n",
     "\n",
-    "os.environ['TAVILY_API_KEY'] = 'TAVILY_API_KEY'"
+    "os.environ['TAVILY_API_KEY'] = 'TAVILY_API_KEY'\n",
+    "os.environ[\"USER_AGENT\"] = \"USER_AGENT_KEY\""
    ]
   },
   {
@@ -126,7 +127,7 @@
     "from langchain.text_splitter import RecursiveCharacterTextSplitter\n",
     "from langchain_community.document_loaders import WebBaseLoader\n",
     "from langchain_community.vectorstores import Chroma\n",
-    "from langchain_community.embeddings import HuggingFaceEmbeddings\n",
+    "from langchain_huggingface import HuggingFaceEmbeddings\n",
     "\n",
     "urls = [\n",
     "    \"https://lilianweng.github.io/posts/2023-06-23-agent/\",\n",
@@ -146,7 +147,7 @@
     "vectorstore = Chroma.from_documents(\n",
     "    documents=doc_splits,\n",
     "    collection_name=\"rag-chroma\",\n",
-    "    embedding=HuggingFaceEmbeddings(),\n",
+    "    embedding=HuggingFaceEmbeddings(model_name=\"sentence-transformers/all-mpnet-base-v2\"),\n",
     ")\n",
     "retriever = vectorstore.as_retriever()"
    ]
@@ -257,7 +258,7 @@
     "    Here is the answer:\n",
     "    {generation}\n",
     "    \"\"\",\n",
-    "    input_variables=[\"generation\", \"documents\"],\n",
+    "    input_variables=[\"generation\", \"documents\"]\n",
     ")\n",
     "\n",
     "hallucination_grader = prompt | llm | JsonOutputParser()\n",
@@ -304,7 +305,7 @@
     "### Router\n",
     "\n",
     "from langchain.prompts import PromptTemplate\n",
-    "from langchain_community.chat_models import ChatOllama\n",
+    "from langchain_ollama import ChatOllama\n",
     "from langchain_core.output_parsers import JsonOutputParser\n",
     "\n",
     "# LLM\n",
@@ -325,7 +326,7 @@
     "\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}))"
    ]
@@ -648,7 +649,7 @@
    "source": [
     "Trace: \n",
     "\n",
-    "https://smith.langchain.com/public/8d449b67-6bc4-4ecf-9153-759cd21df24f/r"
+    "https://smith.langchain.com/public/bbdef8eb-0c42-4df6-9eaa-3e7e75c87df9/r"
    ]
   },
   {
@@ -660,7 +661,6 @@
    "source": [
     "# Compile\n",
     "app = workflow.compile()\n",
-    "\n",
     "# Test\n",
     "from pprint import pprint\n",
     "inputs = {\"question\": \"Who are the Bears expected to draft first in the NFL draft?\"}\n",
@@ -677,13 +677,36 @@
    "source": [
     "Trace: \n",
     "\n",
-    "https://smith.langchain.com/public/c785f9c0-f519-4a38-ad5a-febb59a2139c/r"
+    "https://smith.langchain.com/public/0e6378e7-b8d4-4979-8357-05f854584cc6/r"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 62,
+   "id": "bd0254a8-2e85-4462-8626-711fdb2cc913",
+   "metadata": {},
+   "outputs": [
+    {
+     "ename": "NameError",
+     "evalue": "name 'langchain_community' is not defined",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[31m---------------------------------------------------------------------------\u001b[39m",
+      "\u001b[31mNameError\u001b[39m                                 Traceback (most recent call last)",
+      "\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[62]\u001b[39m\u001b[32m, line 1\u001b[39m\n\u001b[32m----> \u001b[39m\u001b[32m1\u001b[39m \u001b[38;5;28mprint\u001b[39m(\u001b[43mlangchain_community\u001b[49m.__version__)\n",
+      "\u001b[31mNameError\u001b[39m: name 'langchain_community' is not defined"
+     ]
+    }
+   ],
+   "source": [
+    "import langchain\n",
+    "print(langchain_community.__version__)"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "a1059b3e-d197-47fc-b55f-82a3406016f3",
+   "id": "337d5b89-7030-4ae9-85ed-f5f9f6da0c26",
    "metadata": {},
    "outputs": [],
    "source": []
@@ -705,7 +728,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.9"
+   "version": "3.12.7"
   }
  },
  "nbformat": 4,