From d6ffdc895d5de3f5ccb4275b74678e6b1648ea1d Mon Sep 17 00:00:00 2001
From: Tom Liu <tom.5610@gmail.com>
Date: Sun, 10 Aug 2025 01:32:16 +0000
Subject: [PATCH] To upgrade langchain, langgraph, faiss packagge; correct
 embedding QA model id and use correct class on langgraph.

Signed-off-by: Tom Liu <tom.5610@gmail.com>
---
 ...raph_HandlingAgent_IntermediateSteps.ipynb | 54 +++++++++++++------
 1 file changed, 37 insertions(+), 17 deletions(-)

diff --git a/RAG/notebooks/langchain/LangGraph_HandlingAgent_IntermediateSteps.ipynb b/RAG/notebooks/langchain/LangGraph_HandlingAgent_IntermediateSteps.ipynb
index e1f18b27b..9d0a8dd74 100644
--- a/RAG/notebooks/langchain/LangGraph_HandlingAgent_IntermediateSteps.ipynb
+++ b/RAG/notebooks/langchain/LangGraph_HandlingAgent_IntermediateSteps.ipynb
@@ -44,13 +44,19 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "!pip install --upgrade pip\n",
-    "!pip install langchain==0.2.5\n",
-    "!pip install langchain-nvidia-ai-endpoints==0.1.2\n",
-    "!pip install langchain-community==0.2.2\n",
-    "!pip install langgraph==0.0.62\n",
-    "!pip install faiss-gpu==1.7.2\n",
-    "!pip install wikipedia==1.4.0"
+    "# install below package when 'pip' is referred to the dedicated python virtual environment. \n",
+    "# !pip install --upgrade pip\n",
+    "# !pip install langchain==0.3.27\n",
+    "# !pip install langchain-nvidia-ai-endpoints==0.3.13\n",
+    "# !pip install langchain-community==0.3.27\n",
+    "# !pip install langgraph==0.6.3\n",
+    "# !pip install wikipedia==1.4.0\n",
+    "\n",
+    "# faiss-gpu can only be used up to py310, when using later Python versions, please move to faiss-cpu\n",
+    "# with py311+\n",
+    "# !pip install faiss-cpu=1.11.0\n",
+    "# or with GPU & py310 and below\n",
+    "# !pip install faiss-gpu==1.7.2\n"
    ]
   },
   {
@@ -113,8 +119,12 @@
     "from langchain_nvidia_ai_endpoints import ChatNVIDIA\n",
     "from langchain_nvidia_ai_endpoints import NVIDIAEmbeddings\n",
     "\n",
-    "llm = ChatNVIDIA(model=\"mistralai/mixtral-8x7b-instruct-v0.1\", nvidia_api_key=nvapi_key, max_tokens=2048)\n",
-    "embedder = NVIDIAEmbeddings(model=\"NV-Embed-QA\", truncate=\"END\")\n"
+    "llm = ChatNVIDIA(model=\"mistralai/mixtral-8x7b-instruct-v0.1\", \n",
+    "                 nvidia_api_key=nvapi_key, \n",
+    "                 max_completion_tokens=2048) # max_tokens is about to be depreciated.\n",
+    "\n",
+    "embedder = NVIDIAEmbeddings(model=\"nvidia/nv-embedqa-e5-v5\", # recent valid embedding QA model\n",
+    "                            truncate=\"END\")\n"
    ]
   },
   {
@@ -197,12 +207,13 @@
    "outputs": [],
    "source": [
     "from langchain.tools import BaseTool\n",
+    "from pydantic import Field\n",
     "\n",
     "class SwedenRetriever(BaseTool):\n",
-    "    name = \"AboutSweden\"\n",
-    "    description = \"Useful for when you need to answer questions about Sweden's population, history, and so on.\"\n",
+    "    name: str = \"AboutSweden\"\n",
+    "    description: str = \"Useful for when you need to answer questions about Sweden's population, history, and so on.\"\n",
     "\n",
-    "    def _run(self, query):\n",
+    "    def _run(self, query) -> str:\n",
     "        out = retriever.invoke(query)\n",
     "        o = out[0]\n",
     "        item=o.page_content.split('|')\n",
@@ -257,6 +268,7 @@
     "    func=wikipedia.run,\n",
     "    name=\"Wiki\",\n",
     "    description=\"useful for when you need to search certain topic on Wikipedia, aka wiki\")\n",
+    "\n",
     "retriever_tool=Tool.from_function(\n",
     "    func=sv.invoke,\n",
     "    name=\"AboutSweden\",\n",
@@ -283,11 +295,11 @@
    "outputs": [],
    "source": [
     "from langchain_core.agents import AgentFinish\n",
-    "from langgraph.prebuilt.tool_executor import ToolExecutor\n",
+    "from langgraph.prebuilt import ToolNode\n",
     "\n",
     "# This a helper class we have that is useful for running tools\n",
     "# It takes in an agent action and calls that tool and returns the result\n",
-    "tool_executor = ToolExecutor(tools)\n"
+    "tool_node = ToolNode(tools)\n"
    ]
   },
   {
@@ -505,7 +517,7 @@
     "    agent_output = data[\"agent_outcome\"]\n",
     "    if len(agent_output['intermediate_steps'])>=1 :\n",
     "        agent_action = agent_output['intermediate_steps'][0][0]\n",
-    "        output = tool_executor.invoke(agent_action)\n",
+    "        output = tool_node.invoke(agent_action)\n",
     "        return {\"intermediate_steps\": [(agent_action, str(output))]}\n",
     "    else:\n",
     "        return {\"intermediate_steps\":[]}\n",
@@ -622,11 +634,19 @@
     "inputs = {\"input\": \"Find me Taylor Swift information on wiki?\"}\n",
     "outputs=app.invoke(inputs)"
    ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "9801bb4c",
+   "metadata": {},
+   "outputs": [],
+   "source": []
   }
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
+   "display_name": "generativeaiexamples",
    "language": "python",
    "name": "python3"
   },
@@ -640,7 +660,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.6"
+   "version": "3.12.11"
   }
  },
  "nbformat": 4,