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Configuration error
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{
"cells": [
{
"cell_type": "code",
"execution_count": null,
"id": "e02ba404",
"metadata": {},
"outputs": [],
"source": [
"import os\n",
"from dotenv import load_dotenv \n",
"from typing import TypedDict, Optional, Annotated\n",
"from langgraph.graph import StateGraph, START, END\n",
"from langchain_google_genai import ChatGoogleGenerativeAI\n",
"from langchain_core.messages import AnyMessage, HumanMessage\n",
"from langgraph.graph.message import add_messages\n",
"from langgraph.prebuilt import ToolNode, tools_condition\n",
"from IPython.display import Image, display\n",
"\n",
"load_dotenv() \n",
"os.environ[\"GOOGLE_API_KEY\"] = os.getenv(\"GOOGLE\")\n",
"model = ChatGoogleGenerativeAI(model=\"gemini-2.5-flash\", temperature=0)"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "7ec6fbfa",
"metadata": {},
"outputs": [],
"source": [
"class QuestionState(TypedDict):\n",
" input_file: Optional[str]\n",
" messages: Annotated[list[AnyMessage], add_messages]\n"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "34aa1a5c",
"metadata": {},
"outputs": [],
"source": [
"from custom_tools import custom_tools\n",
"\n",
"llm_with_tools = model.bind_tools(custom_tools)"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "c8e0d0ce",
"metadata": {},
"outputs": [],
"source": [
"def assistant(state: QuestionState):\n",
" input_file = state[\"input_file\"]\n",
"\n",
" sys_prompt = f\"\"\"\n",
" You are a general AI assistant. I will ask you a question. Report your thoughts, and finish your answer with the following template: FINAL ANSWER: [YOUR FINAL ANSWER].\\n\n",
" \\n\n",
" YOUR FINAL ANSWER should be a number OR as few words as possible OR a comma separated list of numbers and/or strings. If you are asked for a number, DON'T use comma to write your number NEITHER use units such as $ or percent sign unless specified otherwise. If you are asked for a string, DON'T use articles, NEITHER abbreviations (e.g. for cities) capitalize the first letter, and write the digits in plain text unless specified otherwise. If you are asked for a comma separated list, apply the above rules depending, unless the first letter capitalization, whether the element to be put in the list is a number or a string.\\n\n",
" \\n\n",
" EXAMPLES:\\n\n",
" - What is US President Obama's first name? FINAL ANSWER: Barack\\n\n",
" - What are the 3 mandatory ingredients for pancakes? FINAL ANSWER: eggs, flour, milk\\n\n",
" - What is the final cost of an invoice comprising a $345.00 product and a $355.00 product? Provide the answer with two decimals. FINAL ANSWER: 700.00\\n\n",
" - How many pairs of chromosomes does a human cell contain? FINAL ANSWER : 23\\n\n",
" \\n\n",
" \\n\n",
" You will be provided with tools to help you answer questions.\\n\n",
" If you are asked to make a calculation, absolutely use the tools provided to you. You should AVOID calculating by yourself and ABSOLUTELY use appropriate tools.\\n\n",
" If you are asked to find something in a list of things or people, prefer using the wiki_search tool. Else, prefer to use the web_search tool. After using the web_search tool, look for the first URL provided with the url_search tool and ask yourself if the answer is in the tool response. If it is, answer the question. If not, search on other links.\\n\n",
" \\n\n",
" If needed, use one tool first, then use the output of that tool as an input to another thinking then to the use of another tool.\\n\n",
" \\n\n",
" \\n You have access to some optional files. Currently the loaded file is: {input_file}\"\n",
" \"\"\"\n",
" \n",
" return {\n",
" \"messages\": [llm_with_tools.invoke([sys_prompt] + state[\"messages\"])],\n",
" \"input_file\": state[\"input_file\"]\n",
" }"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "5b569f8c",
"metadata": {},
"outputs": [
{
"data": {
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",
"text/plain": [
"<IPython.core.display.Image object>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# The graph\n",
"builder = StateGraph(QuestionState)\n",
"\n",
"# Define nodes: these do the work\n",
"builder.add_node(\"assistant\", assistant)\n",
"builder.add_node(\"tools\", ToolNode(custom_tools))\n",
"\n",
"# Define edges: these determine how the control flow moves\n",
"builder.add_edge(START, \"assistant\")\n",
"builder.add_conditional_edges(\n",
" \"assistant\",\n",
" # If the latest message requires a tool, route to \"tools\"\n",
" # Otherwise, route to \"END\" and provide a direct response\n",
" tools_condition,\n",
")\n",
"builder.add_edge(\"tools\", \"assistant\")\n",
"react_graph = builder.compile()\n",
"\n",
"# Show the butler's thought process\n",
"display(Image(react_graph.get_graph(xray=True).draw_mermaid_png()))"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "5dcd88bf",
"metadata": {},
"outputs": [],
"source": [
"# Get keys for your project from the project settings page: https://cloud.langfuse.com\n",
"os.environ[\"LANGFUSE_PUBLIC_KEY\"] = os.getenv(\"LANGFUSE_PUBLIC\")\n",
"os.environ[\"LANGFUSE_SECRET_KEY\"] = os.getenv(\"LANGFUSE_SECRET\")\n",
"os.environ[\"LANGFUSE_HOST\"] = \"https://cloud.langfuse.com\" # 🇪🇺 EU region\n",
"\n",
"from langfuse.langchain import CallbackHandler\n",
"\n",
"# Initialize Langfuse CallbackHandler for LangGraph/Langchain (tracing)\n",
"langfuse_handler = CallbackHandler()"
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "25209443",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"================================\u001b[1m Human Message \u001b[0m=================================\n",
"\n",
"The attached Excel file contains the sales of menu items for a local fast-food chain. What were the total sales that the chain made from food (not including drinks)? Express your answer in USD with two decimal places.\n",
"==================================\u001b[1m Ai Message \u001b[0m==================================\n",
"Tool Calls:\n",
" read_file_content (4ed0c3b2-eccc-465a-ab92-38d2ff4ae496)\n",
" Call ID: 4ed0c3b2-eccc-465a-ab92-38d2ff4ae496\n",
" Args:\n",
" file_name: 7bd855d8-463d-4ed5-93ca-5fe35145f733.xlsx\n",
"=================================\u001b[1m Tool Message \u001b[0m=================================\n",
"Name: read_file_content\n",
"\n",
" Location Burgers Hot Dogs Salads Fries Ice Cream Soda\n",
" Pinebrook 1594 1999 2002 2005 1977 1980\n",
" Wharvton 1983 2008 2014 2015 2017 2018\n",
" Sagrada 2019 2022 2022 2023 2021 2019\n",
" Algrimand 1958 1971 1982 1989 1998 2009\n",
" Marztep 2015 2016 2018 2019 2021 2022\n",
"San Cecelia 2011 2010 2012 2013 2015 2016\n",
" Pimento 2017 1999 2001 2003 1969 2967\n",
" Tinseles 1967 1969 1982 1994 2005 2006\n",
" Rosdale 2007 2009 2021 1989 2005 2011\n",
"==================================\u001b[1m Ai Message \u001b[0m==================================\n",
"Tool Calls:\n",
" sum_excel_cols (74b46301-3530-4e91-88bd-347131e46394)\n",
" Call ID: 74b46301-3530-4e91-88bd-347131e46394\n",
" Args:\n",
" file_name: 7bd855d8-463d-4ed5-93ca-5fe35145f733.xlsx\n",
" column_names: ['Burgers', 'Hot Dogs', 'Salads', 'Fries', 'Ice Cream']\n",
"=================================\u001b[1m Tool Message \u001b[0m=================================\n",
"Name: sum_excel_cols\n",
"\n",
"89706\n",
"==================================\u001b[1m Ai Message \u001b[0m==================================\n",
"\n",
"FINAL ANSWER: 89706.00\n"
]
}
],
"source": [
"messages = [HumanMessage(content=\"The attached Excel file contains the sales of menu items for a local fast-food chain. What were the total sales that the chain made from food (not including drinks)? Express your answer in USD with two decimal places.\")]\n",
"messages = react_graph.invoke({\"messages\": messages, \"input_file\": \"7bd855d8-463d-4ed5-93ca-5fe35145f733.xlsx\"},\n",
" config={\n",
" \"callbacks\": [langfuse_handler],\n",
" \"metadata\": {\n",
" \"langfuse_user_id\": \"felix\",\n",
" \"langfuse_session_id\": \"session_1\",\n",
" \"langfuse_tags\": [\"Node\", \"ReActAgent\"]\n",
" }\n",
" })\n",
"\n",
"# Show the messages\n",
"for m in messages['messages']:\n",
" m.pretty_print()"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.11.13"
}
},
"nbformat": 4,
"nbformat_minor": 5
}
|