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6859205 852ec49 6859205 852ec49 6859205 852ec49 6859205 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 | from typing import TypedDict, Annotated, Sequence
from langgraph.graph.message import add_messages
from langchain_core.messages import AnyMessage, HumanMessage, AIMessage, SystemMessage, BaseMessage
from langgraph.prebuilt import ToolNode
from langgraph.graph import START, StateGraph, MessagesState, END
from langgraph.prebuilt import tools_condition
from langchain_huggingface import HuggingFaceEndpoint, ChatHuggingFace
from langchain_core.runnables import RunnableConfig
from langchain_community.tools import DuckDuckGoSearchRun, WikipediaQueryRun, ArxivQueryRun
from langchain_community.utilities import WikipediaAPIWrapper, ArxivAPIWrapper
from langchain_community.tools.wikidata.tool import WikidataAPIWrapper, WikidataQueryRun
from langchain_openai import ChatOpenAI
from tools import GetYouTubeTranscriptTool, ImageRecognitionTool
from dotenv import load_dotenv
import os
load_dotenv()
HUGGINGFACEHUB_API_TOKEN = os.getenv("HF_TOKEN")
# Define your state class if needed
class AgentState(TypedDict):
"""The state of the agent."""
messages: Annotated[Sequence[BaseMessage], add_messages]
def build_graph():
"""
Build and return the compiled LangGraph Runnable agent.
"""
def call_model(
state: AgentState,
config: RunnableConfig,
):
system_prompt = SystemMessage("You are a general AI assistant. I will ask you a question. Report only your final answer without the thoughts or any other text. 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), and write the digits in plain text unless specified otherwise. If you are asked for a comma separated list, apply the above rules depending of whether the element to be put in the list is a number or a string. Also be direct when doing a tool call. Try using other tools before using the DuckDuckGoTool. If you can't find informations, answer based on your personal knowledge.")
response = model.invoke([system_prompt] + state["messages"], config)
# We return a list, because this will get added to the existing list
return {"messages": [response]}
def should_continue(state: AgentState):
messages = state["messages"]
last_message = messages[-1]
print(last_message)
# If there is no function call, then we finish
if not last_message.tool_calls:
return "end"
# Otherwise if there is, we continue
else:
return "continue"
model = ChatOpenAI(model="o1")
image_model = ChatOpenAI(model="gpt-4o")
tools = [GetYouTubeTranscriptTool(),
WikidataQueryRun(api_wrapper=WikidataAPIWrapper()),
DuckDuckGoSearchRun(),
ArxivQueryRun(api_wrapper=ArxivAPIWrapper()),
WikipediaQueryRun(api_wrapper=WikipediaAPIWrapper()),
ImageRecognitionTool(hf_endpoint=image_model)]
model = model.bind_tools(tools)
tool_node = ToolNode(tools)
workflow = StateGraph(AgentState)
# Define the two nodes we will cycle between
workflow.add_node("agent", call_model)
workflow.add_node("tools", tool_node)
# Set the entrypoint as `agent`
# This means that this node is the first one called
workflow.set_entry_point("agent")
# We now add a conditional edge
workflow.add_conditional_edges(
"agent",
should_continue,
{
# If `tools`, then we call the tool node.
"continue": "tools",
"end": END
},
)
workflow.add_edge("tools", "agent")
graph = workflow.compile()
return graph |