File size: 2,641 Bytes
9bcd561 | 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 | import os
from typing import TypedDict, Annotated
from dotenv import load_dotenv
from langgraph.graph.message import add_messages
from langchain_core.messages import AnyMessage, HumanMessage, AIMessage
from langgraph.prebuilt import ToolNode
from langgraph.graph import START, StateGraph, MessagesState
from langgraph.prebuilt import tools_condition
from langchain_huggingface import HuggingFaceEndpoint, ChatHuggingFace
from langchain_google_genai import ChatGoogleGenerativeAI
from langchain_groq import ChatGroq
from langchain_openai import ChatOpenAI
from tools import (
divide,
multiply,
modulus,
add,
subtract,
power,
square_root,
web_search,
wiki_search,
arxiv_search,
)
# load api key
load_dotenv()
def buildAgent(provider="huggingface"):
# Generate the chat interface, including the tools
if provider == "huggingface":
llm = ChatHuggingFace(
llm=HuggingFaceEndpoint(repo_id="Qwen/Qwen2.5-Coder-32B-Instruct"),
)
elif provider == "groq":
llm = ChatGroq(model="qwen-qwq-32b")
elif provider == "openrouter":
llm = ChatOpenAI(
base_url="https://openrouter.ai/api/v1",
api_key=os.environ.get("OPENROUTER_API_KEY"),
model="google/gemini-2.0-flash-exp",
)
tools = [
multiply,
add,
subtract,
divide,
modulus,
power,
square_root,
web_search,
wiki_search,
arxiv_search,
]
chat_with_tools = llm.bind_tools(tools)
# nodes
def assistant(state: MessagesState):
return {
"messages": [chat_with_tools.invoke(state["messages"])],
}
## The graph
builder = StateGraph(MessagesState)
# Define nodes: these do the work
builder.add_node("assistant", assistant)
builder.add_node("tools", ToolNode(tools))
# Define edges: these determine how the control flow moves
builder.add_edge(START, "assistant")
builder.add_conditional_edges(
"assistant",
# If the latest message requires a tool, route to tools
# Otherwise, provide a direct response
tools_condition,
)
builder.add_edge("tools", "assistant")
return builder.compile()
if __name__ == "__main__":
question = "When was a picture of St. Thomas Aquinas first added to the Wikipedia page on the Principle of double effect?"
graph = buildAgent(provider="groq")
messages = [HumanMessage(content=question)]
print(messages)
messages = graph.invoke({"messages": messages})
for m in messages["messages"]:
m.pretty_print()
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