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"""
Build a graph to solve gala problems.
"""
import os
from langchain_core.tools import tool
from langchain_groq import ChatGroq
from langchain_community.tools.tavily_search import TavilySearchResults
from langgraph.graph import START, StateGraph, MessagesState, END
from langgraph.prebuilt import tools_condition, ToolNode
from langchain_huggingface import ChatHuggingFace, HuggingFaceEndpoint
from langchain_community.document_loaders import WikipediaLoader, ArxivLoader
from langchain_core.messages import SystemMessage, HumanMessage
@tool
def multiply(a: int, b: int) -> int:
"""Multiply two numbers.
Args:
a: first int
b: second int
"""
return a * b
@tool
def add(a: int, b: int) -> int:
"""Add two numbers.
Args:
a: first int
b: second int
"""
return a + b
@tool
def subtract(a: int, b: int) -> int:
"""Subtract two numbers.
Args:
a: first int
b: second int
"""
return a - b
@tool
def divide(a: int, b: int) -> int:
"""Divide two numbers.
Args:
a: first int
b: second int
"""
if b == 0:
raise ValueError("Cannot divide by zero.")
return a / b
@tool
def modulus(a: int, b: int) -> int:
"""Get the modulus of two numbers.
Args:
a: first int
b: second int
"""
return a % b
@tool
def wiki_search(query: str) -> str:
"""Search Wikipedia for a query and return maximum 2 results.
Args:
query: The search query."""
search_docs = WikipediaLoader(query=query, load_max_docs=2).load()
formatted_search_docs = "\n\n---\n\n".join(
[
f'<Document source="{doc.metadata["source"]}" page="{doc.metadata.get("page", "")}"/>\n{doc.page_content}\n</Document>'
for doc in search_docs
])
return {"wiki_results": formatted_search_docs}
@tool
def web_search(query: str) -> str:
"""Search Tavily for a query and return maximum 3 results.
Args:
query: The search query."""
search_docs = TavilySearchResults(max_results=3).invoke(query=query)
formatted_search_docs = "\n\n---\n\n".join(
[
f'<Document source="{doc.metadata["source"]}" page="{doc.metadata.get("page", "")}"/>\n{doc.page_content}\n</Document>'
for doc in search_docs
])
return {"web_results": formatted_search_docs}
@tool
def arvix_search(query: str) -> str:
"""Search Arxiv for a query and return maximum 3 result.
Args:
query: The search query."""
search_docs = ArxivLoader(query=query, load_max_docs=3).load()
formatted_search_docs = "\n\n---\n\n".join(
[
f'<Document source="{doc.metadata["source"]}" page="{doc.metadata.get("page", "")}"/>\n{doc.page_content[:1000]}\n</Document>'
for doc in search_docs
])
return {"arvix_results": formatted_search_docs}
SYSTEM_PROMPT = """
You are a helpful assistant that can solve problems using a set of tools.
Now, I will ask you a question. Report your thoughts, and finish your answer with the following template:
FINAL ANSWER: [YOUR FINAL ANSWER].
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.
Your answer should only start with "FINAL ANSWER: ", then follows with the answer.
"""
tools = [multiply, add, subtract, divide, modulus, wiki_search, web_search, arvix_search]
def build_graph():
"""
Build a graph to solve gala problems.
"""
model = HuggingFaceEndpoint(
repo_id="Qwen/QwQ-32B", # 模型ID
task="text-generation", # 任务类型
temperature=0.7,
max_new_tokens=512,
huggingfacehub_api_token=os.getenv('HUGGINGFACE_API_TOKEN'),
top_p=0.95,
)
llm = ChatHuggingFace(llm=model)
# llm = ChatGroq(model="qwen-qwq-32b", temperature=0)
llm_with_tools = llm.bind_tools(tools)
# Node
def assistant(state: MessagesState):
"""Assistant node"""
print(state["messages"])
return {"messages": [llm_with_tools.invoke(state["messages"])]}
def end(state: MessagesState):
"""End node"""
return {"messages": [HumanMessage(content="FINAL ANSWER: " + state["messages"][-1].content)]}
builder = StateGraph(MessagesState)
builder.add_node("assistant", assistant)
builder.add_node("tools", ToolNode(tools))
builder.add_edge(START, "assistant")
builder.add_conditional_edges(
"assistant",
tools_condition
)
builder.add_edge("tools", "assistant")
builder.add_edge("assistant", END)
# Compile graph
return builder.compile()
if __name__ == "__main__":
from pprint import pprint
graph = build_graph()
messages = [SystemMessage(content=SYSTEM_PROMPT), HumanMessage(content="What is the capital of France?")]
msg = graph.invoke({"messages": messages})
for m in msg["messages"]:
m.pretty_print() |