build_graph

graph.py

@@ -0,0 +1,161 @@
+"""
+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()