| """LangGraph Agent""" |
| import os |
| from dotenv import load_dotenv |
| from langchain_groq import ChatGroq |
| from langchain_core.tools import tool |
| from langgraph.prebuilt import ToolNode |
| from langgraph.prebuilt import tools_condition |
| from langgraph.graph import START, StateGraph, MessagesState |
| from langchain_core.messages import SystemMessage, HumanMessage |
| from langchain_community.tools import DuckDuckGoSearchResults |
|
|
| load_dotenv() |
|
|
| @tool |
| def web_search(query: str) -> str: |
| """ |
| Search DuckDuckGo for a query. |
| |
| Args: |
| query: The search query. |
| |
| Returns: |
| A dict with key ``"web_results"`` containing a |
| markdown-formatted string of the retrieved documents. |
| """ |
| |
| search = DuckDuckGoSearchResults(max_results=3) |
|
|
| |
| search_result = search.invoke(query) |
|
|
| return {"web_results": search_result} |
|
|
| tools = [ |
| web_search, |
| ] |
|
|
| llm = ChatGroq(model="meta-llama/llama-4-maverick-17b-128e-instruct", temperature=0) |
| llm_with_tools = llm.bind_tools(tools) |
|
|
| llm_with_tools = llm.bind_tools(tools) |
|
|
| |
| def start_preprocess(state: MessagesState): |
| |
| system_prompt = "You are a general AI assistant. I will ask you a question. Your 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." |
| sys_msg = SystemMessage(content=system_prompt) |
| return {"messages": [sys_msg] + state["messages"]} |
|
|
| |
| def assistant(state: MessagesState): |
| """Assistant node""" |
| return {"messages": [llm_with_tools.invoke(state["messages"])]} |
|
|
| builder = StateGraph(MessagesState) |
| builder.add_node("start_preprocess", start_preprocess) |
| builder.add_node("assistant", assistant) |
| builder.add_node("tools", ToolNode(tools)) |
| builder.add_edge(START, "start_preprocess") |
| builder.add_edge("start_preprocess", "assistant") |
| builder.add_conditional_edges( |
| "assistant", |
| tools_condition, |
| ) |
| builder.add_edge("tools", "assistant") |
|
|
| |
| graph = builder.compile() |
|
|
| if __name__ == "__main__": |
| question = "NAMO age ?" |
| |
| messages = [HumanMessage(content=question)] |
| messages = graph.invoke({"messages": messages}) |
| for m in messages["messages"]: |
| m.pretty_print() |
|
|
