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import os
from dotenv import load_dotenv
load_dotenv()
from langchain_core.tools import tool
from langgraph.graph import StateGraph, START, MessagesState
from langgraph.prebuilt import tools_condition, ToolNode
from langchain_groq import ChatGroq
from langchain_core.messages import HumanMessage, SystemMessage
import math
groq_api_key = os.getenv("GROQ_API_KEY")
serpapi_api_key = os.getenv("SERPAPI_API_KEY")
# -------------------------
# Tools
# -------------------------
@tool
def add(a: float, b: float) -> float:
return a + b
@tool
def subtract(a: float, b: float) -> float:
return a - b
@tool
def multiply(a: float, b: float) -> float:
return a * b
@tool
def divide(a: float, b: float) -> float:
if b == 0:
return float('inf')
return a / b
@tool
def modulus(a: int, b: int) -> int:
return a % b
@tool
def python_eval(code: str) -> str:
try:
result = eval(code)
return f"Result: {result}"
except Exception as e:
return f"Error: {str(e)}"
@tool
def translate_to_arabic(text: str) -> str:
return f"Arabic translation of '{text}'"
@tool
def translate_to_english(text: str) -> str:
return f"English translation of '{text}'"
@tool
def summarize_text(text: str) -> str:
return f"Summary: {text[:100]}..."
@tool
def analyze_sentiment(text: str) -> str:
if any(word in text.lower() for word in ["good", "great", "excellent", "happy"]):
return "Sentiment: Positive"
elif any(word in text.lower() for word in ["bad", "terrible", "sad", "hate"]):
return "Sentiment: Negative"
return "Sentiment: Neutral"
@tool
def speech_to_text_stub(audio: str) -> str:
return "Converted audio to text: (This is a placeholder result)"
# -------------------------
# System Prompt
# -------------------------
system_prompt = """
You are DeepSeek, a thoughtful and curious AI assistant. You analyze before answering.
You always reflect step by step, consider using tools intelligently, and aim for precision and clarity.
Behaviors:
- Think deeply about the user's question.
- Decide if you need tools to calculate, search, translate, or analyze.
- If no tool is needed, answer directly with your own knowledge.
Respond in a helpful, concise, and accurate way.
"""
sys_msg = SystemMessage(content=system_prompt)
# -------------------------
# Build LangGraph Agent
# -------------------------
def build_deepseek_graph():
llm = ChatGroq(model="deepseek-r1-distill-llama-70b", groq_api_key=groq_api_key)
all_tools = [
add, subtract, multiply, divide, modulus,
translate_to_arabic, translate_to_english,
summarize_text, analyze_sentiment,
python_eval, speech_to_text_stub
]
llm_with_tools = llm.bind_tools(all_tools)
def assistant(state: MessagesState):
return {"messages": [llm_with_tools.invoke(state["messages"])]}
builder = StateGraph(MessagesState)
builder.add_node("assistant", assistant)
builder.add_node("tools", ToolNode(all_tools))
builder.add_edge(START, "assistant")
builder.add_conditional_edges("assistant", tools_condition)
builder.add_edge("tools", "assistant")
ninu = builder.compile()
return ninu
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