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Update agent.py
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agent.py
CHANGED
@@ -1,7 +1,5 @@
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import os
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from dotenv import load_dotenv
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from langchain.docstore.document import Document
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from langchain_community.retrievers import BM25Retriever
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from langchain.tools import Tool
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from langchain.utilities import SerpAPIWrapper
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from langgraph.graph.message import add_messages
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from langchain_core.messages import AnyMessage, HumanMessage
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from langchain_groq import ChatGroq
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from typing import TypedDict, Annotated
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import fitz # PyMuPDF
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# Load environment variables
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load_dotenv()
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groq_api_key = os.getenv("GROQ_API_KEY")
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serpapi_api_key = os.getenv("SERPAPI_API_KEY")
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# --- PDF parsing ---
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def parse_pdfs(uploaded_files):
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pdf_docs = []
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for uploaded_file in uploaded_files:
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with fitz.open(stream=uploaded_file.read(), filetype="pdf") as doc:
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text = ""
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for page in doc:
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text += page.get_text()
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pdf_docs.append(Document(page_content=text, metadata={"source": uploaded_file.name}))
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return pdf_docs
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# --- BM25 Retrieval ---
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def build_retriever(all_docs):
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return BM25Retriever.from_documents(all_docs)
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def extract_text(query: str, retriever):
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results = retriever.invoke(query)
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if results:
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return "\n\n".join([doc.page_content for doc in results[:3]])
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else:
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return "لم يتم العثور على معلومات مطابقة في الملفات."
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# --- Additional Tools ---
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def calculator_tool_func(query: str):
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try:
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# أداة حساب بسيطة باستخدام eval (يمكن تطويرها لاحقًا)
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result = str(eval(query, {"__builtins__": {}}))
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return result
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except Exception:
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@@ -60,7 +30,6 @@ calculator_tool = Tool(
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)
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def weather_tool_func(location: str):
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# يمكن ربطها ب API حقيقي للطقس لاحقًا
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return f"حالة الطقس في {location}: مشمس، درجة الحرارة 25 درجة مئوية."
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weather_tool = Tool(
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description="Provides weather information for a given location."
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)
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# ---
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def create_ninu_agent(user_docs=None):
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bm25_retriever = build_retriever(user_docs) if user_docs else None
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def pdf_tool_func(q):
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if bm25_retriever:
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return extract_text(q, bm25_retriever)
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else:
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return "لا توجد ملفات PDF مرفوعة للبحث."
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NINU_tool = Tool(
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name="NINU_Lec_retriever",
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func=pdf_tool_func,
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description="Retrieves content from uploaded PDFs based on a query."
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)
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serpapi = SerpAPIWrapper(serpapi_api_key=serpapi_api_key)
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SerpAPI_tool = Tool(
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name="WebSearch",
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func=serpapi.run,
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description="Searches the web for recent information."
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)
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# دمج جميع التولز
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tools = [NINU_tool, SerpAPI_tool, calculator_tool, weather_tool]
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llm = ChatGroq(model="deepseek-r1-distill-llama-70b", groq_api_key=groq_api_key)
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llm_with_tools = llm.bind_tools(tools)
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@@ -111,27 +64,25 @@ def create_ninu_agent(user_docs=None):
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builder.add_edge(START, "assistant")
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builder.add_conditional_edges("assistant", tools_condition)
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builder.add_edge("tools", "assistant")
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return builder.compile()
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agent = create_ninu_agent(user_docs)
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conversation = []
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intro_prompt = """
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You are a general AI assistant with access to
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1.
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2.
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3.
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YOUR FINAL ANSWER should be a number OR as few words as possible OR a comma separated list of numbers and/or strings.
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If you are asked for a number, don't use commas or units (like $, %, etc.) unless specified.
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If you are asked for a string, avoid articles, abbreviations, and write digits in plain text unless specified.
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"""
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conversation.append(HumanMessage(content=intro_prompt))
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conversation.append(HumanMessage(content=query))
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response = agent.invoke({"messages": conversation})
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return response["messages"][-1].content
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import os
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from dotenv import load_dotenv
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from langchain.tools import Tool
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from langchain.utilities import SerpAPIWrapper
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from langgraph.graph.message import add_messages
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from langchain_core.messages import AnyMessage, HumanMessage
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from langchain_groq import ChatGroq
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from typing import TypedDict, Annotated
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# Load environment variables
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load_dotenv()
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groq_api_key = os.getenv("GROQ_API_KEY")
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serpapi_api_key = os.getenv("SERPAPI_API_KEY")
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# --- أدوات مساعدة ---
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def calculator_tool_func(query: str):
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try:
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result = str(eval(query, {"__builtins__": {}}))
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return result
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except Exception:
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)
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def weather_tool_func(location: str):
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return f"حالة الطقس في {location}: مشمس، درجة الحرارة 25 درجة مئوية."
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weather_tool = Tool(
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description="Provides weather information for a given location."
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)
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serpapi = SerpAPIWrapper(serpapi_api_key=serpapi_api_key)
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SerpAPI_tool = Tool(
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name="WebSearch",
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func=serpapi.run,
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description="Searches the web for recent information."
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)
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# --- بناء الوكيل ---
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def create_search_only_agent():
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tools = [SerpAPI_tool, calculator_tool, weather_tool]
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llm = ChatGroq(model="deepseek-r1-distill-llama-70b", groq_api_key=groq_api_key)
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llm_with_tools = llm.bind_tools(tools)
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builder.add_edge(START, "assistant")
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builder.add_conditional_edges("assistant", tools_condition)
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builder.add_edge("tools", "assistant")
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return builder.compile()
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# --- دالة التفاعل ---
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def run_search_agent(query):
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agent = create_search_only_agent()
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conversation = []
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intro_prompt = """
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You are a general AI assistant with access to the following tools:
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1. WebSearch: to search for general or recent information from the internet.
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2. Calculator: to perform arithmetic calculations.
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3. Weather: to provide weather information.
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Think step by step, and decide which tools to use to answer the query.
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Respond with:
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FINAL ANSWER: [your final answer]
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Only include what the user asked for in the final answer.
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"""
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conversation.append(HumanMessage(content=intro_prompt))
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conversation.append(HumanMessage(content=query))
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response = agent.invoke({"messages": conversation})
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return response["messages"][-1].content
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# يمكن استخدام الدالة التالية لاختبار الوكيل
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if __name__ == "__main__":
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question = "ما هي عاصمة اليابان وكم عدد سكانها؟"
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answer = run_search_agent(question)
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print(answer)
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