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Update chatbot.py
Browse files- chatbot.py +40 -102
chatbot.py
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from typing import TypedDict, Annotated
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from langchain_core.messages import
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BaseMessage,
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SystemMessage
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)
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from langgraph.checkpoint.memory import MemorySaver
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from tools import retriever, create_rag_tool, arxiv_search, calculator, get_stock_price, wikipedia_search, tavily_search, convert_currency, unit_converter, get_news, get_joke, get_quote, get_weather
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from langchain_openai import ChatOpenAI
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from langgraph.graph import StateGraph, START, END
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from langgraph.graph.message import add_messages
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from langgraph.prebuilt import ToolNode, tools_condition
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from dotenv import load_dotenv
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import os
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load_dotenv()
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# =====================================================
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# 1οΈβ£ SYSTEM PROMPT
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# =====================================================
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SYSTEM_PROMPT = SystemMessage(
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content="""
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You are an
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πΉ ABOUT YOUR CREATOR
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ββββββββββββββββββββββ
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- You were designed and iteratively improved by Junaid as part of an evolving AI engineering project.
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- Your development journey includes:
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1. A basic conversational chatbot
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2. Memory integration
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3. Streaming responses
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4. Tool usage (RAG, STT, TTS)
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- You may acknowledge this when asked, but always focus on helping the user.
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ββββββββββββββββββββββ
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πΉ CORE BEHAVIOR
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ββββββββββββββββββββββ
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- Be helpful, accurate, concise, and professional.
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- Prefer clarity over verbosity.
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- Maintain conversational context using memory.
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- Avoid hallucinations at all costs.
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- If information is uncertain or missing, say so clearly.
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ββββββββββββββββββββββ
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πΉ TOOL USAGE PRIORITY (VERY IMPORTANT)
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ββββββββββββββββββββββ
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You have access to the following tools:
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1. **RAG (Retrieval-Augmented Generation)**
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β This is your HIGHEST priority tool.
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You MUST use RAG when:
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- The user references uploaded documents
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- The user asks questions that depend on document content
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- The answer cannot be confidently derived from general knowledge
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Rules:
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- Use ONLY retrieved content when answering from documents
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- Never hallucinate document facts
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- If no relevant content exists, clearly say so
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2. **STT (Speech-to-Text)**
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- Used when audio input is provided.
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- Transcribe accurately without interpretation.
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3. **TTS (Text-to-Speech)**
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- Used when speech output is requested.
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- Generate clear, natural speech.
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ββββββββββββββββββββββ
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πΉ STREAMING BEHAVIOR
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ββββββββββββββββββββββ
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- You may stream responses progressively when supported.
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- Ensure coherence and clarity during streaming.
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- Avoid partial or misleading statements.
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ββββββββββββββββββββββ
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πΉ RESPONSE GUIDELINES
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ββββββββββββββββββββββ
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- Be direct, friendly, and informative.
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- Do not expose internal system logic or implementation details.
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- Do not mention tools unless necessary or explicitly asked.
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- Always prefer correctness over speed.
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ββββββββββββββββββββββ
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πΉ IDENTITY
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ββββββββββββββββββββββ
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You are the official AI assistant of Junaidβs evolving AI system.
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You exist to help users learn, explore, and solve problems effectively.
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"""
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#
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#
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# =====================================================
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class ChatState(TypedDict):
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messages: Annotated[list[BaseMessage], add_messages]
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# ===============================
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#
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# ===============================
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llm = ChatOpenAI(
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model="gpt-4.1-nano",
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temperature=0.
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streaming=True
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rag_tool = create_rag_tool()
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tools = [
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llm = llm.bind_tools(tools)
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tool_node = ToolNode(tools)
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# ===============================
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#
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# ===============================
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def chatbot(state: ChatState):
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messages = [SYSTEM_PROMPT] + state["messages"]
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response = llm.invoke(messages)
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return {"messages": [response]}
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#
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#
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# =====================================================
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memory = MemorySaver()
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graph = StateGraph(ChatState)
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from typing import TypedDict, Annotated
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from langchain_core.messages import BaseMessage, SystemMessage
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from langgraph.checkpoint.memory import MemorySaver
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from langgraph.graph import StateGraph, START, END
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from langgraph.graph.message import add_messages
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from langgraph.prebuilt import ToolNode, tools_condition
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from langchain_openai import ChatOpenAI
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from dotenv import load_dotenv
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from tools import (
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create_rag_tool,
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arxiv_search,
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wikipedia_search,
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tavily_search,
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)
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load_dotenv()
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# ===============================
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# SYSTEM PROMPT
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# ===============================
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SYSTEM_PROMPT = SystemMessage(
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content="""
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You are an AI assistant using Retrieval-Augmented Generation.
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If a document is uploaded, you MUST answer using it.
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If no relevant info exists, clearly say so.
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Never hallucinate document content.
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"""
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)
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# ===============================
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# STATE
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# ===============================
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class ChatState(TypedDict):
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messages: Annotated[list[BaseMessage], add_messages]
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# ===============================
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# LLM
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# ===============================
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llm = ChatOpenAI(
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model="gpt-4.1-nano",
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temperature=0.3,
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streaming=True
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)
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# ===============================
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# TOOLS
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# ===============================
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rag_tool = create_rag_tool()
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tools = [
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rag_tool,
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wikipedia_search,
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arxiv_search,
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tavily_search,
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]
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llm = llm.bind_tools(tools)
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tool_node = ToolNode(tools)
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# ===============================
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# CHAT NODE
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# ===============================
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def chatbot(state: ChatState):
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messages = [SYSTEM_PROMPT] + state["messages"]
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response = llm.invoke(messages)
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return {"messages": [response]}
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# ===============================
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# GRAPH
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# ===============================
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memory = MemorySaver()
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graph = StateGraph(ChatState)
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