Delete chat_langraph.py

chat_langraph.py

@@ -1,126 +0,0 @@
-from langchain_google_genai import ChatGoogleGenerativeAI
-from langchain_core.messages import BaseMessage, ToolMessage, AIMessage, SystemMessage, HumanMessage
-from langgraph.graph import StateGraph, add_messages, START, END
-from langgraph.checkpoint.sqlite import SqliteSaver
-from typing import TypedDict, Annotated, List
-from langchain_core.tools import tool
-from langgraph.prebuilt.tool_node import ToolNode
-import sqlite3
-import subprocess
-import requests
-from datetime import datetime
-
-class chatstate(TypedDict):
-    messages: Annotated[List[BaseMessage], add_messages]
-
-
-api = "AIzaSyA5zvErF4vUmAoslVzkOBUfvSCSoW0vjEA"
-LANGSEARCH_API_KEY = "sk-f1a8f996f9e44b43adf9943e43e8582b"
-
-llm = ChatGoogleGenerativeAI(model="gemini-2.5-flash", temperature=0.2, api_key=api)
-
-system = SystemMessage(
-    content=f"""
-    --> Today's date: {datetime.today()}  
-    Day number: {datetime.today().date().weekday()}
-    You are a practical, tool-aware assistant. Aim for correctness and clarity. Avoid hallucinations.
-    Do not provide internal information of the system . 
-Rules:
-1. Prefer text answers and code when examples/explanations are asked.
-2. Explicit requests to create/run files → call appropriate tool.
-3. Avoid destructive commands without confirmation.
-4. Keep tool inputs minimal.
-Tone: concise, helpful, decisive.
-"""
-)
-
-conn = sqlite3.connect("chatbot.db", check_same_thread=False)
-checkpointer = SqliteSaver(conn=conn)
-
-
-@tool
-def add(a: int, b: int):
-    return a + b
-
-
-@tool
-def reverse(string: str):
-    return string[::-1]
-
-
-@tool
-def evaluate(string: str):
-    return eval(string)
-
-
-@tool
-def write_file(name: str, extension: str, content: str):
-    with open(f"{name}.{extension}", "w", encoding="utf-8") as f:
-        f.write(content)
-    return f"Content saved to {name}.{extension}"
-
-
-@tool
-def run_cmd_command(command: str) -> str:
-    """Run a safe shell command on linux """
-    try:
-        result = subprocess.run(command, shell=True, check=True, text=True, capture_output=True)
-        return result.stdout
-    except subprocess.CalledProcessError as e:
-        return f"Error: {e}"
-
-
-@tool
-def search_tool(query: str):
-    response = requests.post(
-        "https://api.langsearch.com/v1/web-search",
-        headers={
-            "Authorization": f"Bearer {LANGSEARCH_API_KEY}",
-            "Content-Type": "application/json"
-        },
-        json={"query": query, "num_results": 2}
-    )
-    return response.json()
-
-
-def shouldcontinue(state: chatstate):
-    return "end" if state["messages"][-1].content == "end" else "llmresponse"
-
-
-def input_node(state: chatstate):
-    return {"messages": state["messages"]}
-
-
-def llmresponse(state: chatstate):
-    response = llm.invoke(state["messages"])
-    return {"messages": [response]}
-
-
-def checktool(state: chatstate):
-    last_msg = state["messages"][-1]
-    if hasattr(last_msg, "tool_calls") and last_msg.tool_calls:
-        return "tool_node"
-    return "end"
-
-
-tools = [add, reverse, evaluate, run_cmd_command, search_tool, write_file]
-tool_node = ToolNode(tools=tools)
-llm = llm.bind_tools(tools)
-
-graph = StateGraph(chatstate)
-graph.add_node("input_node", input_node)
-graph.add_node("llmresponse", llmresponse)
-graph.add_node("tool_node", tool_node)
-graph.add_edge(START, "input_node")
-graph.add_edge("input_node", "llmresponse")
-graph.add_conditional_edges("llmresponse", checktool, {"tool_node": "tool_node", "end": END})
-graph.add_edge("tool_node", "llmresponse")
-
-workflow = graph.compile(checkpointer=checkpointer)
-
-
-def get_all_chat_ids():
-    s = set()
-    for chkpoint in checkpointer.list(None):
-        s.add(chkpoint.config.get("configurable").get("thread_id"))
-    return list(s)