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import boto3
import pandas as pd
from botocore.exceptions import NoCredentialsError

def get_all_guardduty_alerts(max_results_per_detector=50):
    client = boto3.client('guardduty')
    all_alerts = []

    try:
        # List all GuardDuty detectors

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import json
import pandas as pd
from functools import wraps
from typing import Any, Callable
from pydantic import validate_arguments, BaseModel, validate_call, model_validator, create_model, TypeAdapter
import requests, time, pinecone 
from bs4 import BeautifulSoup
from langchain.indexes import VectorstoreIndexCreator
from langchain.document_loaders import UnstructuredURLLoader

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index_name = 'oktaevents'
index = pinecone.Index(index_name)
embed = OpenAIEmbeddings()

embedding = openai.Embedding.create(
        input=query,
        model="text-embedding-ada-002"
    )
vector = embedding["data"][0]["embedding"]

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from langchain.document_loaders import WebBaseLoader
from langchain.document_loaders import TextLoader

url = 'https://developer.okta.com/docs/reference/api/event-types/#catalog'

loader = TextLoader ('/tmp/okta_events.txt')
scrape_data = loader.load()
index_name = 'oktaevents'

# Chunk your data up into smaller documents

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def ask_llm_to_get_filter (items, query):
    all_text = get_all_items (items)
    #all_text = get_all_above_score (items, 0.9)
    role = 'you are an expert at going through text and finding filter expressions inside text given for specific task. Only use the functions you have been provided with.'

    desc = """ 
    # how to find the filter expresison
    - the filter expressions have characters with dots inside them.
    - the task that the filter expression will help with is right around the that filter expression
    - you must pick one filter expression that best suits the task , the event filter must not have OR or AND 

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# Your Role
You are an excellent research analyst of a topic thats given to you, can do excellent analysis on the topic from all 
angles and write a comprehensive report on the topic.
     
    Your task is to write a comprehensive report to fulfill the objective given to you.
    # Objective
    Qualcomm Stock for Medium Term Investment
     
# Your Task

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import sys, os

# your paths, below is just an example on mac
sys.path .extend (  ['/opt/homebrew/Cellar/python@3.11/3.11.5/Frameworks/Python.framework/Versions/3.11/lib/python311.zip', '/opt/homebrew/Cellar/python@3.11/3.11.5/Frameworks/Python.framework/Versions/3.11/lib/python3.11', '/opt/homebrew/Cellar/python@3.11/3.11.5/Frameworks/Python.framework/Versions/3.11/lib/python3.11/lib-dynload'] )

os.environ["SERPAPI_API_KEY"] = "xxx"

from serpapi import GoogleSearch

def serp_search (query_json) :

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def visualize_knowledge_graph(kg):
    print (kg.keys())
    dot = Digraph(comment="Knowledge Graph")

    # Add nodes
    for node in kg['nodes']:
        dot.node(str(node['id']), node['label'], color=node['color'])

    # Add edges
    for edge in kg['edges']:

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prompt_content = """ 
        Your task is make the knowledge graph from an article for a given objective.
        objective : {objective}
        you must follow all reqirements that are listed below
        ## graph requirements
        - in the edges list, count the number of target ids for each source ids, and the
        number must be list_target_ids for each node
        - when you make the edges, ensure that there must not be more than 10 target node 
            ids connected to any given source node id in the graph. the number in list_target_ids
            for any given source node id must therefore be at most 10

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class Node(BaseModel):
    """
    Node class for the knowledge graph. Each node represents an entity.
    
    Attributes:
        id (int): Unique identifier for the node.
        label (str): Label or name of the node.
        color (str): Color of the node.
        num_targets (int): Number of target nodes connected to this node.