Real Time Search Engine AI - Real-Time AI Search Assistant RealtimeSearchEngine.py is an advanced AI assistant integrating real-time Google search and Groq’s LLaMA-3 model for accurate, up-to-date responses. It processes user queries, retrieves web data, and refines answers using AI, ensuring professional and well-structured responses.

RealtimeSearchEngine.py

from googlesearch import search
from groq import Groq
from json import load, dump
import datetime
from dotenv import dotenv_values


env_vars = dotenv_values(".env")

Username =  env_vars.get("Username")
Assistantname = env_vars.get("Assistantname")
GroqAPIKey = env_vars.get("GroqAPIKey")

client =  Groq(api_key=GroqAPIKey)

System = f"""Hello, I am {Username}, You are a very accurate and advanced AI chatbot named {Assistantname} which has real-time up-to-date information from the internet.
*** Provide Answers In a Professional Way, make sure to add full stops, commas, question marks, and use proper grammar.***
*** Just answer the question from the provided data in a professional way. ***"""

try:
    with open(r"Data\ChatLog.json", "r") as f:
        messages = load(f)
except:
    with open(r"Data\ChatLog.json", "w") as f:
        dump([], f)

def GoogleSearch(query):
    results = list(search(query, advanced=True, num_results=5))
    Answer = f"The search results for '{query}' are:\n[start]\n"

    for i in results:
        Answer += f"Title: {i.title}\nDescription: {i.description}\n\n"

    Answer += "[end]"
    return Answer

def AnswerModifier(Answer):
    lines = Answer.split('\n')
    non_empty_lines = [line for line in lines if line.strip()]
    modified_answer = '\n'.join(non_empty_lines)
    return modified_answer


SystemChatBot = [
    {"role": "system", "content": System},
    {"role": "user", "content": "Hi"},
    {"role": "assistant", "content": "Hello, how can I help you?"},
]

def Information():
    data = ""
    current_date_time = datetime.datetime.now()
    day = current_date_time.strftime("%A")
    date = current_date_time.strftime("%d")
    month = current_date_time.strftime("%B")
    year = current_date_time.strftime("%Y")
    hour = current_date_time.strftime("%H")
    minute = current_date_time.strftime("%M")
    second = current_date_time.strftime("%S")

    data += f"Use this real-time information if needed,\n"
    data += f"Day: {day}\nDate: {date}\nMonth:{month}\nYear: {year}\n"
    data += f"Time: {hour}\n hours : {minute} minutes : {second} seconds.\n"

    return data

def RealtimeSearhEngine(prompt):
    global SystemChatBot, messages

    with open(r"Data\ChatLog.json", "r") as f:
        messages = load(f)

    messages.append({"role": "user", "content": f"{prompt}"})
    SystemChatBot.append({"role": "system", "content": GoogleSearch(prompt)})

    completion = client.chat.completions.create(
            model = "llama3-70b-8192",
            messages= SystemChatBot + [{"role": "system", "content": Information()}] + messages,
            temperature=0.7,
            max_tokens=1024,
            top_p=1,
            stream=True,
            stop=None
    )

    Answer = ""

    for chunk in completion:
        if chunk.choices[0].delta.content:
            Answer += chunk.choices[0].delta.content

    Answer = Answer.replace("</ s>", "")

    messages.append({"role": "assistant", "content": Answer})

    with open(r"Data\ChatLog.json", "w") as f:
        dump(messages, f, indent=4)

    SystemChatBot.pop()
    return AnswerModifier(Answer=Answer)

if __name__ == "__main__":
    while True:
        print(RealtimeSearhEngine(input("Enter Your Query: ")))