app.py

import json
import gradio as gr
from smolagents import CodeAgent
import json
import random
from smolagents import TransformersModel
from smolagents import CodeAgent,DuckDuckGoSearchTool, HfApiModel,load_tool,tool
import datetime
import requests
import pytz
import yaml
import numpy as np

from tools.final_answer import FinalAnswerTool
from tools.visit_webpage import VisitWebpageTool
from tools.web_search import DuckDuckGoSearchTool
from typing import Optional, Tuple

model_id='https://pflgm2locj2t89co.us-east-1.aws.endpoints.huggingface.cloud'
model = HfApiModel(
    max_tokens=2096,
    temperature=0.5,
    # model_id='Qwen/Qwen2.5-Coder-32B-Instruct',
    model_id=model_id,
    # it is possible that this model may be overloaded
    custom_role_conversions=None,
)

# Import tool from Hub
# image_generation_tool = load_tool("agents-course/text-to-image", trust_remote_code=True)

#with open("prompts.yaml", 'r') as stream:
#    prompt_templates = yaml.safe_load(stream)

#final_answer = FinalAnswerTool()
visit_webpage = VisitWebpageTool()
web_search = DuckDuckGoSearchTool()

@tool
def provide_my_information(query: str) -> str:
    """
    Provide information about me (Tianqing LIU)based on the user's query.

    Args:
        query: The user's question or request for information.

    Returns:
        str: A response containing the requested information.
    """
    # Convert the query to lowercase for case-insensitive matching
    query = query.lower()
    my_info = None
    with open("info/info.json", 'r') as file:
        my_info = json.load(file)
    # Check for specific keywords in the query and return the corresponding information
    if "who"  in query or "about" in query or "introduce" in query or "presentation" in query:
        return f" {my_info['introduction']}."
    if "name" in query:
        return f"My name is {my_info['name']}."
    elif "location" in query:
        return f"I am located in {my_info['location']}."
    elif "occupation" in query or "job" in query or "work" in query:
        return f"I work as a {my_info['occupation']}."
    elif "education" in query or "educational" in query:
        return f"I have a {my_info['education']}."
    elif "skills" in query or "what can you do" in query:
        return f"My skills include: {', '.join(my_info['skills'])}."
    elif "hobbies" in query or "interests" in query:
        return f"My hobbies are: {', '.join(my_info['hobbies'])}."
    elif "contact" in query or "email" in query or "linkedin" in query or "github" in query or "cv" in query or "resume" in query:
        contact_info = my_info["contact"]
        return (
            f"You can contact me via email at {contact_info['email']}, "
            f"connect with me on LinkedIn at {contact_info['linkedin']}, "
            f"or check out my GitHub profile at {contact_info['github']}."
            f"or check out my website at {contact_info['website']}."
        )
    else:
        return "I'm sorry, I don't have information on that. Please ask about my name, location, occupation, education, skills, hobbies, or contact details."


agent = CodeAgent(
    model=model,
    tools=[provide_my_information],  ## add your tools here (don't remove final answer)
    max_steps=1,
    verbosity_level=1,
    grammar=None,
    planning_interval=None,
    name=None,
    description=None
    #prompt_templates=prompt_templates
)


def chatbot_response_json(user_input):
    my_info = None
    user_input = user_input.lower()
    with open("info/info.json", 'r') as file:
        my_info = json.load(file)

    if "who" in user_input or "about" in user_input or "introduce" in user_input or "presentation" in user_input:
        return f" {my_info['introduction']}."
    elif "name" in user_input:
        return f"My name is {my_info['name']}."
    elif "hello" in user_input:
        return f"Hello! I'm here to assist you. Feel free to ask me about my background, experience, education, or anything else you'd like to know!"
    elif "bye" in user_input or "bye" in user_input:
        return f"Bye."
    elif "location" in user_input:
        return f"I am located in {my_info['location']}."
    elif "phone" in user_input or "number" in user_input:
        return f"you can send me a message directly here. ex:  send message : your message"
    elif "experiences" in user_input or "career" in user_input or "experience" in user_input:
        return f"{my_info['career']}."
    elif "occupation" in user_input or "job" in user_input or "work" in user_input:
        return f"I work as a {my_info['occupation']}."
    elif "education" in user_input or "educational" in user_input:
        return f"I have a {my_info['education']}."
    elif "skills" in user_input or "what can you do" in user_input:
        return f"My skills include: {', '.join(my_info['skills'])}."
    elif "hobbies" in user_input or "interests" in user_input:
        return f"My hobbies are: {', '.join(my_info['hobbies'])}."
    elif "cv" in user_input or "resume" in user_input:
        return f"My cvs are: {', '.join(my_info['cv'])}."
    elif "contact" in user_input or "email" in user_input or "e-mail" in user_input or "linkedin" in user_input or "github":
        contact_info = my_info["contact"]
        return (
            f"You can contact me via email at {contact_info['email']}, "
            f"connect with me on LinkedIn at {contact_info['linkedin']}, "
            f"or check out my GitHub profile at {contact_info['github']}."
            f"or check out my website at {contact_info['website']}."
        )
    else:
        return agent.run(user_input)


def chatbot_response(user_input, history):
    """
       Get a response from the chatbot
       """
    request = user_input
    history = history or []
    response = chatbot_response_json(request)  # Call the chatbot logic
    #history.append((user_input, response))
    yield response


# Create the Gradio interface
#demo = gr.ChatInterface(fn=chatbot_response, title="My Personal Chatbot", description="Ask me anything about myself!")
demo = gr.ChatInterface(
    chatbot_response,
    type="messages",
    multimodal=False,
    title="Ask me anything about.....",
)
demo.launch()

if __name__ == "__main__":
    demo.launch()