File size: 4,372 Bytes
0119c00 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 | import os
from pathlib import Path
from typing import Any
import gradio as gr
from dotenv import load_dotenv
from openai import OpenAI
from prompts import MODE_DESCRIPTIONS, PROMPT_TEMPLATES
MODEL_NAME = "gpt-4.1-mini"
# Load environment variables from a local .env file if it exists.
load_dotenv(dotenv_path=Path(__file__).parent / ".env")
SYSTEM_PROMPT = (
"You are Advanced Python Tutor Bot, an expert and patient teacher for beginners. "
"Help with Python fundamentals, debugging, quizzes, and code quality. "
"When relevant, include beginner-friendly data structures and algorithms guidance "
"(lists, dicts, sets, stacks, queues, recursion, sorting, searching, Big-O at a simple level)."
)
def _history_to_messages(history: list[Any]) -> list[dict[str, str]]:
"""Convert Gradio chat history into OpenAI message objects.
Supports both older history formats (list of [user, assistant]) and
newer message formats (list of dicts).
"""
messages: list[dict[str, str]] = []
for item in history:
if isinstance(item, dict):
role = item.get("role")
content = item.get("content", "")
if role in {"user", "assistant"} and content:
messages.append({"role": role, "content": str(content)})
continue
if isinstance(item, (list, tuple)) and len(item) == 2:
user_text, assistant_text = item
if user_text:
messages.append({"role": "user", "content": str(user_text)})
if assistant_text:
messages.append({"role": "assistant", "content": str(assistant_text)})
return messages
def build_messages(mode: str, user_input: str, history: list[Any]) -> list[dict[str, str]]:
"""Build OpenAI messages using mode template + ongoing chat history."""
messages = [{"role": "system", "content": SYSTEM_PROMPT}]
messages.extend(_history_to_messages(history))
mode_instruction = PROMPT_TEMPLATES[mode].format(user_input=user_input)
messages.append({"role": "user", "content": mode_instruction})
return messages
def get_tutor_response(user_input: str, history: list[Any], mode: str) -> str:
"""Generate a response from OpenAI for the selected tutoring mode."""
if not user_input or not user_input.strip():
return "Please enter some text or code so I can help you."
api_key = os.getenv("OPENAI_API_KEY")
if not api_key:
return (
"Missing OPENAI_API_KEY. Add it to a `.env` file in this folder like: "
"OPENAI_API_KEY=your_key_here"
)
try:
client = OpenAI(api_key=api_key)
messages = build_messages(mode, user_input.strip(), history or [])
response = client.chat.completions.create(
model=MODEL_NAME,
messages=messages,
temperature=0.4,
)
return response.choices[0].message.content or "I could not generate a response. Please try again."
except Exception as error:
return f"Something went wrong while contacting the AI service: {error}"
def build_app() -> gr.Blocks:
theme = gr.themes.Soft(primary_hue="blue", secondary_hue="slate", neutral_hue="slate")
with gr.Blocks(title="Advanced Python Tutor Bot", theme=theme) as app:
gr.Markdown(
"""
# 🧠 Advanced Python Tutor Bot
A professional learning assistant for beginners: explanations, debugging, quizzes, and code improvements.
"""
)
with gr.Row():
with gr.Column(scale=2):
mode = gr.Dropdown(
choices=["Explain Concept", "Debug Code", "Quiz Me", "Improve Code"],
value="Explain Concept",
label="Tutor Mode",
info="Pick how you want the tutor to help in this chat.",
)
with gr.Column(scale=3):
mode_note = gr.Markdown(MODE_DESCRIPTIONS["Explain Concept"])
mode.change(lambda m: MODE_DESCRIPTIONS[m], inputs=mode, outputs=mode_note)
gr.ChatInterface(
fn=get_tutor_response,
additional_inputs=[mode],
)
return app
if __name__ == "__main__":
build_app().launch() |