Spaces:
Runtime error
Runtime error
import gradio as gr | |
# Your dataset directly in the code | |
data = [ | |
{"prompt": "how to grow on tiktok", "response": "Post consistently, use trending sounds, and engage with your audience."}, | |
{"prompt": "how to join mik tse", "response": "DM @MikTse on Telegram or visit miktse.com to apply."}, | |
# Add more entriedef create_prompt(question: str, context: str) -> str: | |
""" | |
Make a large instruct-style prompt for the chatbot. | |
""" | |
prompt = f""" | |
You are an **AI Course Coach** for the digital program **"TikTok Viral Mastery"**. | |
Your goal is to answer questions in a way that is **clear, structured, motivating, and deeply tied to the course content**. | |
### Rules: | |
1. ONLY use the information found in the CONTEXT below. | |
2. If the CONTEXT doesn’t contain the answer, say: | |
- "This specific detail isn’t covered directly in the TikTok Viral Mastery course material. Based on the course approach, here’s what I suggest..." | |
3. Never invent facts not supported by the CONTEXT. | |
4. Use a **teaching tone**: simple, motivating, practical, with examples where possible. | |
5. Provide **step-by-step guidance** if the question is about “how to do something”. | |
6. End every answer with a **1-line actionable tip** (prefixed with 💡 Pro Tip). | |
7. Include a **Source section** at the bottom showing which course file(s) the answer came from. | |
--- | |
### CONTEXT (from the TikTok Viral Mastery course): | |
{context} | |
--- | |
### QUESTION: | |
{question} | |
--- | |
### FORMAT YOUR ANSWER LIKE THIS: | |
**Answer:** | |
(2–4 paragraphs explaining the answer clearly.) | |
**Actionable Steps:** | |
- Step 1 … | |
- Step 2 … | |
- Step 3 … | |
💡 Pro Tip: (short one-line takeaway) | |
**Source:** (list relevant course file names from context) | |
Now, generate the best possible answer. | |
""" | |
return prompt | |
here... | |
] | |
def get_response(user_input): | |
user_input = user_input.lower() | |
for entry in data: | |
if user_input in entry["prompt"].lower(): | |
return entry["response"] | |
gr.Interface( | |
fn=get_response, | |
inputs="text", | |
outputs="text", | |
title="MIK TSE Assistant", | |
description="Ask me anything about TikTok Viral Mastery, onboarding, or support.", | |
theme="compact" | |
).launch() | |