Spaces:
Running
Running
File size: 2,138 Bytes
6d98bb6 8500420 6d98bb6 3cde712 6d98bb6 8500420 |
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 |
import gradio as gr
from sentence_transformers import SentenceTransformer, util
import numpy as np
# Load embedding model
model = SentenceTransformer("Qwen/Qwen3-Embedding-0.6B")
# Sample startup goals (can be expanded)
known_goals = [
"Build an MVP for a fintech app helping freelancers manage taxes",
"Create a marketplace for local home service providers",
"Launch a SaaS dashboard for tracking team productivity",
"Build a platform to connect investors and climate-tech startups",
"Create an AI tool that helps students summarize academic papers",
"Develop a B2B tool to automate invoice reconciliation",
]
# Sample advice linked to each goal
advice_lookup = {
known_goals[0]: "Use Stripe + Plaid for finance infra. Focus on freelancer pain points first.",
known_goals[1]: "Start with one city. Validate supply-demand balance before scaling.",
known_goals[2]: "Build Notion-style prototypes first. Talk to HR managers in startups.",
known_goals[3]: "Target funds with ESG mandates. Find pilot customers in VC portfolios.",
known_goals[4]: "Use GPT + citation tools. Talk to students and professors for feedback.",
known_goals[5]: "Integrate with QuickBooks early. Focus on finance teams at SMEs.",
}
# Pre-compute known embeddings
known_embeddings = model.encode(known_goals)
# Define logic
def find_similar_advice(user_goal):
input_embedding = model.encode([user_goal])
scores = util.cos_sim(input_embedding, known_embeddings)[0].cpu().numpy()
top_indices = np.argsort(scores)[::-1][:3]
result = ""
for i in top_indices:
goal = known_goals[i]
advice = advice_lookup[goal]
result += f"🎯 **Similar Goal**: {goal}\n💡 **Advice**: {advice}\n\n"
return result
# Gradio UI
demo = gr.Interface(
fn=find_similar_advice,
inputs=gr.Textbox(label="Describe your startup goal", placeholder="e.g. Build a fintech app for freelancers"),
outputs=gr.Markdown(),
title="🧠 AI Cofounder Similarity Coach",
description="Get matched with similar startup goals and actionable advice using Qwen3 Embeddings"
)
demo.launch()
|