app.py

import gradio as gr
import numpy as np
from openai import OpenAI
import voyageai
from typing import List, Tuple


def initialize_clients(openai_key: str, voyage_key: str):
    """Initialize API clients with provided keys or environment variables"""
    openai_key = openai_key.strip() or None
    voyage_key = voyage_key.strip() or None
    return OpenAI(api_key=openai_key), voyageai.Client(api_key=voyage_key)


def get_openai_embedding(client: OpenAI, text: str) -> List[float]:
    """Get embedding from OpenAI's text-embedding-3-large model"""
    response = client.embeddings.create(input=text, model="text-embedding-3-large")
    return response.data[0].embedding


def get_voyage_embedding(client: voyageai.Client, text: str) -> List[float]:
    """Get embedding from Voyage's voyage-3 model"""
    result = client.embed([text], model="voyage-3")
    return result.embeddings[0]


def cosine_similarity(a: List[float], b: List[float]) -> float:
    """Calculate cosine similarity between two vectors"""
    a = np.array(a)
    b = np.array(b)
    return np.dot(a, b) / (np.linalg.norm(a) * np.linalg.norm(b))


def process_texts(
    openai_key: str, voyage_key: str, text1: str, text2: str
) -> Tuple[float, float, float]:
    """Process two texts and return their embeddings and similarities"""
    # Initialize clients with provided keys
    openai_client, voyage_client = initialize_clients(openai_key, voyage_key)

    # Get embeddings from both models
    openai_emb1 = get_openai_embedding(openai_client, text1)
    openai_emb2 = get_openai_embedding(openai_client, text2)
    voyage_emb1 = get_voyage_embedding(voyage_client, text1)
    voyage_emb2 = get_voyage_embedding(voyage_client, text2)

    # Calculate similarities
    openai_similarity = cosine_similarity(openai_emb1, openai_emb2)
    voyage_similarity = cosine_similarity(voyage_emb1, voyage_emb2)

    # Calculate difference in similarities
    similarity_diff = abs(openai_similarity - voyage_similarity)

    return openai_similarity, voyage_similarity, similarity_diff


def compare_embeddings(
    openai_key: str, voyage_key: str, text1: str, text2: str
) -> Tuple[str, str, str]:
    """Compare embeddings from both models and return formatted results"""
    try:
        openai_sim, voyage_sim, sim_diff = process_texts(
            openai_key, voyage_key, text1, text2
        )

        openai_result = f"{openai_sim:.4f}"
        voyage_result = f"{voyage_sim:.4f}"
        diff_result = f"{sim_diff:.4f}"

        return openai_result, voyage_result, diff_result
    except Exception as e:
        return f"Error: {str(e)}", "", ""


# Create Gradio interface
with gr.Blocks() as demo:
    gr.Markdown("""
    # 埋め込みモデルの比較デモ
    
    対象モデルは OpenAI の text-embedding-3-large と Voyage AI の voyage-3 のふたつ。入力テキストに対して、それぞれのモデルでの類似度とその差分を計算する。
    
    ## API Key
    
    OpenAI と Voyage AI の API キーは下記より。
    
    - OpenAI API Key: [https://platform.openai.com/account/api-keys](https://platform.openai.com/account/api-keys)
    - Voyage AI API Key: [https://dash.voyageai.com](https://dash.voyageai.com)
    """)

    with gr.Row():
        openai_key = gr.Textbox(
            label="OpenAI API Key", placeholder="sk-...", type="password", scale=2
        )
        voyage_key = gr.Textbox(
            label="Voyage AI API Key", placeholder="pa-...", type="password", scale=2
        )

    with gr.Row():
        text1 = gr.Textbox(label="Text 1", lines=3)
        text2 = gr.Textbox(label="Text 2", lines=3)

    compare_btn = gr.Button("Compare")

    with gr.Row():
        openai_output = gr.Textbox(label="OpenAI text-embedding-3-large Similarity")
        voyage_output = gr.Textbox(label="Voyage AI voyage-3 Similarity")
        diff_output = gr.Textbox(label="Absolute Difference")

    compare_btn.click(
        compare_embeddings,
        inputs=[openai_key, voyage_key, text1, text2],
        outputs=[openai_output, voyage_output, diff_output],
    )

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