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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()
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