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import gradio as gr | |
from huggingface_hub import InferenceClient | |
# 使用可能なモデルのリスト | |
models = ["Sakalti/Saba1.5-Pro", "Sakalti/Saba2-Preview", "Sakalti/Saba2.1-Preview"] | |
def respond( | |
message, | |
history: list[tuple[str, str]], | |
system_message, | |
max_tokens, | |
temperature, | |
top_p, | |
selected_model | |
): | |
# デバッグ用: 各入力値の型を出力 | |
print(f"Message: {message} (Type: {type(message)})") | |
print(f"History: {history} (Type: {type(history)})") | |
print(f"System Message: {system_message} (Type: {type(system_message)})") | |
print(f"Max Tokens: {max_tokens} (Type: {type(max_tokens)})") | |
print(f"Temperature: {temperature} (Type: {type(temperature)})") | |
print(f"Top-p: {top_p} (Type: {type(top_p)})") | |
print(f"Selected Model: {selected_model} (Type: {type(selected_model)})") | |
# 型変換: selected_modelを文字列に変換 | |
selected_model = str(selected_model) | |
# 選択したモデルに基づいてInferenceClientを初期化 | |
client = InferenceClient(selected_model) | |
messages = [{"role": "system", "content": system_message}] | |
for val in history: | |
if val[0]: | |
messages.append({"role": "user", "content": val[0]}) | |
if val[1]: | |
messages.append({"role": "assistant", "content": val[1]}) | |
messages.append({"role": "user", "content": message}) | |
response = "" | |
for message in client.chat_completion( | |
messages, | |
max_tokens=max_tokens, | |
stream=True, | |
temperature=temperature, | |
top_p=top_p, | |
): | |
token = message.choices[0].delta.content | |
response += token | |
yield response | |
# インターフェース | |
demo = gr.ChatInterface( | |
respond, | |
additional_inputs=[ | |
gr.Textbox(value="あなたはフレンドリーなチャットボットです。", label="システムメッセージ"), | |
gr.Slider(minimum=1, maximum=2048, value=768, step=1, label="新規トークン最大"), | |
gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="温度"), | |
gr.Slider( | |
minimum=0.1, | |
maximum=1.0, | |
value=0.95, | |
step=0.05, | |
label="Top-p (核 sampling)", | |
), | |
gr.Dropdown(choices=models, value=models[0], label="モデル"), | |
], | |
concurrency_limit=30 # 例: 同時に30つのリクエストを処理 | |
) | |
if __name__ == "__main__": | |
demo.launch(share=True) |