Update app.py

app.py

@@ -1,70 +1,155 @@
 import gradio as gr
-from huggingface_hub import InferenceClient
+import requests
 
+# ===== URL API =====
+URLS = {
+    "chatgpt": "http://neblora.fenst4r.life:5400/gpt",
+    "llama": "http://neblora.fenst4r.life:5500/llama",
+    "analyze_image": "http://neblora.fenst4r.life:4848/analyze-image",
+    "draw": "http://neblora.fenst4r.life:4000/draw",
+    "v2draw": "http://neblora.fenst4r.life:4000/v2draw",
+    "v3draw": "http://neblora.fenst4r.life:4000/v3draw",
+    "say": "http://neblora.fenst4r.life:4000/say",
+    "file": "https://fenst4r.life/api/file",
+    "stt": "http://neblora.fenst4r.life:5000/stt",
+    "tts": "http://neblora.fenst4r.life:4949/tts"
+}
 
-def respond(
-    message,
-    history: list[dict[str, str]],
-    system_message,
-    max_tokens,
-    temperature,
-    top_p,
-    hf_token: gr.OAuthToken,
-):
-    """
-    For more information on `huggingface_hub` Inference API support, please check the docs: https://huggingface.co/docs/huggingface_hub/v0.22.2/en/guides/inference
-    """
-    client = InferenceClient(token=hf_token.token, model="openai/gpt-oss-20b")
+# ===== Функции API =====
+def chat_api(text, model="GPT-4", tts=False):
+    payload = {"text": text, "model": model}
+    r = requests.post(URLS["chatgpt"], json=payload)
+    if r.status_code != 200:
+        return f"Ошибка: {r.status_code}", None
+    answer = r.json().get("response", "")
+    
+    audio_file = None
+    if tts:
+        tts_payload = {"text": answer, "voice":"nova"}
+        tts_r = requests.post(URLS["tts"], json=tts_payload)
+        if tts_r.status_code == 200:
+            audio_file = "output.mp3"
+            with open(audio_file, "wb") as f:
+                f.write(tts_r.content)
+    return answer, audio_file
 
-    messages = [{"role": "system", "content": system_message}]
+def llama_api(text):
+    r = requests.post(URLS["llama"], json={"text": text})
+    if r.status_code != 200:
+        return f"Ошибка: {r.status_code}"
+    return r.json().get("response", "")
 
-    messages.extend(history)
+def analyze_image_api(image):
+    r = requests.post(URLS["analyze_image"], files={"file": image})
+    if r.status_code != 200:
+        return f"Ошибка: {r.status_code}"
+    return r.json().get("description", "")
 
-    messages.append({"role": "user", "content": message})
+def draw_api(prompt, size="512x512"):
+    r = requests.post(URLS["draw"], json={"prompt": prompt, "size": size})
+    if r.status_code != 200:
+        return None
+    with open("draw_result.png", "wb") as f:
+        f.write(r.content)
+    return "draw_result.png"
 
-    response = ""
+def v2draw_api(prompt, format="json"):
+    r = requests.post(URLS["v2draw"], json={"prompt": prompt, "format": format})
+    if r.status_code != 200:
+        return "Ошибка"
+    if format=="json":
+        data = r.json()
+        return [img for img in data.get("images", [])]
+    return r.content
 
-    for message in client.chat_completion(
-        messages,
-        max_tokens=max_tokens,
-        stream=True,
-        temperature=temperature,
-        top_p=top_p,
-    ):
-        choices = message.choices
-        token = ""
-        if len(choices) and choices[0].delta.content:
-            token = choices[0].delta.content
+def v3draw_api(prompt, width=1280, height=1280, steps=20, scale=7.5, format="file"):
+    payload = {"prompt": prompt, "width": width, "height": height, "steps": steps, "scale": scale, "format": format}
+    r = requests.post(URLS["v3draw"], json=payload)
+    if r.status_code != 200:
+        return None
+    if format=="json":
+        return r.json().get("image")
+    with open("v3draw.png", "wb") as f:
+        f.write(r.content)
+    return "v3draw.png"
 
-        response += token
-        yield response
+def say_api(text):
+    r = requests.post(URLS["say"], json={"text": text})
+    if r.status_code != 200:
+        return f"Ошибка: {r.status_code}"
+    return r.json().get("text", "")
 
+def stt_api(audio_file):
+    r = requests.post(URLS["stt"], files={"file": audio_file})
+    if r.status_code != 200:
+        return f"Ошибка: {r.status_code}"
+    return r.json().get("text", "")
 
-"""
-For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
-"""
-chatbot = gr.ChatInterface(
-    respond,
-    type="messages",
-    additional_inputs=[
-        gr.Textbox(value="You are a friendly Chatbot.", label="System message"),
-        gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
-        gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
-        gr.Slider(
-            minimum=0.1,
-            maximum=1.0,
-            value=0.95,
-            step=0.05,
-            label="Top-p (nucleus sampling)",
-        ),
-    ],
-)
+def upload_file(files):
+    payload = {}
+    for file in files:
+        payload[file.name] = file.read().decode('utf-8')
+    r = requests.post(URLS["file"], json=payload)
+    if r.status_code != 200:
+        return f"Ошибка: {r.status_code}"
+    return r.json().get("url", "")
 
+# ===== Интерфейс Gradio =====
 with gr.Blocks() as demo:
-    with gr.Sidebar():
-        gr.LoginButton()
-    chatbot.render()
+    gr.Markdown("# NEIROST4R API Interface")
+    with gr.Tab("ChatGPT / TTS"):
+        text_input = gr.Textbox(label="Введите текст")
+        model_choice = gr.Radio(choices=["GPT-4", "GPT-5"], value="GPT-4", label="Модель")
+        tts_toggle = gr.Checkbox(label="Озвучить ответ")
+        chat_output = gr.Textbox(label="Ответ ChatGPT")
+        audio_output = gr.Audio(label="TTS", type="filepath")
+        gr.Button("Отправить").click(chat_api, inputs=[text_input, model_choice, tts_toggle], outputs=[chat_output, audio_output])
+    
+    with gr.Tab("LLaMA 3.1"):
+        llama_input = gr.Textbox(label="Введите текст")
+        llama_output = gr.Textbox(label="Ответ LLaMA")
+        gr.Button("Отправить").click(llama_api, inputs=[llama_input], outputs=[llama_output])
+    
+    with gr.Tab("Анализ изображения"):
+        image_input = gr.File(label="Выберите изображение", file_types=[".jpg", ".png", ".webp"])
+        image_desc = gr.Textbox(label="Описание изображения")
+        gr.Button("Анализировать").click(analyze_image_api, inputs=[image_input], outputs=[image_desc])
+    
+    with gr.Tab("Draw / v2draw / v3draw"):
+        prompt_input = gr.Textbox(label="Описание сцены")
+        draw_out = gr.Image(label="Результат Draw")
+        gr.Button("Draw").click(draw_api, inputs=[prompt_input], outputs=[draw_out])
+    
+    with gr.Tab("Say / STT"):
+        say_input = gr.Textbox(label="Введите текст")
+        say_output = gr.Textbox(label="Текстовое преобразование")
+        gr.Button("Say").click(say_api, inputs=[say_input], outputs=[say_output])
+        
+        stt_input = gr.File(label="Аудиофайл")
+        stt_output = gr.Textbox(label="Распознанный текст")
+        gr.Button("STT").click(stt_api, inputs=[stt_input], outputs=[stt_output])
+    
+    with gr.Tab("Файлы"):
+        file_input = gr.File(label="Загрузите файлы", file_types=[".txt", ".json"], file_types_allow_multiple=True)
+        file_url = gr.Textbox(label="Ссылка на файлы")
+        gr.Button("Загрузить").click(upload_file, inputs=[file_input], outputs=[file_url])
+    
+    with gr.Tab("Документация"):
+        gr.Markdown("""
+        ## Содержание
+        - Инструкция по API NEIROST4R
+        - Быстрый старт
+        - API версии 1-5
+        - Python примеры
+        - Библиотека neirost4r
+        - Профили
+        - Флаги
+        - Примеры
+        - Провайдеры и модели
+        - Обработка ошибок
 
+        Новости в канале PUR🩷 CHANNEL: https://t.me/pur_channel
+        Поддержка и баги: @error_kill
+        """)
 
-if __name__ == "__main__":
-    demo.launch()
+demo.launch()