Update app.py

app.py

@@ -1,191 +1,93 @@
 import os
 import time
 import json
-import traceback
 import gradio as gr
 from openai import OpenAI
 
-HOSTS = {
-    "Domestic (Lower Latency)": "https://api.chatanywhere.tech/v1",
-    "Overseas (Fallback)": "https://api.chatanywhere.org/v1"
+API_HOSTS = {
+    "Domestic": "https://api.chatanywhere.tech/v1",
+    "Overseas": "https://api.chatanywhere.org/v1"
 }
 
-MODELS = {
-    "o3": {"input": "0.014 / 1K Tokens", "output": "0.056 / 1K Tokens", "support": "support", "features": "Sets new standards for math, science, coding, visual reasoning tasks, and technical writing. Points o3-2025-04-16"},
-    "o3-2025-04-16": {"input": "0.014 / 1K Tokens", "output": "0.056 / 1K Tokens", "support": "support", "features": "Sets new standards for math, science, coding, visual reasoning tasks, and technical writing."},
-    "o4-mini": {"input": "0.0088 / 1K Tokens", "output": "0.0352 / 1K Tokens", "support": "support", "features": "Sets new standards for math, science, coding, visual reasoning tasks, and technical writing."},
-    "o4-mini-2025-04-16": {"input": "0.0088 / 1K Tokens", "output": "0.0352 / 1K Tokens", "support": "support", "features": "Sets new standards for math, science, coding, visual reasoning tasks, and technical writing."},
-    "gpt-4.1": {"input": "0.014 / 1K Tokens", "output": "0.056 / 1K Tokens", "support": "support", "features": "Improvements in encoding, instruction tracking, and long context. 1M input 32k output."},
-    "gpt-4.1-2025-04-14": {"input": "0.014 / 1K Tokens", "output": "0.056 / 1K Tokens", "support": "support", "features": "Improvements in encoding, instruction tracking, and long context, with 1M input and 32k output."},
-    "gpt-4.1-mini": {"input": "0.0028 / 1K Tokens", "output": "0.0112 / 1K Tokens", "support": "support", "features": "Improvements in encoding, instruction tracking, and long context."},
-    "gpt-4.1-mini-2025-04-14": {"input": "0.0028 / 1K Tokens", "output": "0.0112 / 1K Tokens", "support": "support", "features": "Improvements in encoding, instruction tracking, and long context, with 1M input and 32k output."},
-    "gpt-4.1-nano": {"input": "0.0007 / 1K Tokens", "output": "0.0028 / 1K Tokens", "support": "support", "features": "Improvements in encoding, instruction tracking, and long context."},
-    "gpt-4.1-nano-2025-04-14": {"input": "0.0007 / 1K Tokens", "output": "0.0028 / 1K Tokens", "support": "support", "features": "Improvements in encoding, instruction tracking, and long context, with 1M input and 32k output."},
-    "gpt-oss-20b": {"input": "0.0008 / 1K Tokens", "output": "0.0032 / 1K Tokens", "support": "support", "features": "Open source model."},
-    "gpt-oss-120b": {"input": "0.0044 / 1K Tokens", "output": "0.0176 / 1K Tokens", "support": "support", "features": "Open source model."},
-    "gpt-3.5-turbo": {"input": "0.0035 / 1K Tokens", "output": "0.0105 / 1K Tokens", "support": "support", "features": "Default model, equal to gpt-3.5-turbo-0125."},
-    "gpt-3.5-turbo-1106": {"input": "0.007 / 1K Tokens", "output": "0.014 / 1K Tokens", "support": "support", "features": "Model updated on November 6, 2023."},
-    "gpt-3.5-turbo-0125": {"input": "0.0035 / 1K Tokens", "output": "0.0105 / 1K Tokens", "support": "support", "features": "Model from January 25, 2024."},
-    "gpt-3.5-turbo-16k": {"input": "0.021 / 1K Tokens", "output": "0.028 / 1K Tokens", "support": "support", "features": "Longer context (16k)."},
-    "gpt-3.5-turbo-instruct": {"input": "0.0105 / 1K Tokens", "output": "0.014 / 1K Tokens", "support": "support", "features": "Completions-style instruct model."},
-    "o1-mini": {"input": "0.0088 / 1K Tokens", "output": "0.0352 / 1K Tokens", "support": "support", "features": "Reasoning models for complex tasks."},
-    "o1-preview": {"input": "0.105 / 1K Tokens", "output": "0.42 / 1K Tokens", "support": "support", "features": "Preview reasoning model."},
-    "o3-mini [5]": {"input": "0.0088 / 1K Tokens", "output": "0.0352 / 1K Tokens", "support": "support", "features": "Reasoning models."},
-    "o1 [5]": {"input": "0.12 / 1K Tokens", "output": "0.48 / 1K Tokens", "support": "support", "features": "Powerful reasoning model."},
-    "gpt-4o-search-preview": {"input": "0.0175 / 1K Tokens", "output": "0.07 / 1K Tokens", "support": "support", "features": "Search-enabled model (+search fee)."},
-    "gpt-4o-search-preview-2025-03-11": {"input": "0.0175 / 1K Tokens", "output": "0.07 / 1K Tokens", "support": "support", "features": "Search-enabled model."},
-    "gpt-4o-mini-search-preview": {"input": "0.00105 / 1K Tokens", "output": "0.0042 / 1K Tokens", "support": "support", "features": "Search-enabled mini model."},
-    "gpt-4o-mini-search-preview-2025-03-11": {"input": "0.00105 / 1K Tokens", "output": "0.0042 / 1K Tokens", "support": "support", "features": "Search-enabled mini model."},
-    "gpt-4": {"input": "0.21 / 1K Tokens", "output": "0.42 / 1K Tokens", "support": "support", "features": "Default GPT-4 family model."},
-    "gpt-4o": {"input": "0.0175 / 1K Tokens + Image Fee", "output": "0.07 / 1K Tokens", "support": "support", "features": "Cheaper/faster GPT-4O variant (+image fee)."},
-    "gpt-4o-2024-05-13": {"input": "0.035 / 1K Tokens + image fee", "output": "0.105 / 1K Tokens", "support": "support", "features": "GPT-4O release from 2024-05-13."},
-    "gpt-4o-2024-08-06": {"input": "0.0175 / 1K Tokens + Image Fee", "output": "0.07 / 1K Tokens", "support": "support", "features": "Supports 128k input and 16k output."},
-    "gpt-4o-2024-11-20": {"input": "0.0175 / 1K Tokens + Image Fee", "output": "0.07 / 1K Tokens", "support": "support", "features": "Improved creative writing."},
-    "chatgpt-4o-latest": {"input": "0.035 / 1K Tokens + image fee", "output": "0.105 / 1K Tokens", "support": "support", "features": "Dynamically updated version."},
-    "gpt-4o-mini": {"input": "0.00105 / 1K Tokens + Image Fee", "output": "0.0042 / 1K Tokens", "support": "support", "features": "Mini GPT-4O with image reading."},
-    "gpt-4-0613": {"input": "0.21 / 1K Tokens", "output": "0.42 / 1K Tokens", "support": "support", "features": "Updated June 13, 2023."},
-    "gpt-4-turbo-preview": {"input": "0.07 / 1K Tokens", "output": "0.21 / 1K Tokens", "support": "support", "features": "Preview turbo variant (128K input)."},
-    "gpt-4-0125-preview": {"input": "0.07 / 1K Tokens", "output": "0.21 / 1K Tokens", "support": "support", "features": "Preview updated Jan 25, 2024."},
-    "gpt-4-1106-preview": {"input": "0.07 / 1K Tokens", "output": "0.21 / 1K Tokens", "support": "support", "features": "Preview updated Nov 6, 2023."},
-    "gpt-4-vision-preview": {"input": "0.07 / 1K Tokens + Image Fee", "output": "0.21 / 1K Tokens", "support": "support", "features": "Multimodal with image recognition."},
-    "gpt-4-turbo": {"input": "0.07 / 1K Tokens + Image Fee", "output": "0.21 / 1K Tokens", "support": "support", "features": "Multimodal, function tools."},
-    "gpt-4-turbo-2024-04-09": {"input": "0.07 / 1K Tokens + image fee", "output": "0.21 / 1K Tokens", "support": "support", "features": "Preview turbo model."},
-    "gpt-4.1-ca": {"input": "0.008 / 1K Tokens", "output": "0.032 / 1K Tokens", "support": "support", "features": "Third-party provider CA variant."},
-    "gpt-4.1-mini-ca": {"input": "0.0016 / 1K Tokens", "output": "0.0064 / 1K Tokens", "support": "support", "features": "CA mini variant."},
-    "gpt-4.1-nano-ca": {"input": "0.0004 / 1K Tokens", "output": "0.003 / 1K Tokens", "support": "support", "features": "CA nano variant."},
-    "gpt-3.5-turbo-ca": {"input": "0.001 / 1K Tokens", "output": "0.0016 / 1K Tokens", "support": "support", "features": "CA region variant."},
-    "gpt-4-ca": {"input": "0.12 / 1K Tokens", "output": "0.24 / 1K Tokens", "support": "support", "features": "CA region variant."},
-    "gpt-4-turbo-ca": {"input": "0.04 / 1K Tokens + image fees", "output": "0.12 / 1K Tokens", "support": "support", "features": "CA region turbo."},
-    "gpt-4o-ca": {"input": "0.01 / 1K Tokens + image fees", "output": "0.04 / 1K Tokens", "support": "support", "features": "CA region GPT-4O."},
-    "gpt-4o-mini-ca": {"input": "0.00075 / 1K Tokens", "output": "0.003 / 1K Tokens", "support": "support", "features": "CA mini."},
-    "o1-mini-ca": {"input": "0.012 / 1K Tokens", "output": "0.048 / 1K Tokens", "support": "support", "features": "CA reasoning mini."},
-    "o1-preview-ca": {"input": "0.06 / 1K Tokens", "output": "0.24 / 1K Tokens", "support": "support", "features": "CA preview reasoning."}
-
+MODELS_INFO = {
+    "gpt-3.5-turbo": {"input_price": "0.0035", "output_price": "0.0105", "features": "Default model, equivalent to gpt-3.5-turbo-0125"},
+    "o1-preview": {"input_price": "0.105", "output_price": "0.42", "features": "Powerful preview reasoning model"},
+    "gpt-4o": {"input_price": "0.0175", "output_price": "0.07", "features": "Cheaper and faster GPT-4O; supports image fee"},
+    "gpt-4-turbo": {"input_price": "0.07", "output_price": "0.21", "features": "Multimodal with image recognition, function tools support"},
+    "gpt-4o-ca": {"input_price": "0.01", "output_price": "0.04", "features": "Cheap CA variant, but limited stability/prior daily limit"}
 }
 
-def create_client(base_url):
-    api_key = os.getenv("OPENAI_API_KEY")
-    if not api_key:
-        raise ValueError("Missing OPENAI_API_KEY environment variable")
-    return OpenAI(api_key=api_key, base_url=base_url)
+def create_client(host):
+    key = os.getenv("OPENAI_API_KEY")
+    if not key:
+        raise ValueError("Missing environment variable: OPENAI_API_KEY")
+    return OpenAI(api_key=key, base_url=host)
 
 def get_model_card(model_name):
-    m = MODELS.get(model_name)
-    if not m:
-        return "Model not found in catalog"
-    return f"**{model_name}**\n\nInput price: {m['input']}\n\nOutput price: {m['output']}\n\nSupport: {m['support']}\n\n{m['features']}"
+    info = MODELS_INFO.get(model_name, {})
+    if not info:
+        return "Model info not available."
+    return (
+        f"**{model_name}**\n\n"
+        f"Input price (/1K tokens): {info['input_price']}\n\n"
+        f"Output price (/1K tokens): {info['output_price']}\n\n"
+        f"Features: {info['features']}"
+    )
 
-def export_history(history):
+def respond(user, history, host_choice, model_name, temperature, top_p, max_tokens, sys_prompt):
+    history = history or []
+    if not user.strip():
+        return history + [("", "⚠️ Please enter a message.")]
     try:
-        fname = f"chat_history_{int(time.time())}.json"
-        with open(fname, "w", encoding="utf-8") as f:
-            json.dump([{"user": u, "assistant": a} for u, a in (history or [])], f, ensure_ascii=False, indent=2)
-        return f"Saved to {fname}"
+        client = create_client(API_HOSTS[host_choice])
     except Exception as e:
-        return f"Export failed: {e}"
-
-def respond_stream(user_message, history, host_choice, model_name, temperature, top_p, max_tokens, system_prompt):
-    history = history or []
-    if not user_message or not user_message.strip():
-        yield history + [("", "⚠️ Please enter a message to send.")]
-        return
-    messages = []
-    sys_prompt = system_prompt.strip() if system_prompt and system_prompt.strip() else "You are a helpful, concise assistant."
-    messages.append({"role": "system", "content": sys_prompt})
-    for human, ai in history:
-        messages.append({"role": "user", "content": human})
-        messages.append({"role": "assistant", "content": ai})
-    messages.append({"role": "user", "content": user_message})
-    last_error = None
-    hosts_to_try = [HOSTS.get(host_choice)] if HOSTS.get(host_choice) else list(HOSTS.values())
-    for base in hosts_to_try:
-        try:
-            client = create_client(base)
-        except Exception as e:
-            last_error = e
-            continue
-        try:
-            try:
-                stream = client.chat.completions.stream(model=model_name, messages=messages, temperature=float(temperature), top_p=float(top_p), max_tokens=int(max_tokens), timeout=30)
-                partial = ""
-                last_update = time.time()
-                with stream as s:
-                    for event in s:
-                        try:
-                            if getattr(event, "type", None) == "message.delta":
-                                delta = getattr(event, "delta", None)
-                                content = getattr(delta, "content", None) if delta is not None else None
-                                if content:
-                                    partial += content
-                                    if time.time() - last_update > 0.15:
-                                        yield history + [(user_message, partial)]
-                                        last_update = time.time()
-                            elif getattr(event, "type", None) == "message":
-                                content = getattr(event, "message", None)
-                                content_text = None
-                                if content and hasattr(content, "content"):
-                                    content_text = getattr(content.content, "get", lambda k, d=None: None)("text", None) if hasattr(content, "content") else None
-                                if content_text:
-                                    partial += content_text
-                                    yield history + [(user_message, partial)]
-                        except Exception:
-                            pass
-                if not partial.strip():
-                    partial = "No output received from model. Possible reasons: invalid model, API error, usage limits, or network timeout."
-                history.append((user_message, partial))
-                yield history
-                return
-            except AttributeError:
-                resp = client.chat.completions.create(model=model_name, messages=messages, temperature=float(temperature), top_p=float(top_p), max_tokens=int(max_tokens))
-                bot_reply = ""
-                try:
-                    bot_reply = resp.choices[0].message.content
-                except Exception:
-                    try:
-                        bot_reply = resp["choices"][0]["message"]["content"]
-                    except Exception:
-                        bot_reply = str(resp)
-                if not bot_reply or not str(bot_reply).strip():
-                    bot_reply = "No output received from model. Possible reasons: invalid model, API error, usage limits, or network timeout."
-                history.append((user_message, bot_reply))
-                yield history
-                return
-        except Exception as e:
-            last_error = e
-            continue
-    err_text = f"❌ All hosts failed. Last error: {last_error}\nCheck OPENAI_API_KEY, selected model, and network connectivity."
-    history.append((user_message, err_text))
-    yield history
+        return history + [("", f"❌ {e}")]
+    messages = [{"role": "system", "content": sys_prompt or "You are a helpful assistant."}]
+    for u, a in history:
+        messages.append({"role": "user", "content": u})
+        messages.append({"role": "assistant", "content": a})
+    messages.append({"role": "user", "content": user})
 
-model_choices = sorted(MODELS.keys())
+    try:
+        resp = client.chat.completions.create(
+            model=model_name,
+            messages=messages,
+            temperature=temperature,
+            top_p=top_p,
+            max_tokens=max_tokens
+        )
+        out = resp.choices[0].message.content.strip() or "No response received."
+    except Exception as e:
+        err = str(e)
+        if "429" in err:
+            out = (
+                "🚫 Daily quota reached for the selected model (429).\n"
+                "Please try again after 00:00 (China time) or switch models/hosts."
+            )
+        else:
+            out = f"❌ API Error: {e}"
+    history.append((user, out))
+    return history
 
-with gr.Blocks(title="Polished GPT App", theme=gr.themes.Soft()) as demo:
-    gr.Markdown("<h2 style='text-align:center'>Polished GPT UI — Model Catalog Integrated</h2>")
+with gr.Blocks(title="ChatAnywhere-powered Chatbot", theme=gr.themes.Soft()) as demo:
+    gr.Markdown("##  ChatAnywhere Chatbot\nPowered by the ChatAnywhere API — Use wisely!")
     with gr.Row():
         with gr.Column(scale=3):
-            chatbot = gr.Chatbot(label="Conversation", height=520, show_copy_button=True, render_markdown=True)
-            with gr.Row():
-                txt = gr.Textbox(placeholder="Type a message and press Enter", lines=2)
-                send = gr.Button("Send", variant="primary")
-            with gr.Row():
-                stop_btn = gr.Button("Stop", variant="secondary")
-                clear_btn = gr.Button("Clear", variant="secondary")
-                export_btn = gr.Button("Export")
-                status = gr.Markdown("")
+            chat = gr.Chatbot(label="Chat", height=500, show_copy_button=True, render_markdown=True)
+            msg = gr.Textbox(placeholder="Type your message...", lines=2)
+            clear = gr.Button("Clear")
         with gr.Column(scale=1):
-            host = gr.Radio(list(HOSTS.keys()), value="Domestic (Lower Latency)", label="API Host")
-            model_dropdown = gr.Dropdown(model_choices, value="gpt-3.5-turbo", label="Model")
+            host = gr.Radio(list(API_HOSTS.keys()), value="Domestic", label="API Host")
+            model = gr.Dropdown(list(MODELS_INFO.keys()), value="gpt-3.5-turbo", label="Model")
             model_card = gr.Markdown(get_model_card("gpt-3.5-turbo"))
             temperature = gr.Slider(0.0, 1.5, value=0.7, step=0.05, label="Temperature")
             top_p = gr.Slider(0.05, 1.0, value=1.0, step=0.05, label="Top-p")
             max_tokens = gr.Slider(64, 8192, value=512, step=64, label="Max Tokens")
-            system_prompt = gr.Textbox(label="System Prompt (optional)", lines=3, placeholder="You are a helpful assistant.")
-    send.click(respond_stream, [txt, chatbot, host, model_dropdown, temperature, top_p, max_tokens, system_prompt], chatbot, queue=True)
-    txt.submit(respond_stream, [txt, chatbot, host, model_dropdown, temperature, top_p, max_tokens, system_prompt], chatbot, queue=True)
-    model_dropdown.change(lambda m: get_model_card(m), model_dropdown, model_card)
-    clear_btn.click(lambda: [], None, chatbot)
-    export_btn.click(lambda h: export_history(h), chatbot, status)
-    stop_btn.click(lambda: "stop", None, None)
+            sys_prompt = gr.Textbox(label="System Prompt (optional)", lines=2)
+    msg.submit(respond, [msg, chat, host, model, temperature, top_p, max_tokens, sys_prompt], chat)
+    model.change(lambda m: get_model_card(m), model, model_card)
+    clear.click(lambda: [], None, chat)
+    msg.submit(lambda _: "", msg, msg)
 
 if __name__ == "__main__":
-    demo.queue().launch(server_name="0.0.0.0", server_port=7860, show_api=False)
+    demo.launch()