add: upload gradio

app.py

@@ -0,0 +1,118 @@
+import os
+import time
+from typing import List, Tuple, Optional, Dict, Union
+
+import requests
+import gradio as gr
+
+TITLE = """<h1 align="center">Insight LLM 💬</h1>"""
+SUBTITLE = """<h2 align="center">Effortlessly analyze and compare Thai stocks with advanced LLM insights.</h2>"""
+DUPLICATE = """
+<div style="text-align: center; display: flex; justify-content: center; align-items: center;">
+    <span>Duplicate the Space and run securely with your API KEY.
+    </span>
+</div>
+"""
+
+AVATAR_IMAGES = (
+    None,
+    "https://media.roboflow.com/spaces/gemini-icon.png"
+)
+
+CHAT_HISTORY = List[Tuple[Optional[Union[Tuple[str], str]], Optional[str]]]
+
+def preprocess_chat_history(
+    history: CHAT_HISTORY
+) -> List[Dict[str, Union[str, List[str]]]]:
+    messages = []
+    for user_message, model_message in history:
+        if isinstance(user_message, tuple):
+            pass
+        elif user_message is not None:
+            messages.append({'role': 'user', 'parts': [user_message]})
+        if model_message is not None:
+            messages.append({'role': 'model', 'parts': [model_message]})
+    return messages
+
+def user(text_prompt: str, chatbot: CHAT_HISTORY):
+    if text_prompt:
+        chatbot.append((text_prompt, None))
+    return "", chatbot
+
+def bot(
+    chatbot: CHAT_HISTORY
+):
+    if len(chatbot) == 0:
+        return chatbot
+
+    if chatbot[-1][0] and isinstance(chatbot[-1][0], str):
+        text_prompt = chatbot[-1][0]
+        try:
+            response = requests.get(
+                "https://api-obon.conf.in.th/team15/query",
+                params={"text": text_prompt}
+            )
+            response.raise_for_status()  # Raise an error for bad status codes
+
+            try:
+                response_json = response.json()
+                chatbot[-1][1] = response_json.get("text", "")
+            except ValueError:
+                chatbot[-1][1] = f"{response.text}"
+        except requests.exceptions.RequestException as e:
+            chatbot[-1][1] = f"Error: {e}"
+    else:
+        chatbot[-1][1] = "Invalid input"
+
+    return chatbot
+
+chatbot_component = gr.Chatbot(
+    label='API Chatbot',
+    bubble_full_width=False,
+    avatar_images=AVATAR_IMAGES,
+    scale=2,
+    height=400
+)
+text_prompt_component = gr.Textbox(
+    placeholder="Hi there! [press Enter]", show_label=False, autofocus=True, scale=8
+)
+run_button_component = gr.Button(value="Run", variant="primary", scale=1)
+
+user_inputs = [
+    text_prompt_component,
+    chatbot_component
+]
+
+bot_inputs = [
+    chatbot_component
+]
+
+with gr.Blocks() as demo:
+    gr.HTML(TITLE)
+    gr.HTML(SUBTITLE)
+    gr.HTML(DUPLICATE)
+    with gr.Column():
+        chatbot_component.render()
+        with gr.Row():
+            text_prompt_component.render()
+            run_button_component.render()
+
+    run_button_component.click(
+        fn=user,
+        inputs=user_inputs,
+        outputs=[text_prompt_component, chatbot_component],
+        queue=False
+    ).then(
+        fn=bot, inputs=bot_inputs, outputs=[chatbot_component],
+    )
+
+    text_prompt_component.submit(
+        fn=user,
+        inputs=user_inputs,
+        outputs=[text_prompt_component, chatbot_component],
+        queue=False
+    ).then(
+        fn=bot, inputs=bot_inputs, outputs=[chatbot_component],
+    )
+
+demo.queue(max_size=99).launch(debug=False, show_error=True)

requirements.txt

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+requests
+gradio
+Pillow