import os
import time
from typing import List, Tuple, Optional, Dict, Union
import requests
import gradio as gr
TITLE = """
Insight LLM 💬
"""
SUBTITLE = """Effortlessly analyze and compare Thai stocks with advanced LLM insights.
"""
DUPLICATE = """
Duplicate the Space and run securely with your API KEY.
"""
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)