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from huggingface_hub import InferenceClient
import gradio as gr
import datetime
import re
import requests
import json
# Initialize the InferenceClient
client = InferenceClient("mistralai/Mixtral-8x7B-Instruct-v0.1")
# Enter your API key here
api_key = "1e8cd0385845a649e448cde4917058d6"
# Define the system prompt templates
system_prompt_templates = {
r"\btime\b|\bhour\b|\bclock\b": "server log: ~This message was sent at {formatted_time}. The actual year is 2024.~",
r"\bweather\b|\bforecast\b|\bmeteo": "server log: ~The current weather conditions in {city_name} are {weather_description} with a high of {current_temperature_c}°C ({current_temperature_f}°F) and a pressure of {current_pressure_hpa} hPa ({current_pressure_inHg} inHg) and humidity of {current_humidity}%.~",
r"\bdate\b|\bcalendar\b": "server log: ~Today's date is {formatted_date}.~",
r"\bpolitics\b|\belection\b": "server log: ~This conversation is taking place in a politically neutral environment.~"
}
def format_prompt(message, history, system_prompt):
prompt = "<s>"
for user_prompt, bot_response in history:
prompt += f"\[INST\] {user_prompt} \[/INST\]"
prompt += f" {bot_response}</s> "
prompt += f"\[INST\] {message} \[/INST\]"
return prompt
def generate(prompt, history, system_prompt, temperature=0.9, max_new_tokens=9048, top_p=0.95, repetition_penalty=1.0):
temperature = max(float(temperature), 1e-2)
top_p = float(top_p)
generate_kwargs = dict(
temperature=temperature,
max_new_tokens=max_new_tokens,
top_p=top_p,
repetition_penalty=repetition_penalty,
do_sample=True,
seed=42,
)
# Get current time and date
now = datetime.datetime.now()
formatted_time = now.strftime("%H.%M.%S, %B, %Y")
formatted_date = now.strftime("%B %d, %Y")
# Check for keywords in the user's input and update the system prompt accordingly
city_name = None
weather_description = None
current_temperature_c = None
current_temperature_f = None
current_pressure_hpa = None
current_pressure_inHg = None
current_humidity = None
for keyword, template in system_prompt_templates.items():
if re.search(keyword, prompt, re.IGNORECASE):
if keyword == r"\bweather\b|\bforecast\b|\bmeteo":
base_url = "http://api.openweathermap.org/data/2.5/weather?"
complete_url = base_url + "appid=" + api_key + "&q=" + city_name
response = requests.get(complete_url)
x = response.json()
if x["cod"] != "404":
y = x["main"]
current_temperature_c = y["temp"] - 273.15 # Convert from Kelvin to Celsius
current_temperature_f = current_temperature_c * 9/5 + 32 # Convert from Celsius to Fahrenheit
current_pressure_hpa = y["pressure"]
current_pressure_inHg = current_pressure_hpa * 0.02953 # Convert from hPa to inHg
current_humidity = y["humidity"]
z = x["weather"]
weather_description = z[0]["description"]
city_name = x["name"]
else:
print("City Not Found")
city_name = "unknown"
weather_description = "unknown"
current_temperature_c = 0
current_temperature_f = 32
current_pressure_hpa = 0
current_pressure_inHg = 0
current_humidity = 0
system_prompt = template.format(formatted_time=formatted_time, formatted_date=formatted_date, city_name=city_name, weather_description=weather_description, current_temperature_c=current_temperature_c, current_temperature_f=current_temperature_f, current_pressure_hpa=current_pressure_hpa, current_pressure_inHg=current_pressure_inHg, current_humidity=current_humidity)
break
formatted_prompt = format_prompt(f"{system_prompt}, {prompt}", history)
stream = client.text_generation(formatted_prompt, **generate_kwargs, stream=True, details=True, return_full_text=False)
output = ""
for response in stream:
output += response.token.text
yield output
with gr.Blocks() as demo:
chatbot = gr.Chatbot(show_label=True, show_share_button=False, show_copy_button=True, likeable=True, layout="panel")
with gr.Row():
with gr.Column(scale=3):
user_input = gr.Textbox(label="Your message", placeholder="Type your message here...")
with gr.Column(scale=1):
submit_button = gr.Button("Send")
def check_keywords(text):
for keyword, _ in system_prompt_templates.items():
if re.search(keyword, text, re.IGNORECASE):
return True
return False
user_input.submit(
fn=generate,
inputs=[user_input, chatbot, gr.Textbox(label="System Prompt", max_lines=1, interactive=True)],
outputs=chatbot,
every=200,
_js=None
)
demo.launch(show_api=False)