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#!/usr/bin/env python3 | |
# -*- coding: utf-8 -*- | |
""" | |
Created on Tue Feb 13 11:22:52 2024 | |
@author: stinpankajm | |
""" | |
import os | |
import base64 | |
from huggingface_hub import InferenceClient | |
import gradio as gr | |
client = InferenceClient("mistralai/Mistral-7B-Instruct-v0.2") | |
# Formats the prompt to hold all of the past messages | |
def format_prompt(message, history): | |
prompt = "<s>" | |
prompt_template = "[INST] {} [/INST]" | |
# Iterates through every past user input and response to be added to the prompt | |
for user_prompt, bot_response in history: | |
prompt += prompt_template.format(user_prompt) | |
prompt += f" {bot_response}</s> " | |
prompt += prompt_template.format(message) | |
return prompt | |
MODEL_PATH = "/home/stinpankajm/workspace/FG_POCs/Insects_Scouting/Models/F_Scout_v0.2" | |
css = """ | |
#warning {background-color: #FFCCCB} | |
#flag {color: red;} | |
#topHeading { | |
padding: 30px 0px 30px 15px; | |
box-shadow: 1px 0px 30px 0px rgba(0, 0, 0, 0.1); | |
} | |
#logoImg { | |
max-width: 260px; | |
} | |
""" | |
# Use for GEC, Doesn't track actual history | |
def format_prompt_finadvisor(message, history): | |
prompt = "<s>" | |
# String to add before every prompt | |
prompt_prefix = """\ | |
You are an agriculture expert providing advice to farmers and users. | |
Your task is to answer questions related to agriculture based on the Question provided below. | |
Do not provide any explanations and respond only with medium short answers, add bullet points whenever necessary.. | |
Your TEXT to analyze: | |
""" | |
prompt_template = "[INST] " + prompt_prefix + ' {} [/INST]' | |
# Iterates through every past user input and response to be added to the prompt | |
for user_prompt, bot_response in history: | |
prompt += prompt_template.format(user_prompt) | |
prompt += f" {bot_response}</s> \n" | |
prompt += prompt_template.format(message) | |
return prompt | |
def generate(prompt, history, system_prompt, temperature=0.9, max_new_tokens=512, top_p=0.95, repetition_penalty=1.0): | |
temperature = float(temperature) | |
if temperature < 1e-2: 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,) | |
#formatted_prompt = format_prompt_grammar(f"Corrected Sentence: {prompt}", history) | |
formatted_prompt = format_prompt_finadvisor(f"{system_prompt} {prompt}", history) | |
# print("\nPROMPT: \n\t" + formatted_prompt) | |
# Generate text from the HF inference | |
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 | |
return output | |
additional_inputs=[ | |
gr.Textbox( label="System Prompt", value="" , max_lines=1, interactive=True, ), | |
gr.Slider( label="Temperature", value=0.9, minimum=0.0, maximum=1.0, step=0.05, interactive=True, info="Higher values produce more diverse outputs", ), | |
gr.Slider( label="Max new tokens", value=256, minimum=0, maximum=1048, step=64, interactive=True, info="The maximum numbers of new tokens", ), | |
gr.Slider( label="Top-p (nucleus sampling)", value=0.90, minimum=0.0, maximum=1, step=0.05, interactive=True, info="Higher values sample more low-probability tokens", ), | |
gr.Slider( label="Repetition penalty", value=1.2, minimum=1.0, maximum=2.0, step=0.05, interactive=True, info="Penalize repeated tokens", ) | |
] | |
with gr.Blocks(css=css) as demo: | |
""" | |
Top Custom Header | |
""" | |
with gr.Row(elem_id="topHeading"): | |
# with gr.Column(elem_id="logoImg"): | |
# with open('./static/logo.jpeg', "rb") as image: | |
# encoded = base64.b64encode(image.read()).decode() | |
# logo_image = f"data:image/png;base64,{encoded}" | |
# gr.HTML(f'<img src={logo_image} style="width:155px">') | |
# gr.Image(Image.open('./static/FarmGyan logo_1.png')) | |
with gr.Column(): | |
gr.Markdown( | |
""" | |
# FinAdvisor | |
""", | |
) | |
""" | |
Model Prediction | |
""" | |
gr.ChatInterface( | |
fn=generate, | |
chatbot=gr.Chatbot(show_label=False, show_share_button=False, show_copy_button=True, likeable=True, layout="panel"), | |
additional_inputs=additional_inputs, | |
title="AgExpert", | |
examples=[], | |
).queue().launch() | |
# ).queue().launch(auth=("shivraiAdmin", "FarmERP@2024"), auth_message="Please enter your credentials to get started.") | |
# demo.launch(show_api=False) | |