File size: 1,961 Bytes
63b6262 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 | # -*- coding: utf-8 -*-
"""Copy of Groq_Chat_bot.ipynb
Automatically generated by Colab.
Original file is located at
https://colab.research.google.com/#fileId=https%3A//huggingface.co/spaces/AnwinMJ/project/blob/main/Copy%20of%20Groq_Chat_bot.ipynb
#Install Packages
"""
"""# Import the Packages"""
import gradio
from groq import Groq
import os
client = Groq(
api_key=os.environ.get("API"),
)
"""#Define a function to give content and role"""
def initialize_messages():
return [{"role": "system",
"content": """You are a skilled criminal lawyer with a
successful track record in numerous cases. Your role is to
assist people by providing guidance on Indian laws and
offering answers in a professional legal manner."""}]
"""#Assign it to a variable"""
messages_prmt = initialize_messages()
print(messages_prmt)
[{},{}]
"""#Define a function to connect with LLM"""
def customLLMBot(user_input, history):
global messages_prmt
messages_prmt.append({"role": "user", "content": user_input})
response = client.chat.completions.create(
messages=messages_prmt,
model="llama3-8b-8192",
)
print(response)
LLM_reply = response.choices[0].message.content
messages_prmt.append({"role": "assistant", "content": LLM_reply})
return LLM_reply
"""#Create an object of chat interface class in gradio"""
iface = gradio.ChatInterface(customLLMBot,
chatbot=gradio.Chatbot(height=300),
textbox=gradio.Textbox(placeholder="Ask me a question related to law"),
title="Lawyer ChatBot",
description="Chat bot for law assistance",
theme="soft",
examples=["hi","What is IPC sessions", "how to get a bail"],
submit_btn=True
)
"""#Call launch function to execute"""
iface.launch(share=True)
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