Initial commit with chatbot script and requirements

building_chatbot_ui_with_microsoft_godel_&_gradio.py

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+# -*- coding: utf-8 -*-
+
+
+
+
+GODEL - (Grounded Open
+Dialogue Language Model https://www.microsoft.com/en-us/research/uploads/prod/2022/05/2206.11309.pdf
+"""
+
+! pip install transformers gradio -q
+
+!pip install huggingface_hub
+from huggingface_hub import notebook_login
+
+# Log in to Hugging Face
+notebook_login()
+
+"""# Step 1 — Setting up the Chatbot Model - Microsoft phi-3.5"""
+
+from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
+import torch
+
+tokenizer = AutoTokenizer.from_pretrained("microsoft/GODEL-v1_1-base-seq2seq")
+model = AutoModelForSeq2SeqLM.from_pretrained("microsoft/GODEL-v1_1-base-seq2seq")
+
+"""# Step 2 — Defining a `predict` function with `state` and model prediction"""
+
+def predict(input, history=[]):
+
+    instruction = 'Instruction: given a dialog context, you need to response empathically'
+
+    knowledge = '  '
+
+    s = list(sum(history, ()))
+
+    s.append(input)
+
+    #print(s)
+
+    dialog = ' EOS ' .join(s)
+
+    #print(dialog)
+
+    query = f"{instruction} [CONTEXT] {dialog} {knowledge}"
+
+    top_p = 0.9
+    min_length = 8
+    max_length = 64
+
+
+    # tokenize the new input sentence
+    new_user_input_ids = tokenizer.encode(f"{query}", return_tensors='pt')
+
+
+    output = model.generate(new_user_input_ids, min_length=int(
+        min_length), max_length=int(max_length), top_p=top_p, do_sample=True).tolist()
+
+
+    response = tokenizer.decode(output[0], skip_special_tokens=True)
+
+
+    history.append((input, response))
+
+    return history, history
+
+"""# Step 3 — Creating a Gradio Chatbot UI"""
+
+import gradio as gr
+
+
+gr.Interface(fn=predict,
+             inputs=["text",'state'],
+             outputs=["chatbot",'state']).launch(debug = True, share = True)
+

readme.md

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+# Building a Chatbot UI with Microsoft GODEL and Gradio
+
+This project demonstrates how to create a conversational AI chatbot using Microsoft's GODEL model and deploy it with a Gradio UI. The chatbot is designed to respond empathetically in a dialogue context.
+
+## Features
+
+- **Empathetic Dialogues**: Utilizes Microsoft's GODEL model to generate empathetic responses.
+- **Gradio UI**: Simple and interactive web interface for the chatbot.
+- **Hugging Face Integration**: Easily deploy and manage your model using Hugging Face's platform.
+
+## Installation
+
+To run this project, you'll need to have Python installed. You can install the required packages using the following command:
+
+```bash
+pip install -r requirements.txt

requierements.txt

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+transformers==4.33.2
+gradio==3.30.0
+huggingface_hub==0.17.1
+torch>=1.13.1