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karthikeyan-r
commited on
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•
7ac2436
0
Parent(s):
Duplicate from hudsonhayes/Vodafone_CRM_Chatbot
Browse files- .gitattributes +35 -0
- README.md +13 -0
- app.py +296 -0
- requirements.txt +7 -0
- style.css +9 -0
- vodafone_customer_details.json +256 -0
.gitattributes
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README.md
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---
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title: Vodafone CRM Chatbot
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emoji: 👁
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colorFrom: indigo
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colorTo: gray
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sdk: gradio
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sdk_version: 3.35.2
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app_file: app.py
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pinned: false
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duplicated_from: hudsonhayes/Vodafone_CRM_Chatbot
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---
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Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
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app.py
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from pydantic import NoneStr
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import os
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import mimetypes
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import requests
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import tempfile
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import gradio as gr
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import openai
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import re
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import json
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from transformers import pipeline
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import matplotlib.pyplot as plt
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import plotly.express as px
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class SentimentAnalyzer:
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def __init__(self):
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self.model="facebook/bart-large-mnli"
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def analyze_sentiment(self, text):
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pipe = pipeline("zero-shot-classification", model=self.model)
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label=["positive","negative","neutral"]
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result = pipe(text, label)
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sentiment_scores= {result['labels'][0]:result['scores'][0],result['labels'][1]:result['scores'][1],result['labels'][2]:result['scores'][2]}
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sentiment_scores_str = f"Positive: {sentiment_scores['positive']:.2f}, Neutral: {sentiment_scores['neutral']:.2f}, Negative: {sentiment_scores['negative']:.2f}"
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return sentiment_scores_str
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def emotion_analysis(self,text):
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prompt = f""" Your task is to analyze {text} and predict the emotion using scores. Emotions are categorized into the following list: Sadness, Happiness, Joy, Fear, Disgust, and Anger. You need to provide the emotion with the highest score. The scores should be in the range of 0.0 to 1.0, where 1.0 represents the highest intensity of the emotion.
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Please analyze the text and provide the output in the following format: emotion: score [with one result having the highest score]."""
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response = openai.Completion.create(
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model="text-davinci-003",
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prompt=prompt,
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temperature=1,
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max_tokens=60,
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top_p=1,
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frequency_penalty=0,
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presence_penalty=0
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)
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message = response.choices[0].text.strip().replace("\n","")
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print(message)
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return message
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def analyze_sentiment_for_graph(self, text):
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pipe = pipeline("zero-shot-classification", model=self.model)
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label=["positive", "negative", "neutral"]
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result = pipe(text, label)
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sentiment_scores = {
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result['labels'][0]: result['scores'][0],
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result['labels'][1]: result['scores'][1],
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result['labels'][2]: result['scores'][2]
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}
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return sentiment_scores
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def emotion_analysis_for_graph(self,text):
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list_of_emotion=text.split(":")
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label=list_of_emotion[0]
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score=list_of_emotion[1]
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score_dict={
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label:float(score)
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}
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print(score_dict)
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return score_dict
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class Summarizer:
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def __init__(self):
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pass
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def generate_summary(self, text):
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model_engine = "text-davinci-003"
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prompt = f"""summarize the following conversation delimited by triple backticks.
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write within 30 words.
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```{text}``` """
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completions = openai.Completion.create(
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engine=model_engine,
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prompt=prompt,
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max_tokens=60,
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n=1,
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stop=None,
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temperature=0.5,
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)
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message = completions.choices[0].text.strip()
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return message
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history_state = gr.State()
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summarizer = Summarizer()
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sentiment = SentimentAnalyzer()
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class LangChain_Document_QA:
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+
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def __init__(self):
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pass
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def _add_text(self,history, text):
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history = history + [(text, None)]
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history_state.value = history
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return history,gr.update(value="", interactive=False)
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def _agent_text(self,history, text):
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response = text
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history[-1][1] = response
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history_state.value = history
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return history
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def _chat_history(self):
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history = history_state.value
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formatted_history = " "
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for entry in history:
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customer_text, agent_text = entry
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formatted_history += f"Customer: {customer_text}\n"
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if agent_text:
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formatted_history += f"Agent: {agent_text}\n"
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return formatted_history
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def _display_history(self):
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formatted_history=self._chat_history()
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summary=summarizer.generate_summary(formatted_history)
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return summary
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def _display_graph(self,sentiment_scores):
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labels = sentiment_scores.keys()
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scores = sentiment_scores.values()
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fig = px.bar(x=scores, y=labels, orientation='h', color=labels, color_discrete_map={"Negative": "red", "Positive": "green", "Neutral": "gray"})
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fig.update_traces(texttemplate='%{x:.2f}%', textposition='outside')
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fig.update_layout(height=500, width=200)
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return fig
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def _history_of_chat(self):
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history = history_state.value
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formatted_history = ""
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client=""
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agent=""
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for entry in history:
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customer_text, agent_text = entry
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client+=customer_text
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formatted_history += f"Customer: {customer_text}\n"
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if agent_text:
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agent+=agent_text
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formatted_history += f"Agent: {agent_text}\n"
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return client,agent
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def _suggested_answer(self,text):
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try:
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history = self._chat_history()
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start_sequence = "\nCustomer:"
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restart_sequence = "\nVodafone Customer Relationship Manager:"
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prompt = 'your task is make a conversation between a customer and vodafone telecom customer relationship manager.'
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file_path = "vodafone_customer_details.json"
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with open(file_path) as file:
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customer_details = json.load(file)
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prompt = f"""{history}{start_sequence}{text}{restart_sequence} if customer ask any information take it from {customer_details}.
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if customer say thanks or thankyou tone related messages You should not ask anything to end the conversation with greetings tone.
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"""
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response = openai.Completion.create(
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model="text-davinci-003",
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prompt=prompt,
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+
temperature=0,
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+
max_tokens=500,
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top_p=1,
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+
frequency_penalty=0,
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presence_penalty=0.6,
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)
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message = response.choices[0].text.strip()
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if ":" in message:
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message = re.sub(r'^.*:', '', message)
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return message.strip()
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except:
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return "I can't get the response"
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170 |
+
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+
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+
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def _text_box(self,customer_emotion,agent_emotion,agent_sentiment_score,customer_sentiment_score):
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agent_score = ", ".join([f"{key}: {value:.2f}" for key, value in agent_sentiment_score.items()])
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customer_score = ", ".join([f"{key}: {value:.2f}" for key, value in customer_sentiment_score.items()])
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return f"customer_emotion:{customer_emotion}\nagent_emotion:{agent_emotion}\nAgent_Sentiment_score:{agent_score}\nCustomer_sentiment_score:{customer_score}"
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def _on_sentiment_btn_click(self):
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client,agent=self._history_of_chat()
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customer_emotion=sentiment.emotion_analysis(client)
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customer_sentiment_score = sentiment.analyze_sentiment_for_graph(client)
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183 |
+
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agent_emotion=sentiment.emotion_analysis(agent)
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185 |
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agent_sentiment_score = sentiment.analyze_sentiment_for_graph(agent)
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186 |
+
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scores=self._text_box(customer_emotion,agent_emotion,agent_sentiment_score,customer_sentiment_score)
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customer_fig=self._display_graph(customer_sentiment_score)
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customer_fig.update_layout(title="Sentiment Analysis",width=800)
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agent_fig=self._display_graph(agent_sentiment_score)
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agent_fig.update_layout(title="Sentiment Analysis",width=800)
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agent_emotion_score = sentiment.emotion_analysis_for_graph(agent_emotion)
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agent_emotion_fig=self._display_graph(agent_emotion_score)
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agent_emotion_fig.update_layout(title="Emotion Analysis",width=800)
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customer_emotion_score = sentiment.emotion_analysis_for_graph(customer_emotion)
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201 |
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customer_emotion_fig=self._display_graph(customer_emotion_score)
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customer_emotion_fig.update_layout(title="Emotion Analysis",width=800)
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return scores,customer_fig,agent_fig,customer_emotion_fig,agent_emotion_fig
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def clear_func(self):
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history_state.clear()
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def gradio_interface(self):
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with gr.Blocks(css="style.css",theme=gr.themes.Soft()) as demo:
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with gr.Row():
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gr.HTML("""<img class="leftimage" align="left" src="https://templates.images.credential.net/1612472097627370951721412474196.png" alt="Image" width="210" height="210">
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<img align="right" class="rightimage" src="https://download.logo.wine/logo/Vodafone/Vodafone-Logo.wine.png" alt="Image" width="230" height="230" >""")
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with gr.Row():
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gr.HTML("""<center><h1>Vodafone Generative AI CRM ChatBot</h1></center>""")
|
217 |
+
chatbot = gr.Chatbot([], elem_id="chatbot").style(height=300)
|
218 |
+
with gr.Row():
|
219 |
+
with gr.Column(scale=0.50):
|
220 |
+
txt = gr.Textbox(
|
221 |
+
show_label=False,
|
222 |
+
placeholder="Customer",
|
223 |
+
).style(container=False)
|
224 |
+
with gr.Column(scale=0.50):
|
225 |
+
txt2 = gr.Textbox(
|
226 |
+
show_label=False,
|
227 |
+
placeholder="Agent",
|
228 |
+
).style(container=False)
|
229 |
+
|
230 |
+
with gr.Column(scale=0.40):
|
231 |
+
txt3 =gr.Textbox(
|
232 |
+
show_label=False,
|
233 |
+
placeholder="GPT_Suggestion",
|
234 |
+
).style(container=False)
|
235 |
+
with gr.Column(scale=0.10, min_width=0):
|
236 |
+
button=gr.Button(
|
237 |
+
value="🚀"
|
238 |
+
)
|
239 |
+
with gr.Column(scale=0.10, min_width=0):
|
240 |
+
clear_btn=gr.Button(
|
241 |
+
value="Clear"
|
242 |
+
)
|
243 |
+
with gr.Row():
|
244 |
+
with gr.Column(scale=0.40):
|
245 |
+
txt4 =gr.Textbox(
|
246 |
+
show_label=False,
|
247 |
+
lines=4,
|
248 |
+
placeholder="Summary",
|
249 |
+
).style(container=False)
|
250 |
+
with gr.Column(scale=0.10, min_width=0):
|
251 |
+
end_btn=gr.Button(
|
252 |
+
value="End"
|
253 |
+
)
|
254 |
+
with gr.Column(scale=0.40):
|
255 |
+
txt5 =gr.Textbox(
|
256 |
+
show_label=False,
|
257 |
+
lines=4,
|
258 |
+
placeholder="Sentiment",
|
259 |
+
).style(container=False)
|
260 |
+
|
261 |
+
with gr.Column(scale=0.10, min_width=0):
|
262 |
+
Sentiment_btn=gr.Button(
|
263 |
+
value="📊",callback=self._on_sentiment_btn_click
|
264 |
+
)
|
265 |
+
with gr.Row():
|
266 |
+
gr.HTML("""<center><h1>Sentiment and Emotion Score Graph</h1></center>""")
|
267 |
+
with gr.Row():
|
268 |
+
with gr.Column(scale=0.70, min_width=0):
|
269 |
+
plot =gr.Plot(label="Customer", size=(500, 600))
|
270 |
+
with gr.Row():
|
271 |
+
with gr.Column(scale=0.70, min_width=0):
|
272 |
+
plot_2 =gr.Plot(label="Agent", size=(500, 600))
|
273 |
+
with gr.Row():
|
274 |
+
with gr.Column(scale=0.70, min_width=0):
|
275 |
+
plot_3 =gr.Plot(label="Customer_Emotion", size=(500, 600))
|
276 |
+
with gr.Row():
|
277 |
+
with gr.Column(scale=0.70, min_width=0):
|
278 |
+
plot_4 =gr.Plot(label="Agent_Emotion", size=(500, 600))
|
279 |
+
|
280 |
+
|
281 |
+
txt_msg = txt.submit(self._add_text, [chatbot, txt], [chatbot, txt])
|
282 |
+
txt_msg.then(lambda: gr.update(interactive=True), None, [txt])
|
283 |
+
txt.submit(self._suggested_answer,txt,txt3)
|
284 |
+
button.click(self._agent_text, [chatbot,txt3], chatbot)
|
285 |
+
txt2.submit(self._agent_text, [chatbot, txt2], chatbot).then(
|
286 |
+
self._agent_text, [chatbot, txt2], chatbot
|
287 |
+
)
|
288 |
+
end_btn.click(self._display_history, [], txt4)
|
289 |
+
clear_btn.click(self.clear_func,[],[])
|
290 |
+
clear_btn.click(lambda: None, None, chatbot, queue=False)
|
291 |
+
Sentiment_btn.click(self._on_sentiment_btn_click,[],[txt5,plot,plot_2,plot_3,plot_4])
|
292 |
+
|
293 |
+
demo.title = "Vodafone Generative AI CRM ChatBot"
|
294 |
+
demo.launch()
|
295 |
+
document_qa =LangChain_Document_QA()
|
296 |
+
document_qa.gradio_interface()
|
requirements.txt
ADDED
@@ -0,0 +1,7 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
gradio
|
2 |
+
openai
|
3 |
+
transformers
|
4 |
+
plotly
|
5 |
+
torch
|
6 |
+
torchvision
|
7 |
+
tensorflow
|
style.css
ADDED
@@ -0,0 +1,9 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
|
2 |
+
.leftimage{
|
3 |
+
padding-top:75px;
|
4 |
+
margin-left:250px;
|
5 |
+
}
|
6 |
+
.rightimage{
|
7 |
+
margin-right:260px;
|
8 |
+
margin-top:15px;
|
9 |
+
}
|
vodafone_customer_details.json
ADDED
@@ -0,0 +1,256 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"customers": [
|
3 |
+
{
|
4 |
+
"name": "John Smith",
|
5 |
+
"phone_number": "+1234567890",
|
6 |
+
"recharge_plan": {
|
7 |
+
"plan_name": "Gold Plan",
|
8 |
+
"data_limit": "10GB",
|
9 |
+
"validity": "30 days",
|
10 |
+
"price": "$29.99"
|
11 |
+
},
|
12 |
+
"starting_recharge_date": "2023-06-15",
|
13 |
+
"last_recharge_date": "2023-07-14"
|
14 |
+
},
|
15 |
+
{
|
16 |
+
"name": "Alice Johnson",
|
17 |
+
"phone_number": "+9876543210",
|
18 |
+
"recharge_plan": {
|
19 |
+
"plan_name": "Silver Plan",
|
20 |
+
"data_limit": "5GB",
|
21 |
+
"validity": "15 days",
|
22 |
+
"price": "$19.99"
|
23 |
+
},
|
24 |
+
"starting_recharge_date": "2023-06-12",
|
25 |
+
"last_recharge_date": "2023-06-26"
|
26 |
+
},
|
27 |
+
{
|
28 |
+
"name": "Robert Williams",
|
29 |
+
"phone_number": "+2345678901",
|
30 |
+
"recharge_plan": {
|
31 |
+
"plan_name": "Basic Plan",
|
32 |
+
"data_limit": "2GB",
|
33 |
+
"validity": "7 days",
|
34 |
+
"price": "$9.99"
|
35 |
+
},
|
36 |
+
"starting_recharge_date": "2023-06-10",
|
37 |
+
"last_recharge_date": "2023-06-16"
|
38 |
+
},
|
39 |
+
{
|
40 |
+
"name": "Emily Davis",
|
41 |
+
"phone_number": "+3456789012",
|
42 |
+
"recharge_plan": {
|
43 |
+
"plan_name": "Premium Plan",
|
44 |
+
"data_limit": "15GB",
|
45 |
+
"validity": "60 days",
|
46 |
+
"price": "$49.99"
|
47 |
+
},
|
48 |
+
"starting_recharge_date": "2023-06-13",
|
49 |
+
"last_recharge_date": "2023-08-12"
|
50 |
+
},
|
51 |
+
{
|
52 |
+
"name": "Michael Wilson",
|
53 |
+
"phone_number": "+4567890123",
|
54 |
+
"recharge_plan": {
|
55 |
+
"plan_name": "Unlimited Plan",
|
56 |
+
"data_limit": "Unlimited",
|
57 |
+
"validity": "30 days",
|
58 |
+
"price": "$59.99"
|
59 |
+
},
|
60 |
+
"starting_recharge_date": "2023-06-14",
|
61 |
+
"last_recharge_date": "2023-07-13"
|
62 |
+
},
|
63 |
+
{
|
64 |
+
"name": "Sarah Brown",
|
65 |
+
"phone_number": "+5678901234",
|
66 |
+
"recharge_plan": {
|
67 |
+
"plan_name": "Family Plan",
|
68 |
+
"data_limit": "20GB",
|
69 |
+
"validity": "30 days",
|
70 |
+
"price": "$39.99"
|
71 |
+
},
|
72 |
+
"starting_recharge_date": "2023-06-15",
|
73 |
+
"last_recharge_date": "2023-07-14"
|
74 |
+
},
|
75 |
+
{
|
76 |
+
"name": "David Taylor",
|
77 |
+
"phone_number": "+6789012345",
|
78 |
+
"recharge_plan": {
|
79 |
+
"plan_name": "Student Plan",
|
80 |
+
"data_limit": "8GB",
|
81 |
+
"validity": "30 days",
|
82 |
+
"price": "$24.99"
|
83 |
+
},
|
84 |
+
"starting_recharge_date": "2023-06-10",
|
85 |
+
"last_recharge_date": "2023-07-09"
|
86 |
+
},
|
87 |
+
{
|
88 |
+
"name": "Olivia Davis",
|
89 |
+
"phone_number": "+7890123456",
|
90 |
+
"recharge_plan": {
|
91 |
+
"plan_name": "Premium Plus",
|
92 |
+
"data_limit": "12GB",
|
93 |
+
"validity": "15 days",
|
94 |
+
"price": "$39.99"
|
95 |
+
},
|
96 |
+
"starting_recharge_date": "2023-06-17",
|
97 |
+
"last_recharge_date": "2023-07-01"
|
98 |
+
},
|
99 |
+
{
|
100 |
+
"name": "Daniel Johnson",
|
101 |
+
"phone_number": "+8901234567",
|
102 |
+
"recharge_plan": {
|
103 |
+
"plan_name": "Unlimited Plus",
|
104 |
+
"data_limit": "Unlimited",
|
105 |
+
"validity": "30 days",
|
106 |
+
"price": "$69.99"
|
107 |
+
},
|
108 |
+
"starting_recharge_date": "2023-06-16",
|
109 |
+
"last_recharge_date": "2023-07-16"
|
110 |
+
},
|
111 |
+
{
|
112 |
+
"name": "Sophia Thompson",
|
113 |
+
"phone_number": "+9012345678",
|
114 |
+
"recharge_plan": {
|
115 |
+
"plan_name": "Business Plan",
|
116 |
+
"data_limit": "15GB",
|
117 |
+
"validity": "30 days",
|
118 |
+
"price": "$49.99"
|
119 |
+
},
|
120 |
+
"starting_recharge_date": "2023-06-14",
|
121 |
+
"last_recharge_date": "2023-07-13"
|
122 |
+
},
|
123 |
+
{
|
124 |
+
"name": "James Wilson",
|
125 |
+
"phone_number": "+0123456789",
|
126 |
+
"recharge_plan": {
|
127 |
+
"plan_name": "Premium Plan",
|
128 |
+
"data_limit": "10GB",
|
129 |
+
"validity": "30 days",
|
130 |
+
"price": "$39.99"
|
131 |
+
},
|
132 |
+
"starting_recharge_date": "2023-06-12",
|
133 |
+
"last_recharge_date": "2023-07-11"
|
134 |
+
},
|
135 |
+
{
|
136 |
+
"name": "Lily Martinez",
|
137 |
+
"phone_number": "+9876543210",
|
138 |
+
"recharge_plan": {
|
139 |
+
"plan_name": "Silver Plan",
|
140 |
+
"data_limit": "5GB",
|
141 |
+
"validity": "15 days",
|
142 |
+
"price": "$19.99"
|
143 |
+
},
|
144 |
+
"starting_recharge_date": "2023-06-13",
|
145 |
+
"last_recharge_date": "2023-06-27"
|
146 |
+
},
|
147 |
+
{
|
148 |
+
"name": "Andrew Davis",
|
149 |
+
"phone_number": "+8765432109",
|
150 |
+
"recharge_plan": {
|
151 |
+
"plan_name": "Basic Plan",
|
152 |
+
"data_limit": "2GB",
|
153 |
+
"validity": "7 days",
|
154 |
+
"price": "$9.99"
|
155 |
+
},
|
156 |
+
"starting_recharge_date": "2023-06-11",
|
157 |
+
"last_recharge_date": "2023-06-17"
|
158 |
+
},
|
159 |
+
{
|
160 |
+
"name": "Ava Thomas",
|
161 |
+
"phone_number": "+7654321098",
|
162 |
+
"recharge_plan": {
|
163 |
+
"plan_name": "Gold Plan",
|
164 |
+
"data_limit": "10GB",
|
165 |
+
"validity": "30 days",
|
166 |
+
"price": "$29.99"
|
167 |
+
},
|
168 |
+
"starting_recharge_date": "2023-06-15",
|
169 |
+
"last_recharge_date": "2023-07-14"
|
170 |
+
},
|
171 |
+
{
|
172 |
+
"name": "Ryan White",
|
173 |
+
"phone_number": "+6543210987",
|
174 |
+
"recharge_plan": {
|
175 |
+
"plan_name": "Premium Plus",
|
176 |
+
"data_limit": "12GB",
|
177 |
+
"validity": "15 days",
|
178 |
+
"price": "$39.99"
|
179 |
+
},
|
180 |
+
"starting_recharge_date": "2023-06-18",
|
181 |
+
"last_recharge_date": "2023-07-02"
|
182 |
+
},
|
183 |
+
{
|
184 |
+
"name": "Grace Thompson",
|
185 |
+
"phone_number": "+5432109876",
|
186 |
+
"recharge_plan": {
|
187 |
+
"plan_name": "Unlimited Plan",
|
188 |
+
"data_limit": "Unlimited",
|
189 |
+
"validity": "30 days",
|
190 |
+
"price": "$59.99"
|
191 |
+
},
|
192 |
+
"starting_recharge_date": "2023-06-14",
|
193 |
+
"last_recharge_date": "2023-07-13"
|
194 |
+
},
|
195 |
+
{
|
196 |
+
"name": "Ethan Moore",
|
197 |
+
"phone_number": "+4321098765",
|
198 |
+
"recharge_plan": {
|
199 |
+
"plan_name": "Family Plan",
|
200 |
+
"data_limit": "20GB",
|
201 |
+
"validity": "30 days",
|
202 |
+
"price": "$39.99"
|
203 |
+
},
|
204 |
+
"starting_recharge_date": "2023-06-13",
|
205 |
+
"last_recharge_date": "2023-07-12"
|
206 |
+
},
|
207 |
+
{
|
208 |
+
"name": "Chloe Hill",
|
209 |
+
"phone_number": "+3210987654",
|
210 |
+
"recharge_plan": {
|
211 |
+
"plan_name": "Student Plan",
|
212 |
+
"data_limit": "8GB",
|
213 |
+
"validity": "30 days",
|
214 |
+
"price": "$24.99"
|
215 |
+
},
|
216 |
+
"starting_recharge_date": "2023-06-19",
|
217 |
+
"last_recharge_date": "2023-07-18"
|
218 |
+
},
|
219 |
+
{
|
220 |
+
"name": "Benjamin Clark",
|
221 |
+
"phone_number": "+2109876543",
|
222 |
+
"recharge_plan": {
|
223 |
+
"plan_name": "Premium Plan",
|
224 |
+
"data_limit": "15GB",
|
225 |
+
"validity": "60 days",
|
226 |
+
"price": "$49.99"
|
227 |
+
},
|
228 |
+
"starting_recharge_date": "2023-06-16",
|
229 |
+
"last_recharge_date": "2023-08-15"
|
230 |
+
},
|
231 |
+
{
|
232 |
+
"name": "Victoria Walker",
|
233 |
+
"phone_number": "+1098765432",
|
234 |
+
"recharge_plan": {
|
235 |
+
"plan_name": "Gold Plan",
|
236 |
+
"data_limit": "10GB",
|
237 |
+
"validity": "30 days",
|
238 |
+
"price": "$29.99"
|
239 |
+
},
|
240 |
+
"starting_recharge_date": "2023-06-12",
|
241 |
+
"last_recharge_date": "2023-07-11"
|
242 |
+
},
|
243 |
+
{
|
244 |
+
"name": "Henry Davis",
|
245 |
+
"phone_number": "+0987654321",
|
246 |
+
"recharge_plan": {
|
247 |
+
"plan_name": "Silver Plan",
|
248 |
+
"data_limit": "5GB",
|
249 |
+
"validity": "15 days",
|
250 |
+
"price": "$19.99"
|
251 |
+
},
|
252 |
+
"starting_recharge_date": "2023-06-14",
|
253 |
+
"last_recharge_date": "2023-06-28"
|
254 |
+
}
|
255 |
+
]
|
256 |
+
}
|