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import os |
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import openai |
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import gradio as gr |
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from voice_chat import WhisperChatbot |
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from langchain_community.chat_models import ChatOpenAI |
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from langchain_openai import OpenAIEmbeddings |
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from utils.models_and_path import KNOWLEDGE_BASE_PATH, MODEL_NAME |
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from dotenv import load_dotenv, find_dotenv |
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load_dotenv(find_dotenv()) |
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openai.api_key = os.environ["OPENAI_API_KEY"] |
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whisper_chatbot = WhisperChatbot( |
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model_name=MODEL_NAME, knowledge_base_path=KNOWLEDGE_BASE_PATH |
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) |
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interface = gr.Interface( |
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title="Multi-lingual Voice based RAG chatbot", |
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fn=whisper_chatbot.response, |
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inputs=[gr.components.Audio(source="microphone", type="filepath")], |
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outputs=[ |
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gr.components.Textbox(label="Transcribed Text"), |
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gr.components.Textbox(label="Translated Text"), |
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gr.components.Textbox(label="Language"), |
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gr.components.Textbox(label="English Result"), |
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gr.components.Textbox(label="Translated Result"), |
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], |
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live=False, |
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).launch() |
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