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| import openai | |
| import pandas as pd | |
| import faiss | |
| import numpy as np | |
| from sentence_transformers import SentenceTransformer | |
| import gradio as gr | |
| from gtts import gTTS | |
| import tempfile | |
| import os | |
| import speech_recognition as sr | |
| openai.api_key = os.getenv("OPENAI_API_KEY") | |
| # Load embedding model | |
| embed_model = SentenceTransformer("all-MiniLM-L6-v2") | |
| # Load FAQ CSV | |
| faq_df = pd.read_csv("fact-base-tesco.csv") | |
| questions = faq_df["Question"].tolist() | |
| answers = faq_df["Answer"].tolist() | |
| # Create FAISS index | |
| faq_embeddings = embed_model.encode(questions, convert_to_numpy=True) | |
| index = faiss.IndexFlatL2(faq_embeddings.shape[1]) | |
| index.add(faq_embeddings) | |
| def ask_faq(query): | |
| query_vec = embed_model.encode([query], convert_to_numpy=True) | |
| D, I = index.search(query_vec, k=1) | |
| similarity = D[0][0] | |
| if similarity < 0.5: | |
| answer = answers[I[0][0]] | |
| response = answer | |
| else: | |
| try: | |
| completion = openai.ChatCompletion.create( | |
| model="gpt-3.5-turbo", | |
| messages=[{"role": "user", "content": query}], | |
| max_tokens=200 | |
| ) | |
| response = completion.choices[0].message.content | |
| except: | |
| response = "Sorry, I couldn't generate a response right now." | |
| tts = gTTS(response) | |
| tts_fp = tempfile.NamedTemporaryFile(delete=False, suffix=".mp3") | |
| tts.save(tts_fp.name) | |
| return response, tts_fp.name | |
| def process_input(text, audio): | |
| if audio is not None: | |
| recognizer = sr.Recognizer() | |
| with sr.AudioFile(audio) as source: | |
| audio_data = recognizer.record(source) | |
| try: | |
| text = recognizer.recognize_google(audio_data) | |
| except: | |
| return "Sorry, could not understand audio", None | |
| if text: | |
| return ask_faq(text) | |
| else: | |
| return "Please provide a question.", None | |
| with gr.Blocks() as demo: | |
| gr.Markdown("# 🎙️ FAQ + GPT Chatbot with Voice") | |
| gr.Markdown("Ask via text or mic. Falls back to GPT if FAQ match is not found.") | |
| text_input = gr.Textbox(label="Type your question or click mic below ⬇") | |
| mic_input = gr.Audio(type="filepath", label="🎤 Speak your question") | |
| submit_btn = gr.Button("Ask") | |
| text_output = gr.Textbox(label="Answer") | |
| audio_output = gr.Audio(label="🔊 Voice Answer", autoplay=True) | |
| submit_btn.click(fn=process_input, inputs=[text_input, mic_input], outputs=[text_output, audio_output]) | |
| demo.launch() | |