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app.py

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+import streamlit as st
+import requests
+import base64
+import os
+import llama_index
+from audio_recorder_streamlit import audio_recorder
+from openai import OpenAI
+from llama_index import VectorStoreIndex, SimpleDirectoryReader
+os.environ['OPENAI_API_KEY'] = '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'
+API_KEY = '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'
+def RAG(text):
+    documents = SimpleDirectoryReader("db3").load_data()
+    index = VectorStoreIndex.from_documents(documents)
+    query_engine = index.as_query_engine()
+    response = query_engine.query(text)
+    
+    # Extract the text from the response
+    response_text = response.response if hasattr(response, 'response') else str(response)
+
+    return response_text
+def linkRAGhindi(text):
+    new_prompt="निम्नलिखित प्रश्न के लिए सबसे उपयुक्त वेबसाइट लिंक दें"+text
+    documents = SimpleDirectoryReader("db1").load_data()
+    index = VectorStoreIndex.from_documents(documents)
+    query_engine = index.as_query_engine()
+    response = query_engine.query(new_prompt)
+    
+    # Extract the text from the response
+    response_text = response.response if hasattr(response, 'response') else str(response)
+
+    return response_text
+def rechindi(text):
+    new_prompt="निम्नलिखित प्रश्न के लिए सबसे उपयुक्त वेबसाइट लिंक दें"+text
+    documents = SimpleDirectoryReader("db2").load_data()
+    index = VectorStoreIndex.from_documents(documents)
+    query_engine = index.as_query_engine()
+    response = query_engine.query(new_prompt)
+    
+    # Extract the text from the response
+    response_text = response.response if hasattr(response, 'response') else str(response)
+    return response_text
+def linkRAGenglish(text):
+    new_prompt="Give the most appropiate website link for the following question "+text
+    documents = SimpleDirectoryReader("db1").load_data()
+    index = VectorStoreIndex.from_documents(documents)
+    query_engine = index.as_query_engine()
+    response = query_engine.query(new_prompt)
+    # Extract the text from the response
+    response_text = response.response if hasattr(response, 'response') else str(response)
+    return response_text
+def recenglish(text):
+    new_prompt="Give the most intresting other website link for the following question "+text
+    documents = SimpleDirectoryReader("db2").load_data()
+    index = VectorStoreIndex.from_documents(documents)
+    query_engine = index.as_query_engine()
+    response = query_engine.query(new_prompt)
+    # Extract the text from the response
+    response_text = response.response if hasattr(response, 'response') else str(response)
+    return response_text
+def transcribe_text_to_voice_english(audio_location):
+    client = OpenAI(api_key=API_KEY)
+    audio_file = open(audio_location, "rb")
+    transcript = client.audio.transcriptions.create(model="whisper-1", file=audio_file)
+    return transcript.text
+
+def transcribe_text_to_voice_hindi(audio_location):
+    url = "https://api.runpod.ai/v2/faster-whisper/runsync"
+    
+    with open(audio_location, "rb") as audio_file:
+        audio_base64 = base64.b64encode(audio_file.read()).decode('utf-8')
+
+    payload = {
+        "input": {
+            "audio_base64": audio_base64,
+            "model": "small",
+            "transcription": "plain_text",
+            "translate": True,
+            "language": "hi",
+            "temperature": 0,
+            "best_of": 5,
+            "beam_size": 5,
+            "patience": 1,
+            "suppress_tokens": "-1",
+            "condition_on_previous_text": False,
+            "temperature_increment_on_fallback": 0.2,
+            "compression_ratio_threshold": 2.4,
+            "logprob_threshold": -1,
+            "no_speech_threshold": 0.6,
+            "word_timestamps": False
+        },
+        "enable_vad": False
+    }
+
+    headers = {
+        "accept": "application/json",
+        "content-type": "application/json",
+        "authorization": "X01PG949AHTOVRYHLQZKSRIWN82UHBUU5JYLNAHM"
+    }
+
+    response = requests.post(url, json=payload, headers=headers)
+    response_json = response.json()
+    transcription = response_json["output"]["transcription"]
+    translation = response_json["output"]["translation"].strip().split('\n')[-1].strip()
+    return transcription, translation
+
+
+def recommendation(text):
+    client = OpenAI(api_key=API_KEY)
+    messages = [{"role": "user", "content": text}]
+    response = client.chat.completions.create(model="gpt-3.5-turbo-1106", messages=messages)
+    return response.choices[0].message.content
+def text_to_speech_ai(speech_file_path, api_response):
+    client = OpenAI(api_key=API_KEY)
+    response = client.audio.speech.create(model="tts-1",voice="nova",input=api_response)
+    response.stream_to_file(speech_file_path)
+
+
+
+
+
+st.title("🚀 SHRESHTH 💬 Bhuvan Assistant")
+
+# Radio wheel for language selection
+language = st.radio("Language/भाषा",["English", "हिंदी"])
+# Displaying description based on selected language
+if language == "English":
+    mode = st.radio("Select Mode Of Input", ["Voice","Text"])
+    st.write("Smart - Helpful - Robust - Effortless - System for Text-to-speech and Human-like Assistance")
+    if mode == "Voice" or mode == "आवाज":
+        st.write("Click on the voice recorder and let me know how I can help you today with your Queries Regarding Bhuvan!")
+        audio_bytes = audio_recorder(
+            text="",
+            recording_color="#e8b62c",
+            neutral_color="#6aa36f",
+            icon_name="microphone",
+            icon_size="2x",
+        )
+
+        if audio_bytes:
+            # Save the Recorded File
+            audio_location = "audio_file.wav"
+            with open(audio_location, "wb") as f:
+                f.write(audio_bytes)
+    
+            if language == "English":
+               text=transcribe_text_to_voice_english(audio_location)
+               st.write(text)
+            else:
+               text,trans=transcribe_text_to_voice_hindi(audio_location)
+               st.write(text)
+
+
+            link_response = linkRAGenglish(text)
+            st.write("SHRESHTH:", link_response)
+            api_response = RAG(text)
+            st.write("SHRESHTH:", api_response)
+            speech_file_path = 'audio_response.mp3'
+            text_to_speech_ai(speech_file_path, api_response)
+            st.audio(speech_file_path)
+            recctext="recommend top three other websites that could interest the user depending on this link and answer : " + link_response + api_response
+            recc=linkRAGenglish(recctext)  
+            st.write("SHRESHTH:", recc)
+    else: 
+        # Text input option
+        text_input = st.text_area("Enter your text here and press Enter", "")
+        if st.button("Submit"):
+            # Process the entered text
+            link_response = linkRAGenglish(text_input)
+            st.write("SHRESHTH:", link_response)
+            api_response = RAG(text_input)
+            st.write("SHRESHTH:", api_response)
+            # Read out the text response using tts
+            speech_file_path = 'audio_response.mp3'
+            text_to_speech_ai(speech_file_path, api_response)
+            st.audio(speech_file_path)
+            recctext="recommend top three other websites that could interest the user depending on this link and answer : " + link_response + api_response
+            recc=linkRAGenglish(recctext)  
+            st.write("SHRESHTH:", recc)
+else:
+    mode = st.radio("इनपुट मोड का चयन करें", ["आवाज", "टेक्स्ट"])
+    st.write("स्मार्ट - सहायक - मजबूत - प्रयासहीन - पाठ-से-बोल के लिए एक सिस्टम और मानव जैसी सहायता")
+
+    if mode == "Voice" or mode == "आवाज" or mode == "ভয়েস":
+        st.write("आवाज रेकॉर्डर पर क्लिक करें और मुझसे यह बताएं कि आज आपकी भुवन से संबंधित सवालों में मैं आपकी कैसे मदद कर सकता हूँ!")
+        audio_bytes = audio_recorder(
+            text="",
+            recording_color="#e8b62c",
+            neutral_color="#6aa36f",
+            icon_name="microphone",
+            icon_size="2x",
+        )
+
+        if audio_bytes:
+            # Save the Recorded File
+            audio_location = "audio_file.wav"
+            with open(audio_location, "wb") as f:
+                f.write(audio_bytes)
+
+            if language == "English":
+               text=transcribe_text_to_voice_english(audio_location)
+               st.write(text)
+            else:
+               text,trans=transcribe_text_to_voice_hindi(audio_location)
+               st.write(text)
+    
+            link_response = linkRAGhindi(text)
+            st.write("श्रेष्ठ:", link_response)
+            api_response = RAG(text)
+            st.write("श्रेष्ठ:", api_response)      
+            # Read out the text response using tts
+            speech_file_path = 'audio_response.mp3'
+            text_to_speech_ai(speech_file_path, api_response)
+            st.audio(speech_file_path)
+            recctext="recommend top three other websites that could interest the user depending on this link and answer : " + link_response + api_response
+            recc=rechindi(recctext)  
+            st.write("श्रेष्ठ:", recc)
+            
+    else: 
+        # Text input option
+        text_input = st.text_area("आप यहाँ अपना टेक्स्ट दर्ज करें और एंटर दबाएं", "")
+        if st.button("एंटर"):
+            # Process the entered text
+            link_response = linkRAGhindi(text_input)
+            st.write("श्रेष्ठ:", link_response)
+            api_response = RAG(text_input)
+            st.write("श्रेष्ठ:", api_response)
+    
+            # Read out the text response using tts
+            speech_file_path = 'audio_response.mp3'
+            text_to_speech_ai(speech_file_path, api_response)
+            st.audio(speech_file_path)
+            recctext="recommend top three other websites that could interest the user depending on this link and answer : " + link_response + api_response
+            recc=rechindi(recctext)  
+            st.write("श्रेष्ठ:", recc)

requirements.txt

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+llama_index
+audio_recorder_streamlit
+openai