Update app.py

app.py

@@ -1,70 +1,69 @@
-import streamlit as st
-from llama_index import SimpleDirectoryReader, GPTVectorStoreIndex
+import openai
+import gradio as gr
+import time
+import warnings
+import warnings
 import os
-import shutil
-
-
-def save_file(files):
-    directory_name = 'tmp_docs'
-
-    # Remove existing files in the directory
-    if os.path.exists(directory_name):
-        for filename in os.listdir(directory_name):
-            file_path = os.path.join(directory_name, filename)
-            try:
-                if os.path.isfile(file_path):
-                    os.remove(file_path)
-            except Exception as e:
-                print(f"Error: {e}")
-
-    # Save the new file with original filename
-    if files is not None:
-        for file in files:
-            file_name = file.name
-            file_path = os.path.join(directory_name, file_name)
-            with open(file_path, 'wb') as f:
-                shutil.copyfileobj(file, f)
-
-
-def ingest(docs_dir):
-    documents = SimpleDirectoryReader(docs_dir).load_data()
-    index = GPTVectorStoreIndex.from_documents(documents)
-    return index
-
-
-def get_answer(index, message):
-    response = query(index, message)
-    return [('Chatbot', ''.join(response.response))]
-
-
-def query(index, query_text):
-    query_engine = index.as_query_engine()
-    response = query_engine.query(query_text)
-    return response
-
-
-os.environ['OPENAI_API_KEY'] = st.text_input(
-    "Enter your OpenAI API key", type="password")
-
-if os.environ['OPENAI_API_KEY']:
-    # Initialize chatbot history
-    chatbot = []
-
-    # Display file upload component
-    files = st.file_uploader('Upload Files', accept_multiple_files=True)
-    if files is not None:
-        save_file(files)
-
-    index = ingest('tmp_docs')
-
-    # Display message input component
-    message = st.text_input('Enter message')
-
-    # If message is entered, ingest documents and get chatbot response
-    if message:
-        chatbot.append(('You', message))
-        chatbot += get_answer(index, message)
-
-    # Display chat history
-    st.text_area('Chatbot:', value='\n'.join(
-        [f'{x[0]}: {x[1]}' for x in chatbot]), height=250)
+from gtts import gTTS
+
+warnings.filterwarnings("ignore")
+
+openai.api_key = "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"
+
+def chatgpt_api(input_text):
+    messages = [
+    {"role": "system", "content": "You are a helpful assistant."}]
+    
+    if input_text:
+        messages.append(
+            {"role": "user", "content": input_text},
+        )
+        chat_completion = openai.ChatCompletion.create(
+            model="gpt-3.5-turbo", messages=messages
+        )
+    
+    reply = chat_completion.choices[0].message.content
+    return reply
+
+#ffmpeg -f lavfi -i anullsrc=r=44100:cl=mono -t 10 -q:a 9 -acodec libmp3lame Temp.mp3'
+
+def transcribe(audio, text):
+    language = "en"
+
+    if audio is not None:
+        with open(audio, "rb") as transcript:
+            prompt = openai.Audio.transcribe("whisper-1", transcript)
+        s = prompt["text"]
+    else:
+        s = text
+    
+    response = openai.Completion.create(
+        engine="text-davinci-002",
+        prompt=s,
+        max_tokens=60,
+        n=1,
+        stop=None,
+        temperature=0.5,
+    )
+    
+    out_result = chatgpt_api(s)
+    
+    audioobj = gTTS(text = out_result, 
+                    lang = language, 
+                    slow = False)
+    
+    audioobj.save("Temp.mp3")
+
+    return [s, out_result, "Temp.mp3"]
+
+
+with gr.Blocks() as demo:
+    gr.Markdown("Dilip AI")
+    input1 = gr.inputs.Audio(source="microphone", type = "filepath", label="Use your voice to chat")
+    input2 = gr.inputs.Textbox(lines=7, label="Chat with AI")
+    output_1 = gr.Textbox(label="User Input")
+    output_2 = gr.Textbox(label="Text Output")
+    output_3 = gr.Audio("Temp.mp3", label="Speech Output")
+    btn = gr.Button("Run")
+    btn.click(fn=transcribe, inputs=[input1, input2], outputs=[output_1, output_2, output_3])
+demo.launch()