Create app.py

app.py

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+import streamlit as st
+from gradio_client import Client
+from llama_index.llms import Replicate
+from llama_index.embeddings import LangchainEmbedding
+from langchain.embeddings.huggingface import HuggingFaceEmbeddings
+from llama_index import set_global_service_context, ServiceContext, VectorStoreIndex, SimpleDirectoryReader
+import os
+
+# Ensure the environment variable is set
+if "REPLICATE_API_TOKEN" not in os.environ:
+    raise ValueError("Please set the REPLICATE_API_TOKEN environment variable.")
+else:
+    os.environ["REPLICATE_API_TOKEN"] = os.environ["REPLICATE_API_TOKEN"]
+
+PATH = '/Data'
+
+llm = Replicate(
+    model="replicate/vicuna-13b:6282abe6a492de4145d7bb601023762212f9ddbbe78278bd6771c8b3b2f2a13b"
+)
+
+embeddings = LangchainEmbedding(
+    HuggingFaceEmbeddings(model_name="all-MiniLM-L6-v2")
+)
+
+service_context = ServiceContext.from_defaults(
+    chunk_size=1024,
+    llm=llm,
+    embed_model=embeddings
+)
+set_global_service_context(service_context)
+
+# Transcribe and Query function
+def transcribe_and_query(youtube_url, message):
+    client = Client("https://sanchit-gandhi-whisper-jax.hf.space/")
+    result = client.predict(youtube_url, "transcribe", True, fn_index=7)
+    with open(f'{PATH}/docs.txt','w') as f:
+        f.write(result[1])
+
+    documents = SimpleDirectoryReader(PATH).load_data()
+    index = VectorStoreIndex.from_documents(documents)
+    query_engine = index.as_query_engine()
+    response = query_engine.query(message)
+    
+    # Assuming the response has a 'response' attribute with the answer
+    return response.response
+
+# Streamlit UI
+st.title("YouTube Video Chatbot")
+
+# Input for YouTube URL
+youtube_url = st.text_input("Enter YouTube Video URL:")
+
+# Chatbot UI
+if "messages" not in st.session_state:
+    st.session_state.messages = []
+
+# Display chat history
+for message in st.session_state.messages:
+    if message["role"] == "human":
+        st.write(f"You: {message['content']}")
+    else:
+        st.write(f"Chatbot: {message['content']}")
+
+# User input
+prompt = st.text_input("Ask something about the video:")
+
+# React to user input
+if prompt:
+    # Add user message to chat history
+    st.session_state.messages.append({"role": "human", "content": prompt})
+
+    # Get response from the chatbot
+    response = transcribe_and_query(youtube_url, prompt)
+
+    # Add assistant response to chat history
+    st.session_state.messages.append({"role": "assistant", "content": response})
+
+# Refresh the page to show the updated chat history
+if prompt:
+    st.experimental_rerun()