Update app.py

app.py

@@ -2,14 +2,14 @@ import gradio as gr
 from langchain_community.vectorstores import Qdrant
 from langchain_community.embeddings import HuggingFaceBgeEmbeddings
 from langchain.text_splitter import RecursiveCharacterTextSplitter
-from youtube_transcript_api import YouTubeTranscriptApi
-import re
 from pytubefix import YouTube
+from qdrant_client import QdrantClient
+from langchain_groq import ChatGroq
+import re
 
-
-def get_text(url):
-    yt = YouTube(url)
-
+# Function to extract the transcript text
+def get_text(video_id):
+    yt = YouTube(video_id)
     caption = yt.captions.get_by_language_code('en')
     transcript = caption.generate_srt_captions()
 
@@ -19,19 +19,18 @@ def get_text(url):
     # Extract text from every third line (lines 3, 6, 9, ...)
     extracted_text = " ".join(lines[i] for i in range(2, len(lines), 4))
 
-    #print(extracted_text)
     return extracted_text
 
+# Function to create the Qdrant database
 def create_qdrant_database(url):
-   
     text = get_text(url)
     
     text_splitter = RecursiveCharacterTextSplitter(
-        chunk_size=10000,  # Adjusted chunk size for better processing
-        chunk_overlap=1000  # Adjusted overlap for context preservation
+        chunk_size=10000,
+        chunk_overlap=1000
     )
 
-    docs = text_splitter.split_text(text)  # Split into list of text chunks
+    docs = text_splitter.split_text(text)
 
     model_name = 'BAAI/bge-large-en'
     model_kwargs = {'device': 'cpu'}
@@ -44,11 +43,11 @@ def create_qdrant_database(url):
 
     collection_name = "Youtube_Videos"
     
-    qdrant_url="https://ec1c2790-c2e2-4c78-943f-5f9772492b2e.europe-west3-0.gcp.cloud.qdrant.io:6333"
-    api_key="zIUUg_1QTtjSmCLNEpKnxJZeedKuh635c-YgGkDbI5EJ0ITjpOSyqw"
+    qdrant_url = "https://ec1c2790-c2e2-4c78-943f-5f9772492b2e.europe-west3-0.gcp.cloud.qdrant.io:6333"
+    api_key = "zIUUg_1QTtjSmCLNEpKnxJZeedKuh635c-YgGkDbI5EJ0ITjpOSyqw"
 
     qdrant = Qdrant.from_texts(
-        texts=docs,  # Pass the list of documents
+        texts=docs,
         embedding=embeddings,
         url=qdrant_url,
         prefer_grpc=False,
@@ -59,16 +58,58 @@ def create_qdrant_database(url):
 
     return "Qdrant database created" 
 
-# Gradio Interface
-def gradio_interface(url):
-    result = create_qdrant_database(url)
-    return result
+# Function to answer questions based on the created Qdrant database
+def get_answer(question):
+    qdrant_url = "https://ec1c2790-c2e2-4c78-943f-5f9772492b2e.europe-west3-0.gcp.cloud.qdrant.io:6333"
+    api_key = "zIUUg_1QTtjSmCLNEpKnxJZeedKuh635c-YgGkDbI5EJ0ITjpOSyqw"
 
-with gr.Blocks() as demo:
-    url_input = gr.Textbox(label="YouTube Video URL")
-    output_text = gr.Textbox(label="Result")
-    run_button = gr.Button("Create Qdrant Database")
+    # Initialize the embeddings and Qdrant client
+    model_name = 'BAAI/bge-large-en'
+    model_kwargs = {'device': 'cpu'}
+    encode_kwargs = {'normalize_embeddings': False}
+    embeddings = HuggingFaceBgeEmbeddings(
+        model_name=model_name,
+        model_kwargs=model_kwargs,
+        encode_kwargs=encode_kwargs
+    )
+
+    client = QdrantClient(
+        url=qdrant_url,
+        prefer_grpc=False,
+        api_key=api_key,
+        timeout=50
+    )
+    collection_name = "Youtube_Videos"
+    db = Qdrant(
+        client=client,
+        embeddings=embeddings,
+        collection_name=collection_name,
     
-    run_button.click(fn=gradio_interface, inputs=url_input, outputs=output_text)
+    )
+
+    # Initialize ChatGroq model
+    api_key = "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"
+    model_name = "llama-3.1-70b-versatile"
+    model = ChatGroq(api_key=api_key, model=model_name, temperature=0)
+
+    # Search for the relevant document and generate the answer
+    docs = db.similarity_search_with_score(query=question, k=1)
+    for doc, score in docs:
+        return model.invoke(f"{question} : {doc.page_content}")
+
+# Gradio Interface
+with gr.Blocks() as demo:
+    with gr.Row():
+        with gr.Column():
+            url_input = gr.Textbox(label="YouTube Video URL")
+            output_text = gr.Textbox(label="Result")
+            run_button = gr.Button("Create Qdrant Database")
+            run_button.click(fn=create_qdrant_database, inputs=url_input, outputs=output_text)
+        
+        with gr.Column():
+            question_input = gr.Textbox(label="Ask a Question")
+            answer_output = gr.Textbox(label="Answer")
+            ask_button = gr.Button("Get Answer")
+            ask_button.click(fn=get_answer, inputs=question_input, outputs=answer_output)
 
-demo.launch()
+demo.launch()