Upload 3 files

app.py

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+import streamlit as st
+import assemblyai as aai
+from langchain_huggingface import HuggingFaceEmbeddings
+from langchain_chroma import Chroma
+from config import CHROMA_DB_PATH, EMBEDDING_MODEL, ASSEMBLYAI_API_KEY
+import tempfile
+
+# Initialize AssemblyAI
+aai.settings.api_key = ASSEMBLYAI_API_KEY
+transcriber = aai.Transcriber()
+
+# Load embeddings model
+embeddings = HuggingFaceEmbeddings(model_name=EMBEDDING_MODEL)
+
+# Load ChromaDB
+db = Chroma(persist_directory=CHROMA_DB_PATH, embedding_function=embeddings)
+
+def transcribe_audio(audio_path):
+    """Convert audio to text using AssemblyAI."""
+    transcript = transcriber.transcribe(audio_path)
+    return transcript.text if transcript else ""
+
+def retrieve_similar_chunks(query: str, k=5):
+    """Retrieve top-k most relevant document chunks from ChromaDB."""
+    results = db.similarity_search(query, k=k)
+    return [(doc.metadata['num'], doc.page_content) for doc in results]
+
+# Streamlit UI
+st.title("Video Subtitle Search Engine")
+
+uploaded_file = st.file_uploader("Upload an audio/video file", type=["mp3", "wav", "mp4"])
+num_results = st.slider("Number of results", 1, 10, 5)
+
+if uploaded_file:
+    with tempfile.NamedTemporaryFile(delete=False) as tmp_file:
+        tmp_file.write(uploaded_file.read())
+        tmp_path = tmp_file.name
+    
+    st.write("Transcribing audio...")
+    query_text = transcribe_audio(tmp_path)
+    st.write("Transcription:", query_text)
+    
+    if query_text:
+        st.write("Searching for relevant subtitles...")
+        results = retrieve_similar_chunks(query_text, num_results)
+        
+        for num, content in results:
+            st.markdown(f"**Subtitle ID:** [{num}](https://www.opensubtitles.org/en/subtitles/{num})")
+            st.write(content)
+            st.markdown("---")

config.py

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+import os
+from dotenv import load_dotenv
+
+# Load environment variables from .env file
+load_dotenv()
+
+# Retrieve API key from environment variables
+GOOGLE_API_KEY = os.getenv("GOOGLE_API_KEY")
+
+# Embedding model name
+EMBEDDING_MODEL = "sentence-transformers/all-MiniLM-L6-v2"
+
+# ChromaDB path
+CHROMA_DB_PATH = "./chroma_db"
+
+# AssemblyAI API key
+ASSEMBLYAI_API_KEY=os.getenv("ASSEMBLYAI_API_KEY")

requirements.txt

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+pandas
+ipykernel
+langchain
+langchain-community
+dotenv
+torch
+torchaudio
+transformers
+numpy
+streamlit
+sentence-transformers
+chromadb
+scikit-learn
+langchain_huggingface
+langchain_chroma
+assemblyai