Update app.py
Browse files
app.py
CHANGED
@@ -7,6 +7,7 @@ from langchain.docstore.document import Document
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import chromadb
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from sentence_transformers import SentenceTransformer
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import google.generativeai as genai
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# Initialize Gemini API
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genai.configure(api_key="AIzaSyAxUd2tS-qj9C7frYuHRsv92tziXHgIvLo")
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@@ -19,7 +20,7 @@ chroma_client = chromadb.PersistentClient(path=CHROMA_PATH)
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if 'scraped' not in st.session_state:
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st.session_state.scraped = False
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if 'collection_name' not in st.session_state:
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st.session_state.collection_name = ""
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# Initialize embedding model
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embedding_model = SentenceTransformer("all-MiniLM-L6-v2")
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@@ -43,17 +44,20 @@ def add_chunks_to_db(chunks, collection_name):
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embeddings = embedding_model.encode(documents, convert_to_list=True)
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collection.upsert(documents=documents, ids=ids, embeddings=embeddings)
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def scrape_text(url
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try:
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response = requests.get(url)
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response.raise_for_status()
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soup = BeautifulSoup(response.text, 'html.parser')
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text = clean_text(soup.get_text())
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chunks = split_content_into_chunks(text)
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add_chunks_to_db(chunks, collection_name)
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#
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st.session_state.collection_name = collection_name
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st.session_state.scraped = True
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return "Scraping and processing complete. You can now ask questions!"
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@@ -62,7 +66,7 @@ def scrape_text(url, collection_name):
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def ask_question(query, collection_name):
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# Get the collection
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collection = chroma_client.
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query_embedding = embedding_model.encode(query, convert_to_list=True)
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results = collection.query(query_embeddings=[query_embedding], n_results=2)
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@@ -90,24 +94,19 @@ st.title("Web Scraper & Q&A Chatbot")
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with st.container():
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st.subheader("Step 1: Scrape a Website")
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# Let user create a new database or use existing one
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collection_name = st.text_input("Enter a name for this data collection:",
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value="my_collection",
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help="This will create a new database or use an existing one with this name")
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url = st.text_input("Enter the URL to scrape:")
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if url
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if st.button("Scrape & Process"):
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with st.spinner("Scraping and processing content..."):
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result = scrape_text(url
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st.success(result)
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# Q&A section - only appears after scraping is complete
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if st.session_state.scraped:
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with st.container():
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st.subheader("Step 2: Ask Questions About the Scraped Content")
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st.write(
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# Chat history
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if 'chat_history' not in st.session_state:
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@@ -144,8 +143,8 @@ with st.sidebar:
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# List available collections
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try:
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collection_names =
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if collection_names:
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st.write("Available data collections:")
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@@ -155,11 +154,11 @@ with st.sidebar:
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st.session_state.collection_name = selected_collection
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st.session_state.scraped = True
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st.success(f"Loaded collection: {selected_collection}")
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st.rerun()
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except Exception as e:
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st.error(f"Error
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# Add a button to clear the session and start over
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if st.button("Clear Chat History"):
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st.session_state.chat_history = []
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st.rerun()
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import chromadb
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from sentence_transformers import SentenceTransformer
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import google.generativeai as genai
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import uuid
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# Initialize Gemini API
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genai.configure(api_key="AIzaSyAxUd2tS-qj9C7frYuHRsv92tziXHgIvLo")
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if 'scraped' not in st.session_state:
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st.session_state.scraped = False
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if 'collection_name' not in st.session_state:
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st.session_state.collection_name = "default_collection"
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# Initialize embedding model
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embedding_model = SentenceTransformer("all-MiniLM-L6-v2")
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embeddings = embedding_model.encode(documents, convert_to_list=True)
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collection.upsert(documents=documents, ids=ids, embeddings=embeddings)
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def scrape_text(url):
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try:
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response = requests.get(url)
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response.raise_for_status()
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soup = BeautifulSoup(response.text, 'html.parser')
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# Extract domain for collection name
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collection_name = st.session_state.collection_name
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text = clean_text(soup.get_text())
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chunks = split_content_into_chunks(text)
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add_chunks_to_db(chunks, collection_name)
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# Set scraped state to True
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st.session_state.scraped = True
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return "Scraping and processing complete. You can now ask questions!"
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def ask_question(query, collection_name):
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# Get the collection
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collection = chroma_client.get_or_create_collection(name=collection_name)
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query_embedding = embedding_model.encode(query, convert_to_list=True)
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results = collection.query(query_embeddings=[query_embedding], n_results=2)
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with st.container():
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st.subheader("Step 1: Scrape a Website")
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url = st.text_input("Enter the URL to scrape:")
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if url:
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if st.button("Scrape & Process"):
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with st.spinner("Scraping and processing content..."):
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result = scrape_text(url)
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st.success(result)
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# Q&A section - only appears after scraping is complete
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if st.session_state.scraped:
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with st.container():
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st.subheader("Step 2: Ask Questions About the Scraped Content")
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st.write("Ask a question about the content you've scraped:")
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# Chat history
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if 'chat_history' not in st.session_state:
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# List available collections
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try:
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# Fix for ChromaDB v0.6.0 - list_collections() now returns only names
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collection_names = chroma_client.list_collections()
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if collection_names:
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st.write("Available data collections:")
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st.session_state.collection_name = selected_collection
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st.session_state.scraped = True
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st.success(f"Loaded collection: {selected_collection}")
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st.rerun()
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except Exception as e:
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st.error(f"Error: {str(e)}")
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# Add a button to clear the session and start over
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if st.button("Clear Chat History"):
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st.session_state.chat_history = []
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st.rerun()
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