Delete app.py

app.py

@@ -1,64 +0,0 @@
-import gradio as gr
-from langchain.document_loaders.base import Document, BaseLoader
-from langchain.indexes import VectorstoreIndexCreator
-from apify_client import ApifyClient
-import os
-
-# Update with your OpenAI API key
-os.environ["OPENAI_API_KEY"] = "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"
-
-# Page Function to extract website content
-page_function_code = """
-function pageFunction(context) {
-    const $ = context.jQuery;
-    const data = {
-        title: $('title').text(),
-        content: $('body').text(),
-        url: context.request.url
-    };
-    return data;
-}
-"""
-
-# Function to fetch website content using the updated actor
-def fetch_website_content(website_url):
-    apify_client = ApifyClient("apify_api_uz0y556N4IG2aLcESj67kmnGSUpHF12XAkLp")
-    run_input = {
-        "startUrls": [{"url": website_url}],
-        "pageFunction": page_function_code
-    }
-    run = apify_client.actor("moJRLRc85AitArpNN").call(run_input=run_input)
-    items = list(apify_client.dataset(run["defaultDatasetId"]).iterate_items())
-    return items if items else None
-
-# Custom loader for our documents
-class CustomLoader(BaseLoader):
-    def __init__(self, documents):
-        self.documents = documents
-
-    def load(self):
-        return self.documents
-
-# Fetch content
-content = fetch_website_content("https://python.langchain.com/en/latest/")
-documents = [Document(page_content=item["content"] or "", metadata={"source": item.get("url", "Unknown URL")}) for item in content]
-
-# Use custom loader
-loader = CustomLoader(documents)
-index = VectorstoreIndexCreator().from_loaders([loader])
-
-# Function for the Gradio UI
-def ask_langchain(question):
-    result = index.query_with_sources(question)
-    answer = result["answer"]
-    sources = ", ".join(result["sources"])
-    return f"{answer}\n\nSources: {sources}"
-
-# Gradio interface
-iface = gr.Interface(fn=ask_langchain, 
-                     inputs="text", 
-                     outputs="text",
-                     live=True,
-                     title="LangChain Query",
-                     description="Ask a question about LangChain based on the indexed content.")
-iface.launch()