upload app(1).py.

app (1).py

@@ -0,0 +1,67 @@
+# -*- coding: utf-8 -*-
+"""app
+
+Automatically generated by Colab.
+
+Original file is located at
+    https://colab.research.google.com/drive/1MuuKKNek3EmP5A5aGk8ail0MmT7w10f9
+"""
+
+!pip install -U langchain-community
+
+!pip install langchain==0.3.0 llama-index==0.12.0 sentence-transformers faiss-cpu gradio
+
+import pandas as pd
+
+# Load your uploaded file
+data = pd.read_csv('/content/course.csv')
+
+# Combine TITLE, DESCRIPTION, and CURRICULUM for processing
+docs = []
+for _, row in data.iterrows():
+    content = f"{row['TITLE']}\n{row['DESCRIPTION']}\n{row['CURRICULUM']}"
+    docs.append({"content": content, "metadata": {"title": row['TITLE'], "url": row['URL']}})
+
+from langchain.embeddings import HuggingFaceEmbeddings
+from langchain.vectorstores import FAISS
+
+# Create embeddings
+embedding_model = HuggingFaceEmbeddings(model_name="sentence-transformers/all-MiniLM-L6-v2")
+texts = [doc["content"] for doc in docs]
+metadatas = [doc["metadata"] for doc in docs]
+
+# Create FAISS Index
+vectorstore = FAISS.from_texts(texts, embedding_model, metadatas=metadatas)
+
+import os
+
+# Replace 'YOUR_API_KEY' with your actual OpenAI API key
+os.environ["OPENAI_API_KEY"] = "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"
+
+from langchain.chains import RetrievalQA
+from langchain.llms import OpenAI
+
+retriever = vectorstore.as_retriever()
+qa_chain = RetrievalQA.from_chain_type(llm=OpenAI(model_name="text-davinci-003"), retriever=retriever)
+
+import gradio as gr
+
+def smart_search(query):
+    results = retriever.get_relevant_documents(query)
+    response = ""
+    for result in results:
+        title = result.metadata.get("title", "No Title")
+        url = result.metadata.get("url", "No URL")
+        response += f"**{title}**\n[Link to Course]({url})\n\n"
+    return response.strip()
+
+interface = gr.Interface(
+    fn=smart_search,
+    inputs="text",
+    outputs="markdown",
+    title="Smart Search for Analytics Vidhya Free Courses",
+    description="Enter a keyword or a query to find relevant free courses on Analytics Vidhya."
+)
+
+# Launch the Gradio app
+interface.launch(share=True)