Merge pull request #1 from roverflow/bot_script

Added basic bot script to to interact with docs

Author: Ruchip16

data/__init__.py

@@ -6,4 +6,8 @@ faiss-cpu
 streamlit
 python-dotenv
 slack-sdk
-pyyaml
+pyyaml
+llama-index-llms-ollama
+llama-index-embeddings-huggingface
+llama-index-readers-file
+PyMuPDF

requirements.txt

@@ -0,0 +1,64 @@
+import asyncio
+import os
+from pathlib import Path
+from llama_index.core import (
+    VectorStoreIndex,
+    StorageContext,
+    load_index_from_storage,
+    Settings,
+)
+from llama_index.llms.ollama import Ollama
+from llama_index.embeddings.huggingface import HuggingFaceEmbedding
+from llama_index.readers.file import PDFReader
+
+# Config
+ROOT_DIR = Path(__file__).resolve().parent.parent
+DATA_DIR = ROOT_DIR / "data"
+STORAGE_DIR = ROOT_DIR / "storage"
+
+async def build_and_save_index():
+    """Builds the index from PDF files and saves it."""
+    print("Loading PDF documents...")
+    reader = PDFReader()
+    documents = reader.load_data(folder_path=DATA_DIR)
+
+    print("Building index...")
+    index = VectorStoreIndex.from_documents(documents)
+
+    print(f"Saving index to {STORAGE_DIR}/...")
+    index.storage_context.persist(persist_dir=STORAGE_DIR)
+    return index
+
+async def load_or_build_index():
+    """Loads existing index or builds a new one if not found."""
+    if os.path.exists(STORAGE_DIR):
+        print(f"Loading existing index from {STORAGE_DIR}/...")
+        storage_context = StorageContext.from_defaults(persist_dir=STORAGE_DIR)
+        index = load_index_from_storage(storage_context)
+    else:
+        index = await build_and_save_index()
+    return index
+
+async def main():
+    # Step 1: Setup global Settings
+    Settings.embed_model = HuggingFaceEmbedding(model_name="BAAI/bge-base-en-v1.5")
+    Settings.llm = Ollama(model="llama3.1", request_timeout=360.0)
+
+    # Step 2: Load or build the index
+    index = await load_or_build_index()
+
+    # Step 3: Create a query engine
+    query_engine = index.as_query_engine()
+
+    print("\n🔵 Chatbot ready! Type your questions (type 'exit' to quit):\n")
+
+    while True:
+        user_query = input("You: ")
+        if user_query.lower() in ("exit", "quit"):
+            print("Bye!")
+            break
+        response = await query_engine.aquery(user_query)
+        print(f"Bot: {response}\n")
+
+if __name__ == "__main__":
+    asyncio.run(main())