TR updates, first round

Author: lpozo

python-llamaindex/async_query.py

@@ -1,5 +1,4 @@
 import asyncio
-import logging
 from pathlib import Path
 
 from llama_index.core import (
@@ -9,24 +8,24 @@
     load_index_from_storage,
 )
 
-# Disable logging messages
-logging.getLogger("llama_index").setLevel(logging.WARNING)
-logging.getLogger("httpx").setLevel(logging.WARNING)
-
 # Define the storage directory
-PERSIST_DIR = "./storage"
+BASE_DIR = Path(__file__).resolve().parent
+PERSIST_DIR = BASE_DIR / "storage"
+DATA_FILE = BASE_DIR / "data" / "pep8.rst"
 
 
-def get_index(persist_dir=PERSIST_DIR):
-    if Path(persist_dir).exists():
-        storage_context = StorageContext.from_defaults(persist_dir=persist_dir)
+def get_index(persist_dir=PERSIST_DIR, data_file=DATA_FILE):
+    if persist_dir.exists():
+        storage_context = StorageContext.from_defaults(
+            persist_dir=str(persist_dir),
+        )
         index = load_index_from_storage(storage_context)
         print("Index loaded from storage...")
     else:
-        reader = SimpleDirectoryReader(input_files=["./data/pep8.rst"])
+        reader = SimpleDirectoryReader(input_files=[str(data_file)])
         documents = reader.load_data()
         index = VectorStoreIndex.from_documents(documents)
-        index.storage_context.persist(persist_dir=persist_dir)
+        index.storage_context.persist(persist_dir=str(persist_dir))
         print("Index created and persisted to storage...")
 
     return index

python-llamaindex/demo.py

@@ -2,6 +2,8 @@
 
 reader = SimpleDirectoryReader(input_files=["./data/pep8.rst"])
 documents = reader.load_data()
+
 index = VectorStoreIndex.from_documents(documents)
+
 query_engine = index.as_query_engine()
 print(query_engine.query("What is this document about?"))

python-llamaindex/demo_google.py

@@ -0,0 +1,15 @@
+from llama_index.core import SimpleDirectoryReader, VectorStoreIndex
+from llama_index.embeddings.google_genai import GoogleGenAIEmbedding
+from llama_index.llms.google_genai import GoogleGenAI
+
+reader = SimpleDirectoryReader(input_files=["./data/pep8.rst"])
+documents = reader.load_data()
+
+embed_model = GoogleGenAIEmbedding(model="models/embedding-gecko-001")
+index = VectorStoreIndex.from_documents(documents, embed_model=embed_model)
+
+llm = GoogleGenAI(model="gemini-2.5-flash")
+query_engine = index.as_query_engine(llm=llm)
+
+response = query_engine.query("What is this document about?")
+print(response)

python-llamaindex/demo_gpt5.py

@@ -0,0 +1,12 @@
+from llama_index.core import SimpleDirectoryReader, VectorStoreIndex
+from llama_index.llms.openai import OpenAI
+
+reader = SimpleDirectoryReader(input_files=["./data/pep8.rst"])
+documents = reader.load_data()
+index = VectorStoreIndex.from_documents(documents)
+
+llm = OpenAI(model="gpt-5.1")
+query_engine = index.as_query_engine(llm=llm)
+
+response = query_engine.query("Summarize the import rules.")
+print(response)

python-llamaindex/demo_ollama.py

@@ -0,0 +1,15 @@
+from llama_index.core import SimpleDirectoryReader, VectorStoreIndex
+from llama_index.embeddings.ollama import OllamaEmbedding
+from llama_index.llms.ollama import Ollama
+
+reader = SimpleDirectoryReader(input_files=["./data/pep8.rst"])
+documents = reader.load_data()
+
+embed_model = OllamaEmbedding(model_name="embeddinggemma")
+index = VectorStoreIndex.from_documents(documents, embed_model=embed_model)
+
+llm = Ollama(model="llama3.2")
+query_engine = index.as_query_engine(llm=llm)
+
+response = query_engine.query("What is this document about?")
+print(response)

python-llamaindex/sync_query.py python-llamaindex/single_query.pypython-llamaindex/sync_query.py renamed to python-llamaindex/single_query.py

@@ -1,4 +1,3 @@
-import logging
 from pathlib import Path
 
 from llama_index.core import (
@@ -8,24 +7,24 @@
     load_index_from_storage,
 )
 
-# Disable logging messages
-logging.getLogger("llama_index").setLevel(logging.WARNING)
-logging.getLogger("httpx").setLevel(logging.WARNING)
-
 # Define the storage directory
-PERSIST_DIR = "./storage"
+BASE_DIR = Path(__file__).resolve().parent
+PERSIST_DIR = BASE_DIR / "storage"
+DATA_FILE = BASE_DIR / "data" / "pep8.rst"
 
 
-def get_index(persist_dir=PERSIST_DIR):
-    if Path(persist_dir).exists():
-        storage_context = StorageContext.from_defaults(persist_dir=persist_dir)
+def get_index(persist_dir=PERSIST_DIR, data_file=DATA_FILE):
+    if persist_dir.exists():
+        storage_context = StorageContext.from_defaults(
+            persist_dir=str(persist_dir),
+        )
         index = load_index_from_storage(storage_context)
         print("Index loaded from storage...")
     else:
-        reader = SimpleDirectoryReader(input_files=["./data/pep8.rst"])
+        reader = SimpleDirectoryReader(input_files=[str(data_file)])
         documents = reader.load_data()
         index = VectorStoreIndex.from_documents(documents)
-        index.storage_context.persist(persist_dir=persist_dir)
+        index.storage_context.persist(persist_dir=str(persist_dir))
         print("Index created and persisted to storage...")
 
     return index