Update app.py

app.py

@@ -1,89 +1,66 @@
-
 import subprocess
 import gradio as gr
-subprocess.call(["/usr/local/bin/python", "-m", "pip", "install", "--upgrade", "sentence-transformers"])
-
-subprocess.call(["pip ","-q","install", "sentence-transformers"])
-subprocess.call(["pip","install","langchain"])
-# Install pypdf
-subprocess.call(["pip", "install", "-q", "pypdf"])
-
-# Install python-dotenv
-subprocess.call(["pip", "install", "-q", "python-dotenv"])
-
-# Install transformers
-subprocess.call(["pip", "install", "-q", "transformers"])
-
-# Install llama-cpp-python with specific CMAKE_ARGS
-subprocess.call(["pip", "install", "llama-cpp-python", "--no-cache-dir", "--install-option", "--CMAKE_ARGS=-DLLAMA_CUBLAS=on", "--install-option", "--FORCE_CMAKE=1"])
-
-# Install llama-index
-subprocess.call(["pip", "install", "-q", "llama-index"])
-
-
-
 import logging
 import sys
+from llama_index import VectorStoreIndex, SimpleDirectoryReader, ServiceContext
+from llama_index.llms import LlamaCPP
+from llama_index.llms.llama_utils import messages_to_prompt, completion_to_prompt
+from langchain.embeddings.huggingface import HuggingFaceEmbeddings
+from llama_index.embeddings import LangchainEmbedding
 
+# Install necessary packages
+subprocess.run(["/usr/local/bin/python", "-m", "pip", "install", "--upgrade", "sentence-transformers"])
+subprocess.run(["pip", "install", "sentence-transformers"])
+subprocess.run(["pip", "install", "langchain"])
+subprocess.run(["pip", "install", "-q", "pypdf"])
+subprocess.run(["pip", "install", "-q", "python-dotenv"])
+subprocess.run(["pip", "install", "-q", "transformers"])
+subprocess.run(["pip", "install", "llama-cpp-python", "--no-cache-dir", "--install-option", "--CMAKE_ARGS=-DLLAMA_CUBLAS=on", "--install-option", "--FORCE_CMAKE=1"])
+subprocess.run(["pip", "install", "-q", "llama-index"])
+
+# Set up logging
 logging.basicConfig(stream=sys.stdout, level=logging.INFO)
 logging.getLogger().addHandler(logging.StreamHandler(stream=sys.stdout))
 
-from llama_index import VectorStoreIndex, SimpleDirectoryReader, ServiceContext
-
-
+# Load documents
 documents = SimpleDirectoryReader("/content/Data/").load_data()
 
-import torch
-
-from llama_index.llms import LlamaCPP
-from llama_index.llms.llama_utils import messages_to_prompt, completion_to_prompt
+# Set up LlamaCPP
 llm = LlamaCPP(
-    # You can pass in the URL to a GGML model to download it automatically
     model_url='https://huggingface.co/TheBloke/Mistral-7B-Instruct-v0.1-GGUF/resolve/main/mistral-7b-instruct-v0.1.Q4_K_M.gguf',
-    # optionally, you can set the path to a pre-downloaded model instead of model_url
     model_path=None,
     temperature=0.1,
     max_new_tokens=256,
-    # llama2 has a context window of 4096 tokens, but we set it lower to allow for some wiggle room
     context_window=3900,
-    # kwargs to pass to __call__()
     generate_kwargs={},
-    # kwargs to pass to __init__()
-    # set to at least 1 to use GPU
     model_kwargs={"n_gpu_layers": -1},
-    # transform inputs into Llama2 format
     messages_to_prompt=messages_to_prompt,
     completion_to_prompt=completion_to_prompt,
     verbose=True,
 )
 
-
-
-from langchain.embeddings.huggingface import HuggingFaceEmbeddings
-from llama_index.embeddings import LangchainEmbedding
-from llama_index import ServiceContext
-
-
+# Set up embeddings
 embed_model = LangchainEmbedding(
-  HuggingFaceEmbeddings(model_name="thenlper/gte-large")
+    HuggingFaceEmbeddings(model_name="thenlper/gte-large")
 )
 
-
+# Set up service context
 service_context = ServiceContext.from_defaults(
     chunk_size=256,
     llm=llm,
     embed_model=embed_model
 )
 
+# Create index
 index = VectorStoreIndex.from_documents(documents, service_context=service_context)
-
 query_engine = index.as_query_engine()
 
+# Define query handler
 def query_handler(query):
     response = query_engine.query(query)
     return response
 
-# Create an interface with a text input for user query
+# Create Gradio interface
 iface = gr.Interface(
     fn=query_handler,
     inputs=gr.Textbox(prompt="Enter your question here..."),
@@ -95,5 +72,3 @@ iface = gr.Interface(
 
 # Launch the interface
 iface.launch()
-
-