Update as per the feedback.

- moved args parser inside main
- assigned empty list to docs.
- Updated README.md.

README.md

@@ -83,25 +83,7 @@ Type `exit` to finish the script.
 
 
 ### Script Arguments
-The script also supports optional command-line arguments to modify its behavior:
+The script also supports optional command-line arguments to modify its behavior. You can see a full list of these arguments by running the command ```python privateGPT.py --help``` in your terminal
-
-- `--hide-source` or `-S`: Use this flag to disable printing of the source documents used for answers. By default, the source documents are printed.
-  
-```shell
-python privateGPT.py --hide-source
-```
-
-- `--mute-stream` or `-M`: Use this flag to disable LLM standard output streaming response, which by default prints progress to the console.
-
-```shell
-python privateGPT.py --mute-stream
-```
-
-You can combine these options if needed:
-
-```shell
-python privateGPT.py --hide-source --mute-callback
-```
 
 
 # How does it work?

privateGPT.py

@@ -18,12 +18,14 @@ model_n_ctx = os.environ.get('MODEL_N_CTX')
 
 from constants import CHROMA_SETTINGS
 
-def main(hide_source=False, mute_stream=False):
+def main():
+    # Parse the command line arguments
+    args = parse_arguments()
     embeddings = HuggingFaceEmbeddings(model_name=embeddings_model_name)
     db = Chroma(persist_directory=persist_directory, embedding_function=embeddings, client_settings=CHROMA_SETTINGS)
     retriever = db.as_retriever()
     # activate/deactivate the streaming StdOut callback for LLMs
-    callbacks = [] if mute_stream else [StreamingStdOutCallbackHandler()]
+    callbacks = [] if args.mute_stream else [StreamingStdOutCallbackHandler()]
     # Prepare the LLM
     match model_type:
         case "LlamaCpp":
@@ -33,7 +35,7 @@ def main(hide_source=False, mute_stream=False):
         case _default:
             print(f"Model {model_type} not supported!")
             exit;
-    qa = RetrievalQA.from_chain_type(llm=llm, chain_type="stuff", retriever=retriever, return_source_documents= not hide_source)
+    qa = RetrievalQA.from_chain_type(llm=llm, chain_type="stuff", retriever=retriever, return_source_documents= not args.hide_source)
     # Interactive questions and answers
     while True:
         query = input("\nEnter a query: ")
@@ -42,7 +44,7 @@ def main(hide_source=False, mute_stream=False):
 
         # Get the answer from the chain
         res = qa(query)
-        answer, docs = res['result'], None if hide_source else res['source_documents']
+        answer, docs = res['result'], [] if args.hide_source else res['source_documents']
 
         # Print the result
         print("\n\n> Question:")
@@ -50,14 +52,14 @@ def main(hide_source=False, mute_stream=False):
         print("\n> Answer:")
         print(answer)
 
-        # Print the relevant sources used for the answer, if source is True
+        # Print the relevant sources used for the answer
-        if not hide_source and docs:
         for document in docs:
             print("\n> " + document.metadata["source"] + ":")
             print(document.page_content)
 
 def parse_arguments():
-    parser = argparse.ArgumentParser()
+    parser = argparse.ArgumentParser(description='privateGPT: Ask questions to your documents without an internet connection, '
+                                                 'using the power of LLMs.')
     parser.add_argument("--hide-source", "-S", action='store_true',
                         help='Use this flag to disable printing of source documents used for answers.')
 
@@ -69,6 +71,4 @@ def parse_arguments():
 
 
 if __name__ == "__main__":
-    # Parse the command line arguments
+    main()
-    args = parse_arguments()
-    main(hide_source=args.hide_source, mute_stream=args.mute_stream)