auto generate help

Signed-off-by: reidliu41 <[email protected]>

Author: reidliu41

docs/source/deployment/frameworks/retrieval_augmented_generation.md

@@ -39,40 +39,11 @@ vllm serve qwen/Qwen1.5-0.5B-Chat --port 8001
 
 - Use the script: <gh-file:examples/online_serving/retrieval_augmented_generation_with_langchain.py>
 
-```python
-python retrieval_augmented_generation_with_langchain.py --help
-usage: retrieval_augmented_generation_with_langchain.py [-h] [--vllm-api-key VLLM_API_KEY]
-                                                        [--vllm-embedding-endpoint VLLM_EMBEDDING_ENDPOINT]
-                                                        [--vllm-chat-endpoint VLLM_CHAT_ENDPOINT]
-                                                        [--uri URI] [--url URL]
-                                                        [--embedding-model EMBEDDING_MODEL]
-                                                        [--chat-model CHAT_MODEL] [-i] [-k TOP_K]
-                                                        [-c CHUNK_SIZE] [-o CHUNK_OVERLAP]
-
-RAG Demo with vLLM and langchain
-
-options:
-  -h, --help            show this help message and exit
-  --vllm-api-key VLLM_API_KEY
-                        API key for vLLM compatible services
-  --vllm-embedding-endpoint VLLM_EMBEDDING_ENDPOINT
-                        Base URL for embedding service
-  --vllm-chat-endpoint VLLM_CHAT_ENDPOINT
-                        Base URL for chat service
-  --uri URI             URI for Milvus database
-  --url URL             URL of the document to process
-  --embedding-model EMBEDDING_MODEL
-                        Model name for embeddings
-  --chat-model CHAT_MODEL
-                        Model name for chat
-  -i, --interactive     Enable interactive Q&A mode
-  -k TOP_K, --top-k TOP_K
-                        Number of top results to retrieve
-  -c CHUNK_SIZE, --chunk-size CHUNK_SIZE
-                        Chunk size for document splitting
-  -o CHUNK_OVERLAP, --chunk-overlap CHUNK_OVERLAP
-                        Chunk overlap for document splitting
-```
+:::{argparse}
+:module: examples.online_serving.retrieval_augmented_generation_with_langchain
+:func: get_parser
+:prog: retrieval_augmented_generation_with_langchain.py
+:::
 
 - Run the script
 
@@ -112,34 +83,11 @@ vllm serve qwen/Qwen1.5-0.5B-Chat --port 8001
 
 - Use the script: <gh-file:examples/online_serving/retrieval_augmented_generation_with_llamaindex.py>
 
-```python
-python retrieval_augmented_generation_with_llamaindex.py --help
-usage: retrieval_augmented_generation_with_llamaindex.py [-h] [--url URL]
-                                                         [--embedding-model EMBEDDING_MODEL]
-                                                         [--chat-model CHAT_MODEL]
-                                                         [--vllm-api-key VLLM_API_KEY]
-                                                         [--embedding-endpoint EMBEDDING_ENDPOINT]
-                                                         [--chat-endpoint CHAT_ENDPOINT]
-                                                         [--db-path DB_PATH] [-i]
-
-RAG with vLLM and LlamaIndex
-
-options:
-  -h, --help            show this help message and exit
-  --url URL             URL of the document to process
-  --embedding-model EMBEDDING_MODEL
-                        Model name for embeddings
-  --chat-model CHAT_MODEL
-                        Model name for chat
-  --vllm-api-key VLLM_API_KEY
-                        API key for vLLM compatible services
-  --embedding-endpoint EMBEDDING_ENDPOINT
-                        Base URL for embedding service
-  --chat-endpoint CHAT_ENDPOINT
-                        Base URL for chat service
-  --db-path DB_PATH     Path to Milvus database
-  -i, --interactive     Enable interactive Q&A mode
-```
+:::{argparse}
+:module: examples.online_serving.retrieval_augmented_generation_with_llamaindex
+:func: get_parser
+:prog: retrieval_augmented_generation_with_llamaindex.py
+:::
 
 - Run the script
 

examples/online_serving/retrieval_augmented_generation_with_langchain.py

@@ -130,7 +130,7 @@ def create_qa_chain(retriever: Any, llm: ChatOpenAI, prompt: PromptTemplate):
             | StrOutputParser())
 
 
-def parse_args():
+def get_parser() -> argparse.ArgumentParser:
     """
     Parse command line arguments
     """
@@ -180,7 +180,7 @@ def parse_args():
                         default=200,
                         help='Chunk overlap for document splitting')
 
-    return parser.parse_args()
+    return parser
 
 
 def init_config(args: Namespace):
@@ -204,7 +204,7 @@ def init_config(args: Namespace):
 
 def main():
     # Parse command line arguments
-    args = parse_args()
+    args = get_parser().parse_args()
 
     # Initialize configuration
     config = init_config(args)

examples/online_serving/retrieval_augmented_generation_with_llamaindex.py

@@ -115,7 +115,7 @@ def query_document(index: VectorStoreIndex, question: str, top_k: int):
     return query_engine.query(question)
 
 
-def parse_args():
+def get_parser() -> argparse.ArgumentParser:
     """Parse command line arguments"""
     parser = argparse.ArgumentParser(
         description='RAG with vLLM and LlamaIndex')
@@ -164,12 +164,12 @@ def parse_args():
                         default=3,
                         help='Number of top results to retrieve')
 
-    return parser.parse_args()
+    return parser
 
 
 def main():
     # Parse command line arguments
-    args = parse_args()
+    args = get_parser().parse_args()
 
     # Initialize configuration
     config = init_config(args)