Adds more usage notes for conversational rag

Author: skrawcz

contrib/hamilton/contrib/dagworks/conversational_rag/README.md

@@ -16,6 +16,28 @@ specific question for the LLM given the found context.
 
 ## Example Usage
 
+### Inputs
+These are the defined inputs you can provide.
+
+ - *input_texts*: A list of strings. Each string will be encoded into a vector and stored in the vector store.
+ - *question*: A string. This is the question you want to ask the LLM, and vector store which will provide context.
+ - *chat_history*: A list of strings. Each string is a line of conversation. They need to be prefixed with "Human" or "AI" to indicate who said it. They should be alternating.
+ - *top_k*: An integer. This is the number of vectors to retrieve from the vector store. Defaults to 5.
+
+### Overrides
+With Hamilton you can easily override a function and provide a value for it. For example if you're
+iterating you might just want to override these two values before modifying the functions:
+
+ - *context*: if you want to skip going to the vector store and provide the context directly, you can do so by providing this override.
+ - *standalone_question*: if you want to skip the rewording of the question, you can provide the standalone question directly.
+ - *answer_prompt*: if you want to provide the prompt to pass to the LLM, pass it in as an override.
+
+### Execution
+You can ask to get back any result of an intermediate function by providing the function name in the `execute` call.
+Here we just ask for the final result, but if you wanted to, you could ask for outputs of any of the functions, which
+you can then introspect or log for debugging/evaluation purposes. Note if you want more platform integrations,
+you can add adapters that will do this automatically for you, e.g. like we have the `PrintLn` adapter here.
+
 ```python
 # import the module
 from hamilton import driver