Update main.py

main.py

@@ -15,7 +15,8 @@ import transformers  # to load an LLM
 GREETING = (
     "Howdy! I'm an AI agent that uses a [retrieval-augmented generation]("
     "https://en.wikipedia.org/wiki/Retrieval-augmented_generation) pipeline to answer questions about research by the "
-    "Design Research Collective. And the best part is that I always cite my sources! What can I tell you about today?"
+    "[Design Research Collective](https://cmudrc.github.io/). And the best part is that I always cite my sources! What"
+    " can I tell you about today?"
 )
 EXAMPLE_QUERIES = [
     "Tell me about new research at the intersection of additive manufacturing and machine learning",
@@ -94,8 +95,7 @@ def search(query: str, k: int) -> tuple[str, str]:
         )
 
     search_results += (
-        "\nIf these abstract aren't relevant to the following query, please reply 'I am unsure' or "
-        "similar. Respond to the following query from the perspective of the provided abstracts only:"
+        "\nUsing the information provided above, respond to this  query: "
     )
 
     return search_results, references
@@ -150,14 +150,6 @@ def reply(message: str, history: list[str]) -> str:
     message, bypass = preprocess(message)
 
     # This is some handling that is applied to the history variable to put it in a good format
-    # if isinstance(history, list):
-    #     if len(history) > 0:
-    #         history = history[-1]
-    # print(history)
-    # history_transformer_format = [
-    #     {"role": "assistant" if idx & 1 else "user", "content": msg}
-    #     for idx, msg in enumerate(history)
-    # ] + [{"role": "user", "content": message}]
     history_transformer_format = [
         {"role": role, "content": message_pair[idx]}
         for message_pair in history