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1 Parent(s): 260750b

Update app.py

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  1. app.py +3 -23
app.py CHANGED
@@ -15,24 +15,6 @@ GREETING = (
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  "What can I tell you about today?"
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  )
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- # Example queries
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- EXAMPLE_QUERIES = [
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- "What is multi-material 3D printing?",
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- "How is additive manufacturing being applied in aerospace?",
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- "Tell me about innovations in metal 3D printing techniques.",
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- "What are some sustainable materials for 3D printing?",
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- "What are the biggest challenges with support structures in additive manufacturing?",
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- "How is 3D printing impacting the medical field?",
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- "What are some common applications of additive manufacturing in industry?",
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- "What are the benefits and limitations of using polymers in 3D printing?",
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- "Are there recent breakthroughs in enhancing precision for additive manufacturing?",
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- "Tell me about the environmental impacts of additive manufacturing.",
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- "What are the primary limitations of current 3D printing technologies?",
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- "What future trends are expected in the field of additive manufacturing?",
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- "How are researchers improving the speed of 3D printing processes?",
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- "What are the best practices for managing post-processing in additive manufacturing?",
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- ]
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-
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  # The embedding model name
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  EMBEDDING_MODEL_NAME = "all-MiniLM-L12-v2"
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@@ -108,7 +90,9 @@ def preprocess(query: str, k: int) -> tuple[str, str]:
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  )
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  prompt = (
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- "You are an AI assistant who delights in helping people learn about research from the Design Research Collective, which is a research lab at Carnegie Mellon University led by Professor Chris McComb. "
 
 
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  "Your main task is to use the RESEARCH_EXCERPTS to provide a concise ANSWER to the USER_QUERY. "
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  "DO NOT list references at the end of the answer.\n\n"
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  "===== RESEARCH_EXCERPTS =====:\n{{EXCERPTS_GO_HERE}}\n\n"
@@ -164,16 +148,12 @@ def reply(message: str, history: list[str]) -> str:
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  for new_token in streamer:
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  if new_token != "<":
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  partial_message += new_token
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- time.sleep(0.01)
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  yield partial_message
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- yield partial_message + "\n\n" + bypass
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-
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  # Create and run the gradio interface
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  gradio.ChatInterface(
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  reply,
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- examples=EXAMPLE_QUERIES,
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  chatbot=gradio.Chatbot(
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  show_label=False,
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  show_share_button=False,
 
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  "What can I tell you about today?"
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  )
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  # The embedding model name
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  EMBEDDING_MODEL_NAME = "all-MiniLM-L12-v2"
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  )
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  prompt = (
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+ "You are an AI assistant who delights in helping people learn about research. "
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+ "Do your best to answer the following question about additive manufacturing research. "
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+ "Do not refuse to answer or mention any issues with the research excerpts. "
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  "Your main task is to use the RESEARCH_EXCERPTS to provide a concise ANSWER to the USER_QUERY. "
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  "DO NOT list references at the end of the answer.\n\n"
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  "===== RESEARCH_EXCERPTS =====:\n{{EXCERPTS_GO_HERE}}\n\n"
 
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  for new_token in streamer:
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  if new_token != "<":
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  partial_message += new_token
 
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  yield partial_message
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  # Create and run the gradio interface
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  gradio.ChatInterface(
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  reply,
 
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  chatbot=gradio.Chatbot(
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  show_label=False,
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  show_share_button=False,