start

app.py

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+from transformers import pipeline, Conversation
+import gradio as gr
+
+chatbot = pipeline("text-generation", model="models/epfl-llm/meditron-70b")
+
+message_list = []
+response_list = []
+
+def vanilla_chatbot(message, history):
+    conversation = Conversation(text=message, past_user_inputs=message_list, generated_responses=response_list)
+    conversation = chatbot(conversation)
+
+    return conversation.generated_responses[-1]
+
+def summarizer_bot(message, history):
+    return chatbot(message, min_length=5, max_length=500)[0]['summary_text']
+
+demo_chatbot = gr.ChatInterface(vanilla_chatbot, title="Check medical chatbot", description="Enter question")
+
+# def responseFun(message, history):
+#     return history[len(history) - 1]
+    
+# demo_chatbot = gr.ChatInterface(responseFun, title="Test medical summarization chatbot", description="Enter text to summarize.")
+
+demo_chatbot.launch()

requirements.txt

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+gradio==3.39.0
+transformers==4.31.0
+torch==2.0.1