new

app.py

@@ -0,0 +1,83 @@
+import gradio as gr
+import os
+from gradio_client import Client
+
+hf_key = os.environ['HF_API_KEY']
+
+messages = [
+    {"role": "system", "content": "You are a helpful assistant."},
+]
+msg_count = 0
+
+client = Client("https://amitagh-medbot-back.hf.space/--replicas/2ewvx/", hf_token=hf_key)
+def get_llm_rsp(text):
+  rsp = client.predict(
+		text,	# str  in 'Input your question:' Textbox component
+		api_name="/get_llm_resp"
+  )
+  return rsp
+
+def add_text(history, text):
+    global messages  #message[list] is defined globally
+    history = history + [(text,'')]
+    messages = messages + [{"role":'user', 'content': text}]
+    return history, ""
+
+def generate_response(history, text):
+        global messages, msg_count
+
+        #arsp = bizbot([chatbot, text], api_name="bizbot-api")
+        response_msg = get_llm_rsp(text)
+
+        msg_count = msg_count + 1
+        messages = messages + [{"role":'assistant', 'content': response_msg}]
+        
+        for char in response_msg:
+
+            history[-1][1] += char
+            time.sleep(0.03)
+            yield history
+
+
+def calc_cost():
+  global msg_count
+  return msg_count
+
+
+with gr.Blocks() as demo:
+    
+    gr.Markdown(value="## MedBot")
+    gr.Markdown(value="Bot helps with medical information on nearly 1,700 common medical disorders, conditions, tests, and treatments, including high-profile diseases such as \
+    Alzheimer’s disease, cancer, and heart attack. It uses language that laypersons can understand,")
+    gr.Markdown(value="**Please use info cautiously. Please consult a doctor for final treatment.**")
+    chatbot = gr.Chatbot(value=[], label="MedBot")
+
+    txt = gr.Textbox(
+                label="Input your question:",
+                placeholder="Enter text and press enter",
+            )    #.style(container=False)
+    gr.Examples(
+        label="Question examples",
+        examples=[["What is ultrasound?"], 
+         ["What is cancer?"],
+         ["What is treatment for cancer?"],
+                 ],
+        inputs=[txt],)
+    btn = gr.Button("Submit")
+
+
+    count_msg_view = gr.Textbox(label='Number of questions answered in current conversation:',value=0)
+    #btn2 = gr.Button("Clear and Start New Conversation ")
+
+    txt.submit(add_text, [chatbot, txt], [chatbot, txt], queue=False).then(
+            generate_response, inputs =[chatbot, txt],outputs = chatbot,).then(
+            calc_cost, outputs=count_msg_view)
+    btn.click(add_text, [chatbot, txt], [chatbot, txt], queue=False).then(
+            generate_response, inputs =[chatbot, txt],outputs = chatbot,).then(
+            calc_cost, outputs=count_msg_view)
+
+    #Button click action to clear conversation
+    #btn2.click(clear_conv,inputs=chatbot, outputs=[chatbot, count_msg_view])
+
+demo.queue()
+demo.launch(debug=True)