fix for chat + session state

app.py

@@ -8,62 +8,80 @@ import json
 import os
 from functools import partial
 from pathlib import Path
+from pprint import pprint
 
 import gradio as gr
-from elevenlabs import generate, play
-from langchain.chains import LLMChain
 from langchain.chat_models import ChatOpenAI
-from langchain.prompts import PromptTemplate
+from langchain.prompts import (HumanMessagePromptTemplate,
+                               PromptTemplate, SystemMessagePromptTemplate)
 
 # import whisper
 
 # model = whisper.load_model("base", device="cuda")
 
 
-prompt = PromptTemplate(
-    input_variables=["patient", "user_input"],
-    template=Path("prompts/patient.prompt").read_text(),
+system_message_prompt = SystemMessagePromptTemplate(
+    prompt=PromptTemplate(
+        input_variables=["patient"],
+        template=Path("prompts/patient.prompt").read_text(),
+    )
 )
 
-llm = ChatOpenAI(temperature=0.7)
+human_template = "Doctor: {text}"
+human_message_prompt = HumanMessagePromptTemplate.from_template(human_template)
 
-chain = LLMChain(llm=llm, prompt=prompt)
+chat = ChatOpenAI(temperature=0.7)
 
 with open("data/patients.json") as f:
     patiens = json.load(f)
 
 patients_names = [el["name"] for el in patiens]
-patient = [patiens[0]]
 
 
-def run_text_prompt(message, chat_history, patient):
-    print(message, chat_history, patient[0]["name"])
-    bot_message = chain.run(patient=patient[0], user_input=message)
+def run_text_prompt(message, chat_history, messages):
+    if not messages:
+        messages = []
+        messages.append(system_message_prompt.format(patient=patient))
+    messages.append(human_message_prompt.format(text=message))
+    messages.append(chat(messages))
+    pprint(messages)
+    chat_history.append((message, messages[-1].content))
+    return "", chat_history, messages
 
-    chat_history.append((message, bot_message))
-    return "", chat_history
 
+def on_clear_button_click(patient, messages):
+    messages = [system_message_prompt.format(patient=patient)]
+    return [], messages
 
-def on_drop_down_change(selected_item):
+
+def on_drop_down_change(selected_item, messages):
     index = patients_names.index(selected_item)
-    patient[0] = patiens[index]
+    patient = patiens[index]
+    messages = [system_message_prompt.format(patient=patient)]
     print(f"You selected: {selected_item}", index)
-    return f"```json\n{json.dumps(patient[0], indent=2)}\n```"
+    return f"```json\n{json.dumps(patient, indent=2)}\n```", patient, [], messages
 
 
 with gr.Blocks() as demo:
     chatbot = gr.Chatbot()
+    messages = gr.State([])
+    patient = gr.State(patiens[0])
 
     with gr.Row():
         with gr.Column():
             msg = gr.Textbox()
             msg.submit(
-                partial(run_text_prompt, patient=patient),
-                [msg, chatbot],
-                [msg, chatbot],
+                run_text_prompt,
+                [msg, chatbot, messages],
+                [msg, chatbot, messages],
             )
             clear = gr.Button("Clear")
-            clear.click(lambda: None, None, chatbot, queue=False)
+            clear.click(
+                on_clear_button_click,
+                [patient, messages],
+                [chatbot, messages],
+                queue=False,
+            )
 
         with gr.Column():
             patients_names = [el["name"] for el in patiens]
@@ -73,8 +91,12 @@ with gr.Blocks() as demo:
                 interactive=True,
                 label="Patient",
             )
-            markdown = gr.Markdown(f"```json\n{json.dumps(patient[0], indent=2)}\n```")
-            dropdown.change(fn=on_drop_down_change, inputs=dropdown, outputs=markdown)
-            print(patient)
-            # dropdown.value(lambda x: print(x))
-            # patient = dropdown.select(on_dropdown_select)
+            markdown = gr.Markdown(
+                f"```json\n{json.dumps(patient.value, indent=2)}\n```"
+            )
+            dropdown.change(
+                fn=on_drop_down_change,
+                inputs=[dropdown, messages],
+                outputs=[markdown, patient, chatbot, messages],
+            ),
+# demo.launch(debug=True)

prompts/patient.prompt

@@ -4,7 +4,4 @@ You will act like a patient with a given persona and a present complain. I will
 
 Please reply using `presentingComplaint`. You should also use `characterSummary` to impersonate the patient.  `levelOfUnderstanding` is between 0 and 10 and represent the level of the patient in medicine. A low number indicate somebody who is not familiar with medical terminology. 
 
-Send only one reply
-
-Doctor: {user_input}
-Patient: 
+Send only one reply