Update app.py

app.py

@@ -16,6 +16,7 @@ import plotly.express as px
 class SentimentAnalyzer:
     def __init__(self):
         self.model="facebook/bart-large-mnli"
+        openai.api_key=os.getenv("OPENAI_API_KEY")
     def analyze_sentiment(self, text):
         pipe = pipeline("zero-shot-classification", model=self.model)
         label=["positive","negative","neutral"]
@@ -65,7 +66,7 @@ Please analyze the text and provide the output in the following format: emotion:
 
 class Summarizer:
     def __init__(self):
-        pass
+        openai.api_key=os.getenv("OPENAI_API_KEY")
     def generate_summary(self, text):
         model_engine = "text-davinci-003"
         prompt = f"""summarize the following conversation delimited by triple backticks.
@@ -89,7 +90,7 @@ sentiment = SentimentAnalyzer()
 class LangChain_Document_QA:
 
     def __init__(self):
-        pass
+        openai.api_key=os.getenv("OPENAI_API_KEY")
 
     def _add_text(self,history, text):
         history = history + [(text, None)]
@@ -107,9 +108,9 @@ class LangChain_Document_QA:
         formatted_history = " "
         for entry in history:
             customer_text, agent_text = entry
-            formatted_history += f"Customer: {customer_text}\n"
+            formatted_history += f"Patient: {customer_text}\n"
             if agent_text:
-                formatted_history += f"Agent: {agent_text}\n"
+                formatted_history += f"Psycotherapist Bot: {agent_text}\n"
         return formatted_history
 
     def _display_history(self):
@@ -150,11 +151,6 @@ class LangChain_Document_QA:
         except:
           pass
 
-        # prompt = f"""You are an AI psychotherapist chatbot for Mental Healthcare.You are a brilliant and empathic counselor for Mental Healthcare.you should suggest solution to patient for his problem. Analyse the patient json If asked for information take it from {patient_details}.
-        #       patient say thanks tone you should end the conversation with thanking greeting.
-        #       Chat History:[{history}]
-        #       Patient: [{text}]
-        #       Perform as Mental Healthcare Doctor Chatbot"""
         prompt = f"""As an empathic AI psychotherapist chatbot, provide effective solutions to patients' mental health concerns.
               if patient say thanking tone message to end the conversation with a thanking greeting when the patient expresses gratitude.
               Analyse the patient json If asked for information take it from {patient_details}
@@ -192,28 +188,19 @@ class LangChain_Document_QA:
         customer_emotion=sentiment.emotion_analysis(client)
         customer_sentiment_score = sentiment.analyze_sentiment_for_graph(client)
 
-        agent_emotion=sentiment.emotion_analysis(agent)
-        agent_sentiment_score = sentiment.analyze_sentiment_for_graph(agent)
 
         scores=self._text_box(customer_emotion,agent_emotion,agent_sentiment_score,customer_sentiment_score)
 
         customer_fig=self._display_graph(customer_sentiment_score)
         customer_fig.update_layout(title="Sentiment Analysis",width=775)
 
-        agent_fig=self._display_graph(agent_sentiment_score)
-        agent_fig.update_layout(title="Sentiment Analysis",width=775)
-
-        agent_emotion_score = sentiment.emotion_analysis_for_graph(agent_emotion)
-
-        agent_emotion_fig=self._display_graph(agent_emotion_score)
-        agent_emotion_fig.update_layout(title="Emotion Analysis",width=775)
 
         customer_emotion_score = sentiment.emotion_analysis_for_graph(customer_emotion)
 
         customer_emotion_fig=self._display_graph(customer_emotion_score)
         customer_emotion_fig.update_layout(title="Emotion Analysis",width=775)
 
-        return scores,customer_fig,agent_fig,customer_emotion_fig,agent_emotion_fig
+        return scores,customer_fig,customer_emotion_fig
 
 
     def clear_func(self):
@@ -221,24 +208,20 @@ class LangChain_Document_QA:
 
     def gradio_interface(self):
       with gr.Blocks(css="style.css",theme=gr.themes.Soft()) as demo:
-          # with gr.Row():
-          #   gr.HTML("""<img class="leftimage" align="left" src="https://templates.images.credential.net/1612472097627370951721412474196.png" alt="Image" width="210" height="210">
-          #   <img align="right" class="rightimage" src="https://download.logo.wine/logo/Vodafone/Vodafone-Logo.wine.png" alt="Image" width="230" height="230" >""")
           with gr.Row():
-            gr.HTML("""<center><h1>AI Psychotherapist ChatBot</h1></center>""")
+            gr.HTML("""<img class="image" src="https://www.syrahealth.com/images/SyraHealth_Logo_Dark.svg" alt="Image" width="210" height="210">
+            """)
+          with gr.Row():
+            gr.HTML("""<center><h1>AI Mental Healthcare ChatBot</h1></center>""")
           chatbot = gr.Chatbot([], elem_id="chatbot").style(height=360)
           with gr.Row():
-              with gr.Column(scale=0.47):
+              with gr.Column(scale=0.8):
                   txt = gr.Textbox(
                       show_label=False,
                       placeholder="Patient",elem_classes="height"
                   ).style(container=False)
-              with gr.Column(scale=0.47):
-                  txt2 = gr.Textbox(
-                      show_label=False,
-                      placeholder="psychotherapist",elem_classes="height"
-                  ).style(container=False)
-              with gr.Column(scale=0.06):
+            
+              with gr.Column(scale=0.2):
                   emptyBtn = gr.Button(
                       "🧹 Clear",elem_classes="height"
                   )
@@ -246,10 +229,10 @@ class LangChain_Document_QA:
             with gr.Column(scale=0.80):
                 txt3 =gr.Textbox(
                       show_label=False,
-                      placeholder="AI Psychotherapist Suggesstion",elem_classes="height"
+                      placeholder="AI Healthcare Suggesstion"
                   ).style(container=False)
             with gr.Column(scale=0.20, min_width=0):
-                button=gr.Button(value="🚀send",elem_classes="height")
+                button=gr.Button(value="🚀send")
           with gr.Row():
               with gr.Column(scale=0.50):
                   txt4 =gr.Textbox(