Update app.py

app.py

@@ -11,6 +11,7 @@ from docx import Document
 from docx.enum.text import WD_PARAGRAPH_ALIGNMENT
 from io import BytesIO
 
+
 # Set up OpenAI API
 openai.api_key = "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"
 
@@ -18,13 +19,20 @@ openai.api_key = "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"
 st.markdown(
     """
 <style>
+    body {
+        background-color: transparent;
+    }
     .container {
         display: flex;
         justify-content: center;
         align-items: center;
+        background-color: rgba(255, 255, 255, 0.7);
         border-radius: 15px;
         padding: 20px;
     }
+    .stApp {
+        background-color: transparent;
+    }
 </style>
 """,
     unsafe_allow_html=True,
@@ -37,12 +45,14 @@ model = CLIPModel().to(device)
 model.load_state_dict(torch.load("weights.pt", map_location=torch.device('cpu')))
 text_embeddings = torch.load('saved_text_embeddings.pt', map_location=device)
 
+
 def show_predicted_caption(image):
     matches = predict_caption(
         image, model, text_embeddings, testing_df["caption"]
     )[0]
     return matches
 
+
 def generate_radiology_report(prompt):
     response = openai.Completion.create(
         engine="text-davinci-003",
@@ -54,6 +64,7 @@ def generate_radiology_report(prompt):
     )
     return response.choices[0].text.strip()
 
+
 def chatbot_response(prompt):
     response = openai.Completion.create(
         engine="text-davinci-003",
@@ -65,6 +76,7 @@ def chatbot_response(prompt):
     )
     return response.choices[0].text.strip()
 
+# Add this function to your code
 def save_as_docx(text, filename):
     document = Document()
     document.add_paragraph(text)
@@ -73,12 +85,14 @@ def save_as_docx(text, filename):
         output.seek(0)
         return output.getvalue()
 
+# Add this function to your code
 def download_link(content, filename, link_text):
     b64 = base64.b64encode(content).decode()
     href = f'<a href="data:application/octet-stream;base64,{b64}" download="{filename}">{link_text}</a>'
     return href
 
-st.title("RadiXGPT: An Evolution of machine doctors towrads Radiology")
+
+st.title("RadiXGPT: An Evolution of machine doctors towards Radiology")
 st.write("Upload Scan to get Radiological Report:")
 
 uploaded_file = st.file_uploader("Choose an image...", type=["jpg", "png", "jpeg"])
@@ -91,8 +105,10 @@ if uploaded_file is not None:
         with st.spinner("Generating caption..."):
             image_np = np.array(image)
             caption = show_predicted_caption(image_np)
+           
             st.success(f"Caption: {caption}")
 
+            # Add the OpenAI API call here and generate the radiology report
             radiology_report = generate_radiology_report(f"Write Complete Radiology Report for this: {caption}")
             container = st.container()
             with container:
@@ -105,13 +121,21 @@ if uploaded_file is not None:
             st.write("Ask any questions you have about the radiology report:")
 
             user_input = st.text_input("Enter your question:")
-            while user_input.lower() != "thank you":
-                if user_input:
-                    answer = chatbot_response(f"Answer to the user's question based on the generated radiology report: {user_input}")
-                    st.write(f"Bot: {answer}")
-                    user_input = st.text_input("Enter your question:")
+            chat_history = []
+
+            if user_input:
+                chat_history.append({"user": user_input})
+
+                if user_input.lower() == "thank you":
+                    st.write("Bot: You're welcome! If you have any more questions, feel free to ask.")
                 else:
-                    break
+                    # Add the OpenAI API call here and generate the answer to the user's question
+                    prompt = f"Answer to the user's question based on the generated radiology report: {user_input}"
+                    for history_item in chat_history:
+                        prompt += f"\nUser: {history_item['user']}"
+                        if 'bot' in history_item:
+                            prompt += f"\nBot: {history_item['bot']}"
 
-            if user_input.lower() == "thank you":
-                st.write("Bot: You're welcome! If you have any more questions, feel free to ask.")
+                    answer = chatbot_response(prompt)
+                    chat_history[-1]["bot"] = answer
+                    st.write(f"Bot: {answer}")