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app.py

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+
+
+# # # # # from langchain_google_genai import ChatGoogleGenerativeAI
+
+
+
+# # # # # llm = ChatGoogleGenerativeAI(
+# # # # #     model="gemini-1.5-flash",
+# # # # #     google_api_key='AIzaSyC7Rhv4L6_oNl-nW3Qeku2SPRkxL5hhtoE',
+# # # # #     temperature=0.2)
+
+# # # # # poem = llm.invoke("Write a poem on love for burger")
+# # # # # print(poem)
+
+
+# # # # import streamlit as st
+# # # # from langchain_google_genai import ChatGoogleGenerativeAI
+
+# # # # # Set up the AI model
+# # # # llm = ChatGoogleGenerativeAI(
+# # # #     model="gemini-1.5-flash",  # Free model
+# # # #     google_api_key="AIzaSyC7Rhv4L6_oNl-nW3Qeku2SPRkxL5hhtoE",
+# # # #     temperature=0.5
+# # # # )
+
+# # # # # Streamlit UI
+# # # # st.title("🩺 Healthcare AI Assistant")
+# # # # st.write("Ask me anything about health, symptoms, diet, or general medical advice!")
+
+# # # # # User Input
+# # # # user_question = st.text_input("Enter your health-related question:")
+
+# # # # # Process User Query
+# # # # if st.button("Get Recommendation"):
+# # # #     if user_question.strip():
+# # # #         with st.spinner("Analyzing..."):
+# # # #             response = llm.invoke(user_question)
+# # # #         st.success("Recommendation:")
+# # # #         st.write(response)
+# # # #     else:
+# # # #         st.warning("Please enter a question!")
+
+# # # # # Footer
+# # # # st.markdown("---")
+# # # # st.markdown("💡 *Disclaimer: This AI assistant provides general health information. Always consult a doctor for medical concerns.*")
+
+
+
+# # # import streamlit as st
+# # # from langchain_google_genai import ChatGoogleGenerativeAI
+
+# # # # Set up AI model
+# # # llm = ChatGoogleGenerativeAI(
+# # #     model="gemini-1.5-flash",  # Free model
+# # #     google_api_key="AIzaSyC7Rhv4L6_oNl-nW3Qeku2SPRkxL5hhtoE",
+# # #     temperature=0.5
+# # # )
+
+# # # # Streamlit UI
+# # # st.title("🩺 AI Healthcare Learning Assistant")
+# # # st.write("Ask me anything about healthcare, symptoms, diet, or medical learning!")
+
+# # # # User Input
+# # # user_question = st.text_input("Enter your healthcare question:")
+
+# # # # Function to filter AI disclaimers
+# # # def is_valid_response(response):
+# # #     disclaimers = [
+# # #         "I am an AI and cannot give medical advice",
+# # #         "Seek medical attention",
+# # #         "Consult a doctor",
+# # #         "Contact your doctor",
+# # #         "Go to an emergency room",
+# # #     ]
+# # #     return not any(phrase.lower() in response.lower() for phrase in disclaimers)
+
+# # # # Process User Query
+# # # if st.button("Get Information"):
+# # #     if user_question.strip():
+# # #         with st.spinner("Analyzing..."):
+# # #             response = llm.invoke(user_question)
+        
+# # #         # Check if response is valid
+# # #         if is_valid_response(response):
+# # #             st.success("Here is the relevant information:")
+# # #             st.write(response)
+# # #         else:
+# # #             st.warning("AI provided a disclaimer. Trying again...")
+# # #             # Modify prompt to avoid disclaimers
+# # #             better_prompt = f"Give a well-explained answer for educational purposes only: {user_question}"
+# # #             retry_response = llm.invoke(better_prompt)
+
+# # #             # Display the retried response if it's valid
+# # #             if is_valid_response(retry_response):
+# # #                 st.success("Here is the refined information:")
+# # #                 st.write(retry_response)
+# # #             else:
+# # #                 st.error("Unable to get a useful response. Try rephrasing your question.")
+
+# # #     else:
+# # #         st.warning("Please enter a question!")
+
+# # # # Footer
+# # # st.markdown("---")
+# # # st.markdown("💡 *This AI provides learning-based medical insights, not actual medical advice.*")
+
+
+
+# # import streamlit as st
+# # from langchain_google_genai import ChatGoogleGenerativeAI
+
+# # # Set up AI model
+# # llm = ChatGoogleGenerativeAI(
+# #     model="gemini-1.5-flash",  # Free model
+# #     google_api_key="AIzaSyC7Rhv4L6_oNl-nW3Qeku2SPRkxL5hhtoE",
+# #     temperature=0.5
+# # )
+
+# # # Streamlit UI
+# # st.title("🩺 AI Healthcare Learning Assistant")
+# # st.write("Ask me anything about healthcare, symptoms, diet, or medical learning!")
+
+# # # User Input
+# # user_question = st.text_input("Enter your healthcare question:")
+
+# # # Function to filter AI disclaimers
+# # def is_valid_response(response_text):
+# #     disclaimers = [
+# #         "I am an AI and cannot give medical advice",
+# #         "Seek medical attention",
+# #         "Consult a doctor",
+# #         "Contact your doctor",
+# #         "Go to an emergency room",
+# #     ]
+# #     return not any(phrase.lower() in response_text.lower() for phrase in disclaimers)
+
+# # # Process User Query
+# # if st.button("Get Information"):
+# #     if user_question.strip():
+# #         with st.spinner("Analyzing..."):
+# #             response = llm.invoke(user_question)
+
+# #         # Extract the text content from AIMessage
+# #         response_text = response.content if hasattr(response, "content") else str(response)
+
+# #         # Check if response is valid
+# #         if is_valid_response(response_text):
+# #             st.success("Here is the relevant information:")
+# #             st.write(response_text)
+# #         else:
+# #             st.warning("AI provided a disclaimer. Trying again...")
+# #             # Modify prompt to avoid disclaimers
+# #             better_prompt = f"Give a well-explained answer for educational purposes only: {user_question}"
+# #             retry_response = llm.invoke(better_prompt)
+
+# #             # Extract text from the retried response
+# #             retry_response_text = retry_response.content if hasattr(retry_response, "content") else str(retry_response)
+
+# #             # Display the retried response if it's valid
+# #             if is_valid_response(retry_response_text):
+# #                 st.success("Here is the refined information:")
+# #                 st.write(retry_response_text)
+# #             else:
+# #                 st.error("Unable to get a useful response. Try rephrasing your question.")
+
+# #     else:
+# #         st.warning("Please enter a question!")
+
+# # # Footer
+# # st.markdown("---")
+# # st.markdown("💡 *This AI provides learning-based medical insights, not actual medical advice.*")
+
+
+
+
+# import streamlit as st
+# from langchain_google_genai import ChatGoogleGenerativeAI
+
+# # Set up AI model
+# llm = ChatGoogleGenerativeAI(
+#     model="gemini-1.5-flash",  # Free model
+#     google_api_key="AIzaSyC7Rhv4L6_oNl-nW3Qeku2SPRkxL5hhtoE",
+#     temperature=0.5
+# )
+
+# # Streamlit UI
+# st.title("🩺 AI Healthcare Learning Assistant")
+# st.write("Ask about symptoms, medicines, and alternative treatments.")
+
+# # User Input
+# user_question = st.text_input("Enter your health-related query:")
+
+# # Function to filter AI disclaimers
+# def is_valid_response(response_text):
+#     disclaimers = [
+#         "I am an AI and cannot give medical advice",
+#         "Seek medical attention",
+#         "Consult a doctor",
+#         "Contact your doctor",
+#         "Go to an emergency room",
+#     ]
+#     return not any(phrase.lower() in response_text.lower() for phrase in disclaimers)
+
+# # Process User Query
+# if st.button("Get Recommendation"):
+#     if user_question.strip():
+#         # Modify user input to ensure the model focuses on learning-based insights
+#         formatted_question = f"Without any disclaimer, recommend me medicine for {user_question}. Only for learning purposes, not for treatment. Also, suggest some different ways to cure it."
+
+#         with st.spinner("Analyzing..."):
+#             response = llm.invoke(formatted_question)
+
+#         # Extract text content
+#         response_text = response.content if hasattr(response, "content") else str(response)
+
+#         # # Check if response is valid
+#         if is_valid_response(response_text):
+#             st.success("Here is the relevant information:")
+#             st.write(response_text)
+#         else:
+#             st.warning("AI provided a disclaimer. Trying again...")
+#             # Retry with a refined prompt
+#             better_prompt = f"Its only for leaning purpose not for treatment provide medicine names and alternative treatments for: {user_question}"
+#             retry_response = llm.invoke(better_prompt)
+
+#             # Extract text from retry response
+#             retry_response_text = retry_response.content if hasattr(retry_response, "content") else str(retry_response)
+
+#             # # Display the retried response if valid
+#             # if is_valid_response(retry_response_text):
+#             #     st.success("Here is the refined information:")
+#             #     st.write(retry_response_text)
+#             # else:
+#             #     st.error("Unable to get a useful response. Try rephrasing your question.")
+
+#     else:
+#         st.warning("Please enter a question!")
+
+# # Footer
+# st.markdown("---")
+# st.markdown("💡 *This AI provides learning-based medical insights, not actual medical advice.*")
+
+
+import streamlit as st
+from langchain_google_genai import ChatGoogleGenerativeAI
+
+# Set up AI model
+llm = ChatGoogleGenerativeAI(
+    model="gemini-1.5-flash",  # Free model
+    google_api_key="AIzaSyC7Rhv4L6_oNl-nW3Qeku2SPRkxL5hhtoE",
+    temperature=0.5
+)
+
+# Streamlit UI
+st.title("🩺 AI Healthcare Learning Assistant")
+st.write("Get medicine recommendations and alternative treatments for learning purposes.")
+
+# User Input
+user_question = st.text_input("Enter your health-related query:")
+
+# Function to filter AI disclaimers
+def is_valid_response(response_text):
+    disclaimers = [
+        "I am an AI and cannot give medical advice",
+        "Seek medical attention",
+        "Consult a doctor",
+        "Contact your doctor",
+        "Go to an emergency room",
+    ]
+    return not any(phrase.lower() in response_text.lower() for phrase in disclaimers)
+
+# Process User Query
+if st.button("Get Recommendation"):
+    if user_question.strip():
+        # Ensure the AI provides both medicine and alternative treatments
+        formatted_question = (
+            f"Without any disclaimer, recommend medicine for {user_question}. "
+            f"Also, provide alternative treatments such as home remedies, lifestyle changes, exercises, or dietary suggestions. "
+            f"Only for learning purposes, not for treatment."
+        )
+
+        with st.spinner("Analyzing..."):
+            response = llm.invoke(formatted_question)
+
+        # Extract text content
+        response_text = response.content if hasattr(response, "content") else str(response)
+
+        # Check if response is valid
+        if is_valid_response(response_text):
+            st.success("Here is the relevant information:")
+            st.write(response_text)
+        else:
+            st.warning("AI provided a disclaimer. Trying again...")
+            # Retry with a refined prompt
+            better_prompt = (
+                f"Strictly provide a detailed answer including:\n"
+                f"1. Medicine names\n"
+                f"2. Home remedies\n"
+                f"3. Lifestyle changes\n"
+                f"4. Exercises\n"
+                f"5. Diet recommendations\n"
+                f"Do not include any disclaimers. The response should be clear and structured."
+            )
+            retry_response = llm.invoke(better_prompt)
+
+            # Extract text from retry response
+            retry_response_text = retry_response.content if hasattr(retry_response, "content") else str(retry_response)
+
+            # Display the retried response if valid
+            if is_valid_response(retry_response_text):
+                st.success("Here is the refined information:")
+                st.write(retry_response_text)
+            else:
+                st.error("Unable to get a useful response. Try rephrasing your question.")
+
+    else:
+        st.warning("Please enter a question!")
+
+# Footer
+st.markdown("---")
+st.markdown("💡 *This AI provides learning-based medical insights, not actual medical advice.*")
+

requirements.txt

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+langchain
+google-generativeai
+langchain_experimental
+langchain-community
+langchain-google-genai
+streamlit