new

README.md

@@ -1,12 +1,10 @@
 ---
-title: Neuro Chatbot
-emoji: 🐠
-colorFrom: red
-colorTo: yellow
+title: Neurology Chatbot
+emoji: 🏃
+colorFrom: purple
+colorTo: green
 sdk: streamlit
-sdk_version: 1.42.2
+sdk_version: 1.42.1
 app_file: app.py
 pinned: false
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+---

app.py

@@ -0,0 +1,58 @@
+import streamlit as st
+from groq import Client
+
+# API Key Configuration (Use environment variables in production)
+GROQ_API_KEY = "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"
+
+def main():
+    st.set_page_config(page_title="🧠 Neurology Chatbot", layout="wide")
+    st.title("🧠 Neurology AI Chatbot")
+
+    # Load chatbot model
+    @st.cache_resource
+    def load_model():
+        return Client(api_key=GROQ_API_KEY)
+
+    chatbot = load_model()
+
+    # Strict system prompt
+    system_prompt = {
+        "role": "system",
+        "content": ("You are a professional neurology assistant. Your role is to provide accurate and up-to-date medical insights related to neurological disorders, brain health, symptoms, treatments, and neuroscience research. Always ensure that responses are factual, empathetic, and professional. If a query is **unrelated to neurology** or medical concerns, politely redirect the user by saying: 'I specialize in neurology-related assistance. Let me know how I can help with your neurological health concerns.'"
+        )
+    }
+
+    # Initialize chat history
+    if "messages" not in st.session_state:
+        st.session_state["messages"] = [system_prompt]
+
+    # Display chat history (excluding system message)
+    for message in st.session_state["messages"]:
+        if message["role"] != "system":
+            with st.chat_message(message["role"]):
+                st.markdown(message["content"])
+
+    # User input
+    user_input = st.chat_input("Ask me anything about neurology...")
+
+    if user_input:
+        # Add user message to session state
+        st.session_state["messages"].append({"role": "user", "content": user_input})
+        with st.chat_message("user"):
+            st.markdown(user_input)
+
+        # Generate response with strict system prompt
+        response = chatbot.chat.completions.create(
+            model="llama-3.3-70b-versatile",
+            messages=[system_prompt] + st.session_state["messages"]  # Always include system prompt
+        )
+
+        bot_response = response.choices[0].message.content
+
+        # Add assistant's response to session state
+        st.session_state["messages"].append({"role": "assistant", "content": bot_response})
+        with st.chat_message("assistant"):
+            st.markdown(bot_response)
+
+if __name__ == "__main__":
+    main()

requirements.txt

@@ -0,0 +1,2 @@
+streamlit
+groq