Upload app.py

app.py

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+import os
+import streamlit as st
+from huggingface_hub import InferenceClient
+from dotenv import load_dotenv
+
+# Load environment variables (for local development)
+load_dotenv()
+
+# Initialize InferenceClient
+token = os.environ.get("HUGGINGFACEHUB_API_TOKEN")
+client = InferenceClient(provider="auto", api_key=token)
+
+st.set_page_config(page_title="Interview Prep Bot", layout="wide")
+st.title("🎓 Interview Preparation Chatbot")
+
+# Initialize history
+if "history" not in st.session_state:
+    st.session_state.history = []
+
+# Render chat history
+for sender, msg in st.session_state.history:
+    role = "user" if sender == "You" else "assistant"
+    st.chat_message(role).write(msg)
+
+# Prompt input
+text = st.chat_input("Ask me anything about interview prep…")
+if text:
+    # record user
+    st.session_state.history.append(("You", text))
+    st.chat_message("user").write(text)
+
+    # placeholder
+    placeholder = st.chat_message("assistant")
+    placeholder.write("⏳ Thinking...")
+
+    # build messages for API
+    messages = []
+    for s, m in st.session_state.history:
+        role = "user" if s == "You" else "assistant"
+        messages.append({"role": role, "content": m})
+
+    # call HF chat completion
+    try:
+        completion = client.chat.completions.create(
+            model="mistralai/Mistral-7B-Instruct-v0.1",
+            messages=messages,
+        )
+        reply = completion.choices[0].message["content"].strip()
+    except Exception as e:
+        reply = f"❌ API Error: {e}"
+
+    # display and store reply
+    placeholder.write(reply)
+    st.session_state.history.append(("Bot", reply))