Create app.py

app.py

@@ -0,0 +1,149 @@
+import subprocess
+import time
+
+# start backend
+subprocess.Popen(
+    ["uvicorn", "backend.main:app", "--host", "0.0.0.0", "--port", "8000"]
+)
+
+# small delay so backend boots
+time.sleep(2)
+
+
+
+
+import streamlit as st
+import requests
+import time
+
+
+API_URL = "http://0.0.0.0:8000"
+
+
+
+st.set_page_config(page_title="GenAI RAG App (Docs + Code)", layout="wide")
+st.title("🧠 GenAI RAG App (Docs + Code)")
+
+
+# ---------------- Chat Memory ----------------
+if "history" not in st.session_state:
+    st.session_state["history"] = []
+
+
+# ---------------- Sidebar Settings ----------------
+with st.sidebar:
+    st.header("Settings")
+
+    domain = st.radio("Knowledge Base:", ["doc", "code"])
+
+    if st.button("Clear Chat"):
+        st.session_state["history"] = []
+
+
+# ---------------- Tabs ----------------
+upload_tab, query_tab = st.tabs(["⬆ Upload", "💬 Chat"])
+
+
+# ---------------- Upload Tab ----------------
+with upload_tab:
+    st.subheader("Upload File")
+
+    file = st.file_uploader("Upload PDF / TXT / Python code", type=["pdf", "txt", "md", "py", "js", "ts"])
+
+    if file:
+        ext = file.name.split(".")[-1]
+
+        if ext in ["pdf", "txt", "md"]:
+            endpoint = "/upload/doc"
+        else:
+            endpoint = "/upload/code"
+
+        files = {"file": (file.name, file.getvalue())}
+
+        with st.spinner("Indexing file..."):
+            r = requests.post(API_URL + endpoint, files=files)
+
+        if r.status_code == 200:
+            st.success("File Indexed!")
+            st.json(r.json())
+        else:
+            st.error("Upload Failed! Check FastAPI backend.")
+
+
+
+# ---------------- Helper: Streaming Output ----------------
+def stream_text(text, delay=0.025):
+    """Yield tokens to simulate streaming."""
+    for token in text.split():
+        yield token + " "
+        time.sleep(delay)
+
+
+
+# ---------------- Query / Chat Tab ----------------
+with query_tab:
+    st.subheader("Ask a Question")
+
+    # Show chat history
+    for msg in st.session_state["history"]:
+        role = "You" if msg["role"] == "user" else "AI"
+        st.markdown(f"**{role}:** {msg['text']}")
+
+
+    # Mode selection based on domain
+    if domain == "code":
+        mode = st.selectbox("Mode:", [
+            "Explain",
+            "Debug",
+            "Fix",
+            "Refactor",
+            "Add Comments",
+            "Complexity"
+        ])
+    else:
+        mode = st.selectbox("Mode:", [
+            "Answer",
+            "Summarize",
+            "Bullet Points",
+            "Keywords"
+        ])
+
+    question = st.text_input("Enter your question")
+
+    if st.button("Ask"):
+        if not question.strip():
+            st.warning("Enter a question before submitting.")
+        else:
+            payload = {"question": question, "domain": domain, "mode": mode}
+
+            with st.spinner("Thinking..."):
+                r = requests.post(API_URL + "/query", json=payload)
+
+            if r.status_code == 200:
+                data = r.json()
+                answer = data["answer"]
+                context = data["context"]
+
+                # Save history
+                st.session_state["history"].append({"role": "user", "text": question})
+                st.session_state["history"].append({"role": "assistant", "text": answer})
+
+                # Stream output
+                st.success("AI:")
+                placeholder = st.empty()
+                stream = stream_text(answer)
+
+                full = ""
+                for token in stream:
+                    full += token
+                    placeholder.markdown(full + "▌")
+
+                # RAG Context section
+                with st.expander("🔍 Retrieved Context (RAG)"):
+                    if domain == "code":
+                        st.code(context)
+                    else:
+                        st.text(context)
+
+            else:
+                st.error("Query Failed! Check backend or logs.")