Initial Streamlit + Supabase memory bot

app.py

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+import os
+import streamlit as st
+from transformers import pipeline, AutoTokenizer, AutoModelForCausalLM
+from peft import PeftModel
+from supabase import create_client
+from sentence_transformers import SentenceTransformer
+
+# — Supabase creds from Secrets —
+SUPA_URL = os.getenv("SUPABASE_URL")
+SUPA_KEY = os.getenv("SUPABASE_SERVICE_ROLE_KEY")
+supabase = create_client(SUPA_URL, SUPA_KEY)
+
+# — Embedding model & retrieval function —
+embedder = SentenceTransformer("paraphrase-MiniLM-L3-v2")
+def fetch_mems(query, k=5):
+    vec = embedder.encode(query).tolist()
+    # call your RPC
+    data = supabase.rpc("match_memories", {"query_embedding": vec, "match_count": k}).execute().data
+    return data
+
+def add_mem(speaker, text):
+    vec = embedder.encode(text).tolist()
+    supabase.table("memories").insert({
+      "speaker": speaker, "text": text, "embedding": vec
+    }).execute()
+
+# — Load LoRA model from HF hub —
+REPO = "sourize/phi2-memory-lora"
+tokenizer = AutoTokenizer.from_pretrained(REPO, trust_remote_code=True, padding_side="left")
+model_base = AutoModelForCausalLM.from_pretrained(REPO, trust_remote_code=True)
+model_base.resize_token_embeddings(len(tokenizer))
+model = PeftModel.from_pretrained(model_base, REPO)
+pipe  = pipeline("text-generation", model=model, tokenizer=tokenizer, device=0,
+                 do_sample=True, top_p=0.9, temperature=0.8)
+
+st.title("🧠 Memory-Aware Phi-2 Bot")
+if "history" not in st.session_state:
+    st.session_state.history = []
+
+def chat(u):
+    add_mem("user", u)
+    mems = fetch_mems(u, 3)
+    block = "\n".join(f"{m['speaker']}: {m['text']}" for m in mems)
+    prompt = f"Memory:\n{block}\n\nUser: {u}\nAssistant:"
+    out    = pipe(prompt, max_length=200)[0]["generated_text"].split("Assistant:")[-1].strip()
+    add_mem("assistant", out)
+    return out
+
+user = st.text_input("You:")
+if user:
+    resp = chat(user)
+    st.session_state.history.append(("You", user))
+    st.session_state.history.append(("Bot", resp))
+
+for s, t in st.session_state.history:
+    style = "### You:" if s=="You" else "**Bot:**"
+    st.markdown(f"{style} {t}")

requirements.txt

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+streamlit
+transformers>=4.30
+peft
+supabase
+sentence-transformers
+faiss-cpu