Update app.py

app.py

@@ -2,73 +2,101 @@ import gradio as gr
 from groq import Groq
 import os
 import time
+import json
 
 # =========================
-# LOAD API KEY (HUGGING FACE SECRETS)
+# API KEY
 # =========================
 api_key = os.getenv("GROQ_API_KEY")
 
 if not api_key:
-    raise ValueError("GROQ_API_KEY not found in environment variables")
+    raise ValueError("GROQ_API_KEY not found")
 
 client = Groq(api_key=api_key.strip())
 
 # =========================
-# CHAT FUNCTION (STREAMING)
+# MEMORY FILE
+# =========================
+MEMORY_FILE = "memory.json"
+
+def load_memory():
+    if os.path.exists(MEMORY_FILE):
+        with open(MEMORY_FILE, "r") as f:
+            return json.load(f)
+    return {"facts": {}}
+
+def save_memory(data):
+    with open(MEMORY_FILE, "w") as f:
+        json.dump(data, f)
+
+memory = load_memory()
+
+# =========================
+# CHAT FUNCTION
 # =========================
 def chat(message, history):
-    try:
-        messages = [
-            {
-                "role": "system",
-                "content": "You are a helpful AI assistant."
-            }
-        ]
 
-        # Add history
-        for user, bot in history:
-            messages.append({"role": "user", "content": user})
-            messages.append({"role": "assistant", "content": bot})
+    global memory
 
-        messages.append({"role": "user", "content": message})
+    # -------------------------
+    # MEMORY DETECTION
+    # -------------------------
+    if "my name is" in message.lower():
+        name = message.lower().split("my name is")[-1].strip()
+        memory["facts"]["name"] = name
+        save_memory(memory)
 
-        # Streaming request
-        stream = client.chat.completions.create(
-            model="llama-3.3-70b-versatile",
-            messages=messages,
-            stream=True,
-            temperature=0.7
-        )
+    # -------------------------
+    # SYSTEM PROMPT WITH MEMORY
+    # -------------------------
+    system_prompt = "You are a helpful AI assistant."
 
-        response_text = ""
+    if "name" in memory["facts"]:
+        system_prompt += f" User name is {memory['facts']['name']}."
 
-        # Stream output token by token
-        for chunk in stream:
-            if chunk.choices[0].delta.content:
-                token = chunk.choices[0].delta.content
-                response_text += token
+    messages = [{"role": "system", "content": system_prompt}]
 
-                # Slow typing effect
-                time.sleep(0.03)
+    # -------------------------
+    # SAFE HISTORY HANDLING (FIXED ERROR)
+    # -------------------------
+    for item in history:
+        if isinstance(item, (list, tuple)) and len(item) == 2:
+            user_msg, bot_msg = item
+            messages.append({"role": "user", "content": user_msg})
+            messages.append({"role": "assistant", "content": bot_msg})
 
-                yield response_text + "▌"
+    messages.append({"role": "user", "content": message})
 
-        # Final clean output
-        yield response_text
+    # -------------------------
+    # STREAM RESPONSE
+    # -------------------------
+    stream = client.chat.completions.create(
+        model="llama-3.3-70b-versatile",
+        messages=messages,
+        stream=True,
+        temperature=0.7
+    )
 
-    except Exception as e:
-        yield f"Error: {str(e)}"
+    response_text = ""
+
+    for chunk in stream:
+        if chunk.choices[0].delta.content:
+            token = chunk.choices[0].delta.content
+            response_text += token
+
+            time.sleep(0.03)
+
+            yield response_text + "▌"
+
+    yield response_text
 
 # =========================
-# UI (PROFESSIONAL)
+# UI
 # =========================
 demo = gr.ChatInterface(
     fn=chat,
     title="Streaming AI Chatbot using Groq",
-    description="AI chatbot with real-time response streaming",
+    description="AI chatbot with memory + streaming",
 )
 
-# =========================
-# LAUNCH APP
-# =========================
 demo.launch()