Added new demo

llm_app_personalized_memory/multi_llm_memory.py

@@ -0,0 +1,87 @@
+import streamlit as st
+from mem0 import Memory
+from openai import OpenAI
+import os
+from litellm import completion
+
+st.title("LLM App with Shared Memory 🧠")
+st.caption("LLM App with a personalized memory layer that remembers each user's choices and interests across multiple users and LLMs")
+
+openai_api_key = st.text_input("Enter OpenAI API Key", type="password")
+anthropic_api_key = st.text_input("Enter Anthropic API Key", type="password")
+
+if openai_api_key and anthropic_api_key:
+    os.environ["ANTHROPIC_API_KEY"] = anthropic_api_key
+
+    # Initialize Mem0 with Qdrant
+    config = {
+        "vector_store": {
+            "provider": "qdrant",
+            "config": {
+                "host": "localhost",
+                "port": 6333,
+            }
+        },
+    }
+
+    memory = Memory.from_config(config)
+
+    user_id = st.sidebar.text_input("Enter your Username")
+    llm_choice = st.sidebar.radio("Select LLM", ('OpenAI GPT-4o', 'Claude Sonnet 3.5'))
+
+    if llm_choice == 'OpenAI GPT-4o':
+        client = OpenAI(api_key=openai_api_key)
+    elif llm_choice == 'Claude Sonnet 3.5':
+        config = {
+            "llm": {
+                "provider": "litellm",
+                "config": {
+                    "model": "claude-3-5-sonnet-20240620",
+                    "temperature": 0.5,
+                    "max_tokens": 2000,
+                }
+            }
+        }
+        client = Memory.from_config(config)
+
+    prompt = st.text_input("Ask the LLM")
+
+    if st.button('Chat with LLM'):
+        with st.spinner('Searching...'):
+            relevant_memories = memory.search(query=prompt, user_id=user_id)
+            context = "Relevant past information:\n"
+
+            for mem in relevant_memories:
+                context += f"- {mem['text']}\n"
+                
+            full_prompt = f"{context}\nHuman: {prompt}\nAI:"
+
+            if llm_choice == 'OpenAI GPT-4o':
+                response = client.chat.completions.create(
+                    model="gpt-4o",
+                    messages=[
+                        {"role": "system", "content": "You are a helpful assistant with access to past conversations."},
+                        {"role": "user", "content": full_prompt}
+                    ]
+                )
+                answer = response.choices[0].message.content
+            elif llm_choice == 'Claude Sonnet 3.5':
+                messages=[
+                        {"role": "system", "content": "You are a helpful assistant with access to past conversations."},
+                        {"role": "user", "content": full_prompt}
+                    ]
+                response = completion(model="claude-3-5-sonnet-20240620", messages=messages)
+                answer = response.choices[0].message.content
+            st.write("Answer: ", answer)
+
+            memory.add(answer, user_id=user_id)
+
+    st.sidebar.title("Memory Info")
+    if st.sidebar.button("View Memory Info"):
+        memories = memory.get_all(user_id=user_id)
+        if memories:
+            st.sidebar.write(f"You are viewing memory for user **{user_id}**")
+            for mem in memories:
+                st.sidebar.write(f"- {mem['text']}")
+        else:
+            st.sidebar.info("No learning history found for this user ID.")

llm_app_personalized_memory/requirements.txt

@@ -1,3 +1,4 @@
 streamlit 
 openai
-mem0ai
+mem0ai
+litellm