Merge pull request #895 from Undertone0809/hizeros/mem0

Hizeros/mem0

example/mem0/app.py

@@ -0,0 +1,48 @@
+import pne
+import streamlit as st
+from core import PersonalHealingAssistant
+
+
+def main():
+    config = pne.beta.st.model_sidebar()
+    # todo llm default answer with cn
+    with st.sidebar:
+        mem0_user_id = st.text_input("mem0 user id", type="password")
+        mem0_api_key = st.text_input(
+            "mem0 API Key", key="provider_mem0_api_key", type="password"
+        )
+
+    st.title("PersonalHealingAssistant")
+    st.caption(
+        """
+        Personal Healing Assistant combines pne and mem0ai to create a personalized healing assistant for you \n
+        🚀 Power by [promptulate](https://github.com/Undertone0809/promptulate)
+        """  # noqa
+    )
+    st.chat_message("assistant").write(
+        "I am your personal healing assistant, how can I help you? "
+    )
+
+    ai_assistant = PersonalHealingAssistant()
+
+    if prompt := st.chat_input("Please enter what you want to know "):
+        if not config.api_key:
+            st.info("Please add your model API key to continue.")
+            st.stop()
+
+        if not mem0_api_key:
+            st.error("Please provide your mem0 API Key to continue.")
+            st.stop()
+
+        ai_assistant.set_mem0_api_key(mem0_api_key)
+
+        answer = ai_assistant.ask_question(
+            question=prompt, user_id=mem0_user_id, config=config
+        )
+
+        st.chat_message("user").write(prompt)
+        st.chat_message("assistant").write_stream(answer)
+
+
+if __name__ == "__main__":
+    main()

example/mem0/core.py

@@ -0,0 +1,41 @@
+import pne
+from mem0 import MemoryClient
+
+
+class PersonalHealingAssistant:
+    def __init__(self):
+        self.memory = None
+        self.messages = [
+            {"role": "system", "content": "You are a personal healing AI Assistant."}
+        ]
+
+    def set_mem0_api_key(self, mem0_api_key: str):
+        self.memory = MemoryClient(api_key=mem0_api_key)
+
+    def ask_question(self, question: str, user_id: str, config) -> str:
+        # Fetch previous related memories
+        previous_memories = self.search_memories(question, user_id=user_id)
+        prompt = question
+        if previous_memories:
+            prompt = f"User input: {question}\n Previous memories: {previous_memories}"
+        self.messages.append({"role": "user", "content": prompt})
+
+        response = pne.chat(
+            model=config.model_name,
+            stream=True,
+            messages=self.messages,
+            model_config={"api_base": config.api_base, "api_key": config.api_key},
+        )
+        self.messages.append({"role": "assistant", "content": response})
+
+        # Store the question in memory
+        self.memory.add(question, user_id=user_id)
+        return response
+
+    def get_memories(self, user_id):
+        memories = self.memory.get_all(user_id=user_id)
+        return memories
+
+    def search_memories(self, query, user_id):
+        memories = self.memory.search(query, user_id=user_id)
+        return memories

example/mem0/requirements.txt

@@ -0,0 +1,3 @@
+streamlit>=1.28
+pne
+mem0ai