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Quickstart

Install memary

1st Option

Make sure you are running python version <= 3.11.9, then run 

pip install memary

2nd Option

You can also install memary locally:

i. Create a virtual environment with the python version set as specified above

ii. Install python dependencies: 

pip install -r requirements.txt

Specify models used

Local OS Support

At the time of writing, memary assumes installation of local models and we currently support all models available through Ollama:

  • LLM running locally using Ollama (Llama 3 8B/40B as suggested defaults) OR gpt-3.5-turbo
  • Vision model running locally using Ollama (LLaVA as suggested default) OR gpt-4-vision-preview

memary will default to the locally run models unless explicitly specified. Additionally, memary allows developers to easily switch between downloaded models.

Run memary

  • (Optional) If running models locally using Ollama, follow the instructions in this repo.

  • Ensure that an .env exists with any necessary API keys and Neo4j credentials

.env 
OPENAI_API_KEY=YOUR_API_KEY
NEO4J_PW=YOUR_NEO4J_PW
NEO4J_URL=YOUR_NEO4J_URL
PERPLEXITY_API_KEY=YOUR_API_KEY
GOOGLEMAPS_API_KEY=YOUR_API_KEY
ALPHA_VANTAGE_API_KEY=YOUR_API_KEY

  • Update user persona which can be found in streamlit_app/data/user_persona.txt using the user persona template which can be found in streamlit_app/data/user_persona_template.txt. Instructions have been provided for customization - replace the curly brackets with relevant information.

  • (Optional) Update system persona, if needed, which can be found in streamlit_app/data/system_persona.txt.

Lastly Run

cd streamlit_app
streamlit run app.py

More Basic Functionality

memary_usage
from memary.agent.chat_agent import ChatAgent

system_persona_txt = "data/system_persona.txt"
user_persona_txt = "data/user_persona.txt"
past_chat_json = "data/past_chat.json"
memory_stream_json = "data/memory_stream.json"
entity_knowledge_store_json = "data/entity_knowledge_store.json"
chat_agent = ChatAgent(
    "Personal Agent",
    memory_stream_json,
    entity_knowledge_store_json,
    system_persona_txt,
    user_persona_txt,
    past_chat_json,
)

Agent Configuration

Pass in subset of the template tools ['search', 'vision', 'locate', 'stocks'] as include_from_defaults for different set of default tools upon initialization. Tools can be imported to configure the agents capabilties.

Adding Custom Tools

add_tool
def multiply(a: int, b: int) -> int:
    """Multiply two integers and returns the result integer"""
    return a * b

chat_agent.add_tool({"multiply": multiply})

ReAct Custom Tools

More information about creating custom tools for the LlamaIndex ReAct Agent can be found here.

Removing Custom Tools

remove_tool
def multiply(a: int, b: int) -> int:
    """Multiply two integers and returns the result integer"""
    return a * b

chat_agent.remove_tool("multiply")