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Documentation Index

Fetch the complete documentation index at: https://docs.hub.agentsea.ai/llms.txt

Use this file to discover all available pages before exploring further.

ThreadMem is a library for building and manipulating persistent chat threads. It makes it easier to communicate with LLMs, but it’s not limited to that alone. For example, you can create a Thread in the code and add messages to it (like, a message from “system”, a message from “user”, a message from “assistant”, from “user” again, etc). The threads get written to a DB (SQLite/Postgres), so you can return to the chat at any time and pick up where you left off.

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Installation

pip install threadmem

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Basic Example

By default, the threads you create are stored in a local SQLite database, located at ./data/threads.db. 
owner_id = "random123"
public = True
name = "My thread"
metadata = {"purpose": "demo"}

thread = RoleThread(owner_id=owner_id, public=public, name=name, metadata=metadata)

role_user = "user"
role_assistant = "assistant"

thread.post(role=role_user, msg="Hey there!")
thread.post(role=role_assistant, msg="Hello!")
thread.post(role=role_user, msg="What do you see on this picture?", images=["https://upload.wikimedia.org/wikipedia/commons/c/c7/Tabby_cat_with_blue_eyes-3336579.jpg"])
thread.post(role=role_assistant, msg="I see a cat with blue eyes.")
As mentioned above, the library is designed for making it easier to communicate with LLMs, so we support a to_oai method for exporting the thread to OpenAI format. 
json_load = thread.to_oai()
Add images of any variety to the thread. We support base64, filepath, PIL, and URL: 
from PIL import Image

img1 = Image.open("img1.png")

thread.post(
  role="user",
  msg="Whats this image?",
  images=["data:image/jpeg;base64,...", "./img1.png", img1, "https://shorturl.at/rVyAS"]
)

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Using PostgreSQL

To use PostgreSQL as a database backend, you should set up a few environment variables. 
export DB_TYPE=postgres
export DB_USER=<username>
export DB_PASS=<password>
export DB_HOST=<host:port>
export DB_NAME=<database>

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Remote Connection

It’s possible to connect to a remote server with ThreadMem. To do that, you pass the remote server URL to the thread constructor: 
thread = RoleThread(owner_id=owner_id, 
                    public=public, name=name, metadata=metadata, 
                    remote="https://agentsea.com/threadmem")