feat: Add memgpt quickstart command (#641)

* Revert "Revert "nonfunctional 404 quickstart command w/ some other typo corrections""

This reverts commit 5dbdf31f1ce939843ff97e649554d8bc0556a834.

* Revert "Revert "added example config file""

This reverts commit 72a58f6de31f3ff71847bbaf083a91182469f9af.

* tested and working

* added and tested openai quickstart, added fallback if internet 404's to pull from local copy

* typo

* updated openai key input message to include html link

* renamed --type to --backend, added --latest flag which fetches from online default is to pull from local file

* fixed links

configs/memgpt_hosted.json

@@ -0,0 +1,12 @@
+{
+    "context_window": 32768,
+    "model": "ehartford/dolphin-2.5-mixtral-8x7b",
+    "model_endpoint_type": "vllm",
+    "model_endpoint": "http://api.memgpt.ai",
+    "model_wrapper": "airoboros-l2-70b-2.1",
+    "embedding_endpoint_type": "hugging-face",
+    "embedding_endpoint": "http://embeddings.memgpt.ai",
+    "embedding_model": "BAAI/bge-large-en-v1.5",
+    "embedding_dim": 1536,
+    "embedding_chunk_size": 300
+}

configs/openai.json

@@ -0,0 +1,12 @@
+{
+    "context_window": 8192,
+    "model": "gpt-4",
+    "model_endpoint_type": "openai",
+    "model_endpoint": "https://api.openai.com/v1",
+    "model_wrapper": null,
+    "embedding_endpoint_type": "openai",
+    "embedding_endpoint": "https://api.openai.com/v1",
+    "embedding_model": null,
+    "embedding_dim": 1536,
+    "embedding_chunk_size": 300
+}

memgpt/cli/cli.py

@@ -1,5 +1,6 @@
 import typer
 import json
+import requests
 import sys
 import io
 import logging
@@ -25,6 +26,136 @@ from memgpt.embeddings import embedding_model
 from memgpt.server.constants import WS_DEFAULT_PORT, REST_DEFAULT_PORT
 
 
+class QuickstartChoice(Enum):
+    openai = "openai"
+    # azure = "azure"
+    memgpt_hosted = "memgpt"
+
+
+def set_config_with_dict(new_config: dict):
+    """Set the base config using a dict"""
+    from memgpt.utils import printd
+
+    old_config = MemGPTConfig.load()
+    modified = False
+    for k, v in vars(old_config).items():
+        if k in new_config:
+            if v != new_config[k]:
+                printd(f"Replacing config {k}: {v} -> {new_config[k]}")
+                modified = True
+                # old_config[k] = new_config[k]
+                setattr(old_config, k, new_config[k])  # Set the new value using dot notation
+            else:
+                printd(f"Skipping new config {k}: {v} == {new_config[k]}")
+
+    if modified:
+        printd(f"Saving new config file.")
+        old_config.save()
+
+
+def quickstart(
+    backend: QuickstartChoice = typer.Option("memgpt", help="Quickstart setup backend"),
+    latest: bool = typer.Option(False, "--latest", help="Use --latest to pull the latest config from online"),
+    debug: bool = typer.Option(False, "--debug", help="Use --debug to enable debugging output"),
+):
+    """Set the base config file with a single command"""
+    # setup logger
+    utils.DEBUG = debug
+    logging.getLogger().setLevel(logging.CRITICAL)
+    if debug:
+        logging.getLogger().setLevel(logging.DEBUG)
+
+    if backend == QuickstartChoice.memgpt_hosted:
+        # if latest, try to pull the config from the repo
+        # fallback to using local
+        if latest:
+            # Download the latest memgpt hosted config
+            url = "https://raw.githubusercontent.com/cpacker/MemGPT/main/configs/memgpt_hosted.json"
+            response = requests.get(url)
+
+            # Check if the request was successful
+            if response.status_code == 200:
+                # Parse the response content as JSON
+                config = response.json()
+                # Output a success message and the first few items in the dictionary as a sample
+                print("JSON config file downloaded successfully.")
+                set_config_with_dict(config)
+            else:
+                print(f"Failed to download config from {url}. Status code:", response.status_code)
+
+                # Load the file from the relative path
+                script_dir = os.path.dirname(__file__)  # Get the directory where the script is located
+                backup_config_path = os.path.join(script_dir, "..", "..", "configs", "memgpt_hosted.json")
+                try:
+                    with open(backup_config_path, "r") as file:
+                        backup_config = json.load(file)
+                    print("Loaded backup config file successfully.")
+                    set_config_with_dict(backup_config)
+                except FileNotFoundError:
+                    print(f"Backup config file not found at {backup_config_path}")
+        else:
+            # Load the file from the relative path
+            script_dir = os.path.dirname(__file__)  # Get the directory where the script is located
+            backup_config_path = os.path.join(script_dir, "..", "..", "configs", "memgpt_hosted.json")
+            try:
+                with open(backup_config_path, "r") as file:
+                    backup_config = json.load(file)
+                print("Loaded config file successfully.")
+                set_config_with_dict(backup_config)
+            except FileNotFoundError:
+                print(f"Config file not found at {backup_config_path}")
+
+    elif backend == QuickstartChoice.openai:
+        # if latest, try to pull the config from the repo
+        # fallback to using local
+        if latest:
+            # Make sure we have an API key
+            api_key = os.getenv("OPENAI_API_KEY")
+            while api_key is None or len(api_key) == 0:
+                # Ask for API key as input
+                api_key = questionary.text("Enter your OpenAI API key (starts with 'sk-', see https://platform.openai.com/api-keys):").ask()
+
+            url = "https://raw.githubusercontent.com/cpacker/MemGPT/main/configs/openai.json"
+            response = requests.get(url)
+
+            # Check if the request was successful
+            if response.status_code == 200:
+                # Parse the response content as JSON
+                config = response.json()
+                # Output a success message and the first few items in the dictionary as a sample
+                print("JSON config file downloaded successfully.")
+                # Add the API key
+                config["openai_key"] = api_key
+                set_config_with_dict(config)
+            else:
+                print(f"Failed to download config from {url}. Status code:", response.status_code)
+
+                # Load the file from the relative path
+                script_dir = os.path.dirname(__file__)  # Get the directory where the script is located
+                backup_config_path = os.path.join(script_dir, "..", "..", "configs", "openai.json")
+                try:
+                    with open(backup_config_path, "r") as file:
+                        backup_config = json.load(file)
+                    print("Loaded backup config file successfully.")
+                    set_config_with_dict(backup_config)
+                except FileNotFoundError:
+                    print(f"Backup config file not found at {backup_config_path}")
+        else:
+            # Load the file from the relative path
+            script_dir = os.path.dirname(__file__)  # Get the directory where the script is located
+            backup_config_path = os.path.join(script_dir, "..", "..", "configs", "openai.json")
+            try:
+                with open(backup_config_path, "r") as file:
+                    backup_config = json.load(file)
+                print("Loaded config file successfully.")
+                set_config_with_dict(backup_config)
+            except FileNotFoundError:
+                print(f"Config file not found at {backup_config_path}")
+
+    else:
+        raise NotImplementedError(backend)
+
+
 def open_folder():
     """Open a folder viewer of the MemGPT home directory"""
     try:

memgpt/local_llm/chat_completion_proxy.py

@@ -54,7 +54,7 @@ def get_chat_completion(
         # Warn the user that we're using the fallback
         if not has_shown_warning:
             print(
-                f"{CLI_WARNING_PREFIX}no wrapper specified for local LLM, using the default wrapper (you can remove this warning by specifying the wrapper with --wrapper)"
+                f"{CLI_WARNING_PREFIX}no wrapper specified for local LLM, using the default wrapper (you can remove this warning by specifying the wrapper with --model-wrapper)"
             )
             has_shown_warning = True
         if endpoint_type in ["koboldcpp", "llamacpp", "webui"]:

memgpt/local_llm/vllm/api.py

@@ -20,7 +20,7 @@ def get_vllm_completion(endpoint, model, prompt, context_window, user, grammar=N
     settings = get_completions_settings()
     request = settings
     request["prompt"] = prompt
-    request["max_tokens"] = int(context_window - prompt_tokens)
+    request["max_tokens"] = 3000  # int(context_window - prompt_tokens)
     request["stream"] = False
     request["user"] = user
 

memgpt/main.py

@@ -21,7 +21,7 @@ from memgpt.interface import CLIInterface as interface  # for printing to termin
 import memgpt.agent as agent
 import memgpt.system as system
 import memgpt.constants as constants
-from memgpt.cli.cli import run, attach, version, server, open_folder
+from memgpt.cli.cli import run, attach, version, server, open_folder, quickstart
 from memgpt.cli.cli_config import configure, list, add
 from memgpt.cli.cli_load import app as load_app
 from memgpt.connectors.storage import StorageConnector
@@ -35,6 +35,7 @@ app.command(name="list")(list)
 app.command(name="add")(add)
 app.command(name="server")(server)
 app.command(name="folder")(open_folder)
+app.command(name="quickstart")(quickstart)
 # load data commands
 app.add_typer(load_app, name="load")