feat: Add MemGPT "Python Client" (#713)

* First commit of memgpt client and some messy test code

* rolled back unnecessary changes to abstract interface; switched client to always use Queueing Interface

* Added missing interface clear() in run_command;  added convenience method for checking if an agent exists, used that in create_agent

* Formatting fixes

* Fixed incorrect naming of get_agent_memory in rest server

* Removed erroneous clear from client save method;  Replaced print statements with appropriate logger calls in server

* Updated readme with client usage instructions

* added tests for Client

* make printing to terminal togglable on queininginterface (should probably refactor this to a logger)

* turn off printing to stdout via interface by default

* allow importing the python client in a similar fashion to openai-python (see https://github.com/openai/openai-python)

* Allowed quickstart on init of client;  updated readme and test_client accordingly

* oops, fixed name of openai_api_key config key

* Fixed small typo

* Fixed broken test by adding memgpt hosted model details to agent config

* silence llamaindex 'LLM is explicitly disabled. Using MockLLM.' on server

* default to openai if user's memgpt directory is empty (first time)

* correct type hint

* updated section on client in readme

* added comment about how MemGPT config != Agent config

* patch unrelated test

* update wording on readme

* patch another unrelated test

* added python client to readme docs

* Changed 'user' to 'human' in example;  Defaulted AgentConfig.model to 'None';  Fixed issue in create_agent (accounting for dict config);  matched test code to example

* Fixed advanced example

* patch test

* patch

---------

Co-authored-by: cpacker <packercharles@gmail.com>

docs/python_client.md

@@ -0,0 +1,88 @@
+---
+title: Python client
+excerpt: Developing using the MemGPT Python client
+category: 6580dab16cade8003f996d17 
+---
+
+The fastest way to integrate MemGPT with your own Python projects is through the `MemGPT` client class:
+```python
+from memgpt import MemGPT
+
+# Create a MemGPT client object (sets up the persistent state)
+client = MemGPT(
+  quickstart="openai",
+  config={
+    "openai_api_key": "YOUR_API_KEY"
+  }
+)
+
+# You can set many more parameters, this is just a basic example
+agent_id = client.create_agent(
+  agent_config={
+    "persona": "sam_pov",
+    "user": "cs_phd",
+  }
+)
+
+# Now that we have an agent_name identifier, we can send it a message!
+# The response will have data from the MemGPT agent
+my_message = "Hi MemGPT! How's it going?"
+response = client.user_message(agent_id=agent_id, message=my_message)
+```
+
+## More in-depth example of using the MemGPT Python client
+
+```python
+from memgpt.config import AgentConfig
+from memgpt import MemGPT
+from memgpt import constants
+from memgpt.cli.cli import QuickstartChoice
+
+
+client = MemGPT(
+    # When auto_save is 'True' then the agent(s) will be saved after every
+    # user message.  This may have performance implications, so you
+    # can otherwise choose when to save explicitly using client.save().
+    auto_save=True,
+    
+    # Quickstart will automatically configure MemGPT (without having to run `memgpt configure`
+    # If you choose 'openai' then you must set the api key (env or in config)
+    quickstart=QuickstartChoice.memgpt_hosted,
+    
+    # Allows you to override default config generated by quickstart or `memgpt configure`
+    config={}
+)
+
+# Create an AgentConfig with default persona and human txt
+# In this case, assume we wrote a custom persona file "my_persona.txt", located at ~/.memgpt/personas/my_persona.txt
+# Same for a custom user file "my_user.txt", located at ~/.memgpt/humans/my_user.txt
+agent_config = AgentConfig(
+    name="CustomAgent",
+    persona="my_persona",
+    human="my_user",
+    preset="memgpt_chat",
+    model="gpt-4",
+)
+
+# Create the agent according to AgentConfig we set up. If an agent with
+# the same name already exists it will simply return, unless you set
+# throw_if_exists to 'True'
+agent_id = client.create_agent(agent_config=agent_config)
+
+# Create a helper that sends a message and prints the assistant response only
+def send_message(message: str):
+    """
+    sends a message and prints the assistant output only.
+    :param message: the message to send
+    """
+    response = client.user_message(agent_id=agent_id, message=message)
+    for r in response:
+        # Can also handle other types "function_call", "function_return", "function_message"
+        if "assistant_message" in r:
+            print("ASSISTANT:", r["assistant_message"])
+        elif "thoughts" in r:
+            print("THOUGHTS:", r["internal_monologue"])
+
+# Send a message and see the response
+send_message("Please introduce yourself and tell me about your abilities!")
+```