diff --git a/memgpt/local_llm/lmstudio/api.py b/memgpt/local_llm/lmstudio/api.py
index a379914d19..1715ba445f 100644
--- a/memgpt/local_llm/lmstudio/api.py
+++ b/memgpt/local_llm/lmstudio/api.py
@@ -2,39 +2,59 @@
 from urllib.parse import urljoin
 import requests
 
-# from .settings import SIMPLE
+from .settings import SIMPLE
 
 HOST = os.getenv("OPENAI_API_BASE")
 HOST_TYPE = os.getenv("BACKEND_TYPE")  # default None == ChatCompletion
-LMSTUDIO_API_SUFFIX = "/v1/completions"
+LMSTUDIO_API_CHAT_SUFFIX = "/v1/chat/completions"
+LMSTUDIO_API_COMPLETIONS_SUFFIX = "/v1/completions"
 DEBUG = False
 
-from .settings import SIMPLE
-
 
-def get_lmstudio_completion(prompt, settings=SIMPLE):
+def get_lmstudio_completion(prompt, settings=SIMPLE, api="chat"):
     """Based on the example for using LM Studio as a backend from https://github.com/lmstudio-ai/examples/tree/main/Hello%2C%20world%20-%20OpenAI%20python%20client"""
 
     # Settings for the generation, includes the prompt + stop tokens, max length, etc
     request = settings
-    request["prompt"] = prompt
+
+    if api == "chat":
+        # Uses the ChatCompletions API style
+        # Seems to work better, probably because it's applying some extra settings under-the-hood?
+        URI = urljoin(HOST.strip("/") + "/", LMSTUDIO_API_CHAT_SUFFIX.strip("/"))
+        message_structure = [{"role": "user", "content": prompt}]
+        request["messages"] = message_structure
+    elif api == "completions":
+        # Uses basic string completions (string in, string out)
+        # Does not work as well as ChatCompletions for some reason
+        URI = urljoin(HOST.strip("/") + "/", LMSTUDIO_API_COMPLETIONS_SUFFIX.strip("/"))
+        request["prompt"] = prompt
+    else:
+        raise ValueError(api)
 
     if not HOST.startswith(("http://", "https://")):
         raise ValueError(f"Provided OPENAI_API_BASE value ({HOST}) must begin with http:// or https://")
 
     try:
-        URI = urljoin(HOST.strip("/") + "/", LMSTUDIO_API_SUFFIX.strip("/"))
         response = requests.post(URI, json=request)
         if response.status_code == 200:
             result = response.json()
-            # result = result["results"][0]["text"]
-            result = result["choices"][0]["text"]
+            if api == "chat":
+                result = result["choices"][0]["message"]["content"]
+            elif api == "completions":
+                result = result["choices"][0]["text"]
             if DEBUG:
                 print(f"json API response.text: {result}")
         else:
-            raise Exception(
-                f"API call got non-200 response code for address: {URI}. Make sure that the LM Studio local inference server is running and reachable at {URI}."
-            )
+            # Example error: msg={"error":"Context length exceeded. Tokens in context: 8000, Context length: 8000"}
+            if "context length" in str(response.text).lower():
+                # "exceeds context length" is what appears in the LM Studio error message
+                # raise an alternate exception that matches OpenAI's message, which is "maximum context length"
+                raise Exception(f"Request exceeds maximum context length (code={response.status_code}, msg={response.text}, URI={URI})")
+            else:
+                raise Exception(
+                    f"API call got non-200 response code (code={response.status_code}, msg={response.text}) for address: {URI}."
+                    + f"Make sure that the LM Studio local inference server is running and reachable at {URI}."
+                )
     except:
         # TODO handle gracefully
         raise
diff --git a/memgpt/local_llm/lmstudio/settings.py b/memgpt/local_llm/lmstudio/settings.py
index cdf8962e95..3d8622ace8 100644
--- a/memgpt/local_llm/lmstudio/settings.py
+++ b/memgpt/local_llm/lmstudio/settings.py
@@ -9,5 +9,12 @@
         # '\n#',
         # '\n\n\n',
     ],
-    "max_tokens": 500,
+    # This controls the maximum number of tokens that the model can generate
+    # Cap this at the model context length (assuming 8k for Mistral 7B)
+    "max_tokens": 8000,
+    # This controls how LM studio handles context overflow
+    # In MemGPT we handle this ourselves, so this should be commented out
+    # "lmstudio": {"context_overflow_policy": 2},
+    "stream": False,
+    "model": "local model",
 }