diff --git a/open_notebook/graphs/chat.py b/open_notebook/graphs/chat.py
index 84a30be..88f5cb1 100644
--- a/open_notebook/graphs/chat.py
+++ b/open_notebook/graphs/chat.py
@@ -22,12 +22,12 @@ class ThreadState(TypedDict):
 
 
 def call_model_with_messages(state: ThreadState, config: RunnableConfig) -> dict:
-    model_name = config.get("configurable", {}).get(
-        "model_name", DEFAULT_MODELS.default_chat_model
+    model_id = config.get("configurable", {}).get(
+        "model_id", DEFAULT_MODELS.default_chat_model
     )
     ai_message = run_pattern(
         "chat",
-        model_name,
+        model_id,
         messages=state["messages"],
         state=state,
     )
diff --git a/open_notebook/graphs/doc_query.py b/open_notebook/graphs/doc_query.py
index 9a2ffb9..34445e7 100644
--- a/open_notebook/graphs/doc_query.py
+++ b/open_notebook/graphs/doc_query.py
@@ -19,10 +19,10 @@ class DocQueryState(TypedDict):
 
 
 def call_model(state: dict, config: RunnableConfig) -> dict:
-    model_name = config.get("configurable", {}).get(
-        "model_name", os.environ.get("RETRIEVAL_MODEL")
+    model_id = config.get("configurable", {}).get(
+        "model_id", os.environ.get("RETRIEVAL_MODEL")
     )
-    return {"answer": run_pattern("doc_query", model_name, state)}
+    return {"answer": run_pattern("doc_query", model_id, state)}
 
 
 # todo: there is probably a better way to do this and avoid repetition
diff --git a/open_notebook/graphs/multipattern.py b/open_notebook/graphs/multipattern.py
index e74d7a3..b1ef19b 100644
--- a/open_notebook/graphs/multipattern.py
+++ b/open_notebook/graphs/multipattern.py
@@ -18,8 +18,8 @@ class PatternChainState(TypedDict):
 
 
 def call_model(state: dict, config: RunnableConfig) -> dict:
-    model_name = config.get("configurable", {}).get(
-        "model_name", DEFAULT_MODELS.default_transformation_model
+    model_id = config.get("configurable", {}).get(
+        "model_id", DEFAULT_MODELS.default_transformation_model
     )
     transformations = state["transformations"]
     current_transformation = transformations.pop(0)
@@ -34,7 +34,7 @@ def call_model(state: dict, config: RunnableConfig) -> dict:
 
     transformation_result = run_pattern(
         pattern_name=current_transformation,
-        model_name=model_name,
+        model_id=model_id,
         state=input_args,
     )
     return {
diff --git a/open_notebook/graphs/pattern.py b/open_notebook/graphs/pattern.py
index c47cc14..faf15f9 100644
--- a/open_notebook/graphs/pattern.py
+++ b/open_notebook/graphs/pattern.py
@@ -15,13 +15,13 @@ class PatternState(TypedDict):
 
 
 def call_model(state: dict, config: RunnableConfig) -> dict:
-    model_name = config.get("configurable", {}).get(
-        "model_name", DEFAULT_MODELS.default_transformation_model
+    model_id = config.get("configurable", {}).get(
+        "model_id", DEFAULT_MODELS.default_transformation_model
     )
     return {
         "output": run_pattern(
             pattern_name=state["pattern"],
-            model_name=model_name,
+            model_id=model_id,
             state=state,
         )
     }
diff --git a/open_notebook/graphs/recursive_toc.py b/open_notebook/graphs/recursive_toc.py
index a9cb795..f52ceae 100644
--- a/open_notebook/graphs/recursive_toc.py
+++ b/open_notebook/graphs/recursive_toc.py
@@ -49,13 +49,13 @@ def chunk_condition(state: TocState) -> Literal["get_chunk", END]:  # type: igno
 
 
 def call_model(state: TocState, config: RunnableConfig) -> dict:
-    model_name = config.get("configurable", {}).get(
-        "model_name", DEFAULT_MODELS.default_transformation_model
+    model_id = config.get("configurable", {}).get(
+        "model_id", DEFAULT_MODELS.default_transformation_model
     )
     return {
         "toc": run_pattern(
             pattern_name="recursive_toc",
-            model_name=model_name,
+            model_id=model_id,
             state=state,
         ).content
     }
diff --git a/open_notebook/graphs/summary.py b/open_notebook/graphs/summary.py
index df54ff5..8cd0ec1 100644
--- a/open_notebook/graphs/summary.py
+++ b/open_notebook/graphs/summary.py
@@ -59,14 +59,14 @@ def chunk_condition(state: SummaryState) -> Literal["get_chunk", END]:  # type:
 
 
 def call_model(state: dict, config: RunnableConfig) -> dict:
-    model_name = config.get("configurable", {}).get(
-        "model_name", DEFAULT_MODELS.default_transformation_model
+    model_id = config.get("configurable", {}).get(
+        "model_id", DEFAULT_MODELS.default_transformation_model
     )
     parser = PydanticOutputParser(pydantic_object=SummaryResponse)
     return {
         "output": run_pattern(
             pattern_name="summarize",
-            model_name=model_name,
+            model_id=model_id,
             state=state,
             parser=parser,
         )
diff --git a/open_notebook/graphs/utils.py b/open_notebook/graphs/utils.py
index f004e7f..cdba57a 100644
--- a/open_notebook/graphs/utils.py
+++ b/open_notebook/graphs/utils.py
@@ -9,36 +9,41 @@ from open_notebook.utils import token_count
 
 def run_pattern(
     pattern_name: str,
-    model_name=None,
+    model_id=None,
     messages=[],
     state: dict = {},
     parser=None,
-    output_fixing_model_name=None,
+    output_fixing_model_id=None,
 ) -> dict:
     system_prompt = Prompter(prompt_template=pattern_name, parser=parser).render(
         data=state
     )
 
     tokens = token_count(str(system_prompt) + str(messages))
-    if tokens > 105_000 and DEFAULT_MODELS.large_context_model:
-        model_name = DEFAULT_MODELS.large_context_model
-        logger.debug(
-            f"Using large context model ({model_name}) because the content has {tokens} tokens"
-        )
-        logger.warning(system_prompt)
-    elif tokens > 105_000 and not DEFAULT_MODELS.large_context_model:
-        logger.critical(
-            f"Content has {tokens} tokens, but no large context model is configured"
-        )
-    elif not model_name:
-        model_name = DEFAULT_MODELS.default_transformation_model
 
-    chain = get_model(model_name, model_type="language")
+    model_id = (
+        DEFAULT_MODELS.large_context_model
+        or DEFAULT_MODELS.default_transformation_model
+        or DEFAULT_MODELS.default_chat_model
+    )
+    if tokens > 105_000:
+        model_id = DEFAULT_MODELS.large_context_model
+        logger.debug(
+            f"Using large context model ({model_id}) because the content has {tokens} tokens"
+        )
+
+    model_id = (
+        model_id
+        or DEFAULT_MODELS.default_transformation_model
+        or DEFAULT_MODELS.default_chat_model
+    )
+
+    chain = get_model(model_id, model_type="language")
     if parser:
         chain = chain | parser
 
-    if output_fixing_model_name and parser:
-        output_fix_model = get_model(output_fixing_model_name, model_type="language")
+    if output_fixing_model_id and parser:
+        output_fix_model = get_model(output_fixing_model_id, model_type="language")
         chain = chain | OutputFixingParser.from_llm(
             parser=parser,
             llm=output_fix_model,