openai:gpt-5.4 -> google_genai:gemini-3.1-pro-preview

Author: ccurme

src/code-samples/deepagents/content-builder.py

@@ -140,7 +140,7 @@ def load_subagents(config_path: Path) -> list:
 def create_content_writer():
     """Create a content writer agent configured by filesystem files."""
     return create_deep_agent(
-        model="openai:gpt-5.4",
+        model="google_genai:gemini-3.1-pro-preview",
         memory=["./AGENTS.md"],
         skills=["./skills/"],
         tools=[generate_cover, generate_social_image],

src/langsmith/trace-deep-agents.mdx

@@ -103,7 +103,7 @@ def yearly_balance_schedule(
 
 
 agent = create_deep_agent(
-    model="openai:gpt-5.4",
+    model="google_genai:gemini-3.1-pro-preview",
     tools=[compute_compound_interest, yearly_balance_schedule],
     system_prompt=(
         "You are a careful assistant. "
@@ -239,7 +239,7 @@ def yearly_balance_schedule(
 
 
 agent = create_deep_agent(
-    model="openai:gpt-5.4",
+    model="google_genai:gemini-3.1-pro-preview",
     tools=[compute_compound_interest, yearly_balance_schedule],
     system_prompt=(
         "You are a careful assistant. "

src/oss/deepagents/acp.mdx

@@ -59,7 +59,7 @@ from deepagents_acp.server import AgentServerACP
 
 async def main() -> None:
     agent = create_deep_agent(
-        model="openai:gpt-5.4",
+        model="google_genai:gemini-3.1-pro-preview",
         # You can customize your Deep Agent here: set a custom prompt,
         # add your own tools, attach middleware, or compose subagents.
         system_prompt="You are a helpful coding assistant",

src/oss/deepagents/backends.mdx

@@ -43,11 +43,11 @@ Here are a few prebuilt filesystem backends that you can quickly use with your d
 
 | Built-in backend | Description |
 |---|---|
-| [Default](#statebackend-ephemeral) | `agent = create_deep_agent(model="openai:gpt-5.4")` <br></br> Ephemeral in state. The default filesystem backend for an agent is stored in `langgraph` state. Note that this filesystem only persists _for a single thread_. |
-| [Local filesystem persistence](#filesystembackend-local-disk) | `agent = create_deep_agent(model="openai:gpt-5.4", backend=FilesystemBackend(root_dir="/Users/nh/Desktop/"))` <br></br>This gives the deep agent access to your local machine's filesystem. You can specify the root directory that the agent has access to. Note that any provided `root_dir` must be an absolute path. |
-| [Durable store (LangGraph store)](#storebackend-langgraph-store) | `agent = create_deep_agent(model="openai:gpt-5.4", backend=StoreBackend())` <br></br>This gives the agent access to long-term storage that is _persisted across threads_. This is great for storing longer term memories or instructions that are applicable to the agent over multiple executions. |
-| [Sandbox](/oss/deepagents/sandboxes) | `agent = create_deep_agent(model="openai:gpt-5.4", backend=sandbox)` <br></br>Execute code in isolated environments. Sandboxes provide filesystem tools plus the `execute` tool for running shell commands. Choose from Modal, Daytona, Deno, or local VFS. |
-| [Local shell](#localshellbackend-local-shell) | `agent = create_deep_agent(model="openai:gpt-5.4", backend=LocalShellBackend(root_dir=".", env={"PATH": "/usr/bin:/bin"}))` <br></br>Filesystem and shell execution directly on the host. No isolation—use only in controlled development environments. See [security considerations](#localshellbackend-local-shell) below. |
+| [Default](#statebackend-ephemeral) | `agent = create_deep_agent(model="google_genai:gemini-3.1-pro-preview")` <br></br> Ephemeral in state. The default filesystem backend for an agent is stored in `langgraph` state. Note that this filesystem only persists _for a single thread_. |
+| [Local filesystem persistence](#filesystembackend-local-disk) | `agent = create_deep_agent(model="google_genai:gemini-3.1-pro-preview", backend=FilesystemBackend(root_dir="/Users/nh/Desktop/"))` <br></br>This gives the deep agent access to your local machine's filesystem. You can specify the root directory that the agent has access to. Note that any provided `root_dir` must be an absolute path. |
+| [Durable store (LangGraph store)](#storebackend-langgraph-store) | `agent = create_deep_agent(model="google_genai:gemini-3.1-pro-preview", backend=StoreBackend())` <br></br>This gives the agent access to long-term storage that is _persisted across threads_. This is great for storing longer term memories or instructions that are applicable to the agent over multiple executions. |
+| [Sandbox](/oss/deepagents/sandboxes) | `agent = create_deep_agent(model="google_genai:gemini-3.1-pro-preview", backend=sandbox)` <br></br>Execute code in isolated environments. Sandboxes provide filesystem tools plus the `execute` tool for running shell commands. Choose from Modal, Daytona, Deno, or local VFS. |
+| [Local shell](#localshellbackend-local-shell) | `agent = create_deep_agent(model="google_genai:gemini-3.1-pro-preview", backend=LocalShellBackend(root_dir=".", env={"PATH": "/usr/bin:/bin"}))` <br></br>Filesystem and shell execution directly on the host. No isolation—use only in controlled development environments. See [security considerations](#localshellbackend-local-shell) below. |
 | [Composite](#compositebackend-router) | Ephemeral by default, `/memories/` persisted. The Composite backend is maximally flexible. You can specify different routes in the filesystem to point towards different backends. See Composite routing below for a ready-to-paste example. |
 
 
@@ -369,7 +369,7 @@ from deepagents import create_deep_agent
 from deepagents.backends import CompositeBackend, StateBackend, FilesystemBackend
 
 agent = create_deep_agent(
-    model="openai:gpt-5.4",
+    model="google_genai:gemini-3.1-pro-preview",
     backend=CompositeBackend(
         default=StateBackend(),
         routes={
@@ -555,7 +555,7 @@ Use [permissions](/oss/deepagents/permissions) to declaratively control which fi
 from deepagents import create_deep_agent, FilesystemPermission
 
 agent = create_deep_agent(
-    model="openai:gpt-5.4",
+    model="google_genai:gemini-3.1-pro-preview",
     backend=CompositeBackend(
         default=StateBackend(),
         routes={
@@ -828,7 +828,7 @@ from deepagents import create_deep_agent
 from deepagents.backends import CompositeBackend, StateBackend, StoreBackend
 
 agent = create_deep_agent(
-    model="openai:gpt-5.4",
+    model="google_genai:gemini-3.1-pro-preview",
     backend=lambda rt: CompositeBackend(
         default=StateBackend(rt),
         routes={"/memories/": StoreBackend(rt, namespace=lambda rt: (rt.server_info.user.identity,))},
@@ -837,7 +837,7 @@ agent = create_deep_agent(
 
 # After
 agent = create_deep_agent(
-    model="openai:gpt-5.4",
+    model="google_genai:gemini-3.1-pro-preview",
     backend=CompositeBackend(
         default=StateBackend(),
         routes={"/memories/": StoreBackend(namespace=lambda rt: (rt.server_info.user.identity,))},

src/oss/deepagents/customization.mdx

@@ -177,7 +177,7 @@ def internet_search(
     )
 
 agent = create_deep_agent(
-    model="openai:gpt-5.4",
+    model="google_genai:gemini-3.1-pro-preview",
     tools=[internet_search]
 )
 ```
@@ -248,7 +248,7 @@ thorough research, and then write a polished report. \
 """
 
 agent = create_deep_agent(
-    model="openai:gpt-5.4",
+    model="google_genai:gemini-3.1-pro-preview",
     system_prompt=research_instructions,
 )
 ```
@@ -343,7 +343,7 @@ def log_tool_calls(request, handler):
 
 
 agent = create_deep_agent(
-    model="openai:gpt-5.4",
+    model="google_genai:gemini-3.1-pro-preview",
     tools=[get_weather],
     middleware=[log_tool_calls],
 )
@@ -644,7 +644,7 @@ You can pass one or more file paths to the `memory` parameter when creating your
         checkpointer = MemorySaver()
 
         agent = create_deep_agent(
-            model="openai:gpt-5.4",
+            model="google_genai:gemini-3.1-pro-preview",
             memory=[
                 "/AGENTS.md"
             ],
@@ -688,7 +688,7 @@ You can pass one or more file paths to the `memory` parameter when creating your
         )
 
         agent = create_deep_agent(
-            model="openai:gpt-5.4",
+            model="google_genai:gemini-3.1-pro-preview",
             backend=StoreBackend(),
             store=store,
             memory=[
@@ -720,7 +720,7 @@ You can pass one or more file paths to the `memory` parameter when creating your
         checkpointer = MemorySaver()
 
         agent = create_deep_agent(
-            model="openai:gpt-5.4",
+            model="google_genai:gemini-3.1-pro-preview",
             backend=FilesystemBackend(root_dir="/Users/user/{project}"),
             memory=[
                 "./AGENTS.md"
@@ -912,7 +912,7 @@ class WeatherReport(BaseModel):
 
 
 agent = create_deep_agent(
-    model="openai:gpt-5.4",
+    model="google_genai:gemini-3.1-pro-preview",
     response_format=WeatherReport,
     tools=[internet_search]
 )

src/oss/deepagents/frontend/overview.mdx

@@ -45,7 +45,7 @@ graph LR
 from deepagents import create_deep_agent
 
 agent = create_deep_agent(
-    model="openai:gpt-5.4",
+    model="google_genai:gemini-3.1-pro-preview",
     tools=[get_weather],
     system_prompt="You are a helpful assistant",
     subagents=[

src/oss/deepagents/going-to-production.mdx

@@ -213,7 +213,7 @@ from deepagents import create_deep_agent
 from deepagents.backends import CompositeBackend, StateBackend, StoreBackend
 
 agent = create_deep_agent(
-    model="openai:gpt-5.4",
+    model="google_genai:gemini-3.1-pro-preview",
     backend=CompositeBackend(
         default=StateBackend(),
         routes={
@@ -269,7 +269,7 @@ from deepagents import create_deep_agent
 from deepagents.backends import CompositeBackend, StateBackend, StoreBackend
 
 agent = create_deep_agent(
-    model="openai:gpt-5.4",
+    model="google_genai:gemini-3.1-pro-preview",
     backend=CompositeBackend(
         default=StateBackend(),
         routes={
@@ -311,7 +311,7 @@ from deepagents import create_deep_agent
 from deepagents.backends import CompositeBackend, StateBackend, StoreBackend
 
 agent = create_deep_agent(
-    model="openai:gpt-5.4",
+    model="google_genai:gemini-3.1-pro-preview",
     backend=CompositeBackend(
         default=StateBackend(),
         routes={
@@ -351,7 +351,7 @@ from deepagents import create_deep_agent
 from deepagents.backends import CompositeBackend, StateBackend, StoreBackend
 
 agent = create_deep_agent(
-    model="openai:gpt-5.4",
+    model="google_genai:gemini-3.1-pro-preview",
     backend=CompositeBackend(
         default=StateBackend(),
         routes={
@@ -451,7 +451,7 @@ async def agent(config: RunnableConfig):
                 auto_delete_interval=3600,  # TTL: clean up when idle
             )
         )
-    return create_deep_agent(model="openai:gpt-5.4", backend=DaytonaSandbox(sandbox=sandbox))
+    return create_deep_agent(model="google_genai:gemini-3.1-pro-preview", backend=DaytonaSandbox(sandbox=sandbox))
 ```
 :::
 
@@ -502,7 +502,7 @@ async def agent(config: RunnableConfig):
         sandbox = await client.create(
             CreateSandboxFromSnapshotParams(labels={"assistant_id": assistant_id})
         )
-    return create_deep_agent(model="openai:gpt-5.4", backend=DaytonaSandbox(sandbox=sandbox))
+    return create_deep_agent(model="google_genai:gemini-3.1-pro-preview", backend=DaytonaSandbox(sandbox=sandbox))
 ```
 :::
 
@@ -759,7 +759,7 @@ backend = CompositeBackend(
 )
 
 agent = create_deep_agent(
-    model="openai:gpt-5.4",
+    model="google_genai:gemini-3.1-pro-preview",
     backend=backend,
     middleware=[SandboxSyncMiddleware(backend)],
 )

src/oss/deepagents/human-in-the-loop.mdx

@@ -328,7 +328,7 @@ Each subagent can have its own `interrupt_on` configuration that overrides the m
 :::python
 ```python
 agent = create_deep_agent(
-    model="openai:gpt-5.4",
+    model="google_genai:gemini-3.1-pro-preview",
     tools=[delete_file, read_file],
     interrupt_on={
         "delete_file": True,
@@ -424,7 +424,7 @@ def main():
     )
 
     parent_agent = create_deep_agent(
-        model="openai:gpt-5.4",
+        model="google_genai:gemini-3.1-pro-preview",
         checkpointer=checkpointer,
         subagents=[
             CompiledSubAgent(
@@ -648,7 +648,7 @@ from langgraph.checkpoint.memory import MemorySaver
 
 checkpointer = MemorySaver()
 agent = create_deep_agent(
-    model="openai:gpt-5.4",
+    model="google_genai:gemini-3.1-pro-preview",
     tools=[...],
     interrupt_on={...},
     checkpointer=checkpointer  # Required for HITL

src/oss/deepagents/memory.mdx

@@ -45,7 +45,7 @@ from deepagents import create_deep_agent
 from deepagents.backends import CompositeBackend, StateBackend, StoreBackend
 
 agent = create_deep_agent(
-    model="openai:gpt-5.4",
+    model="google_genai:gemini-3.1-pro-preview",
     memory=["/memories/AGENTS.md"],
     skills=["/skills/"],
     backend=CompositeBackend(
@@ -130,7 +130,7 @@ Use the fetch_url tool to read https://docs.langchain.com/llms.txt, then fetch r
 )
 
 agent = create_deep_agent(
-    model="openai:gpt-5.4",
+    model="google_genai:gemini-3.1-pro-preview",
     memory=["/memories/AGENTS.md"],
     skills=["/skills/"],
     backend=lambda rt: CompositeBackend(
@@ -241,7 +241,7 @@ from deepagents import create_deep_agent
 from deepagents.backends import CompositeBackend, StateBackend, StoreBackend
 
 agent = create_deep_agent(
-    model="openai:gpt-5.4",
+    model="google_genai:gemini-3.1-pro-preview",
     memory=["/memories/preferences.md"],
     skills=["/skills/"],
     backend=CompositeBackend(
@@ -331,7 +331,7 @@ Use the fetch_url tool to read https://docs.langchain.com/llms.txt, then fetch r
 )
 
 agent = create_deep_agent(
-    model="openai:gpt-5.4",
+    model="google_genai:gemini-3.1-pro-preview",
     memory=["/memories/preferences.md"],
     skills=["/skills/"],
     backend=lambda rt: CompositeBackend(
@@ -552,7 +552,7 @@ from deepagents import create_deep_agent
 from deepagents.backends import CompositeBackend, StateBackend, StoreBackend
 
 agent = create_deep_agent(
-    model="openai:gpt-5.4",
+    model="google_genai:gemini-3.1-pro-preview",
     memory=[
         "/memories/preferences.md",
         "/policies/compliance.md",

src/oss/deepagents/overview.mdx

@@ -37,7 +37,7 @@ def get_weather(city: str) -> str:
     return f"It's always sunny in {city}!"
 
 agent = create_deep_agent(
-    model="openai:gpt-5.4",
+    model="google_genai:gemini-3.1-pro-preview",
     tools=[get_weather],
     system_prompt="You are a helpful assistant",
 )