OpenHands · mamoodi · Mar 11, 2026 · Mar 11, 2026
diff --git a/llms-full.txt b/llms-full.txt
@@ -24610,7 +24610,7 @@ Source: https://docs.openhands.dev/openhands/usage/cli/installation.md
     docker run -it \
         --pull=always \
         -e AGENT_SERVER_IMAGE_REPOSITORY=ghcr.io/openhands/agent-server \
-        -e AGENT_SERVER_IMAGE_TAG=1.11.4-python \
+        -e AGENT_SERVER_IMAGE_TAG=1.12.0-python \
         -e SANDBOX_USER_ID=$(id -u) \
         -e SANDBOX_VOLUMES=$SANDBOX_VOLUMES \
         -v /var/run/docker.sock:/var/run/docker.sock \
@@ -26708,7 +26708,7 @@ These variables correspond to the `[sandbox]` section in `config.toml`:
 | `SANDBOX_BROWSERGYM_EVAL_ENV` | string | `""` | BrowserGym evaluation environment |
 | `SANDBOX_VOLUMES` | string | `""` | Volume mounts (replaces deprecated workspace settings) |
 | `AGENT_SERVER_IMAGE_REPOSITORY` | string | `""` | Runtime container image repository (e.g., `ghcr.io/openhands/agent-server`) |
-| `AGENT_SERVER_IMAGE_TAG` | string | `""` | Runtime container image tag (e.g., `1.11.4-python`) |
+| `AGENT_SERVER_IMAGE_TAG` | string | `""` | Runtime container image tag (e.g., `1.12.0-python`) |
 | `SANDBOX_KEEP_RUNTIME_ALIVE` | boolean | `false` | Keep runtime alive after session ends |
 | `SANDBOX_PAUSE_CLOSED_RUNTIMES` | boolean | `false` | Pause instead of stopping closed runtimes |
 | `SANDBOX_CLOSE_DELAY` | integer | `300` | Delay before closing idle runtimes (seconds) |
@@ -28967,20 +28967,20 @@ Download and install the LM Studio desktop app from [lmstudio.ai](https://lmstud
 ```bash
 docker run -it --rm --pull=always \
     -e AGENT_SERVER_IMAGE_REPOSITORY=ghcr.io/openhands/agent-server \
-    -e AGENT_SERVER_IMAGE_TAG=1.11.4-python \
+    -e AGENT_SERVER_IMAGE_TAG=1.12.0-python \
     -e LOG_ALL_EVENTS=true \
     -v /var/run/docker.sock:/var/run/docker.sock \
     -v ~/.openhands:/.openhands \
     -p 3000:3000 \
     --add-host host.docker.internal:host-gateway \
     --name openhands-app \
-    docker.openhands.dev/openhands/openhands:1.4
+    docker.openhands.dev/openhands/openhands:1.5
 ```
 
 2. Wait until the server is running (see log below):
 ```
 Digest: sha256:e72f9baecb458aedb9afc2cd5bc935118d1868719e55d50da73190d3a85c674f
-Status: Image is up to date for docker.openhands.dev/openhands/openhands:1.4
+Status: Image is up to date for docker.openhands.dev/openhands/openhands:1.5
 Starting OpenHands...
 Running OpenHands as root
 14:22:13 - openhands:INFO: server_config.py:50 - Using config class None
@@ -29560,14 +29560,14 @@ Note that you'll still need `uv` installed for the default MCP servers to work p
 ```bash
 docker run -it --rm --pull=always \
   -e AGENT_SERVER_IMAGE_REPOSITORY=ghcr.io/openhands/agent-server \
-  -e AGENT_SERVER_IMAGE_TAG=1.11.4-python \
+  -e AGENT_SERVER_IMAGE_TAG=1.12.0-python \
   -e LOG_ALL_EVENTS=true \
   -v /var/run/docker.sock:/var/run/docker.sock \
   -v ~/.openhands:/.openhands \
   -p 3000:3000 \
   --add-host host.docker.internal:host-gateway \
   --name openhands-app \
-    docker.openhands.dev/openhands/openhands:1.4
+    docker.openhands.dev/openhands/openhands:1.5
 ```
 
 </Accordion>
@@ -30518,7 +30518,7 @@ To fix this:
    docker run -it --rm \
        -e SANDBOX_VSCODE_PORT=41234 \
        -e AGENT_SERVER_IMAGE_REPOSITORY=ghcr.io/openhands/agent-server \
-       -e AGENT_SERVER_IMAGE_TAG=1.11.4-python \
+       -e AGENT_SERVER_IMAGE_TAG=1.12.0-python \
        -v /var/run/docker.sock:/var/run/docker.sock \
        -v ~/.openhands:/.openhands \
        -p 3000:3000 \

@@ -71,7 +71,7 @@ description: Install the OpenHands CLI on your system
     docker run -it \
         --pull=always \
         -e AGENT_SERVER_IMAGE_REPOSITORY=ghcr.io/openhands/agent-server \
-        -e AGENT_SERVER_IMAGE_TAG=1.11.4-python \
+        -e AGENT_SERVER_IMAGE_TAG=1.12.0-python \
         -e SANDBOX_USER_ID=$(id -u) \
         -e SANDBOX_VOLUMES=$SANDBOX_VOLUMES \
         -v /var/run/docker.sock:/var/run/docker.sock \

@@ -36,7 +36,7 @@
 | `RUNTIME` | string | `"docker"` | Runtime environment (`docker`, `local`, `cli`, etc.) |
 | `DEFAULT_AGENT` | string | `"CodeActAgent"` | Default agent class to use |
 | `JWT_SECRET` | string | auto-generated | JWT secret for authentication |
 | `RUN_AS_OPENHANDS` | boolean | `true` | Whether to run as the openhands user |
 | `VOLUMES` | string | `""` | Volume mounts in format `host:container[:mode]` |

 ## LLM Configuration Variables
@@ -58,12 +58,12 @@
 | `LLM_NUM_RETRIES` | integer | `8` | Number of retry attempts |
 | `LLM_RETRY_MIN_WAIT` | integer | `15` | Minimum wait time between retries (seconds) |
 | `LLM_RETRY_MAX_WAIT` | integer | `120` | Maximum wait time between retries (seconds) |
 | `LLM_RETRY_MULTIPLIER` | float | `2.0` | Exponential backoff multiplier |
 | `LLM_DROP_PARAMS` | boolean | `false` | Drop unsupported parameters without error |
 | `LLM_CACHING_PROMPT` | boolean | `true` | Enable prompt caching if supported |
 | `LLM_DISABLE_VISION` | boolean | `false` | Disable vision capabilities for cost reduction |
 | `LLM_CUSTOM_LLM_PROVIDER` | string | `""` | Custom LLM provider name |
 | `LLM_OLLAMA_BASE_URL` | string | `""` | Base URL for Ollama API |
 | `LLM_INPUT_COST_PER_TOKEN` | float | `0.0` | Cost per input token |
 | `LLM_OUTPUT_COST_PER_TOKEN` | float | `0.0` | Cost per output token |
 | `LLM_REASONING_EFFORT` | string | `""` | Reasoning effort for o-series models (`low`, `medium`, `high`) |
@@ -87,7 +87,7 @@
 | `AGENT_ENABLE_LLM_EDITOR` | boolean | `false` | Enable LLM-based editor |
 | `AGENT_ENABLE_JUPYTER` | boolean | `false` | Enable Jupyter integration |
 | `AGENT_ENABLE_HISTORY_TRUNCATION` | boolean | `true` | Enable history truncation |
 | `AGENT_ENABLE_PROMPT_EXTENSIONS` | boolean | `true` | Enable skills (formerly known as microagents) (prompt extensions) |
 | `AGENT_DISABLED_MICROAGENTS` | list | `[]` | List of skills to disable |

 ## Sandbox Configuration Variables
@@ -108,10 +108,10 @@
 | `SANDBOX_BROWSERGYM_EVAL_ENV` | string | `""` | BrowserGym evaluation environment |
 | `SANDBOX_VOLUMES` | string | `""` | Volume mounts (replaces deprecated workspace settings) |
 | `AGENT_SERVER_IMAGE_REPOSITORY` | string | `""` | Runtime container image repository (e.g., `ghcr.io/openhands/agent-server`) |
-| `AGENT_SERVER_IMAGE_TAG` | string | `""` | Runtime container image tag (e.g., `1.11.4-python`) |
+| `AGENT_SERVER_IMAGE_TAG` | string | `""` | Runtime container image tag (e.g., `1.12.0-python`) |
 | `SANDBOX_KEEP_RUNTIME_ALIVE` | boolean | `false` | Keep runtime alive after session ends |
 | `SANDBOX_PAUSE_CLOSED_RUNTIMES` | boolean | `false` | Pause instead of stopping closed runtimes |
 | `SANDBOX_CLOSE_DELAY` | integer | `300` | Delay before closing idle runtimes (seconds) |
 | `SANDBOX_RM_ALL_CONTAINERS` | boolean | `false` | Remove all containers when stopping |
 | `SANDBOX_ENABLE_GPU` | boolean | `false` | Enable GPU support |
 | `SANDBOX_CUDA_VISIBLE_DEVICES` | string | `""` | Specify GPU devices by ID |
@@ -178,7 +178,7 @@
 | `ANTHROPIC_API_KEY` | string | `""` | Anthropic API key |
 | `GOOGLE_API_KEY` | string | `""` | Google API key |
 | `AZURE_API_KEY` | string | `""` | Azure API key |
 | `TAVILY_API_KEY` | string | `""` | Tavily search API key |

 ## Server Configuration Variables


@@ -1,6 +1,6 @@
 ---
 title: Local LLMs
 description: When using a Local LLM, OpenHands may have limited functionality. It is highly recommended that you use GPUs to serve local models for optimal experience.
 ---

 ## News
@@ -32,7 +32,7 @@

 ![image](./screenshots/01_lm_studio_open_model_hub.png)

 3. Search for **"Qwen3-Coder-30B-A3B-Instruct"**, confirm you're downloading from the official Qwen publisher, then proceed to download.

 ![image](./screenshots/02_lm_studio_download_devstral.png)

@@ -50,7 +50,7 @@

 ![image](./screenshots/04_lm_studio_setup_devstral_part_1.png)

 5. Enable the "Show advanced settings" switch at the bottom of the Model settings flyout to show all the available settings.
 6. Set "Context Length" to at least 22000 (for lower VRAM systems) or 32768 (recommended for better performance) and enable Flash Attention.
 7. Click "Load Model" to start loading the model.

@@ -70,20 +70,20 @@
 ```bash
 docker run -it --rm --pull=always \
     -e AGENT_SERVER_IMAGE_REPOSITORY=ghcr.io/openhands/agent-server \
-    -e AGENT_SERVER_IMAGE_TAG=1.11.4-python \
+    -e AGENT_SERVER_IMAGE_TAG=1.12.0-python \
     -e LOG_ALL_EVENTS=true \
     -v /var/run/docker.sock:/var/run/docker.sock \
     -v ~/.openhands:/.openhands \
     -p 3000:3000 \
     --add-host host.docker.internal:host-gateway \
     --name openhands-app \
-    docker.openhands.dev/openhands/openhands:1.4
+    docker.openhands.dev/openhands/openhands:1.5
 ```
 
 2. Wait until the server is running (see log below):
 ```
 Digest: sha256:e72f9baecb458aedb9afc2cd5bc935118d1868719e55d50da73190d3a85c674f
-Status: Image is up to date for docker.openhands.dev/openhands/openhands:1.4
+Status: Image is up to date for docker.openhands.dev/openhands/openhands:1.5
 Starting OpenHands...
 Running OpenHands as root
 14:22:13 - openhands:INFO: server_config.py:50 - Using config class None
@@ -122,11 +122,11 @@

 ## Advanced: Alternative LLM Backends

 This section describes how to run local LLMs with OpenHands using alternative backends like Ollama, SGLang, or vLLM — without relying on LM Studio.

 ### Create an OpenAI-Compatible Endpoint with Ollama

 - Install Ollama following [the official documentation](https://ollama.com/download).
 - Example launch command for Qwen3-Coder-30B-A3B-Instruct:

 ```bash
@@ -137,7 +137,7 @@
 ollama pull qwen3-coder:30b
 ```

 ### Create an OpenAI-Compatible Endpoint with vLLM or SGLang

 First, download the model checkpoint:

@@ -145,10 +145,10 @@
 huggingface-cli download Qwen/Qwen3-Coder-30B-A3B-Instruct --local-dir Qwen/Qwen3-Coder-30B-A3B-Instruct
 ```

 #### Serving the model using SGLang

 - Install SGLang following [the official documentation](https://docs.sglang.io/get_started/install.html).
 - Example launch command (with at least 2 GPUs):

 ```bash
 SGLANG_ALLOW_OVERWRITE_LONGER_CONTEXT_LEN=1 python3 -m sglang.launch_server \
@@ -163,7 +163,7 @@
 #### Serving the model using vLLM

 - Install vLLM following [the official documentation](https://docs.vllm.ai/en/latest/getting_started/installation.html).
 - Example launch command (with at least 2 GPUs):

 ```bash
 vllm serve Qwen/Qwen3-Coder-30B-A3B-Instruct \
@@ -215,10 +215,10 @@
 2. Enable the **Advanced** toggle at the top of the page.
 3. Set the following parameters, if you followed the examples above:
   - **Custom Model**: `openai/<served-model-name>`
     - For **Ollama**: `openai/qwen3-coder:30b`
     - For **SGLang/vLLM**: `openai/Qwen3-Coder-30B-A3B-Instruct`
   - **Base URL**: `http://host.docker.internal:<port>/v1`
     Use port `11434` for Ollama, or `8000` for SGLang and vLLM.
   - **API Key**:
     - For **Ollama**: any placeholder value (e.g. `dummy`, `local-llm`)
     - For **SGLang** or **vLLM**: use the same key provided when starting the server (e.g. `mykey`)
@@ -71,11 +71,11 @@

 ### Start the App

 #### Option 1: Using the CLI Launcher with uv (Recommended)

 We recommend using [uv](https://docs.astral.sh/uv/) for the best OpenHands experience. uv provides better isolation from your current project's virtual environment and is required for OpenHands' default MCP servers (like the [fetch MCP server](https://github.com/modelcontextprotocol/servers/tree/main/src/fetch)).

 **Install uv** (if you haven't already):

 See the [uv installation guide](https://docs.astral.sh/uv/getting-started/installation/) for the latest installation instructions for your platform.

@@ -126,14 +126,14 @@
 ```bash
 docker run -it --rm --pull=always \
   -e AGENT_SERVER_IMAGE_REPOSITORY=ghcr.io/openhands/agent-server \
-  -e AGENT_SERVER_IMAGE_TAG=1.11.4-python \
+  -e AGENT_SERVER_IMAGE_TAG=1.12.0-python \
   -e LOG_ALL_EVENTS=true \
   -v /var/run/docker.sock:/var/run/docker.sock \
   -v ~/.openhands:/.openhands \
   -p 3000:3000 \
   --add-host host.docker.internal:host-gateway \
   --name openhands-app \
-    docker.openhands.dev/openhands/openhands:1.4
+    docker.openhands.dev/openhands/openhands:1.5
 ```
 
 </Accordion>
@@ -164,7 +164,7 @@
 2. Go to the Settings page and navigate to the `API Keys` tab.
 3. Copy your `LLM API Key`.

 OpenHands provides access to state-of-the-art agentic coding models with competitive pricing. [Learn more about OpenHands LLM provider](/openhands/usage/llms/openhands-llms).

 </Accordion>

@@ -216,8 +216,8 @@

 To enable search functionality in OpenHands:

 1. Get a Tavily API key from [tavily.com](https://tavily.com/).
 2. Enter the Tavily API key in the Settings page under `LLM` tab > `Search API Key (Tavily)`

 For more details, see the [Search Engine Setup](/openhands/usage/advanced/search-engine-setup) guide.


@@ -87,7 +87,7 @@
    docker run -it --rm \
        -e SANDBOX_VSCODE_PORT=41234 \
        -e AGENT_SERVER_IMAGE_REPOSITORY=ghcr.io/openhands/agent-server \
-       -e AGENT_SERVER_IMAGE_TAG=1.11.4-python \
+       -e AGENT_SERVER_IMAGE_TAG=1.12.0-python \
        -v /var/run/docker.sock:/var/run/docker.sock \
        -v ~/.openhands:/.openhands \
        -p 3000:3000 \
@@ -126,7 +126,7 @@
  git remote set-url origin https://github.com/OpenHands/OpenHands.git
  ```
 * Update Docker image references from `ghcr.io/all-hands-ai/` to `ghcr.io/openhands/`
 * Find and update any hardcoded references:
  ```bash
  git grep -i "all-hands-ai"
  git grep -i "ghcr.io/all-hands-ai"