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https://github.com/OpenHands/OpenHands.git
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342302ceef
* simplified get * resolved merge conflicts * removed default param for get * add dood setup * add readme * better build process * multi-stage build * revert makefile * rm entrypoint.sh * adjust ssh box for docker * update readme * update readme * fix hostname * change workspace setting * add workspace_mount_base * fixes for workspace dir * clean up frontend * refactor dockerfile * try download.py * change docker order a bit * remove workspace_dir from frontend settings * fix merge issues * Update opendevin/config.py * remove relpath logic from server * rename workspace_mount_base to workspace_base * remove workspace dir plumbing for now * delint * delint * move workspace base dir * remove refs to workspace_dir * factor out constant * fix local directory usage * dont require dir * fix docs * fix arg parsing for task * implement WORKSPACE_MOUNT_PATH * fix workspace dir * fix ports * fix merge issues * add makefile * revert settingsService * fix string * Add address * Update Dockerfile * Update local_box.py * fix lint * move to port 3000 --------- Co-authored-by: மனோஜ்குமார் பழனிச்சாமி <smartmanoj42857@gmail.com> Co-authored-by: enyst <engel.nyst@gmail.com>
87 lines
2.8 KiB
Markdown
87 lines
2.8 KiB
Markdown
# OpenDevin Server
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This is a WebSocket server that executes tasks using an agent.
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## Install
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Follow the instructions in the base README.md to install dependencies and set up.
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## Start the Server
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```sh
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uvicorn opendevin.server.listen:app --reload --port 3000
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```
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## Test the Server
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You can use `websocat` to test the server: https://github.com/vi/websocat
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```sh
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websocat ws://127.0.0.1:3000/ws
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{"action": "start", "args": {"task": "write a bash script that prints hello"}}
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```
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## Supported Environment Variables
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```sh
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LLM_API_KEY=sk-... # Your OpenAI API Key
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LLM_MODEL=gpt-3.5-turbo-1106 # Default model for the agent to use
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WORKSPACE_BASE=/path/to/your/workspace # Default path to model's workspace
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```
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## API Schema
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There are two types of messages that can be sent to, or received from, the server:
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* Actions
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* Observations
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### Actions
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An action has three parts:
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* `action`: The action to be taken
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* `args`: The arguments for the action
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* `message`: A friendly message that can be put in the chat log
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There are several kinds of actions. Their arguments are listed below.
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This list may grow over time.
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* `initialize` - initializes the agent. Only sent by client.
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* `model` - the name of the model to use
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* `directory` - the path to the workspace
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* `agent_cls` - the class of the agent to use
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* `start` - starts a new development task. Only sent by the client.
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* `task` - the task to start
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* `read` - reads the content of a file.
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* `path` - the path of the file to read
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* `write` - writes the content to a file.
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* `path` - the path of the file to write
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* `content` - the content to write to the file
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* `run` - runs a command.
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* `command` - the command to run
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* `background` - if true, run the command in the background
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* `kill` - kills a background command
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* `id` - the ID of the background command to kill
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* `browse` - opens a web page.
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* `url` - the URL to open
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* `recall` - searches long-term memory
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* `query` - the query to search for
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* `think` - Allows the agent to make a plan, set a goal, or record thoughts
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* `thought` - the thought to record
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* `finish` - agent signals that the task is completed
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### Observations
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An observation has four parts:
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* `observation`: The observation type
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* `content`: A string representing the observed data
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* `extras`: additional structured data
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* `message`: A friendly message that can be put in the chat log
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There are several kinds of observations. Their extras are listed below.
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This list may grow over time.
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* `read` - the content of a file
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* `path` - the path of the file read
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* `browse` - the HTML content of a url
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* `url` - the URL opened
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* `run` - the output of a command
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* `command` - the command run
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* `exit_code` - the exit code of the command
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* `recall` - the result of a search
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* `query` - the query searched for
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* `chat` - a message from the user
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