### Setup Agent Instance

Source: https://swe-agent.com/latest/reference/agent

Initializes the agent for a specific problem instance, including directory creation, tool installation, and history population. This method is typically invoked by the run process.

```python
def setup(
    self,
    env: SWEEnv,
    problem_statement: ProblemStatement | ProblemStatementConfig,
    output_dir: Path = Path("."),
) -> None:
    """Setup the agent for a new instance. This includes
    formatting the system message and adding demonstrations to the history.

    This method is called by `self.run`.
    """
    output_dir.mkdir(parents=True, exist_ok=True)

    # apply template configuration to multimodal problem statements
    if hasattr(problem_statement, "type") and problem_statement.type == "swe_bench_multimodal":
        from sweagent.agent.problem_statement import SWEBenchMultimodalProblemStatement

        if isinstance(problem_statement, SWEBenchMultimodalProblemStatement):
            # apply the global disable_image_processing setting if it's not explicitly set
            if not problem_statement.disable_image_processing and self.templates.disable_image_processing:
                problem_statement.disable_image_processing = True

    self._problem_statement = problem_statement
    self._env = env
    iid = self._problem_statement.id
    self.logger.info("Setting up agent for instance %s", iid)

    # Save/reset some attributes
    self.traj_path = output_dir / (self._problem_statement.id + ".traj")
    self.logger.info("Trajectory will be saved to %s", self.traj_path)

    self._chook.on_tools_installation_started()
    self.tools.install(self._env)
    self._chook.on_setup_attempt()
    self.info = AgentInfo()
    self.info["swe_agent_hash"] = get_agent_commit_hash()
    self.info["swe_agent_version"] = __version__
    self.info["swe_rex_version"] = get_rex_version()
    self.info["swe_rex_hash"] = get_rex_commit_hash()
    assert self._env is not None
    assert self._problem_statement is not None
    self._env.set_env_variables({"PROBLEM_STATEMENT": self._problem_statement.get_problem_statement_for_env()})
    self.add_system_message_to_history()
    self.add_demonstrations_to_history()
    self.add_instance_template_to_history(state=self.tools.get_state(self._env))
    self._chook.on_setup_done()
```

--------------------------------

### Example Tool Configuration (filemap)

Source: https://swe-agent.com/latest/config/tools

An example configuration for a 'filemap' tool. It defines the tool's signature, a docstring explaining its purpose, and its required arguments.

```yaml
tools:
  filemap:
    signature: "filemap <file_path>"
    docstring: "Print the contents of a Python file, skipping lengthy function and method definitions."
    arguments:
      - name: file_path
        type: string
        description: The path to the file to be read
        required: true

```

--------------------------------

### Start Environment

Source: https://swe-agent.com/latest/reference/env

Initializes the deployment, resets the environment, and executes post-startup commands.

```python
start() -> None
```

```python
def start(self) -> None:
    """Start the environment and reset it to a clean state."""
    self._init_deployment()
    self.reset()
    for command in self._post_startup_commands:
        self.communicate(command, check="raise", timeout=self.post_startup_command_timeout)
```

--------------------------------

### SWEEnv.start

Source: https://swe-agent.com/latest/reference/env

Starts the environment and resets it to a clean state, executing any configured post-startup commands.

```APIDOC
## SWEEnv.start

### Description
Starts the environment and resets it to a clean state, then executes post-startup commands.
```

--------------------------------

### Test Docker Installation

Source: https://swe-agent.com/latest/installation/tips

Run this command to verify if Docker is installed and functioning correctly.

```bash
docker run hello-world

```

--------------------------------

### Set Installation Timeout

Source: https://swe-agent.com/latest/reference/tools_config

Sets the timeout in seconds for each installation command.

```python
install_timeout: int = 300
```

--------------------------------

### SWEEnv.from_config

Source: https://swe-agent.com/latest/reference/env

Creates an environment instance from a configuration object, which is the recommended approach for standard setups.

```APIDOC
## SWEEnv.from_config

### Description
Creates an environment instance from a configuration object.

### Parameters
- **config** (EnvironmentConfig) - Required - Configuration object used to initialize the environment.
```

--------------------------------

### Environment configuration file example

Source: https://swe-agent.com/latest/usage/cl_tutorial

Specifies the repository URL for the environment.

```yaml
env:
  repo:
    github_url: https://github.com/SWE-agent/test-repo
```

--------------------------------

### Open setup.py for inspection

Source: https://swe-agent.com/latest/usage/trajectories

This action opens the setup.py file to inspect its contents. This is often a precursor to understanding how to install or build the project locally.

```bash
open setup.py

```

--------------------------------

### Install SWE-agent with Development Dependencies

Source: https://swe-agent.com/latest/dev/contribute

Install the repository from source with the `[dev]` option for development purposes. This ensures all necessary tools for development are included.

```bash
pip install -e '.[dev]'
```

--------------------------------

### Define post-startup commands

Source: https://swe-agent.com/latest/reference/env_config

Commands to execute in the agent shell after setup. Each command is provided as a string.

```python
post_startup_commands: list[str] = []
```

--------------------------------

### Custom Dockerfile for SWE-agent

Source: https://swe-agent.com/latest/config/environments

Define a custom Docker environment for SWE-agent. This example installs Python 3.11, swe-rex for faster startup, and flake8. Ensure to build this Dockerfile and specify the image when running the agent.

```docker
FROM python:3.11.10-bullseye  

ARG DEBIAN_FRONTEND=noninteractive  
ENV TZ=Etc/UTC

WORKDIR /

# Install swe-rex for faster startup
RUN pip install pipx
RUN pipx install swe-rex
RUN pipx ensurepath
ENV PATH="$PATH:/root/.local/bin/"

# Install any extra dependencies
RUN pip install flake8

SHELL ["/bin/bash", "-c"]
```

--------------------------------

### Example Tool Structure

Source: https://swe-agent.com/latest/usage/adding_custom_tools

Illustrates the basic directory structure for a SWE-agent tool bundle, including configuration and executable scripts.

```text
tools/submit/
├── config.yaml
└── bin/
    └── submit

```

--------------------------------

### Agent configuration file example

Source: https://swe-agent.com/latest/usage/cl_tutorial

Defines the model name and cost limits for the agent instance.

```yaml
agent:
  model:
    name: gpt-4o
    per_instance_cost_limit: 2.00
```

--------------------------------

### Tool Installation Script

Source: https://swe-agent.com/latest/usage/adding_custom_tools

An optional bash script (`install.sh`) for a tool bundle that installs necessary dependencies, such as Python packages, using pip.

```bash
#!/bin/bash
# This script runs when the tool bundle is installed

# Example: Install Python packages
pip install cowsay
pip install colorama

echo "Morale boost tools installed! Ready to spread joy! 🎉"

```

--------------------------------

### RetryAgent setup Method

Source: https://swe-agent.com/latest/reference/agent

Configures the agent for a new problem instance.

```python
setup(env: SWEEnv, problem_statement: ProblemStatement | ProblemStatementConfig, output_dir: Path = Path('.')) -> None
```

```python
def setup(
    self, env: SWEEnv, problem_statement: ProblemStatement | ProblemStatementConfig, output_dir: Path = Path(".")
) -> None:
    """Setup the retry agent for a new problem instance.
    This is mostly a bookkeeping step.
    """
    self._total_instance_attempt_stats = InstanceStats()
    self._problem_statement = problem_statement
    self._traj_path = output_dir / (self._problem_statement.id + ".traj")
    self._env = env
    self._output_dir = output_dir
    self._rloop = get_retry_loop_from_config(self.config.retry_loop, problem_statement=problem_statement)
```

--------------------------------

### Run method implementation

Source: https://swe-agent.com/latest/reference/agent

The full implementation of the run method, which manages the setup, the action-observation loop, and trajectory saving.

```python
def run(
    self,
    env: SWEEnv,
    problem_statement: ProblemStatement | ProblemStatementConfig,
    output_dir: Path = Path("."),
) -> AgentRunResult:
    """Run the agent on a problem instance. This method contains the
    main loop that repeatedly calls `self._step` until the problem is solved.

    Args:
        setup_args: Arguments to pass to the agent's setup method.
        env: The environment to run the agent on.
        traj_dir: Directory to save the trajectory to
    """
    self.setup(env=env, problem_statement=problem_statement, output_dir=output_dir)

    # Run action/observation loop
    self._chook.on_run_start()
    step_output = StepOutput()
    while not step_output.done:
        step_output = self.step()
        self.save_trajectory()
    self._chook.on_run_done(trajectory=self.trajectory, info=self.info)

    self.logger.info("Trajectory saved to %s", self.traj_path)

    # Here we want to return the "global" information (e.g., submission should
    # be the best submission instead of the last one, etc.), so we get it from the traj file
    data = self.get_trajectory_data()
    return AgentRunResult(info=data["info"], trajectory=data["trajectory"])
```

--------------------------------

### Tool Configuration with Arguments

Source: https://swe-agent.com/latest/usage/adding_custom_tools

An example of a tool configuration that includes arguments, specifying their names, types, descriptions, and whether they are required.

```yaml
tools:
  print_animal:
    signature: "print_animal <animal_type> [--size=<size>]"
    docstring: "Prints ASCII art of the specified animal"
    arguments:
      - name: animal_type
        type: string
        description: "Type of animal to print (cat, dog, elephant)"
        required: true
      - name: size
        type: string
        description: "Size of the art (small, medium, large)"
        required: false


```

--------------------------------

### Model Configuration for Vision

Source: https://swe-agent.com/latest/usage/multimodal

Example configuration for a vision-capable model.

```yaml
# model_configs/claude-sonnet-4-20250514_mm.yaml
model:
  name: claude-sonnet-4-20250514
  # Vision capabilities automatically detected
```

--------------------------------

### Install Pdbpp Debugger

Source: https://swe-agent.com/latest/dev/contribute

Install `pdbpp`, an enhanced Python debugger, for improved debugging capabilities.

```bash
pip install pdbpp
```

--------------------------------

### ThoughtActionParser Example

Source: https://swe-agent.com/latest/reference/parsers

Example of the expected model response format for the ThoughtActionParser.

```text
Let's look at the files in the current directory.

Action:
 ```
ls -l
 ```
```

--------------------------------

### Install Marshmallow Package

Source: https://swe-agent.com/latest/usage/trajectories

Installs the marshmallow package using pip. Ensure you are in a virtual environment for best practices.

```bash
d: pluggy<2.0,>=1.4 in /root/miniconda3/envs/marshmallow-code__marshmallow__3.13/lib/python3.9/site-packages (from pytest) (1.4.0)
Requirement already satisfied: exceptiongroup>=1.0.0rc8 in /root/miniconda3/envs/marshmallow-code__marshmallow__3.13/lib/python3.9/site-packages (from pytest) (1.2.0)
Requirement already satisfied: tomli>=1 in /root/miniconda3/envs/marshmallow-code__marshmallow__3.13/lib/python3.9/site-packages (from pytest) (2.0.1)
Requirement already satisfied: cachetools>=5.3.2 in /root/miniconda3/envs/marshmallow-code__marshmallow__3.13/lib/python3.9/site-packages (from tox) (5.3.3)
Requirement already satisfied: chardet>=5.2 in /root/miniconda3/envs/marshmallow-code__marshmallow__3.13/lib/python3.9/site-packages (from tox) (5.2.0)
Requirement already satisfied: colorama>=0.4.6 in /root/miniconda3/envs/marshmallow-code__marshmallow__3.13/lib/python3.9/site-packages (from tox) (0.4.6)
Requirement already satisfied: filelock>=3.13.1 in /root/miniconda3/envs/marshmallow-code__marshmallow__3.13/lib/python3.9/site-packages (from tox) (3.13.3)
Requirement already satisfied: platformdirs>=4.1 in /root/miniconda3/envs/marshmallow-code__marshmallow__3.13/lib/python3.9/site-packages (from tox) (4.2.0)
Requirement already satisfied: pyproject-api>=1.6.1 in /root/miniconda3/envs/marshmallow-code__marshmallow__3.13/lib/python3.9/site-packages (from tox) (1.6.1)
Requirement already satisfied: setuptools in /root/miniconda3/envs/marshmallow-code__marshmallow__3.13/lib/python3.9/site-packages (from nodeenv>=0.11.1->pre-commit~=2.4) (68.2.2)
Requirement already satisfied: distlib<1,>=0.3.7 in /root/miniconda3/envs/marshmallow-code__marshmallow__3.13/lib/python3.9/site-packages (from virtualenv>=20.10.0->pre-commit~=2.4) (0.3.8)
Checking if build backend supports build_editable: started
Checking if build backend supports build_editable: finished with status 'done'
Building wheels for collected packages: marshmallow
  Building editable for marshmallow (pyproject.toml): started
  Building editable for marshmallow (pyproject.toml): finished with status 'done'
  Created wheel for marshmallow: filename=marshmallow-3.13.0-0.editable-py3-none-any.whl size=4534 sha256=fcca61a41cd2783d4a5b8471ebc48cf886d36f6c66a29cc9b02761fc174a024d
  Stored in directory: /tmp/pip-ephem-wheel-cache-h335xxo8/wheels/4d/da/d4/e230bf0a3f16cad5a83d235ac24a34b55178ddda181cb64dae
Successfully built marshmallow
Installing collected packages: marshmallow
  Attempting uninstall: marshmallow
    Found existing installation: marshmallow 3.13.0
    Uninstalling marshmallow-3.13.0:
      Successfully uninstalled marshmallow-3.13.0
Successfully installed marshmallow-3.13.0
WARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv

```

--------------------------------

### Full Example Trajectory (v0.7.0)

Source: https://swe-agent.com/latest/usage/trajectories

This is a complete example of a trajectory from an older version of SWE-agent (v0.7.0). It illustrates the 'environment', 'trajectory' array, and the structure of individual steps including 'action', 'observation', 'response', 'state', and 'thought'. Note that newer versions may have a different format, particularly regarding the 'query' field.

```json
{
    "environment": "swe_main",
    "trajectory": [
        {
            "action": "ls -F\n",
            "observation": "AUTHORS.rst\nCHANGELOG.rst\nCODE_OF_CONDUCT.md\nCONTRIBUTING.rst\nLICENSE\nMANIFEST.in\nNOTICE\nREADME.rst\nRELEASING.md\nazure-pipelines.yml\ndocs/\nexamples/\nperformance/\npyproject.toml\nsetup.cfg\nsetup.py\nsrc/\ntests/\ntox.ini\n",
            "response": "Let's list out some of the files in the repository to get an idea of the structure and contents. We can use the `ls -F` command to list the files in the current directory.\n```\nls -F\n```",
            "state": "{\"open_file\": \"n/a\", \"working_dir\": \"/marshmallow-code__marshmallow\"}\n",
            "thought": "Let's list out some of the files in the repository to get an idea of the structure and contents. We can use the `ls -F` command to list the files in the current directory.\n"
        },
        {
            "action": "open setup.py\n",

```

--------------------------------

### Install Pre-commit Hooks

Source: https://swe-agent.com/latest/dev/contribute

Set up `pre-commit` to automatically check for formatting and basic syntax errors before each commit. Run this command from the repository root.

```bash
pre-commit install
```

--------------------------------

### EditFormat Parser Example

Source: https://swe-agent.com/latest/reference/parsers

Example of the expected model response format for the EditFormat parser.

```python
import os
os.listdir()
```

--------------------------------

### Verify SWE-agent Installation

Source: https://swe-agent.com/latest/installation/source

Run this command to check if SWE-agent is installed correctly and to view available commands. If 'sweagent' is not found, try 'python -m sweagent'.

```bash
sweagent --help

```

--------------------------------

### Run SWE-agent with post-startup commands

Source: https://swe-agent.com/latest/usage/cl_tutorial

Executes additional commands within the container before the agent starts. Use single quotes to wrap the list syntax to avoid shell interpretation issues.

```bash
sweagent run \
    --agent.model.name=claude-3-7-sonnet-latest \
    --env.post_startup_commands='["pip install flake8"]' \
    ...
```

--------------------------------

### Install SWE-agent with Pip

Source: https://swe-agent.com/latest/installation/source

Install SWE-agent in editable mode using pip from the repository root. It's recommended to use virtual environments for dependency management.

```bash
python -m pip install --upgrade pip && pip install --editable .

```

--------------------------------

### Configure History Processors in YAML

Source: https://swe-agent.com/latest/reference/history_processor_config

Example configuration for setting up history processors within the agent configuration file.

```yaml
agent:
  history_processors:
    - type: last_n_observations
      n: 5
```

--------------------------------

### Clone SWE-agent Repository

Source: https://swe-agent.com/latest/installation/source

Clone the SWE-agent repository to your local machine using Git. This is the first step for source installation.

```bash
git clone https://github.com/SWE-agent/SWE-agent.git

```

--------------------------------

### Web Inspector with Custom Port

Source: https://swe-agent.com/latest/usage/inspector

Starts the web-based inspector on a specified port. Useful if the default port 8000 is already in use.

```bash
sweagent inspector --port 8001
```

--------------------------------

### SWEEnv.__init__

Source: https://swe-agent.com/latest/reference/env

Initializes a new SWEEnv instance with the specified deployment, repository configuration, and startup commands.

```APIDOC
## SWEEnv.__init__

### Description
Initializes the environment where tasks are solved.

### Parameters
- **deployment** (AbstractDeployment) - Required - SWE-ReX deployment instance
- **repo** (Repo | RepoConfig | None) - Required - Repository configuration object
- **post_startup_commands** (list[str]) - Required - Commands to execute before starting the agent
- **post_startup_command_timeout** (int) - Optional - Timeout for startup commands (default: 500)
- **hooks** (list[EnvHook] | None) - Optional - Environment hooks for custom functionality
- **name** (str) - Optional - Name of the environment (default: 'main')
```

--------------------------------

### Serve Documentation Locally

Source: https://swe-agent.com/latest/dev/contribute

Build and serve the project documentation locally using `mkdocs`. Access it via your browser on port 8000.

```bash
# cd repo root
mkdocs serve
```

--------------------------------

### Initialize Repository for Coding Challenge

Source: https://swe-agent.com/latest/usage/coding_challenges

Create a new directory, initialize it as a Git repository, and set up a .gitignore file to exclude binary files. This prepares the environment for SWE-agent.

```bash
mkdir empty
git init
touch main.py
echo "*.pyc" > .gitignore  # to avoid binary files in patches
```

--------------------------------

### Define demonstrations

Source: https://swe-agent.com/latest/reference/template_config

Sets the paths to demonstration files.

```python
demonstrations: list[Path]
```

--------------------------------

### Install Package with Development Dependencies

Source: https://swe-agent.com/latest/usage/trajectories

Install the marshmallow package in editable mode with all development dependencies. This command is useful for setting up the project for local development and testing.

```bash
pip install -e .[dev]
```

--------------------------------

### Build and Run Custom Docker Environment

Source: https://swe-agent.com/latest/config/environments

Instructions for building the custom Docker image and running the SWE-agent with the specified image.

```bash
docker build -f tiny.Dockerfile -t swe-agent-tiny .
sweagent run --env.deployment.image swe-agent-tiny ...
```

--------------------------------

### Run SWE-agent with configuration file

Source: https://swe-agent.com/latest/usage/cl_tutorial

Demonstrates running the agent using a YAML configuration file.

```bash
sweagent run --config my_run.yaml
```

```yaml
agent:
  model:
    name: gpt-4o
    per_instance_cost_limit: 2.00
env:
  repo:
    github_url: https://github.com/SWE-agent/test-repo
problem_statement:
  github_url: https://github.com/SWE-agent/test-repo/issues/1
```

--------------------------------

### Define demonstration_template

Source: https://swe-agent.com/latest/reference/template_config

Sets the demonstration template.

```python
demonstration_template: str | None = None
```

--------------------------------

### Marshmallow setup.py file content

Source: https://swe-agent.com/latest/usage/trajectories

This snippet displays the content of the setup.py file for the Marshmallow project. It includes package metadata, dependencies, and configuration details for distribution.

```python
import re
from setuptools import setup, find_packages

EXTRAS_REQUIRE = {
    "tests": ["pytest", "pytz", "simplejson"],
    "lint": [
        "mypy==0.910",
        "flake8==4.0.1",
        "flake8-bugbear==21.9.2",
        "pre-commit~=2.4",
    ],
    "docs": [
        "sphinx==4.2.0",
        "sphinx-issues==1.2.0",
        "alabaster==0.7.12",
        "sphinx-version-warning==1.1.2",
        "autodocsumm==0.2.7",
    ],
}
EXTRAS_REQUIRE["dev"] = EXTRAS_REQUIRE["tests"] + EXTRAS_REQUIRE["lint"] + ["tox"]

def find_version(fname):
    """Attempts to find the version number in the file names fname.
    Raises RuntimeError if not found.
    """
    version = ""
    with open(fname) as fp:
        reg = re.compile(r'__version__ = [\'"]([^\'"]*)[\'"]')
        for line in fp:
            m = reg.match(line)
            if m:
                version = m.group(1)
                break
    if not version:
        raise RuntimeError("Cannot find version information")
    return version


def read(fname):
    with open(fname) as fp:
        content = fp.read()
    return content


setup(
    name="marshmallow",
    version=find_version("src/marshmallow/__init__.py"),
    description=(
        "A lightweight library for converting complex "
        "datatypes to and from native Python datatypes."
    ),
    long_description=read("README.rst"),
    author="Steven Loria",
    author_email="sloria1@gmail.com",
    url="https://github.com/marshmallow-code/marshmallow",
    packages=find_packages("src", exclude=("test*", "examples")),
    package_dir={"": "src"},
    package_data={"marshmallow": ["py.typed"]},
    include_package_data=True,
    extras_require=EXTRAS_REQUIRE,
    license="MIT",
    zip_safe=False,
    keywords=[
        "serialization",
        "rest",
        "json",
        "api",
        "marshal",
        "marshalling",
        "deserialization",
        "validation",
        "schema",
    ],
    python_requires=">=3.6",
    classifiers=[
        "Development Status :: 5 - Production/Stable",
        "Intended Audience :: Developers",
        "License :: OSI Approved :: MIT License",
        "Programming Language :: Python :: 3",
        "Programming Language :: Python :: 3.6",
        "Programming Language :: Python :: 3.7",
        "Programming Language :: Python :: 3.8",
        "Programming Language :: Python :: 3.9",
        "Programming Language :: Python :: 3.10",
    ],
    test_suite="tests",
    project_urls={
        "Changelog": "https://marshmallow.readthedocs.io/en/latest/changelog.html",
        "Issues": "https://github.com/marshmallow-code/marshmallow/issues",
        "Funding": "https://opencollective.com/marshmallow",
        "Tidelift": "https://tidelift.com/subscription/pkg/pypi-marshmallow?utm_source=pypi-marshmallow&utm_medium=pypi",  # noqa
    },
)

```

--------------------------------

### Perform hard reset of environment

Source: https://swe-agent.com/latest/reference/env

Completely restarts the deployment by closing and starting the environment.

```python
hard_reset()
```

```python
def hard_reset(self):
    """Resets the environment and deployment, i.e., completely restarts the
    deployment.
    """
    self.close()
    self.start()
```

--------------------------------

### Implement get_instance_configs

Source: https://swe-agent.com/latest/reference/batch_instances

Abstract method for retrieving a list of environment configurations.

```python
get_instance_configs() -> list[EnvironmentConfig]
```

--------------------------------

### Get repository reset commands

Source: https://swe-agent.com/latest/reference/repo

Retrieves the git reset commands to be executed after copying or environment reset.

```python
def get_reset_commands(self) -> list[str]:
    """Issued after the copy operation or when the environment is reset."""
    return _get_git_reset_commands(self.base_commit)
```

--------------------------------

### Specify problem statement via CLI

Source: https://swe-agent.com/latest/reference/problem_statements

Examples of using the --problem-statement flag with different input types.

```bash
--problem-statement.text="This is a problem statement"
--problem-statement.type=text
```

```bash
--problem-statement.path=path/to/file.txt
--problem-statement.type=text_file
```

```bash
--problem-statement.url=https://github.com/org/repo/issues/123
--problem-statement.type=github_issue
```

--------------------------------

### Load Instances from File

Source: https://swe-agent.com/latest/usage/batch_mode

Run SWE-agent in batch mode by loading instances from a local file. Supports `.jsonl`, `.json`, and `.yaml` formats. The `instance_id` key is supported for compatibility, though `id` was used previously.

```bash
sweagent run-batch \
    --config config/default.yaml \
    --agent.model.name gpt-4o \
    --instances.type file \
    --instances.path instances.yaml \
    --instances.slice :3 \
    --instances.shuffle=True
```

--------------------------------

### InstancesFromFile get_instance_configs Method

Source: https://swe-agent.com/latest/reference/batch_instances

Retrieves the list of batch instance configurations.

```python
get_instance_configs() -> list[BatchInstance]
```

--------------------------------

### Get trajectory data

Source: https://swe-agent.com/latest/reference/agent

Retrieves the data saved in .traj files, optionally including the best attempt information.

```python
get_trajectory_data(choose: bool) -> dict[str, Any]
```

```python
def get_trajectory_data(self, choose: bool) -> dict[str, Any]:
    """Get all data that we save in .traj files."""
    assert self._rloop is not None

    data = {
        "attempts": self._attempt_data,
    }

    if choose:
        try:
            best_attempt_idx = self._rloop.get_best()
        except TotalCostLimitExceededError:
            raise
        except Exception as e:
            self.logger.critical(f"Error getting best attempt index: {e}. Setting to 0.", exc_info=True)
            best_attempt_idx = 0
        data |= copy.deepcopy(self._attempt_data[best_attempt_idx])  # type: ignore
        data["info"]["best_attempt_idx"] = best_attempt_idx
        data["info"]["rloop_model_stats"] = self._rloop.review_model_stats.model_dump()
        # Overwrite model stats with total stats
        data["info"]["model_stats"] = self._total_instance_stats.model_dump()
        if isinstance(self._rloop, ChooserRetryLoop):
            data["info"]["chooser"] = (
                self._rloop._chooser_output.model_dump() if self._rloop._chooser_output else {}
            )
    return data
```

--------------------------------

### Run SWE-agent with multiple configurations

Source: https://swe-agent.com/latest/usage/cl_tutorial

Execute the agent by chaining multiple configuration files and providing a problem statement text.

```bash
sweagent run --config agent.yaml --config env.yaml \
    --problem_statement.text="Hey, can you fix all the bugs?"
```

--------------------------------

### ExpertInstancesFromFile get_instance_configs method

Source: https://swe-agent.com/latest/reference/batch_instances

Retrieves the list of batch instance configurations.

```python
get_instance_configs() -> list[BatchInstance]

```

--------------------------------

### Configure repository via CLI

Source: https://swe-agent.com/latest/reference/repo

Use these flags with the sweagent run command to specify the repository type and location.

```bash
--env.repo.repo_name="testbed" 
--env.repo.type=preexisting
```

```bash
--env.repo.path=/path/to/repo
--env.repo.type=local
```

--------------------------------

### Initialize SWEEnv

Source: https://swe-agent.com/latest/reference/env

Constructor for the SWEEnv class, defining the environment configuration and initial state.

```python
SWEEnv(*, deployment: AbstractDeployment, repo: Repo | RepoConfig | None, post_startup_commands: list[str], post_startup_command_timeout: int = 500, hooks: list[EnvHook] | None = None, name: str = 'main')
```

```python
def __init__(
    self,
    *,
    deployment: AbstractDeployment,
    repo: Repo | RepoConfig | None,
    post_startup_commands: list[str],
    post_startup_command_timeout: int = 500,
    hooks: list[EnvHook] | None = None,
    name: str = "main",
):
    """This class represents the environment in which we solve the tasks.

    Args:
        deployment: SWE-ReX deployment instance
        repo: Repository configuration object, or anything following the `Repo` protocol
        post_startup_commands: Commands to execute before starting the agent
        hooks: Environment hooks (used to inject custom functionality)
            Equivalent to calling `add_hook` for each hook after initialization.
        name: Name of the environment
    """
    super().__init__()
    self.deployment = deployment
    self.repo = repo
    self._post_startup_commands = post_startup_commands
    self.post_startup_command_timeout = post_startup_command_timeout
    self.logger = get_logger("swea-env", emoji="🪴")
    self.name = name
    self.clean_multi_line_functions = lambda x: x
    self._chook = CombinedEnvHooks()
    for hook in hooks or []:
        self.add_hook(hook)
```

--------------------------------

### Add Instance Template to History

Source: https://swe-agent.com/latest/reference/agent

Adds the instance template or demonstrations to the history, typically used at the start of a new attempt.

```python
def add_instance_template_to_history(self, state: dict[str, str]) -> None:
    """Add observation to history, as well as the instance template or demonstrations if we're
    at the start of a new attempt.
    """
    templates: list[str] = []
    # Determine observation template based on what prior observation was
    assert self.history[-1]["role"] == "system" or self.history[-1].get("is_demo", False)
    # Show instance template if prev. obs. was initial system message
    templates = [self.templates.instance_template]
    if self.templates.strategy_template is not None:
        templates.append(self.templates.strategy_template)

    self._add_templated_messages_to_history(templates, **state)  # type: ignore
```

--------------------------------

### Get model requery history

Source: https://swe-agent.com/latest/reference/agent

Queries the model to correct errors by adding temporary history based on an error template.

```python
def get_model_requery_history(
    self, error_template: str, *, output: str, **kwargs: str | int | float | bool | None
) -> list[dict[str, str]]:
    """Ask the model to correct after a hitting one of the following errors:

    1. Malformatted output (could not parse action)
    2. Blocked action (command is on the blocklist)
    3. Bash command syntax error

    At the time this function is called, the proposed action and observation are not part of the history
    yet.

    This function adds temporary history based on the error template and queries the model.
    If the model is able to correct itself, the records of the mistakes will not be part of the history
    (but they are saved in the trajectory).

    Args:
        error_template: error template
        output: model output
        **kwargs: keyword arguments to be passed to the error template

    Returns:
        model output after requery
    """
    format_dict = {**kwargs, **self._get_format_dict()}
    error_template = Template(error_template).render(**format_dict)

    self.logger.warning(f"{error_template}")

    return self.messages + [
        {"role": "assistant", "content": output, "agent": self.name, "message_type": "assistant"},
        {"role": "user", "content": error_template, "agent": self.name, "message_type": "user"},
    ]
```

--------------------------------

### Convert SimpleBatchInstance to full instance

Source: https://swe-agent.com/latest/reference/batch_instances

Merges deployment options into a SimpleBatchInstance to create a full BatchInstance.

```python
to_full_batch_instance(deployment: DeploymentConfig) -> BatchInstance
```

--------------------------------

### Initialize Repository Configuration

Source: https://swe-agent.com/latest/reference/repo

Creates a RepoConfig object based on a local path, GitHub URL, or existing repository name. Automatically detects the type if set to 'auto'.

```python
def repo_from_simplified_input(
    *, input: str, base_commit: str = "HEAD", type: Literal["local", "github", "preexisting", "auto"] = "auto"
) -> RepoConfig:
    """Get repo config from a simplified input.

    Args:
        input: Local path or GitHub URL
        type: The type of repo. Set to "auto" to automatically detect the type
            (does not work for preexisting repos).
    """
    if type == "local":
        return LocalRepoConfig(path=Path(input), base_commit=base_commit)
    if type == "github":
        return GithubRepoConfig(github_url=input, base_commit=base_commit)
    if type == "preexisting":
        return PreExistingRepoConfig(repo_name=input, base_commit=base_commit)
    if type == "auto":
        if input.startswith("https://github.com/"):
            return GithubRepoConfig(github_url=input, base_commit=base_commit)
        else:
            return LocalRepoConfig(path=Path(input), base_commit=base_commit)
    msg = f"Unknown repo type: {type}"
    raise ValueError(msg)
```

--------------------------------

### Get Trajectory Data

Source: https://swe-agent.com/latest/reference/agent

Retrieves the full trajectory data, including history and environment state, formatted for .traj file storage.

```python
def get_trajectory_data(self) -> dict[str, Any]:
    """Get all data that we save in .traj files."""

    assert self._env is not None
    # The deepcopy here is important because else the
    # data["info"]["model_stats"] update will create havoc!
    attempt_data = copy.deepcopy(
        {
            "trajectory": self.trajectory,
            "history": self.history,
            "info": self.info,
        }
    )
    attempt_data["replay_config"] = self.replay_config.model_dump_json() if self.replay_config is not None else None
    attempt_data["environment"] = self._env.name
    return attempt_data
```

--------------------------------

### Run SWE-agent on Multimodal SWE-bench Issues

Source: https://swe-agent.com/latest/usage/batch_mode

Process a batch of multimodal SWE-bench issues that include images. This requires a specific configuration file and uses a model capable of handling multimodal input. Images are automatically downloaded, converted to base64, and provided as context to the AI.

```bash
sweagent run-batch \
    --config config/default_mm_with_images.yaml \
    --agent.model.name claude-sonnet-4-20250514 \
    --agent.model.per_instance_cost_limit 2.00 \
    --instances.type swe_bench \
    --instances.subset multimodal \
    --instances.split dev  \
    --instances.slice :3 \
    --instances.shuffle=True

```

--------------------------------

### Set Command Documentation

Source: https://swe-agent.com/latest/reference/tools_config

Provides documentation generated from loaded tool bundles.

```python
command_docs: str = None
```

--------------------------------

### Tool Bundle Directory Structure

Source: https://swe-agent.com/latest/config/tools

This is the standard directory structure for a tool bundle in SWE-agent. It includes executables, configuration, installation scripts, and project metadata.

```bash
bundle/
├── bin/
│   └── <tool executable>
│   └── <state executable>
├── config.yaml
├── install.sh
├── README.md
└── pyproject.toml

```

--------------------------------

### Create Tool Directory

Source: https://swe-agent.com/latest/usage/adding_custom_tools

Command to create the necessary directory structure for a new custom tool bundle.

```bash
mkdir -p tools/morale_boost/bin

```

--------------------------------

### Specify Repository via Command Line

Source: https://swe-agent.com/latest/usage/cl_tutorial

Use these flags to define the target repository for the agent using either a GitHub URL or a local file path.

```bash
--env.repo.github_url=https://github.com/SWE-agent/test-repo
--env.repo.path=/path/to/repo
```

--------------------------------

### Example Union Type Error Command

Source: https://swe-agent.com/latest/usage/cl_tutorial

Demonstrates a command execution that triggers a union type error due to conflicting or missing configuration options.

```bash
sweagent run --problem_statement.path="test" --problem_statement.github_url="asdf"
```

--------------------------------

### SWE-agent Patch Application Instructions

Source: https://swe-agent.com/latest/usage/coding_challenges

Instructions on how to inspect and apply a patch file generated by SWE-agent. This includes commands to view the patch content and apply it to a local repository.

```bash
# The patch has been saved to your local filesystem at:
PATCH_FILE_PATH='/Users/fuchur/Documents/24/git_sync/SWE-agent/trajectories/fuchur/azure-gpt4__problem__coding_challenge__t-0.00__p-0
5__c-3.00__install-1/patches/26d111.patch'
# Inspect it:
cat "${PATCH_FILE_PATH}"
# Apply it to a local repository:
cd <your local repo root>
git apply "${PATCH_FILE_PATH}"
```

--------------------------------

### Run agent on problem instance

Source: https://swe-agent.com/latest/reference/agent

Executes the main agent loop to solve a problem instance. This method handles environment setup, step iteration, and trajectory saving.

```python
def run(
    self,
    env: SWEEnv,
    problem_statement: ProblemStatement | ProblemStatementConfig,
    output_dir: Path = Path("."),
) -> AgentRunResult:
    """Run the agent on a problem instance. This method contains the
    main loop that repeatedly calls `self._step` until the problem is solved.

    Args:
        env: The environment to run the agent on.
        problem_statement: The problem statement to run the agent on.
        output_dir: Directory to save the trajectory to
    """
    output_dir.mkdir(parents=True, exist_ok=True)
    self.setup(env=env, problem_statement=problem_statement, output_dir=output_dir)
    assert self._rloop is not None

    # Run action/observation loop
    self._chook.on_run_start()
    step_output = StepOutput()
    self._setup_agent()
    assert self._agent is not None
    while not step_output.done:
        step_output = self.step()
        self.save_trajectory(choose=False)
        if step_output.done:
            self._rloop.on_submit(
                ReviewSubmission(
                    trajectory=self._agent.trajectory,
                    info=self._agent.info,
                    model_stats=self._agent.model.stats,
                )
            )
            if isinstance(self._rloop, ScoreRetryLoop):
                self._agent.info["review"] = self._rloop.reviews[-1].model_dump()  # type: ignore
            self._finalize_agent_run()
            self.save_trajectory(choose=False)
            if self._rloop.retry():
                assert self._env is not None
                self._next_attempt()
                step_output.done = False
    self.save_trajectory(choose=True)  # call again after we finalized
    self._chook.on_run_done(trajectory=self._agent.trajectory, info=self._agent.info)

    self.logger.info("Trajectory saved to %s", self._traj_path)

    # Here we want to return the "global" information (e.g., submission should
    # be the best submission instead of the last one, etc.), so we get it from the traj file
    data = self.get_trajectory_data(choose=True)
    return AgentRunResult(info=data["info"], trajectory=data["trajectory"])
```

--------------------------------

### Load Expert Instances from File

Source: https://swe-agent.com/latest/usage/batch_mode

Run SWE-agent in batch mode using expert-defined instances loaded from a YAML file. This allows for detailed configuration of environment, problem statement, and repository.

```bash
sweagent run-batch \
    ... \
    --instances.type expert_file \
    --instances.path instances.yaml
```

--------------------------------

### Accessing and Setting Registry Variables in Python

Source: https://swe-agent.com/latest/usage/adding_custom_tools

Utilize the `registry` object in Python tools to get values (with fallbacks) and set new values. Data stored in the registry persists between tool invocations.

```python
#!/usr/bin/env python3

from registry import registry

def main():
    # Get a simple value with a fallback
    setting = registry.get("MY_CUSTOM_SETTING", "default value")
    print(f"Setting: {setting}")

    # Get a list of messages
    messages = registry.get("MORALE_MESSAGES", [])
    if messages:
        import random
        message = random.choice(messages)
        print(f"🐱 {message}")

    # Set a value (persists across tool calls)
    registry["LAST_MORALE_BOOST"] = "2024-01-15 10:30:00"

    print("Morale boosted! 🚀")

if __name__ == "__main__":
    main()

```

--------------------------------

### Run SWE-agent on Multiple SWE-bench Issues

Source: https://swe-agent.com/latest/usage/batch_mode

Execute SWE-agent on a batch of SWE-bench issues. This command downloads issues automatically and processes them using specified configurations. Ensure Docker is installed for sandbox execution.

```bash
sweagent run-batch \
    --config config/default.yaml \
    --agent.model.name gpt-4o \
    --agent.model.per_instance_cost_limit 2.00 \
    --instances.type swe_bench \
    --instances.subset lite \
    --instances.split dev  \
    --instances.slice :3 \
    --instances.shuffle=True

```

--------------------------------

### Create Environment from Config

Source: https://swe-agent.com/latest/reference/env

Factory method to instantiate SWEEnv from an EnvironmentConfig object.

```python
from_config(config: EnvironmentConfig) -> Self
```

```python
@classmethod
def from_config(cls, config: EnvironmentConfig) -> Self:
    """Create an environment instance from a configuration object.
    This is the recommended way to create an environment instance, unless you need
    more flexibility.
    """
    # Always copy config to avoid shared state between different instances
    config = config.model_copy(deep=True)
    return cls(
        deployment=get_deployment(config.deployment),
        repo=config.repo,
        post_startup_commands=config.post_startup_commands,
        post_startup_command_timeout=config.post_startup_command_timeout,
        name=config.name,
    )
```

--------------------------------

### Basic Tool Configuration

Source: https://swe-agent.com/latest/usage/adding_custom_tools

Defines a simple tool named 'print_cat' with no arguments, suitable for SWE-agent integration. Includes its signature and a docstring for AI guidance.

```yaml
tools:
  print_cat:
    signature: "print_cat"
    docstring: "Prints an ASCII art cat for morale boost. Use when you need encouragement!"
    arguments: []


```

--------------------------------

### Run Batch with Multimodal Configuration

Source: https://swe-agent.com/latest/usage/multimodal

Execute a batch run using the pre-configured multimodal settings.

```bash
sweagent run-batch \
    --config config/default_mm_with_images.yaml \
    --instances.type swe_bench \
    --instances.subset multimodal \
    --instances.split dev
```

--------------------------------

### Load Instances from Hugging Face

Source: https://swe-agent.com/latest/usage/batch_mode

Utilize SWE-agent in batch mode by loading instances directly from a Hugging Face dataset. Specify the dataset name, split, and slice as needed.

```bash
sweagent run-batch \
    ... \
    --instances.type huggingface \
    --instances.dataset_name "your_username/your_dataset" \
    --instances.split "dev" \
    --instances.slice :3 \
    --instances.shuffle=True
```

--------------------------------

### Configure Fallbacks and Threading

Source: https://swe-agent.com/latest/reference/model_config

Sets up model fallbacks and API key selection logic based on threads.

```python
fallbacks: list[dict[str, Any]] = []

```

```python
choose_api_key_by_thread: bool = True

```

--------------------------------

### Alternative Verification Command

Source: https://swe-agent.com/latest/installation/source

Use this command if the primary 'sweagent --help' command is not found. This can help resolve path issues.

```bash
python -m sweagent

```

--------------------------------

### Define Reset Commands

Source: https://swe-agent.com/latest/reference/tools_config

Lists commands used to reset the environment state upon startup or reset.

```python
reset_commands: list[str | list[str]] = []
```

--------------------------------

### Set post-startup command timeout

Source: https://swe-agent.com/latest/reference/env_config

Defines the timeout in seconds applied individually to each command in post_startup_commands.

```python
post_startup_command_timeout: int = 500
```

--------------------------------

### DefaultAgent.__init__

Source: https://swe-agent.com/latest/reference/agent

Initializes a new instance of the DefaultAgent. The agent handles the behavior of the model and how it interacts with the environment.

```APIDOC
## DefaultAgent.__init__

### Description
Initializes the DefaultAgent with necessary configurations, tools, and model instances.

### Signature
DefaultAgent(*, templates: TemplateConfig, tools: ToolHandler, history_processors: list[HistoryProcessor], model: AbstractModel, max_requeries: int = 3, name: str = 'main', _catch_errors: bool = True, _always_require_zero_exit_code: bool = False, action_sampler_config: ActionSamplerConfig | None = None)
```

--------------------------------

### Create Reproduction Script

Source: https://swe-agent.com/latest/usage/trajectories

Create a new Python file named 'reproduce.py' to house the code for reproducing the issue. This is a preparatory step before adding the specific reproduction logic.

```bash
create reproduce.py
```

--------------------------------

### Update Formatting Configuration Files

Source: https://swe-agent.com/latest/dev/formatting_conflicts

Checkout the latest `.pre-commit-config.yaml` and `pyproject.toml` files from the main branch of the upstream repository. This ensures your local environment uses the new formatting tools.

```bash
git checkout upstream/main -- .pre-commit-config.yaml pyproject.toml
git commit -m "Update formatting instructions" --no-verify

```

--------------------------------

### handle_action

Source: https://swe-agent.com/latest/reference/agent

Runs an action proposed by the agent in the environment and returns the corresponding output.

```APIDOC
## handle_action(step: StepOutput) -> StepOutput

### Description
Runs an action proposed by the agent in the environment and returns the corresponding output.

### Parameters
- **step** (StepOutput) - Required - The step containing the action to run and model output for error handling.

### Returns
- **action_execution_output** (StepOutput) - The result of the action execution.
```

--------------------------------

### Define instance_template

Source: https://swe-agent.com/latest/reference/template_config

Sets the instance prompt template.

```python
instance_template: str = ''
```

--------------------------------

### Convert SWE-bench instances

Source: https://swe-agent.com/latest/reference/batch_instances

Class method to convert SWE-bench dataset instances to SimpleBatchInstance format.

```python
from_swe_bench(instance: dict[str, Any]) -> Self
```

--------------------------------

### Define deployment configuration

Source: https://swe-agent.com/latest/reference/env_config

Specifies the deployment options for the environment.

```python
deployment: DeploymentConfig
```

--------------------------------

### Submit Code

Source: https://swe-agent.com/latest/usage/coding_challenges

Adds all changes, creates a patch file, and prints it. This function assumes a git repository and a patch file named 'test.patch'.

```shell
submit() {
    cd $ROOT
    # Check if the patch file exists and is non-empty
    if
        [ -s "/root/test.patch" ]; then
        # Apply the patch in reverse
        git
        apply -R < "/root/test.patch"
    fi
    git add -A
    git diff --cached > model.patch
    echo
    "<<SUBMISSION||"
    cat model.patch
    echo "||SUBMISSION>>"
}
```