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Make llama stack build not create a new conda by default (#788)

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## What does this PR do?

So far `llama stack build` has always created a separate conda
environment for packaging the dependencies of a distribution. The main
reason to do so is isolation -- distributions are composed of providers
which can have a variety of potentially conflicting dependencies. That
said, this has created significant annoyance for new users since it is
not at all transparent. The fact that `llama stack run` is actually
running the code in some other conda is very surprising.

This PR tries to make things better. 

- Both `llama stack build` and `llama stack run` now accept an
`--image-name` argument which represents the (conda, docker, virtualenv)
image you want to operate upon.
- For the default (conda) mode, the script checks if a current conda
environment exists. If one exists, it uses it.
- If `--image-name` is provided, that option is used. In this case, an
environment is created if needed.
- There is no automatic `llamastack-` prefixing of the environment names
done anymore.


## Test Plan

Start in a conda environment, run `llama stack build --template
fireworks`; verify that it successfully built into the current
environment and stored the build file at
`$CONDA_PREFIX/llamastack-build.yaml`. Run `llama stack run fireworks`
which started correctly in the current environment.

Ran the same build command outside of conda. It failed asking for
`--image-name`. Ran it with `llama stack build --template fireworks
--image-name foo`. This successfully created a conda environment called
`foo` and installed deps. Ran `llama stack run fireworks` outside conda
which failed. Activated a different conda, ran again, it failed saying
it did not find the `llamastack-build.yaml` file. Then used
`--image-name foo` option and it ran successfully.
This commit is contained in:
Ashwin Bharambe 2025-01-16 13:44:53 -08:00 • committed by GitHub
parent 59eeaf7f81
commit cee3816609
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GPG key ID: B5690EEEBB952194
8 changed files with 400 additions and 338 deletions
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307
llama_stack/cli/stack/_build.py Normal file
View file

@ -0,0 +1,307 @@
# Copyright (c) Meta Platforms, Inc. and affiliates.
# All rights reserved.
#
# This source code is licensed under the terms described in the LICENSE file in
# the root directory of this source tree.
import argparse
import importlib.resources
import json
import os
import shutil
import textwrap
from functools import lru_cache
from pathlib import Path
from typing import Dict, Optional
import yaml
from prompt_toolkit import prompt
from prompt_toolkit.completion import WordCompleter
from prompt_toolkit.validation import Validator
from termcolor import cprint
from llama_stack.cli.table import print_table
from llama_stack.distribution.build import build_image, ImageType
from llama_stack.distribution.datatypes import (
BuildConfig,
DistributionSpec,
Provider,
StackRunConfig,
)
from llama_stack.distribution.distribution import get_provider_registry
from llama_stack.distribution.resolver import InvalidProviderError
from llama_stack.distribution.utils.config_dirs import DISTRIBS_BASE_DIR
from llama_stack.distribution.utils.dynamic import instantiate_class_type
from llama_stack.providers.datatypes import Api
TEMPLATES_PATH = Path(__file__).parent.parent.parent / "templates"
@lru_cache()
def available_templates_specs() -> Dict[str, BuildConfig]:
import yaml
template_specs = {}
for p in TEMPLATES_PATH.rglob("*build.yaml"):
template_name = p.parent.name
with open(p, "r") as f:
build_config = BuildConfig(**yaml.safe_load(f))
template_specs[template_name] = build_config
return template_specs
def run_stack_build_command(
parser: argparse.ArgumentParser, args: argparse.Namespace
) -> None:
if args.list_templates:
return _run_template_list_cmd()
current_conda_env = os.environ.get("CONDA_DEFAULT_ENV")
image_name = args.image_name or current_conda_env
if args.template:
available_templates = available_templates_specs()
if args.template not in available_templates:
cprint(
f"Could not find template {args.template}. Please run `llama stack build --list-templates` to check out the available templates",
color="red",
)
return
build_config = available_templates[args.template]
if args.image_type:
build_config.image_type = args.image_type
else:
cprint(
f"Please specify a image-type (docker | conda | venv) for {args.template}",
color="red",
)
return
_run_stack_build_command_from_build_config(
build_config,
image_name=image_name,
template_name=args.template,
)
return
if not args.config and not args.template:
name = prompt(
"> Enter a name for your Llama Stack (e.g. my-local-stack): ",
validator=Validator.from_callable(
lambda x: len(x) > 0,
error_message="Name cannot be empty, please enter a name",
),
)
image_type = prompt(
"> Enter the image type you want your Llama Stack to be built as (docker or conda or venv): ",
validator=Validator.from_callable(
lambda x: x in ["docker", "conda", "venv"],
error_message="Invalid image type, please enter conda or docker or venv",
),
default="conda",
)
if image_type == "conda":
if not image_name:
cprint(
f"No current conda environment detected or specified, will create a new conda environment with the name `llamastack-{name}`",
color="yellow",
)
image_name = f"llamastack-{name}"
else:
cprint(
f"Using conda environment {image_name}",
color="green",
)
cprint(
textwrap.dedent(
"""
Llama Stack is composed of several APIs working together. Let's select
the provider types (implementations) you want to use for these APIs.
""",
),
color="green",
)
print("Tip: use <TAB> to see options for the providers.\n")
providers = dict()
for api, providers_for_api in get_provider_registry().items():
available_providers = [
x
for x in providers_for_api.keys()
if x not in ("remote", "remote::sample")
]
api_provider = prompt(
"> Enter provider for API {}: ".format(api.value),
completer=WordCompleter(available_providers),
complete_while_typing=True,
validator=Validator.from_callable(
lambda x: x in available_providers,
error_message="Invalid provider, use <TAB> to see options",
),
)
providers[api.value] = api_provider
description = prompt(
"\n > (Optional) Enter a short description for your Llama Stack: ",
default="",
)
distribution_spec = DistributionSpec(
providers=providers,
description=description,
)
build_config = BuildConfig(
image_type=image_type, distribution_spec=distribution_spec
)
else:
with open(args.config, "r") as f:
try:
build_config = BuildConfig(**yaml.safe_load(f))
except Exception as e:
cprint(
f"Could not parse config file {args.config}: {e}",
color="red",
)
return
_run_stack_build_command_from_build_config(build_config, image_name=image_name)
def _generate_run_config(
build_config: BuildConfig, build_dir: Path, image_name: str
) -> None:
"""
Generate a run.yaml template file for user to edit from a build.yaml file
"""
apis = list(build_config.distribution_spec.providers.keys())
run_config = StackRunConfig(
docker_image=(
image_name if build_config.image_type == ImageType.docker.value else None
),
image_name=image_name,
apis=apis,
providers={},
)
# build providers dict
provider_registry = get_provider_registry()
for api in apis:
run_config.providers[api] = []
provider_types = build_config.distribution_spec.providers[api]
if isinstance(provider_types, str):
provider_types = [provider_types]
for i, provider_type in enumerate(provider_types):
pid = provider_type.split("::")[-1]
p = provider_registry[Api(api)][provider_type]
if p.deprecation_error:
raise InvalidProviderError(p.deprecation_error)
config_type = instantiate_class_type(
provider_registry[Api(api)][provider_type].config_class
)
if hasattr(config_type, "sample_run_config"):
config = config_type.sample_run_config(
__distro_dir__=f"distributions/{image_name}"
)
else:
config = {}
p_spec = Provider(
provider_id=f"{pid}-{i}" if len(provider_types) > 1 else pid,
provider_type=provider_type,
config=config,
)
run_config.providers[api].append(p_spec)
run_config_file = build_dir / f"{image_name}-run.yaml"
with open(run_config_file, "w") as f:
to_write = json.loads(run_config.model_dump_json())
f.write(yaml.dump(to_write, sort_keys=False))
cprint(
f"You can now edit {run_config_file} and run `llama stack run {image_name}`",
color="green",
)
def _run_stack_build_command_from_build_config(
build_config: BuildConfig,
image_name: Optional[str] = None,
template_name: Optional[str] = None,
) -> None:
if build_config.image_type == ImageType.docker.value:
if template_name:
image_name = f"distribution-{template_name}"
else:
if not image_name:
raise ValueError(
"Please specify an image name when building a docker image without a template"
)
elif build_config.image_type == ImageType.conda.value:
if not image_name:
raise ValueError("Please specify an image name when building a conda image")
if template_name:
build_dir = DISTRIBS_BASE_DIR / template_name
build_file_path = build_dir / f"{template_name}-build.yaml"
else:
build_dir = DISTRIBS_BASE_DIR / image_name
build_file_path = build_dir / f"{image_name}-build.yaml"
os.makedirs(build_dir, exist_ok=True)
with open(build_file_path, "w") as f:
to_write = json.loads(build_config.model_dump_json())
f.write(yaml.dump(to_write, sort_keys=False))
return_code = build_image(
build_config, build_file_path, image_name, template_name=template_name
)
if return_code != 0:
return
if template_name:
# copy run.yaml from template to build_dir instead of generating it again
template_path = (
importlib.resources.files("llama_stack")
/ f"templates/{template_name}/run.yaml"
)
with importlib.resources.as_file(template_path) as path:
run_config_file = build_dir / f"{template_name}-run.yaml"
shutil.copy(path, run_config_file)
# Find all ${env.VARIABLE} patterns
cprint("Build Successful!", color="green")
else:
_generate_run_config(build_config, build_dir, image_name)
def _run_template_list_cmd() -> None:
# eventually, this should query a registry at llama.meta.com/llamastack/distributions
headers = [
"Template Name",
# "Providers",
"Description",
]
rows = []
for template_name, spec in available_templates_specs().items():
rows.append(
[
template_name,
# json.dumps(spec.distribution_spec.providers, indent=2),
spec.distribution_spec.description,
]
)
print_table(
rows,
headers,
separate_rows=True,
)

292
llama_stack/cli/stack/build.py
View file

@ -4,38 +4,9 @@
# This source code is licensed under the terms described in the LICENSE file in
# the root directory of this source tree.
import argparse
import importlib.resources
import os
import shutil
from functools import lru_cache
from pathlib import Path
from typing import List, Optional
import textwrap
from llama_stack.cli.subcommand import Subcommand
from llama_stack.distribution.datatypes import (
BuildConfig,
DistributionSpec,
Provider,
StackRunConfig,
)
from llama_stack.distribution.distribution import get_provider_registry
from llama_stack.distribution.resolver import InvalidProviderError
from llama_stack.distribution.utils.dynamic import instantiate_class_type
from llama_stack.providers.datatypes import Api
TEMPLATES_PATH = Path(__file__).parent.parent.parent / "templates"
@lru_cache()
def available_templates_specs() -> List[BuildConfig]:
import yaml
template_specs = []
for p in TEMPLATES_PATH.rglob("*build.yaml"):
with open(p, "r") as f:
build_config = BuildConfig(**yaml.safe_load(f))
template_specs.append(build_config)
return template_specs
class StackBuild(Subcommand):
@ -81,250 +52,21 @@ class StackBuild(Subcommand):
default="conda",
)
self.parser.add_argument(
"--image-name",
type=str,
help=textwrap.dedent(
"""[for image-type=conda] Name of the conda environment to use for the build. If
not specified, currently active Conda environment will be used. If no Conda
environment is active, you must specify a name.
"""
),
default=None,
)
def _run_stack_build_command(self, args: argparse.Namespace) -> None:
import textwrap
# always keep implementation completely silo-ed away from CLI so CLI
# can be fast to load and reduces dependencies
from ._build import run_stack_build_command
import yaml
from prompt_toolkit import prompt
from prompt_toolkit.completion import WordCompleter
from prompt_toolkit.validation import Validator
from termcolor import cprint
from llama_stack.distribution.distribution import get_provider_registry
if args.list_templates:
self._run_template_list_cmd(args)
return
if args.template:
available_templates = available_templates_specs()
for build_config in available_templates:
if build_config.name == args.template:
if args.image_type:
build_config.image_type = args.image_type
else:
self.parser.error(
f"Please specify a image-type (docker | conda | venv) for {args.template}"
)
self._run_stack_build_command_from_build_config(
build_config,
template_name=args.template,
)
return
self.parser.error(
f"Could not find template {args.template}. Please run `llama stack build --list-templates` to check out the available templates"
)
return
if not args.config and not args.template:
name = prompt(
"> Enter a name for your Llama Stack (e.g. my-local-stack): ",
validator=Validator.from_callable(
lambda x: len(x) > 0,
error_message="Name cannot be empty, please enter a name",
),
)
image_type = prompt(
"> Enter the image type you want your Llama Stack to be built as (docker or conda or venv): ",
validator=Validator.from_callable(
lambda x: x in ["docker", "conda", "venv"],
error_message="Invalid image type, please enter conda or docker or venv",
),
default="conda",
)
cprint(
textwrap.dedent(
"""
Llama Stack is composed of several APIs working together. Let's select
the provider types (implementations) you want to use for these APIs.
""",
),
color="green",
)
print("Tip: use <TAB> to see options for the providers.\n")
providers = dict()
for api, providers_for_api in get_provider_registry().items():
available_providers = [
x
for x in providers_for_api.keys()
if x not in ("remote", "remote::sample")
]
api_provider = prompt(
"> Enter provider for API {}: ".format(api.value),
completer=WordCompleter(available_providers),
complete_while_typing=True,
validator=Validator.from_callable(
lambda x: x in available_providers,
error_message="Invalid provider, use <TAB> to see options",
),
)
providers[api.value] = api_provider
description = prompt(
"\n > (Optional) Enter a short description for your Llama Stack: ",
default="",
)
distribution_spec = DistributionSpec(
providers=providers,
description=description,
)
build_config = BuildConfig(
name=name, image_type=image_type, distribution_spec=distribution_spec
)
self._run_stack_build_command_from_build_config(build_config)
return
with open(args.config, "r") as f:
try:
build_config = BuildConfig(**yaml.safe_load(f))
except Exception as e:
self.parser.error(f"Could not parse config file {args.config}: {e}")
return
self._run_stack_build_command_from_build_config(build_config)
def _generate_run_config(self, build_config: BuildConfig, build_dir: Path) -> None:
"""
Generate a run.yaml template file for user to edit from a build.yaml file
"""
import json
import yaml
from termcolor import cprint
from llama_stack.distribution.build import ImageType
apis = list(build_config.distribution_spec.providers.keys())
run_config = StackRunConfig(
docker_image=(
build_config.name
if build_config.image_type == ImageType.docker.value
else None
),
image_name=build_config.name,
conda_env=(
build_config.name
if build_config.image_type == ImageType.conda.value
else None
),
apis=apis,
providers={},
)
# build providers dict
provider_registry = get_provider_registry()
for api in apis:
run_config.providers[api] = []
provider_types = build_config.distribution_spec.providers[api]
if isinstance(provider_types, str):
provider_types = [provider_types]
for i, provider_type in enumerate(provider_types):
pid = provider_type.split("::")[-1]
p = provider_registry[Api(api)][provider_type]
if p.deprecation_error:
raise InvalidProviderError(p.deprecation_error)
config_type = instantiate_class_type(
provider_registry[Api(api)][provider_type].config_class
)
if hasattr(config_type, "sample_run_config"):
config = config_type.sample_run_config(
__distro_dir__=f"distributions/{build_config.name}"
)
else:
config = {}
p_spec = Provider(
provider_id=f"{pid}-{i}" if len(provider_types) > 1 else pid,
provider_type=provider_type,
config=config,
)
run_config.providers[api].append(p_spec)
os.makedirs(build_dir, exist_ok=True)
run_config_file = build_dir / f"{build_config.name}-run.yaml"
with open(run_config_file, "w") as f:
to_write = json.loads(run_config.model_dump_json())
f.write(yaml.dump(to_write, sort_keys=False))
cprint(
f"You can now edit {run_config_file} and run `llama stack run {run_config_file}`",
color="green",
)
def _run_stack_build_command_from_build_config(
self,
build_config: BuildConfig,
template_name: Optional[str] = None,
) -> None:
import json
import os
import yaml
from termcolor import cprint
from llama_stack.distribution.build import build_image
from llama_stack.distribution.utils.config_dirs import DISTRIBS_BASE_DIR
# save build.yaml spec for building same distribution again
build_dir = DISTRIBS_BASE_DIR / f"llamastack-{build_config.name}"
os.makedirs(build_dir, exist_ok=True)
build_file_path = build_dir / f"{build_config.name}-build.yaml"
with open(build_file_path, "w") as f:
to_write = json.loads(build_config.model_dump_json())
f.write(yaml.dump(to_write, sort_keys=False))
return_code = build_image(build_config, build_file_path)
if return_code != 0:
return
if template_name:
# copy run.yaml from template to build_dir instead of generating it again
template_path = (
importlib.resources.files("llama_stack")
/ f"templates/{template_name}/run.yaml"
)
with importlib.resources.as_file(template_path) as path:
run_config_file = build_dir / f"{build_config.name}-run.yaml"
shutil.copy(path, run_config_file)
# Find all ${env.VARIABLE} patterns
cprint("Build Successful!", color="green")
else:
self._generate_run_config(build_config, build_dir)
def _run_template_list_cmd(self, args: argparse.Namespace) -> None:
import json
from llama_stack.cli.table import print_table
# eventually, this should query a registry at llama.meta.com/llamastack/distributions
headers = [
"Template Name",
"Providers",
"Description",
]
rows = []
for spec in available_templates_specs():
rows.append(
[
spec.name,
json.dumps(spec.distribution_spec.providers, indent=2),
spec.distribution_spec.description,
]
)
print_table(
rows,
headers,
separate_rows=True,
)
return run_stack_build_command(self.parser, args)

63
llama_stack/cli/stack/run.py
View file

@ -37,6 +37,11 @@ class StackRun(Subcommand):
help="Port to run the server on. Defaults to 5000",
default=int(os.getenv("LLAMA_STACK_PORT", 5000)),
)
self.parser.add_argument(
"--image-name",
type=str,
help="Name of the image to run. Defaults to the current conda environment",
)
self.parser.add_argument(
"--disable-ipv6",
action="store_true",
@ -53,8 +58,11 @@ class StackRun(Subcommand):
def _run_stack_run_cmd(self, args: argparse.Namespace) -> None:
import importlib.resources
import json
import subprocess
import yaml
from termcolor import cprint
from llama_stack.distribution.build import ImageType
from llama_stack.distribution.configure import parse_and_maybe_upgrade_config
@ -99,11 +107,11 @@ class StackRun(Subcommand):
if not config_file.exists():
self.parser.error(
f"File {str(config_file)} does not exist. Please run `llama stack build` to generate (and optionally edit) a run.yaml file"
f"File {str(config_file)} does not exist.\n\nPlease run `llama stack build` to generate (and optionally edit) a run.yaml file"
)
return
print(f"Using config file: {config_file}")
print(f"Using run configuration: {config_file}")
config_dict = yaml.safe_load(config_file.read_text())
config = parse_and_maybe_upgrade_config(config_dict)
@ -114,13 +122,52 @@ class StackRun(Subcommand):
)
run_args = [script, config.docker_image]
else:
current_conda_env = os.environ.get("CONDA_DEFAULT_ENV")
image_name = args.image_name or current_conda_env
if not image_name:
cprint(
"No current conda environment detected, please specify a conda environment name with --image-name",
color="red",
)
return
def get_conda_prefix(env_name):
# Get conda environments info
conda_env_info = json.loads(
subprocess.check_output(
["conda", "info", "--envs", "--json"]
).decode()
)
envs = conda_env_info["envs"]
for envpath in envs:
if envpath.endswith(env_name):
return envpath
return None
print(f"Using conda environment: {image_name}")
conda_prefix = get_conda_prefix(image_name)
if not conda_prefix:
cprint(
f"Conda environment {image_name} does not exist.",
color="red",
)
return
build_file = Path(conda_prefix) / "llamastack-build.yaml"
if not build_file.exists():
cprint(
f"Build file {build_file} does not exist.\n\nPlease run `llama stack build` or specify the correct conda environment name with --image-name",
color="red",
)
return
script = (
importlib.resources.files("llama_stack")
/ "distribution/start_conda_env.sh"
)
run_args = [
script,
config.conda_env,
image_name,
]
run_args.extend([str(config_file), str(args.port)])
@ -129,13 +176,17 @@ class StackRun(Subcommand):
for env_var in args.env:
if "=" not in env_var:
self.parser.error(
f"Environment variable '{env_var}' must be in KEY=VALUE format"
cprint(
f"Environment variable '{env_var}' must be in KEY=VALUE format",
color="red",
)
return
key, value = env_var.split("=", 1) # split on first = only
if not key:
self.parser.error(f"Environment variable '{env_var}' has empty key")
cprint(
f"Environment variable '{env_var}' has empty key",
color="red",
)
return
run_args.extend(["--env", f"{key}={value}"])

20
llama_stack/distribution/build.py
View file

@ -10,7 +10,7 @@ import sys
from enum import Enum
from pathlib import Path
from typing import Dict, List
from typing import Dict, List, Optional
from pydantic import BaseModel
from termcolor import cprint
@ -106,6 +106,8 @@ def print_pip_install_help(providers: Dict[str, List[Provider]]):
def build_image(
build_config: BuildConfig,
build_file_path: Path,
image_name: str,
template_name: Optional[str] = None,
):
docker_image = build_config.distribution_spec.docker_image or "python:3.10-slim"
@ -115,32 +117,34 @@ def build_image(
normal_deps += SERVER_DEPENDENCIES
if build_config.image_type == ImageType.docker.value:
script = (
script = str(
importlib.resources.files("llama_stack") / "distribution/build_container.sh"
)
args = [
script,
build_config.name,
image_name,
docker_image,
str(build_file_path),
str(BUILDS_BASE_DIR / ImageType.docker.value),
" ".join(normal_deps),
]
elif build_config.image_type == ImageType.conda.value:
script = (
script = str(
importlib.resources.files("llama_stack") / "distribution/build_conda_env.sh"
)
args = [
script,
build_config.name,
str(image_name),
str(build_file_path),
" ".join(normal_deps),
]
elif build_config.image_type == ImageType.venv.value:
script = importlib.resources.files("llama_stack") / "distribution/build_venv.sh"
script = str(
importlib.resources.files("llama_stack") / "distribution/build_venv.sh"
)
args = [
script,
build_config.name,
str(image_name),
str(build_file_path),
" ".join(normal_deps),
]
@ -156,7 +160,7 @@ def build_image(
if return_code != 0:
log.error(
f"Failed to build target {build_config.name} with return code {return_code}",
f"Failed to build target {image_name} with return code {return_code}",
)
return return_code

11
llama_stack/distribution/build_conda_env.sh
View file

@ -18,8 +18,8 @@ if [ -n "$LLAMA_MODELS_DIR" ]; then
fi
if [ "$#" -lt 3 ]; then
echo "Usage: $0 <distribution_type> <build_name> <build_file_path> <pip_dependencies> [<special_pip_deps>]" >&2
echo "Example: $0 <distribution_type> mybuild ./my-stack-build.yaml 'numpy pandas scipy'" >&2
echo "Usage: $0 <distribution_type> <conda_env_name> <build_file_path> <pip_dependencies> [<special_pip_deps>]" >&2
echo "Example: $0 <distribution_type> my-conda-env ./my-stack-build.yaml 'numpy pandas scipy'" >&2
exit 1
fi
@ -27,8 +27,7 @@ special_pip_deps="$4"
set -euo pipefail
build_name="$1"
env_name="llamastack-$build_name"
env_name="$1"
build_file_path="$2"
pip_dependencies="$3"
@ -137,8 +136,8 @@ ensure_conda_env_python310() {
fi
fi
mv $build_file_path $CONDA_PREFIX/
echo "Build spec configuration saved at $CONDA_PREFIX/$build_name-build.yaml"
mv $build_file_path $CONDA_PREFIX/llamastack-build.yaml
echo "Build spec configuration saved at $CONDA_PREFIX/llamastack-build.yaml"
}
ensure_conda_env_python310 "$env_name" "$pip_dependencies" "$special_pip_deps"

6
llama_stack/distribution/datatypes.py
View file

@ -131,10 +131,6 @@ this could be just a hash
default=None,
description="Reference to the docker image if this package refers to a container",
)
conda_env: Optional[str] = Field(
default=None,
description="Reference to the conda environment if this package refers to a conda environment",
)
apis: List[str] = Field(
default_factory=list,
description="""
@ -166,7 +162,7 @@ a default SQLite store will be used.""",
class BuildConfig(BaseModel):
version: str = LLAMA_STACK_BUILD_CONFIG_VERSION
name: str
distribution_spec: DistributionSpec = Field(
description="The distribution spec to build including API providers. "
)

3
llama_stack/distribution/start_conda_env.sh
View file

@ -23,8 +23,7 @@ if [ $# -lt 3 ]; then
exit 1
fi
build_name="$1"
env_name="llamastack-$build_name"
env_name="$1"
shift
yaml_config="$1"

36
llama_stack/providers/inline/inference/meta_reference/quantization/scripts/build_conda.sh
View file

@ -1,36 +0,0 @@
#!/bin/bash
# Copyright (c) Meta Platforms, Inc. and affiliates.
# All rights reserved.
#
# This source code is licensed under the terms described in the LICENSE file in
# the root directory of this source tree.
if [[ $# -ne 1 ]]; then
echo "Error: Please provide the name of CONDA environment you wish to create"
exit 1
fi
ENV_NAME=$1
set -eu
eval "$(conda shell.bash hook)"
echo "Will build env (or overwrite) named '$ENV_NAME'"
set -x
run_build() {
# Set up the conda environment
yes | conda remove --name $ENV_NAME --all
yes | conda create -n $ENV_NAME python=3.10
conda activate $ENV_NAME
# PT nightly
pip install --pre torch --index-url https://download.pytorch.org/whl/nightly/cu121
# install dependencies for `llama-agentic-system`
pip install -r fp8_requirements.txt
}
run_build