Introduce Llama stack distributions (#22)

* Add distribution CLI scaffolding

* More progress towards `llama distribution install`

* getting closer to a distro definition, distro install + configure works

* Distribution server now functioning

* read existing configuration, save enums properly

* Remove inference uvicorn server entrypoint and llama inference CLI command

* updated dependency and client model name

* Improved exception handling

* local imports for faster cli

* undo a typo, add a passthrough distribution

* implement full-passthrough in the server

* add safety adapters, configuration handling, server + clients

* cleanup, moving stuff to common, nuke utils

* Add a Path() wrapper at the earliest place

* fixes

* Bring agentic system api to toolchain

Add adapter dependencies and resolve adapters using a topological sort

* refactor to reduce size of `agentic_system`

* move straggler files and fix some important existing bugs

* ApiSurface -> Api

* refactor a method out

* Adapter -> Provider

* Make each inference provider into its own subdirectory

* installation fixes

* Rename Distribution -> DistributionSpec, simplify RemoteProviders

* dict key instead of attr

* update inference config to take model and not model_dir

* Fix passthrough streaming, send headers properly not part of body :facepalm

* update safety to use model sku ids and not model dirs

* Update cli_reference.md

* minor fixes

* add DistributionConfig, fix a bug in model download

* Make install + start scripts do proper configuration automatically

* Update CLI_reference

* Nuke fp8_requirements, fold fbgemm into common requirements

* Update README, add newline between API surface configurations

* Refactor download functionality out of the Command so can be reused

* Add `llama model download` alias for `llama download`

* Show message about checksum file so users can check themselves

* Simpler intro statements

* get ollama working

* Reduce a bunch of dependencies from toolchain

Some improvements to the distribution install script

* Avoid using `conda run` since it buffers everything

* update dependencies and rely on LLAMA_TOOLCHAIN_DIR for dev purposes

* add validation for configuration input

* resort imports

* make optional subclasses default to yes for configuration

* Remove additional_pip_packages; move deps to providers

* for inline make 8b model the default

* Add scripts to MANIFEST

* allow installing from test.pypi.org

* Fix #2 to help with testing packages

* Must install llama-models at that same version first

* fix PIP_ARGS

---------

Co-authored-by: Hardik Shah <hjshah@fb.com>
Co-authored-by: Hardik Shah <hjshah@meta.com>

llama_toolchain/cli/distribution/configure.py

@@ -0,0 +1,106 @@
+# 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 json
+import shlex
+
+import yaml
+
+from llama_toolchain.cli.subcommand import Subcommand
+from llama_toolchain.common.config_dirs import DISTRIBS_BASE_DIR
+from termcolor import cprint
+
+
+class DistributionConfigure(Subcommand):
+    """Llama cli for configuring llama toolchain configs"""
+
+    def __init__(self, subparsers: argparse._SubParsersAction):
+        super().__init__()
+        self.parser = subparsers.add_parser(
+            "configure",
+            prog="llama distribution configure",
+            description="configure a llama stack distribution",
+            formatter_class=argparse.RawTextHelpFormatter,
+        )
+        self._add_arguments()
+        self.parser.set_defaults(func=self._run_distribution_configure_cmd)
+
+    def _add_arguments(self):
+        self.parser.add_argument(
+            "--name",
+            type=str,
+            help="Name of the distribution to configure",
+            required=True,
+        )
+
+    def _run_distribution_configure_cmd(self, args: argparse.Namespace) -> None:
+        from llama_toolchain.distribution.datatypes import DistributionConfig
+        from llama_toolchain.distribution.registry import resolve_distribution_spec
+
+        config_file = DISTRIBS_BASE_DIR / args.name / "config.yaml"
+        if not config_file.exists():
+            self.parser.error(
+                f"Could not find {config_file}. Please run `llama distribution install` first"
+            )
+            return
+
+        # we need to find the spec from the name
+        with open(config_file, "r") as f:
+            config = DistributionConfig(**yaml.safe_load(f))
+
+        dist = resolve_distribution_spec(config.spec)
+        if dist is None:
+            raise ValueError(f"Could not find any registered spec `{config.spec}`")
+
+        configure_llama_distribution(dist, config)
+
+
+def configure_llama_distribution(dist: "Distribution", config: "DistributionConfig"):
+    from llama_toolchain.common.exec import run_command
+    from llama_toolchain.common.prompt_for_config import prompt_for_config
+    from llama_toolchain.common.serialize import EnumEncoder
+    from llama_toolchain.distribution.dynamic import instantiate_class_type
+
+    python_exe = run_command(shlex.split("which python"))
+    # simple check
+    conda_env = config.conda_env
+    if conda_env not in python_exe:
+        raise ValueError(
+            f"Please re-run configure by activating the `{conda_env}` conda environment"
+        )
+
+    if config.providers:
+        cprint(
+            f"Configuration already exists for {config.name}. Will overwrite...",
+            "yellow",
+            attrs=["bold"],
+        )
+
+    for api, provider_spec in dist.provider_specs.items():
+        cprint(f"Configuring API surface: {api.value}", "white", attrs=["bold"])
+        config_type = instantiate_class_type(provider_spec.config_class)
+        provider_config = prompt_for_config(
+            config_type,
+            (
+                config_type(**config.providers[api.value])
+                if api.value in config.providers
+                else None
+            ),
+        )
+        print("")
+
+        config.providers[api.value] = {
+            "provider_id": provider_spec.provider_id,
+            **provider_config.dict(),
+        }
+
+    config_path = DISTRIBS_BASE_DIR / config.name / "config.yaml"
+    with open(config_path, "w") as fp:
+        dist_config = json.loads(json.dumps(config.dict(), cls=EnumEncoder))
+        fp.write(yaml.dump(dist_config, sort_keys=False))
+
+    print(f"YAML configuration has been written to {config_path}")