diff --git a/llama-index-cli/.gitignore b/llama-index-cli/.gitignore
new file mode 100644
index 0000000000000..990c18de22908
--- /dev/null
+++ b/llama-index-cli/.gitignore
@@ -0,0 +1,153 @@
+llama_index/_static
+.DS_Store
+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[cod]
+*$py.class
+
+# C extensions
+*.so
+
+# Distribution / packaging
+.Python
+bin/
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+etc/
+include/
+lib/
+lib64/
+parts/
+sdist/
+share/
+var/
+wheels/
+pip-wheel-metadata/
+share/python-wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+MANIFEST
+
+# PyInstaller
+#  Usually these files are written by a python script from a template
+#  before PyInstaller builds the exe, so as to inject date/other infos into it.
+*.manifest
+*.spec
+
+# Installer logs
+pip-log.txt
+pip-delete-this-directory.txt
+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.nox/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+*.py,cover
+.hypothesis/
+.pytest_cache/
+.ruff_cache
+
+# Translations
+*.mo
+*.pot
+
+# Django stuff:
+*.log
+local_settings.py
+db.sqlite3
+db.sqlite3-journal
+
+# Flask stuff:
+instance/
+.webassets-cache
+
+# Scrapy stuff:
+.scrapy
+
+# Sphinx documentation
+docs/_build/
+
+# PyBuilder
+target/
+
+# Jupyter Notebook
+.ipynb_checkpoints
+notebooks/
+
+# IPython
+profile_default/
+ipython_config.py
+
+# pyenv
+.python-version
+
+# pipenv
+#   According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
+#   However, in case of collaboration, if having platform-specific dependencies or dependencies
+#   having no cross-platform support, pipenv may install dependencies that don't work, or not
+#   install all needed dependencies.
+#Pipfile.lock
+
+# PEP 582; used by e.g. github.com/David-OConnor/pyflow
+__pypackages__/
+
+# Celery stuff
+celerybeat-schedule
+celerybeat.pid
+
+# SageMath parsed files
+*.sage.py
+
+# Environments
+.env
+.venv
+env/
+venv/
+ENV/
+env.bak/
+venv.bak/
+pyvenv.cfg
+
+# Spyder project settings
+.spyderproject
+.spyproject
+
+# Rope project settings
+.ropeproject
+
+# mkdocs documentation
+/site
+
+# mypy
+.mypy_cache/
+.dmypy.json
+dmypy.json
+
+# Pyre type checker
+.pyre/
+
+# Jetbrains
+.idea
+modules/
+*.swp
+
+# VsCode
+.vscode
+
+# pipenv
+Pipfile
+Pipfile.lock
+
+# pyright
+pyrightconfig.json
diff --git a/llama-index-cli/BUILD b/llama-index-cli/BUILD
new file mode 100644
index 0000000000000..0b67818b466ca
--- /dev/null
+++ b/llama-index-cli/BUILD
@@ -0,0 +1,5 @@
+python_sources()
+
+poetry_requirements(
+    name="poetry",
+)
diff --git a/llama-index-cli/CHANGELOG.MD b/llama-index-cli/CHANGELOG.MD
new file mode 100644
index 0000000000000..109adf94b711b
--- /dev/null
+++ b/llama-index-cli/CHANGELOG.MD
@@ -0,0 +1,5 @@
+# CHANGELOG
+
+## [0.1.0] - 2024-02-15
+
+- Initial release of cli (ripped out from core)
diff --git a/llama-index-cli/Makefile b/llama-index-cli/Makefile
new file mode 100644
index 0000000000000..b9eab05aa3706
--- /dev/null
+++ b/llama-index-cli/Makefile
@@ -0,0 +1,17 @@
+GIT_ROOT ?= $(shell git rev-parse --show-toplevel)
+
+help:	## Show all Makefile targets.
+	@grep -E '^[a-zA-Z_-]+:.*?## .*$$' $(MAKEFILE_LIST) | awk 'BEGIN {FS = ":.*?## "}; {printf "\033[33m%-30s\033[0m %s\n", $$1, $$2}'
+
+format:	## Run code autoformatters (black).
+	pre-commit install
+	git ls-files | xargs pre-commit run black --files
+
+lint:	## Run linters: pre-commit (black, ruff, codespell) and mypy
+	pre-commit install && git ls-files | xargs pre-commit run --show-diff-on-failure --files
+
+test:	## Run tests via pytest.
+	pytest tests
+
+watch-docs:	## Build and watch documentation.
+	sphinx-autobuild docs/ docs/_build/html --open-browser --watch $(GIT_ROOT)/llama_index/
diff --git a/llama-index-cli/README.md b/llama-index-cli/README.md
new file mode 100644
index 0000000000000..3232c32f3fcd9
--- /dev/null
+++ b/llama-index-cli/README.md
@@ -0,0 +1,30 @@
+# LlamaIndex CLI
+
+## Installation
+
+```sh
+pip install llama-index-cli
+```
+
+## Usage
+
+```sh
+llamaindex -h
+
+usage: llamaindex [-h] {rag,download-llamapack,download-llamadataset,upgrade,upgrade-file,new-package} ...
+
+LlamaIndex CLI tool.
+
+options:
+  -h, --help            show this help message and exit
+
+commands:
+  {rag,download-llamapack,download-llamadataset,upgrade,upgrade-file,new-package}
+    rag                 Ask a question to a document / a directory of documents.
+    download-llamapack  Download a llama-pack
+    download-llamadataset
+                        Download a llama-dataset
+    upgrade             Upgrade a directory containing notebooks or python files.
+    upgrade-file        Upgrade a single notebook or python file.
+    new-package         Initialize a new llama-index package
+```
diff --git a/llama-index-cli/llama_index/cli/BUILD b/llama-index-cli/llama_index/cli/BUILD
new file mode 100644
index 0000000000000..db46e8d6c978c
--- /dev/null
+++ b/llama-index-cli/llama_index/cli/BUILD
@@ -0,0 +1 @@
+python_sources()
diff --git a/llama-index-cli/llama_index/cli/__init__.py b/llama-index-cli/llama_index/cli/__init__.py
new file mode 100644
index 0000000000000..e69de29bb2d1d
diff --git a/llama-index-cli/llama_index/cli/command_line.py b/llama-index-cli/llama_index/cli/command_line.py
new file mode 100644
index 0000000000000..34af87a864c57
--- /dev/null
+++ b/llama-index-cli/llama_index/cli/command_line.py
@@ -0,0 +1,272 @@
+import argparse
+from typing import Any, Optional
+
+from llama_index.cli.rag.base import RagCLI, default_ragcli_persist_dir
+from llama_index.cli.upgrade.base import upgrade_dir, upgrade_file
+from llama_index.cli.new_package.base import init_new_package
+from llama_index.core.ingestion import IngestionCache, IngestionPipeline
+from llama_index.core.llama_dataset.download import (
+    LLAMA_DATASETS_LFS_URL,
+    LLAMA_DATASETS_SOURCE_FILES_GITHUB_TREE_URL,
+    LLAMA_HUB_URL,
+    download_llama_dataset,
+)
+from llama_index.core.llama_pack.download import (
+    LLAMA_PACKS_CONTENTS_URL,
+    download_llama_pack,
+)
+from llama_index.core.storage.docstore import SimpleDocumentStore
+from llama_index.core.text_splitter import SentenceSplitter
+
+
+def handle_init_package(
+    name: str, kind: str, prefix: Optional[str] = None, **kwargs: Any
+):
+    init_new_package(integration_name=name, integration_type=kind, prefix=prefix)
+    print(f"Successfully initialized package")
+
+
+def handle_download_llama_pack(
+    llama_pack_class: Optional[str] = None,
+    download_dir: Optional[str] = None,
+    llama_pack_url: str = LLAMA_PACKS_CONTENTS_URL,
+    **kwargs: Any,
+) -> None:
+    assert llama_pack_class is not None
+    assert download_dir is not None
+
+    download_llama_pack(
+        llama_pack_class=llama_pack_class,
+        download_dir=download_dir or "./custom_llama_pack",
+        llama_pack_url=llama_pack_url,
+    )
+    print(f"Successfully downloaded {llama_pack_class} to {download_dir}")
+
+
+def handle_download_llama_dataset(
+    llama_dataset_class: Optional[str] = None,
+    download_dir: Optional[str] = None,
+    llama_hub_url: str = LLAMA_HUB_URL,
+    llama_datasets_lfs_url: str = LLAMA_DATASETS_LFS_URL,
+    llama_datasets_source_files_tree_url: str = LLAMA_DATASETS_SOURCE_FILES_GITHUB_TREE_URL,
+    **kwargs: Any,
+) -> None:
+    assert llama_dataset_class is not None
+    assert download_dir is not None
+
+    download_llama_dataset(
+        llama_dataset_class=llama_dataset_class,
+        download_dir=download_dir,
+        llama_hub_url=llama_hub_url,
+        llama_datasets_lfs_url=llama_datasets_lfs_url,
+        llama_datasets_source_files_tree_url=llama_datasets_source_files_tree_url,
+        show_progress=True,
+        load_documents=False,
+    )
+
+    print(f"Successfully downloaded {llama_dataset_class} to {download_dir}")
+
+
+def default_rag_cli() -> RagCLI:
+    import chromadb  # pants: no-infer-dep
+    from llama_index.embeddings.openai import OpenAIEmbedding  # pants: no-infer-dep
+    from llama_index.vector_stores.chroma import (
+        ChromaVectorStore,
+    )  # pants: no-infer-dep
+
+    persist_dir = default_ragcli_persist_dir()
+    chroma_client = chromadb.PersistentClient(path=persist_dir)
+    chroma_collection = chroma_client.create_collection("default", get_or_create=True)
+    vector_store = ChromaVectorStore(
+        chroma_collection=chroma_collection, persist_dir=persist_dir
+    )
+    docstore = SimpleDocumentStore()
+
+    ingestion_pipeline = IngestionPipeline(
+        transformations=[SentenceSplitter(), OpenAIEmbedding()],
+        vector_store=vector_store,
+        docstore=docstore,
+        cache=IngestionCache(),
+    )
+    try:
+        from llama_index.embeddings.openai import OpenAIEmbedding  # pants: no-infer-dep
+    except ImportError:
+        OpenAIEmbedding = None
+
+    try:
+        import chromadb
+
+        from llama_index.vector_stores.chroma import (
+            ChromaVectorStore,
+        )
+    except ImportError:
+        ChromaVectorStore = None
+
+    if OpenAIEmbedding and ChromaVectorStore:
+        persist_dir = default_ragcli_persist_dir()
+        chroma_client = chromadb.PersistentClient(path=persist_dir)
+        chroma_collection = chroma_client.create_collection(
+            "default", get_or_create=True
+        )
+        vector_store = ChromaVectorStore(
+            chroma_collection=chroma_collection, persist_dir=persist_dir
+        )
+        docstore = SimpleDocumentStore()
+
+        ingestion_pipeline = IngestionPipeline(
+            transformations=[SentenceSplitter(), OpenAIEmbedding()],
+            vector_store=vector_store,
+            docstore=docstore,
+            cache=IngestionCache(),
+        )
+        try:
+            ingestion_pipeline.load(persist_dir=persist_dir)
+        except FileNotFoundError:
+            pass
+
+        return RagCLI(
+            ingestion_pipeline=ingestion_pipeline,
+            verbose=False,
+            persist_dir=persist_dir,
+        )
+    else:
+        print(
+            "Default RagCLI was not built. There are packages missing. Please"
+            " install required dependencies by running "
+            "`pip install llama-index-embeddings-openai llama-index-llms-openai chromadb llama-index-vector-stores-chroma`"
+        )
+        return None
+
+
+def main() -> None:
+    parser = argparse.ArgumentParser(description="LlamaIndex CLI tool.")
+
+    # Subparsers for the main commands
+    subparsers = parser.add_subparsers(title="commands", dest="command", required=True)
+
+    # llama rag command
+    llamarag_parser = subparsers.add_parser(
+        "rag", help="Ask a question to a document or a directory of documents."
+    )
+    RagCLI.add_parser_args(llamarag_parser, default_rag_cli)
+
+    # download llamapacks command
+    llamapack_parser = subparsers.add_parser(
+        "download-llamapack", help="Download a llama-pack"
+    )
+    llamapack_parser.add_argument(
+        "llama_pack_class",
+        type=str,
+        help=(
+            "The name of the llama-pack class you want to download, "
+            "such as `GmailOpenAIAgentPack`."
+        ),
+    )
+    llamapack_parser.add_argument(
+        "-d",
+        "--download-dir",
+        type=str,
+        default="./llama_packs",
+        help="Custom dirpath to download the pack into.",
+    )
+    llamapack_parser.add_argument(
+        "--llama-hub-url",
+        type=str,
+        default=LLAMA_HUB_URL,
+        help="URL to llama hub.",
+    )
+    llamapack_parser.set_defaults(
+        func=lambda args: handle_download_llama_pack(**vars(args))
+    )
+
+    # download llamadatasets command
+    llamadataset_parser = subparsers.add_parser(
+        "download-llamadataset", help="Download a llama-dataset"
+    )
+    llamadataset_parser.add_argument(
+        "llama_dataset_class",
+        type=str,
+        help=(
+            "The name of the llama-dataset class you want to download, "
+            "such as `PaulGrahamEssayDataset`."
+        ),
+    )
+    llamadataset_parser.add_argument(
+        "-d",
+        "--download-dir",
+        type=str,
+        default="./llama_datasets",
+        help="Custom dirpath to download the pack into.",
+    )
+    llamadataset_parser.add_argument(
+        "--llama-hub-url",
+        type=str,
+        default=LLAMA_HUB_URL,
+        help="URL to llama hub.",
+    )
+    llamadataset_parser.add_argument(
+        "--llama-datasets-lfs-url",
+        type=str,
+        default=LLAMA_DATASETS_LFS_URL,
+        help="URL to llama datasets.",
+    )
+    llamadataset_parser.set_defaults(
+        func=lambda args: handle_download_llama_dataset(**vars(args))
+    )
+
+    # Upgrade command
+    upgrade_parser = subparsers.add_parser(
+        "upgrade", help="Upgrade a directory containing notebooks or python files."
+    )
+    upgrade_parser.add_argument(
+        "directory",
+        type=str,
+        help="The directory to upgrade. Will run on only .ipynb or .py files.",
+    )
+    upgrade_parser.set_defaults(func=lambda args: upgrade_dir(args.directory))
+
+    # Upgrade command
+    upgrade_file_parser = subparsers.add_parser(
+        "upgrade-file", help="Upgrade a single notebook or python file."
+    )
+    upgrade_file_parser.add_argument(
+        "path",
+        type=str,
+        help="The directory to upgrade. Will run on only .ipynb or .py files.",
+    )
+    upgrade_file_parser.set_defaults(func=lambda args: upgrade_file(args.path))
+
+    # init package command
+    new_package_parser = subparsers.add_parser(
+        "new-package", help="Initialize a new llama-index package"
+    )
+    new_package_parser.add_argument(
+        "-k",
+        "--kind",
+        type=str,
+        help="Kind of package, e.g., llm, embedding, pack, etc.",
+    )
+    new_package_parser.add_argument(
+        "-n",
+        "--name",
+        type=str,
+        help="Name of python package",
+    )
+    new_package_parser.add_argument(
+        "-p",
+        "--prefix",
+        type=str,
+        required=False,
+        help="Name of prefix package",
+    )
+    new_package_parser.set_defaults(func=lambda args: handle_init_package(**vars(args)))
+
+    # Parse the command-line arguments
+    args = parser.parse_args()
+
+    # Call the appropriate function based on the command
+    args.func(args)
+
+
+if __name__ == "__main__":
+    main()
diff --git a/llama-index-cli/llama_index/cli/new_package/BUILD b/llama-index-cli/llama_index/cli/new_package/BUILD
new file mode 100644
index 0000000000000..db46e8d6c978c
--- /dev/null
+++ b/llama-index-cli/llama_index/cli/new_package/BUILD
@@ -0,0 +1 @@
+python_sources()
diff --git a/llama-index-cli/llama_index/cli/new_package/__init__.py b/llama-index-cli/llama_index/cli/new_package/__init__.py
new file mode 100644
index 0000000000000..e69de29bb2d1d
diff --git a/llama-index-cli/llama_index/cli/new_package/base.py b/llama-index-cli/llama_index/cli/new_package/base.py
new file mode 100644
index 0000000000000..68e573babfb96
--- /dev/null
+++ b/llama-index-cli/llama_index/cli/new_package/base.py
@@ -0,0 +1,120 @@
+import os
+import shutil
+from pathlib import Path
+from llama_index.cli.new_package.templates import (
+    pyproject_str,
+    readme_str,
+    init_str,
+    init_with_prefix_str,
+)
+from typing import Optional
+
+
+def _create_init_file(dir: str):
+    # create __init__.py
+    Path(dir + "/__init__.py").touch()
+
+
+def _create_test_file(filename: str):
+    Path(filename).touch()
+
+
+def _makedirs(dir: str):
+    try:
+        os.makedirs(dir)
+    except FileExistsError as e:
+        pass
+
+
+def init_new_package(
+    integration_type: str,
+    integration_name: str,
+    prefix: Optional[str] = None,
+):
+    # create new directory, works in current directory
+    pkg_name = (
+        f"llama-index-{integration_type}-{integration_name}".replace(" ", "-")
+        .replace("_", "-")
+        .lower()
+        if prefix is None
+        else f"llama-index-{prefix}-{integration_type}-{integration_name}".replace(
+            " ", "-"
+        )
+        .replace("_", "-")
+        .lower()
+    )
+    pkg_path = os.path.join(os.getcwd(), pkg_name)
+    tests_path = os.path.join(pkg_path, "tests")
+    examples_path = os.path.join(pkg_path, "examples")
+    pkg_src_dir = os.path.join(
+        pkg_path,
+        (
+            f"llama_index/{integration_type}/{integration_name}".replace(
+                " ", "_"
+            ).lower()
+            if prefix is None
+            else f"llama_index/{prefix}/{integration_type}/{integration_name}".replace(
+                " ", "_"
+            ).lower()
+        ),
+    )
+
+    # make dirs
+    _makedirs(pkg_path)
+    _makedirs(tests_path)
+    _makedirs(examples_path)
+    _makedirs(pkg_src_dir)
+
+    # create init files
+    _create_init_file(tests_path)
+    with open(pkg_src_dir + "/__init__.py", "w") as f:
+        init_string = (
+            init_str.format(
+                TYPE=integration_type.replace(" ", "_").lower(),
+                NAME=integration_name.replace(" ", "_").lower(),
+            )
+            if prefix is None
+            else init_with_prefix_str.format(
+                TYPE=integration_type.replace(" ", "-").lower(),
+                NAME=integration_name.replace(" ", "-").lower(),
+                PREFIX=prefix.replace(" ", "_").lower(),
+            )
+        )
+        f.write(init_string)
+
+    # create pyproject.toml
+    with open(pkg_path + "/pyproject.toml", "w") as f:
+        f.write(
+            pyproject_str.format(
+                PACKAGE_NAME=pkg_name,
+                TYPE=integration_type.lower(),
+                NAME=integration_name.lower(),
+            )
+        )
+
+    # create readme
+    with open(pkg_path + "/README.md", "w") as f:
+        f.write(
+            readme_str.format(
+                PACKAGE_NAME=pkg_name,
+                TYPE=integration_type.lower().title(),
+                NAME=integration_name.lower().title(),
+            )
+        )
+
+    # create an empty test file
+    test_file_name = tests_path + (
+        f"/test_{integration_type}_{integration_name}.py".replace(" ", "_").lower()
+        if prefix is None
+        else f"/test_{prefix}_{integration_type}_{integration_name}.py".replace(
+            " ", "_"
+        ).lower()
+    )
+    _create_test_file(test_file_name)
+
+    # copy common files to folders
+    script_path = Path(__file__).parent.resolve()
+    common_path = os.path.join(script_path, "common")
+    shutil.copyfile(common_path + "/.gitignore", pkg_path + "/.gitignore")
+    shutil.copyfile(common_path + "/Makefile", pkg_path + "/Makefile")
+    shutil.copyfile(common_path + "/BUILD", pkg_path + "/BUILD")
diff --git a/llama-index-cli/llama_index/cli/new_package/common/.gitignore b/llama-index-cli/llama_index/cli/new_package/common/.gitignore
new file mode 100644
index 0000000000000..990c18de22908
--- /dev/null
+++ b/llama-index-cli/llama_index/cli/new_package/common/.gitignore
@@ -0,0 +1,153 @@
+llama_index/_static
+.DS_Store
+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[cod]
+*$py.class
+
+# C extensions
+*.so
+
+# Distribution / packaging
+.Python
+bin/
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+etc/
+include/
+lib/
+lib64/
+parts/
+sdist/
+share/
+var/
+wheels/
+pip-wheel-metadata/
+share/python-wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+MANIFEST
+
+# PyInstaller
+#  Usually these files are written by a python script from a template
+#  before PyInstaller builds the exe, so as to inject date/other infos into it.
+*.manifest
+*.spec
+
+# Installer logs
+pip-log.txt
+pip-delete-this-directory.txt
+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.nox/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+*.py,cover
+.hypothesis/
+.pytest_cache/
+.ruff_cache
+
+# Translations
+*.mo
+*.pot
+
+# Django stuff:
+*.log
+local_settings.py
+db.sqlite3
+db.sqlite3-journal
+
+# Flask stuff:
+instance/
+.webassets-cache
+
+# Scrapy stuff:
+.scrapy
+
+# Sphinx documentation
+docs/_build/
+
+# PyBuilder
+target/
+
+# Jupyter Notebook
+.ipynb_checkpoints
+notebooks/
+
+# IPython
+profile_default/
+ipython_config.py
+
+# pyenv
+.python-version
+
+# pipenv
+#   According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
+#   However, in case of collaboration, if having platform-specific dependencies or dependencies
+#   having no cross-platform support, pipenv may install dependencies that don't work, or not
+#   install all needed dependencies.
+#Pipfile.lock
+
+# PEP 582; used by e.g. github.com/David-OConnor/pyflow
+__pypackages__/
+
+# Celery stuff
+celerybeat-schedule
+celerybeat.pid
+
+# SageMath parsed files
+*.sage.py
+
+# Environments
+.env
+.venv
+env/
+venv/
+ENV/
+env.bak/
+venv.bak/
+pyvenv.cfg
+
+# Spyder project settings
+.spyderproject
+.spyproject
+
+# Rope project settings
+.ropeproject
+
+# mkdocs documentation
+/site
+
+# mypy
+.mypy_cache/
+.dmypy.json
+dmypy.json
+
+# Pyre type checker
+.pyre/
+
+# Jetbrains
+.idea
+modules/
+*.swp
+
+# VsCode
+.vscode
+
+# pipenv
+Pipfile
+Pipfile.lock
+
+# pyright
+pyrightconfig.json
diff --git a/llama-index-cli/llama_index/cli/new_package/common/BUILD b/llama-index-cli/llama_index/cli/new_package/common/BUILD
new file mode 100644
index 0000000000000..db46e8d6c978c
--- /dev/null
+++ b/llama-index-cli/llama_index/cli/new_package/common/BUILD
@@ -0,0 +1 @@
+python_sources()
diff --git a/llama-index-cli/llama_index/cli/new_package/common/Makefile b/llama-index-cli/llama_index/cli/new_package/common/Makefile
new file mode 100644
index 0000000000000..b9eab05aa3706
--- /dev/null
+++ b/llama-index-cli/llama_index/cli/new_package/common/Makefile
@@ -0,0 +1,17 @@
+GIT_ROOT ?= $(shell git rev-parse --show-toplevel)
+
+help:	## Show all Makefile targets.
+	@grep -E '^[a-zA-Z_-]+:.*?## .*$$' $(MAKEFILE_LIST) | awk 'BEGIN {FS = ":.*?## "}; {printf "\033[33m%-30s\033[0m %s\n", $$1, $$2}'
+
+format:	## Run code autoformatters (black).
+	pre-commit install
+	git ls-files | xargs pre-commit run black --files
+
+lint:	## Run linters: pre-commit (black, ruff, codespell) and mypy
+	pre-commit install && git ls-files | xargs pre-commit run --show-diff-on-failure --files
+
+test:	## Run tests via pytest.
+	pytest tests
+
+watch-docs:	## Build and watch documentation.
+	sphinx-autobuild docs/ docs/_build/html --open-browser --watch $(GIT_ROOT)/llama_index/
diff --git a/llama-index-cli/llama_index/cli/new_package/templates/BUILD b/llama-index-cli/llama_index/cli/new_package/templates/BUILD
new file mode 100644
index 0000000000000..db46e8d6c978c
--- /dev/null
+++ b/llama-index-cli/llama_index/cli/new_package/templates/BUILD
@@ -0,0 +1 @@
+python_sources()
diff --git a/llama-index-cli/llama_index/cli/new_package/templates/__init__.py b/llama-index-cli/llama_index/cli/new_package/templates/__init__.py
new file mode 100644
index 0000000000000..1e8fff1879b1b
--- /dev/null
+++ b/llama-index-cli/llama_index/cli/new_package/templates/__init__.py
@@ -0,0 +1,8 @@
+from llama_index.cli.new_package.templates.pyproject import pyproject_str
+from llama_index.cli.new_package.templates.readme import readme_str
+from llama_index.cli.new_package.templates.init import (
+    init_str,
+    init_with_prefix_str,
+)
+
+__all__ = ["pyproject_str", "readme_str", "init_str", "init_with_prefix_str"]
diff --git a/llama-index-cli/llama_index/cli/new_package/templates/init.py b/llama-index-cli/llama_index/cli/new_package/templates/init.py
new file mode 100644
index 0000000000000..c91d15eb5c007
--- /dev/null
+++ b/llama-index-cli/llama_index/cli/new_package/templates/init.py
@@ -0,0 +1,11 @@
+init_str = """from llama_index.{TYPE}.{NAME}.base import <FILL>
+
+
+__all__ = ["<FILL>"]
+"""
+
+init_with_prefix_str = """from llama_index.{PREFIX}.{TYPE}.{NAME}.base import <FILL>
+
+
+__all__ = ["<FILL>"]
+"""
diff --git a/llama-index-cli/llama_index/cli/new_package/templates/pyproject.py b/llama-index-cli/llama_index/cli/new_package/templates/pyproject.py
new file mode 100644
index 0000000000000..7efdadb178a28
--- /dev/null
+++ b/llama-index-cli/llama_index/cli/new_package/templates/pyproject.py
@@ -0,0 +1,50 @@
+pyproject_str = """[build-system]
+requires = ["poetry-core"]
+build-backend = "poetry.core.masonry.api"
+
+[tool.codespell]
+check-filenames = true
+check-hidden = true
+# Feel free to un-skip examples, and experimental, you will just need to
+# work through many typos (--write-changes and --interactive will help)
+skip = "*.csv,*.html,*.json,*.jsonl,*.pdf,*.txt,*.ipynb"
+
+[tool.mypy]
+disallow_untyped_defs = true
+# Remove venv skip when integrated with pre-commit
+exclude = ["_static", "build", "examples", "notebooks", "venv"]
+ignore_missing_imports = true
+python_version = "3.8"
+
+[tool.poetry]
+name = "{PACKAGE_NAME}"
+version = "0.1.0"
+description = "llama-index {TYPE} {NAME} integration"
+authors = ["Your Name <you@example.com>"]
+license = "MIT"
+readme = "README.md"
+packages = [{{include = "llama_index/"}}]
+
+[tool.poetry.dependencies]
+python = ">=3.8.1,<4.0"
+llama-index-core = "^0.10.0"
+
+[tool.poetry.group.dev.dependencies]
+black = {{extras = ["jupyter"], version = "<=23.9.1,>=23.7.0"}}
+codespell = {{extras = ["toml"], version = ">=v2.2.6"}}
+ipython = "8.10.0"
+jupyter = "^1.0.0"
+mypy = "0.991"
+pre-commit = "3.2.0"
+pylint = "2.15.10"
+pytest = "7.2.1"
+pytest-mock = "3.11.1"
+ruff = "0.0.292"
+tree-sitter-languages = "^1.8.0"
+types-Deprecated = ">=0.1.0"
+types-PyYAML = "^6.0.12.12"
+types-protobuf = "^4.24.0.4"
+types-redis = "4.5.5.0"
+types-requests = "2.28.11.8" # TODO: unpin when mypy>0.991
+types-setuptools = "67.1.0.0"
+"""
diff --git a/llama-index-cli/llama_index/cli/new_package/templates/readme.py b/llama-index-cli/llama_index/cli/new_package/templates/readme.py
new file mode 100644
index 0000000000000..01b7924c68a62
--- /dev/null
+++ b/llama-index-cli/llama_index/cli/new_package/templates/readme.py
@@ -0,0 +1,2 @@
+readme_str = """# LlamaIndex {TYPE} Integration: {NAME}
+"""
diff --git a/llama-index-cli/llama_index/cli/rag/BUILD b/llama-index-cli/llama_index/cli/rag/BUILD
new file mode 100644
index 0000000000000..db46e8d6c978c
--- /dev/null
+++ b/llama-index-cli/llama_index/cli/rag/BUILD
@@ -0,0 +1 @@
+python_sources()
diff --git a/llama-index-cli/llama_index/cli/rag/__init__.py b/llama-index-cli/llama_index/cli/rag/__init__.py
new file mode 100644
index 0000000000000..e69de29bb2d1d
diff --git a/llama-index-cli/llama_index/cli/rag/base.py b/llama-index-cli/llama_index/cli/rag/base.py
new file mode 100644
index 0000000000000..041ab25ddf669
--- /dev/null
+++ b/llama-index-cli/llama_index/cli/rag/base.py
@@ -0,0 +1,389 @@
+import asyncio
+import os
+import shutil
+from argparse import ArgumentParser
+from glob import iglob
+from pathlib import Path
+from typing import Any, Callable, Dict, Optional, Union, cast
+
+from llama_index.core import (
+    Response,
+    ServiceContext,
+    SimpleDirectoryReader,
+    VectorStoreIndex,
+)
+from llama_index.core.base.embeddings.base import BaseEmbedding
+from llama_index.core.base.response.schema import RESPONSE_TYPE, StreamingResponse
+from llama_index.core.bridge.pydantic import BaseModel, Field, validator
+from llama_index.core.chat_engine import CondenseQuestionChatEngine
+from llama_index.core.ingestion import IngestionPipeline
+from llama_index.core.llms import LLM
+from llama_index.core.query_engine import CustomQueryEngine
+from llama_index.core.query_pipeline.components.function import FnComponent
+from llama_index.core.query_pipeline.query import QueryPipeline
+from llama_index.core.readers.base import BaseReader
+from llama_index.core.response_synthesizers import CompactAndRefine
+from llama_index.core.utils import get_cache_dir
+
+
+def _try_load_openai_llm():
+    try:
+        from llama_index.llms.openai import OpenAI  # pants: no-infer-dep
+
+        return OpenAI(model="gpt-3.5-turbo", streaming=True)
+    except ImportError:
+        raise ImportError(
+            "`llama-index-llms-openai` package not found, "
+            "please run `pip install llama-index-llms-openai`"
+        )
+
+
+RAG_HISTORY_FILE_NAME = "files_history.txt"
+
+
+def default_ragcli_persist_dir() -> str:
+    return str(Path(get_cache_dir()) / "rag_cli")
+
+
+def query_input(query_str: Optional[str] = None) -> str:
+    return query_str or ""
+
+
+class QueryPipelineQueryEngine(CustomQueryEngine):
+    query_pipeline: QueryPipeline = Field(
+        description="Query Pipeline to use for Q&A.",
+    )
+
+    def custom_query(self, query_str: str) -> RESPONSE_TYPE:
+        return self.query_pipeline.run(query_str=query_str)
+
+    async def acustom_query(self, query_str: str) -> RESPONSE_TYPE:
+        return await self.query_pipeline.arun(query_str=query_str)
+
+
+class RagCLI(BaseModel):
+    """
+    CLI tool for chatting with output of a IngestionPipeline via a QueryPipeline.
+    """
+
+    ingestion_pipeline: IngestionPipeline = Field(
+        description="Ingestion pipeline to run for RAG ingestion."
+    )
+    verbose: bool = Field(
+        description="Whether to print out verbose information during execution.",
+        default=False,
+    )
+    persist_dir: str = Field(
+        description="Directory to persist ingestion pipeline.",
+        default_factory=default_ragcli_persist_dir,
+    )
+    llm: LLM = Field(
+        description="Language model to use for response generation.",
+        default_factory=lambda: _try_load_openai_llm(),
+    )
+    query_pipeline: Optional[QueryPipeline] = Field(
+        description="Query Pipeline to use for Q&A.",
+        default=None,
+    )
+    chat_engine: Optional[CondenseQuestionChatEngine] = Field(
+        description="Chat engine to use for chatting.",
+        default_factory=None,
+    )
+    file_extractor: Optional[Dict[str, BaseReader]] = Field(
+        description="File extractor to use for extracting text from files.",
+        default=None,
+    )
+
+    class Config:
+        arbitrary_types_allowed = True
+
+    @validator("query_pipeline", always=True)
+    def query_pipeline_from_ingestion_pipeline(
+        cls, query_pipeline: Any, values: Dict[str, Any]
+    ) -> Optional[QueryPipeline]:
+        """
+        If query_pipeline is not provided, create one from ingestion_pipeline.
+        """
+        if query_pipeline is not None:
+            return query_pipeline
+
+        ingestion_pipeline = cast(IngestionPipeline, values["ingestion_pipeline"])
+        if ingestion_pipeline.vector_store is None:
+            return None
+        verbose = cast(bool, values["verbose"])
+        query_component = FnComponent(
+            fn=query_input, output_key="output", req_params={"query_str"}
+        )
+        llm = cast(LLM, values["llm"])
+
+        # get embed_model from transformations if possible
+        embed_model = None
+        if ingestion_pipeline.transformations is not None:
+            for transformation in ingestion_pipeline.transformations:
+                if isinstance(transformation, BaseEmbedding):
+                    embed_model = transformation
+                    break
+
+        service_context = ServiceContext.from_defaults(
+            llm=llm, embed_model=embed_model or "default"
+        )
+        retriever = VectorStoreIndex.from_vector_store(
+            ingestion_pipeline.vector_store, service_context=service_context
+        ).as_retriever(similarity_top_k=8)
+        response_synthesizer = CompactAndRefine(
+            service_context=service_context, streaming=True, verbose=verbose
+        )
+
+        # define query pipeline
+        query_pipeline = QueryPipeline(verbose=verbose)
+        query_pipeline.add_modules(
+            {
+                "query": query_component,
+                "retriever": retriever,
+                "summarizer": response_synthesizer,
+            }
+        )
+        query_pipeline.add_link("query", "retriever")
+        query_pipeline.add_link("retriever", "summarizer", dest_key="nodes")
+        query_pipeline.add_link("query", "summarizer", dest_key="query_str")
+        return query_pipeline
+
+    @validator("chat_engine", always=True)
+    def chat_engine_from_query_pipeline(
+        cls, chat_engine: Any, values: Dict[str, Any]
+    ) -> Optional[CondenseQuestionChatEngine]:
+        """
+        If chat_engine is not provided, create one from query_pipeline.
+        """
+        if chat_engine is not None:
+            return chat_engine
+
+        if values.get("query_pipeline", None) is None:
+            values["query_pipeline"] = cls.query_pipeline_from_ingestion_pipeline(
+                query_pipeline=None, values=values
+            )
+
+        query_pipeline = cast(QueryPipeline, values["query_pipeline"])
+        if query_pipeline is None:
+            return None
+        query_engine = QueryPipelineQueryEngine(query_pipeline=query_pipeline)  # type: ignore
+        verbose = cast(bool, values["verbose"])
+        llm = cast(LLM, values["llm"])
+        return CondenseQuestionChatEngine.from_defaults(
+            query_engine=query_engine, llm=llm, verbose=verbose
+        )
+
+    async def handle_cli(
+        self,
+        files: Optional[str] = None,
+        question: Optional[str] = None,
+        chat: bool = False,
+        verbose: bool = False,
+        clear: bool = False,
+        create_llama: bool = False,
+        **kwargs: Dict[str, Any],
+    ) -> None:
+        """
+        Entrypoint for local document RAG CLI tool.
+        """
+        if clear:
+            # delete self.persist_dir directory including all subdirectories and files
+            if os.path.exists(self.persist_dir):
+                # Ask for confirmation
+                response = input(
+                    f"Are you sure you want to delete data within {self.persist_dir}? [y/N] "
+                )
+                if response.strip().lower() != "y":
+                    print("Aborted.")
+                    return
+                os.system(f"rm -rf {self.persist_dir}")
+            print(f"Successfully cleared {self.persist_dir}")
+
+        self.verbose = verbose
+        ingestion_pipeline = cast(IngestionPipeline, self.ingestion_pipeline)
+        if self.verbose:
+            print("Saving/Loading from persist_dir: ", self.persist_dir)
+        if files is not None:
+            documents = []
+            for _file in iglob(files, recursive=True):
+                _file = os.path.abspath(_file)
+                if os.path.isdir(_file):
+                    reader = SimpleDirectoryReader(
+                        input_dir=_file,
+                        filename_as_id=True,
+                        file_extractor=self.file_extractor,
+                    )
+                else:
+                    reader = SimpleDirectoryReader(
+                        input_files=[_file],
+                        filename_as_id=True,
+                        file_extractor=self.file_extractor,
+                    )
+
+                documents.extend(reader.load_data(show_progress=verbose))
+
+            await ingestion_pipeline.arun(show_progress=verbose, documents=documents)
+            ingestion_pipeline.persist(persist_dir=self.persist_dir)
+
+            # Append the `--files` argument to the history file
+            with open(f"{self.persist_dir}/{RAG_HISTORY_FILE_NAME}", "a") as f:
+                f.write(files + "\n")
+
+        if create_llama:
+            if shutil.which("npx") is None:
+                print(
+                    "`npx` is not installed. Please install it by calling `npm install -g npx`"
+                )
+            else:
+                history_file_path = Path(f"{self.persist_dir}/{RAG_HISTORY_FILE_NAME}")
+                if not history_file_path.exists():
+                    print(
+                        "No data has been ingested, "
+                        "please specify `--files` to create llama dataset."
+                    )
+                else:
+                    with open(history_file_path) as f:
+                        stored_paths = {line.strip() for line in f if line.strip()}
+                    if len(stored_paths) == 0:
+                        print(
+                            "No data has been ingested, "
+                            "please specify `--files` to create llama dataset."
+                        )
+                    elif len(stored_paths) > 1:
+                        print(
+                            "Multiple files or folders were ingested, which is not supported by create-llama. "
+                            "Please call `llamaindex-cli rag --clear` to clear the cache first, "
+                            "then call `llamaindex-cli rag --files` again with a single folder or file"
+                        )
+                    else:
+                        path = stored_paths.pop()
+                        if "*" in path:
+                            print(
+                                "Glob pattern is not supported by create-llama. "
+                                "Please call `llamaindex-cli rag --clear` to clear the cache first, "
+                                "then call `llamaindex-cli rag --files` again with a single folder or file."
+                            )
+                        elif not os.path.exists(path):
+                            print(
+                                f"The path {path} does not exist. "
+                                "Please call `llamaindex-cli rag --clear` to clear the cache first, "
+                                "then call `llamaindex-cli rag --files` again with a single folder or file."
+                            )
+                        else:
+                            print(f"Calling create-llama using data from {path} ...")
+                            command_args = [
+                                "npx",
+                                "create-llama@latest",
+                                "--frontend",
+                                "--template",
+                                "streaming",
+                                "--framework",
+                                "fastapi",
+                                "--ui",
+                                "shadcn",
+                                "--vector-db",
+                                "none",
+                                "--engine",
+                                "context",
+                                f"--files {path}",
+                            ]
+                            os.system(" ".join(command_args))
+
+        if question is not None:
+            await self.handle_question(question)
+        if chat:
+            await self.start_chat_repl()
+
+    async def handle_question(self, question: str) -> None:
+        if self.query_pipeline is None:
+            raise ValueError("query_pipeline is not defined.")
+        query_pipeline = cast(QueryPipeline, self.query_pipeline)
+        query_pipeline.verbose = self.verbose
+        chat_engine = cast(CondenseQuestionChatEngine, self.chat_engine)
+        response = chat_engine.chat(question)
+
+        if isinstance(response, StreamingResponse):
+            response.print_response_stream()
+        else:
+            response = cast(Response, response)
+            print(response)
+
+    async def start_chat_repl(self) -> None:
+        """
+        Start a REPL for chatting with the agent.
+        """
+        if self.query_pipeline is None:
+            raise ValueError("query_pipeline is not defined.")
+        chat_engine = cast(CondenseQuestionChatEngine, self.chat_engine)
+        chat_engine.streaming_chat_repl()
+
+    @classmethod
+    def add_parser_args(
+        cls,
+        parser: Union[ArgumentParser, Any],
+        instance_generator: Optional[Callable[[], "RagCLI"]],
+    ) -> None:
+        if instance_generator:
+            parser.add_argument(
+                "-q",
+                "--question",
+                type=str,
+                help="The question you want to ask.",
+                required=False,
+            )
+
+            parser.add_argument(
+                "-f",
+                "--files",
+                type=str,
+                help=(
+                    "The name of the file or directory you want to ask a question about,"
+                    'such as "file.pdf".'
+                ),
+            )
+            parser.add_argument(
+                "-c",
+                "--chat",
+                help="If flag is present, opens a chat REPL.",
+                action="store_true",
+            )
+            parser.add_argument(
+                "-v",
+                "--verbose",
+                help="Whether to print out verbose information during execution.",
+                action="store_true",
+            )
+            parser.add_argument(
+                "--clear",
+                help="Clears out all currently embedded data.",
+                action="store_true",
+            )
+            parser.add_argument(
+                "--create-llama",
+                help="Create a LlamaIndex application with your embedded data.",
+                required=False,
+                action="store_true",
+            )
+            parser.set_defaults(
+                func=lambda args: asyncio.run(
+                    instance_generator().handle_cli(**vars(args))
+                )
+            )
+
+    def cli(self) -> None:
+        """
+        Entrypoint for CLI tool.
+        """
+        parser = ArgumentParser(description="LlamaIndex RAG Q&A tool.")
+        subparsers = parser.add_subparsers(
+            title="commands", dest="command", required=True
+        )
+        llamarag_parser = subparsers.add_parser(
+            "rag", help="Ask a question to a document / a directory of documents."
+        )
+        self.add_parser_args(llamarag_parser, lambda: self)
+        # Parse the command-line arguments
+        args = parser.parse_args()
+
+        # Call the appropriate function based on the command
+        args.func(args)
diff --git a/llama-index-cli/llama_index/cli/upgrade/BUILD b/llama-index-cli/llama_index/cli/upgrade/BUILD
new file mode 100644
index 0000000000000..db46e8d6c978c
--- /dev/null
+++ b/llama-index-cli/llama_index/cli/upgrade/BUILD
@@ -0,0 +1 @@
+python_sources()
diff --git a/llama-index-cli/llama_index/cli/upgrade/__init__.py b/llama-index-cli/llama_index/cli/upgrade/__init__.py
new file mode 100644
index 0000000000000..e69de29bb2d1d
diff --git a/llama-index-cli/llama_index/cli/upgrade/base.py b/llama-index-cli/llama_index/cli/upgrade/base.py
new file mode 100644
index 0000000000000..20db64956f3aa
--- /dev/null
+++ b/llama-index-cli/llama_index/cli/upgrade/base.py
@@ -0,0 +1,283 @@
+import json
+import os
+import re
+from pathlib import Path
+from typing import Dict, List, Tuple
+
+mappings_path = os.path.join(os.path.dirname(__file__), "mappings.json")
+
+
+def _parse_from_imports(
+    mappings: Dict[str, str],
+    installed_modules: List[str],
+    line_idx: int,
+    lines: List[str],
+    verbose: bool = False,
+):
+    new_lines = []
+    new_installs = []
+    imported_modules = []
+    parsing_modules = False
+    skipped_lines = 0
+
+    for line in lines[line_idx:]:
+        skipped_lines += 1
+        if "from " in line:
+            imported_modules = [line, line.strip().split(" import ")[-1].strip()]
+            if imported_modules[-1].startswith("("):
+                imported_modules[-1] = []
+                parsing_modules = True
+            else:
+                imported_modules = [line, imported_modules[-1].split(", ")]
+
+        if parsing_modules:
+            if ")" in line:
+                parsing_modules = False
+            elif "(" not in line:
+                imported_modules[-1].append(line.strip().replace(",", ""))
+
+        if not parsing_modules and len(imported_modules) > 0:
+            imported_module_names = [x.strip() for x in imported_modules[-1]]
+            new_imports = {}
+            for module in imported_module_names:
+                if module in mappings:
+                    new_import_parent = mappings[module]
+                    if new_import_parent not in new_imports:
+                        new_imports[new_import_parent] = [module]
+                    else:
+                        new_imports[new_import_parent].append(module)
+                else:
+                    print(f"Module not found: {module}\nSwitching to core")
+                    new_import_parent = (
+                        imported_modules[0]
+                        .split(" import ")[0]
+                        .split("from ")[-1]
+                        .replace("llama_index", "llama_index.core")
+                    )
+                    if new_import_parent not in new_imports:
+                        new_imports[new_import_parent] = [module]
+                    else:
+                        new_imports[new_import_parent].append(module)
+
+            for new_import_parent, new_imports in new_imports.items():
+                new_install_parent = new_import_parent.replace(".", "-").replace(
+                    "_", "-"
+                )
+                if new_install_parent not in installed_modules:
+                    overlap = [x for x in installed_modules if x in new_install_parent]
+                    if len(overlap) == 0:
+                        installed_modules.append(new_install_parent)
+                        new_installs.append(f"%pip install {new_install_parent}\n")
+                new_imports = ", ".join(new_imports)
+                new_lines.append(f"from {new_import_parent} import {new_imports}\n")
+
+                parsing_modules = False
+                new_imports = {}
+                imported_modules = []
+
+            return new_lines, new_installs, installed_modules, skipped_lines
+
+        elif not parsing_modules:
+            new_lines.append(line)
+
+    return new_lines, new_installs, installed_modules, skipped_lines
+
+
+def _parse_hub_downloads(
+    mappings: Dict[str, str],
+    installed_modules: List[str],
+    line: str,
+):
+    regex = r"download_loader\([\"']([A-Z,a-z]+)[\"'][\s,a-z,A-Z,_=]*\)|download_tool\([\"']([a-z,A-Z]+)[\"'][A-Z,a-z,\s,_=]*\)"
+    result = re.search(regex, line)
+    new_lines = []
+    new_installs = []
+    if result:
+        tool, reader = result.groups()
+        module = tool if tool else reader
+        if module in mappings:
+            new_import_parent = mappings[module]
+            new_lines.append(f"from {new_import_parent} import {module}\n")
+            new_install_parent = new_import_parent.replace(".", "-").replace("_", "-")
+            if new_install_parent not in installed_modules:
+                new_installs.append(f"%pip install {new_install_parent}\n")
+                installed_modules.append(new_install_parent)
+        else:
+            print(f"Reader/Tool not found: {module}\nKeeping line as is.")
+            new_lines.append(line)
+
+    return new_lines, new_installs, installed_modules
+
+
+def parse_lines(
+    lines: List[str], installed_modules: List[str], verbose: bool = False
+) -> Tuple[List[str], List[str]]:
+    with open(mappings_path) as f:
+        mappings = json.load(f)
+
+    new_installs = []
+    new_lines = []
+    just_found_imports = False
+    skipped_lines = 0
+
+    for idx, line in enumerate(lines):
+        this_new_lines = []
+        this_new_installs = []
+        this_installed_modules = []
+
+        if skipped_lines != 0:
+            skipped_lines -= 1
+
+        if just_found_imports and skipped_lines > 0:
+            continue
+        else:
+            just_found_imports = False
+
+        if (
+            "from llama_index." in line
+            or "from llama_index import" in line
+            or "from llama_hub." in line
+        ):
+            (
+                this_new_lines,
+                this_new_installs,
+                this_installed_modules,
+                skipped_lines,
+            ) = _parse_from_imports(
+                mappings=mappings,
+                installed_modules=installed_modules,
+                line_idx=idx,
+                lines=lines,
+                verbose=verbose,
+            )
+            just_found_imports = True
+
+        elif "download_loader(" in line or "download_tool(" in line:
+            (
+                this_new_lines,
+                this_new_installs,
+                this_installed_modules,
+            ) = _parse_hub_downloads(
+                mappings=mappings,
+                installed_modules=installed_modules,
+                line=line,
+            )
+
+        elif not just_found_imports:
+            this_new_lines = [line]
+
+        new_lines += this_new_lines
+        new_installs += this_new_installs
+        installed_modules += this_installed_modules
+        installed_modules = list(set(installed_modules))
+
+    return new_lines, list(set(new_installs))
+
+
+def _cell_installs_llama_hub(cell) -> bool:
+    lines = cell["source"]
+    llama_hub_partial_statements = [
+        "pip install llama-hub",
+        "import download_loader",
+        "import download_tool",
+    ]
+
+    if len(lines) > 1:
+        return False
+    if cell["cell_type"] == "code" and any(
+        el in lines[0] for el in llama_hub_partial_statements
+    ):
+        return True
+    return False
+
+
+def _format_new_installs(new_installs):
+    if new_installs:
+        new_installs = list(set(new_installs))
+        return new_installs[:-1] + [new_installs[-1].replace("\n", "")]
+    return new_installs
+
+
+def upgrade_nb_file(file_path):
+    print(f"\n=====================\n{file_path}\n", flush=True)
+    with open(file_path) as f:
+        notebook = json.load(f)
+
+    verbose = False
+    if file_path == "../docs/examples/managed/manage_retrieval_benchmark.ipynb":
+        verbose = True
+
+    installed_modules = ["llama-index-core"]  # default installs
+    cur_cells = []
+    new_installs = []
+    first_code_idx = -1
+    for idx, cell in enumerate(notebook["cells"]):
+        if cell["cell_type"] == "code":
+            if verbose:
+                print(f"cell: {cell}", flush=True)
+            if first_code_idx == -1:
+                first_code_idx = idx
+
+            code = cell["source"]
+
+            new_lines, cur_new_installs = parse_lines(code, installed_modules, verbose)
+            new_installs += cur_new_installs
+
+            cell["source"] = new_lines
+
+        cur_cells.append(cell)
+
+    if len(new_installs) > 0:
+        notebook["cells"] = cur_cells
+        new_cell = {
+            "cell_type": "code",
+            "metadata": {},
+            "execution_count": None,
+            "outputs": [],
+            "source": _format_new_installs(new_installs),
+        }
+        cur_cells.insert(first_code_idx, new_cell)
+
+    cur_cells = [cell for cell in cur_cells if not _cell_installs_llama_hub(cell)]
+    notebook["cells"] = cur_cells
+    with open(file_path, "w") as f:
+        json.dump(notebook, f, indent=1, ensure_ascii=False)
+
+
+def upgrade_py_md_file(file_path: str) -> None:
+    with open(file_path) as f:
+        lines = f.readlines()
+
+    installed_modules = ["llama-index-core"]  # default installs
+    new_lines, new_installs = parse_lines(lines, installed_modules)
+
+    with open(file_path, "w") as f:
+        f.write("".join(new_lines))
+
+    if len(new_installs) > 0:
+        print("New installs:")
+    for install in new_installs:
+        print(install.strip().replace("%", ""))
+
+
+def upgrade_file(file_path: str) -> None:
+    if file_path.endswith(".ipynb"):
+        upgrade_nb_file(file_path)
+    elif file_path.endswith((".py", ".md")):
+        upgrade_py_md_file(file_path)
+    else:
+        raise Exception(f"File type not supported: {file_path}")
+
+
+def _is_hidden(path: Path) -> bool:
+    return any(part.startswith(".") and part not in [".", ".."] for part in path.parts)
+
+
+def upgrade_dir(input_dir: str) -> None:
+    file_refs = list(Path(input_dir).rglob("*.py"))
+    file_refs += list(Path(input_dir).rglob("*.ipynb"))
+    file_refs += list(Path(input_dir).rglob("*.md"))
+    file_refs = [x for x in file_refs if not _is_hidden(x)]
+    for file_ref in file_refs:
+        if file_ref.is_file():
+            upgrade_file(str(file_ref))
diff --git a/llama-index-cli/llama_index/cli/upgrade/mappings.json b/llama-index-cli/llama_index/cli/upgrade/mappings.json
new file mode 100644
index 0000000000000..59855d154b8d3
--- /dev/null
+++ b/llama-index-cli/llama_index/cli/upgrade/mappings.json
@@ -0,0 +1,832 @@
+{
+  "StorageContext": "llama_index.core",
+  "ServiceContext": "llama_index.core",
+  "ComposableGraph": "llama_index.core",
+  "# indicesSummaryIndex": "llama_index.core",
+  "VectorStoreIndex": "llama_index.core",
+  "SimpleKeywordTableIndex": "llama_index.core",
+  "KeywordTableIndex": "llama_index.core",
+  "RAKEKeywordTableIndex": "llama_index.core",
+  "TreeIndex": "llama_index.core",
+  "DocumentSummaryIndex": "llama_index.core",
+  "KnowledgeGraphIndex": "llama_index.core",
+  "# indices - legacy namesGPTKeywordTableIndex": "llama_index.core",
+  "GPTKnowledgeGraphIndex": "llama_index.core",
+  "GPTSimpleKeywordTableIndex": "llama_index.core",
+  "GPTRAKEKeywordTableIndex": "llama_index.core",
+  "GPTListIndex": "llama_index.core",
+  "ListIndex": "llama_index.core",
+  "GPTTreeIndex": "llama_index.core",
+  "GPTVectorStoreIndex": "llama_index.core",
+  "GPTDocumentSummaryIndex": "llama_index.core",
+  "Prompt": "llama_index.core",
+  "PromptTemplate": "llama_index.core",
+  "BasePromptTemplate": "llama_index.core",
+  "ChatPromptTemplate": "llama_index.core",
+  "SelectorPromptTemplate": "llama_index.core",
+  "SummaryPrompt": "llama_index.core",
+  "TreeInsertPrompt": "llama_index.core",
+  "TreeSelectPrompt": "llama_index.core",
+  "TreeSelectMultiplePrompt": "llama_index.core",
+  "RefinePrompt": "llama_index.core",
+  "QuestionAnswerPrompt": "llama_index.core",
+  "KeywordExtractPrompt": "llama_index.core",
+  "QueryKeywordExtractPrompt": "llama_index.core",
+  "Response": "llama_index.core",
+  "Document": "llama_index.core",
+  "SimpleDirectoryReader": "llama_index.core",
+  "VellumPredictor": "llama_index.core",
+  "VellumPromptRegistry": "llama_index.core",
+  "MockEmbedding": "llama_index.core",
+  "SQLDatabase": "llama_index.core",
+  "SQLDocumentContextBuilder": "llama_index.core",
+  "SQLContextBuilder": "llama_index.core",
+  "PromptHelper": "llama_index.core",
+  "IndexStructType": "llama_index.core",
+  "download_loader": "llama_index.core",
+  "load_graph_from_storage": "llama_index.core",
+  "load_index_from_storage": "llama_index.core",
+  "load_indices_from_storage": "llama_index.core",
+  "QueryBundle": "llama_index.core",
+  "get_response_synthesizer": "llama_index.core",
+  "set_global_service_context": "llama_index.core",
+  "set_global_handler": "llama_index.core",
+  "set_global_tokenizer": "llama_index.core",
+  "get_tokenizer": "llama_index.core",
+  "AgentRunner": "llama_index.core.agent",
+  "ParallelAgentRunner": "llama_index.core.agent",
+  "ReActAgentWorker": "llama_index.core.agent",
+  "ReActAgent": "llama_index.core.agent",
+  "CustomSimpleAgentWorker": "llama_index.core.agent",
+  "QueryPipelineAgentWorker": "llama_index.core.agent",
+  "ReActChatFormatter": "llama_index.core.agent",
+  "# betaMultimodalReActAgentWorker": "llama_index.core.agent",
+  "# schema-relatedAgentChatResponse": "llama_index.core.agent",
+  "Task": "llama_index.core.agent",
+  "CallbackManager": "llama_index.core.callbacks",
+  "CBEvent": "llama_index.core.callbacks",
+  "CBEventType": "llama_index.core.callbacks",
+  "EventPayload": "llama_index.core.callbacks",
+  "LlamaDebugHandler": "llama_index.core.callbacks",
+  "TokenCountingHandler": "llama_index.core.callbacks",
+  "trace_method": "llama_index.core.callbacks",
+  "deepeval_callback_handler": "llama_index.callbacks.deepeval",
+  "OpenInferenceCallbackHandler": "llama_index.callbacks.openinference",
+  "WandbCallbackHandler": "llama_index.callbacks.wandb",
+  "argilla_callback_handler": "llama_index.callbacks.argilla",
+  "honeyhive_callback_handler": "llama_index.callbacks.honeyhive",
+  "arize_phoenix_callback_handler": "llama_index.callbacks.arize_phoenix",
+  "AimCallback": "llama_index.callbacks.aim",
+  "PromptLayerHandler": "llama_index.callbacks.promptlayer",
+  "SimpleChatEngine": "llama_index.core.chat_engine",
+  "CondenseQuestionChatEngine": "llama_index.core.chat_engine",
+  "ContextChatEngine": "llama_index.core.chat_engine",
+  "CondensePlusContextChatEngine": "llama_index.core.chat_engine",
+  "QASummaryQueryEngineBuilder": "llama_index.core.composability",
+  "IndexGraph": "llama_index.core.data_structs",
+  "KeywordTable": "llama_index.core.data_structs",
+  "IndexList": "llama_index.core.data_structs",
+  "IndexDict": "llama_index.core.data_structs",
+  "StructDatapoint": "llama_index.core.data_structs",
+  "Node": "llama_index.core.data_structs",
+  "BaseEmbedding": "llama_index.core.embeddings",
+  "MultiModalEmbedding": "llama_index.core.embeddings",
+  "Pooling": "llama_index.core.embeddings",
+  "BaseEvaluator": "llama_index.core.evaluation",
+  "AnswerRelevancyEvaluator": "llama_index.core.evaluation",
+  "ContextRelevancyEvaluator": "llama_index.core.evaluation",
+  "EvaluationResult": "llama_index.core.evaluation",
+  "FaithfulnessEvaluator": "llama_index.core.evaluation",
+  "RelevancyEvaluator": "llama_index.core.evaluation",
+  "RelevanceEvaluator": "llama_index.core.evaluation",
+  "DatasetGenerator": "llama_index.core.evaluation",
+  "QueryResponseDataset": "llama_index.core.evaluation",
+  "GuidelineEvaluator": "llama_index.core.evaluation",
+  "CorrectnessEvaluator": "llama_index.core.evaluation",
+  "SemanticSimilarityEvaluator": "llama_index.core.evaluation",
+  "PairwiseComparisonEvaluator": "llama_index.core.evaluation",
+  "BatchEvalRunner": "llama_index.core.evaluation",
+  "# legacy: kept for backward compatibilityQueryResponseEvaluator": "llama_index.core.evaluation",
+  "ResponseEvaluator": "llama_index.core.evaluation",
+  "# retrievalgenerate_qa_embedding_pairs": "llama_index.core.evaluation",
+  "generate_question_context_pairs": "llama_index.core.evaluation",
+  "EmbeddingQAFinetuneDataset": "llama_index.core.evaluation",
+  "BaseRetrievalEvaluator": "llama_index.core.evaluation",
+  "RetrievalEvalResult": "llama_index.core.evaluation",
+  "RetrieverEvaluator": "llama_index.core.evaluation",
+  "MultiModalRetrieverEvaluator": "llama_index.core.evaluation",
+  "RetrievalMetricResult": "llama_index.core.evaluation",
+  "resolve_metrics": "llama_index.core.evaluation",
+  "HitRate": "llama_index.core.evaluation",
+  "MRR": "llama_index.core.evaluation",
+  "get_retrieval_results_df": "llama_index.core.evaluation",
+  "LabelledQADataset": "llama_index.core.evaluation",
+  "SummaryExtractor": "llama_index.core.extractors",
+  "QuestionsAnsweredExtractor": "llama_index.core.extractors",
+  "TitleExtractor": "llama_index.core.extractors",
+  "KeywordExtractor": "llama_index.core.extractors",
+  "BaseExtractor": "llama_index.core.extractors",
+  "PydanticProgramExtractor": "llama_index.core.extractors",
+  "SimpleGraphStore": "llama_index.core.graph_stores",
+  "SummaryIndex": "llama_index.core",
+  "PandasIndex": "llama_index.core.indices",
+  "SQLStructStoreIndex": "llama_index.core.indices",
+  "MultiModalVectorStoreIndex": "llama_index.core.indices",
+  "EmptyIndex": "llama_index.core.indices",
+  "# legacyGPTKnowledgeGraphIndex": "llama_index.core.indices",
+  "GPTKeywordTableIndex": "llama_index.core.indices",
+  "GPTPandasIndex": "llama_index.core.indices",
+  "GPTSQLStructStoreIndex": "llama_index.core.indices",
+  "GPTEmptyIndex": "llama_index.core.indices",
+  "DocstoreStrategy": "llama_index.core.ingestion",
+  "IngestionCache": "llama_index.core.ingestion",
+  "IngestionPipeline": "llama_index.core.ingestion",
+  "run_transformations": "llama_index.core.ingestion",
+  "arun_transformations": "llama_index.core.ingestion",
+  "BaseLlamaDataset": "llama_index.core.llama_dataset",
+  "BaseLlamaDataExample": "llama_index.core.llama_dataset",
+  "BaseLlamaExamplePrediction": "llama_index.core.llama_dataset",
+  "BaseLlamaPredictionDataset": "llama_index.core.llama_dataset",
+  "LabelledRagDataExample": "llama_index.core.llama_dataset",
+  "LabelledRagDataset": "llama_index.core.llama_dataset",
+  "LabeledRagDataExample": "llama_index.core.llama_dataset",
+  "LabeledRagDataset": "llama_index.core.llama_dataset",
+  "RagExamplePrediction": "llama_index.core.llama_dataset",
+  "RagPredictionDataset": "llama_index.core.llama_dataset",
+  "CreatedByType": "llama_index.core.llama_dataset",
+  "CreatedBy": "llama_index.core.llama_dataset",
+  "download_llama_dataset": "llama_index.core.llama_dataset",
+  "EvaluatorExamplePrediction": "llama_index.core.llama_dataset",
+  "EvaluatorPredictionDataset": "llama_index.core.llama_dataset",
+  "LabeledEvaluatorDataset": "llama_index.core.llama_dataset",
+  "LabelledEvaluatorDataset": "llama_index.core.llama_dataset",
+  "LabelledEvaluatorDataExample": "llama_index.core.llama_dataset",
+  "LabeledEvaluatorDataExample": "llama_index.core.llama_dataset",
+  "LabelledPairwiseEvaluatorDataExample": "llama_index.core.llama_dataset",
+  "LabelledPairwiseEvaluatorDataset": "llama_index.core.llama_dataset",
+  "LabeledPairwiseEvaluatorDataExample": "llama_index.core.llama_dataset",
+  "LabeledPairwiseEvaluatorDataset": "llama_index.core.llama_dataset",
+  "PairwiseEvaluatorExamplePrediction": "llama_index.core.llama_dataset",
+  "PairwiseEvaluatorPredictionDataset": "llama_index.core.llama_dataset",
+  "BaseLlamaPack": "llama_index.core.llama_pack",
+  "download_llama_pack": "llama_index.core.llama_pack",
+  "CustomLLM": "llama_index.core.llms",
+  "LLM": "llama_index.core.llms",
+  "ChatMessage": "llama_index.core.llms",
+  "ChatResponse": "llama_index.core.llms",
+  "ChatResponseAsyncGen": "llama_index.core.llms",
+  "ChatResponseGen": "llama_index.core.llms",
+  "CompletionResponse": "llama_index.core.llms",
+  "CompletionResponseAsyncGen": "llama_index.core.llms",
+  "CompletionResponseGen": "llama_index.core.llms",
+  "LLMMetadata": "llama_index.core.llms",
+  "MessageRole": "llama_index.core.llms",
+  "BaseMemory": "llama_index.core.memory",
+  "ChatMemoryBuffer": "llama_index.core.memory",
+  "MultiModalLLMMetadata": "llama_index.core.multi_modal_llms",
+  "MultiModalLLM": "llama_index.core.multi_modal_llms",
+  "TokenTextSplitter": "llama_index.core.node_parser",
+  "SentenceSplitter": "llama_index.core.node_parser",
+  "CodeSplitter": "llama_index.core.node_parser",
+  "SimpleFileNodeParser": "llama_index.core.node_parser",
+  "HTMLNodeParser": "llama_index.core.node_parser",
+  "MarkdownNodeParser": "llama_index.core.node_parser",
+  "JSONNodeParser": "llama_index.core.node_parser",
+  "SentenceWindowNodeParser": "llama_index.core.node_parser",
+  "SemanticSplitterNodeParser": "llama_index.core.node_parser",
+  "NodeParser": "llama_index.core.node_parser",
+  "HierarchicalNodeParser": "llama_index.core.node_parser",
+  "TextSplitter": "llama_index.core.node_parser",
+  "MarkdownElementNodeParser": "llama_index.core.node_parser",
+  "MetadataAwareTextSplitter": "llama_index.core.node_parser",
+  "LangchainNodeParser": "llama_index.core.node_parser",
+  "UnstructuredElementNodeParser": "llama_index.core.node_parser",
+  "get_leaf_nodes": "llama_index.core.node_parser",
+  "get_root_nodes": "llama_index.core.node_parser",
+  "# deprecated": "llama_index.core.node_parser",
+  "for backwards compatibilitySimpleNodeParser": "llama_index.core.node_parser",
+  "ObjectRetriever": "llama_index.core.objects",
+  "ObjectIndex": "llama_index.core.objects",
+  "SimpleObjectNodeMapping": "llama_index.core.objects",
+  "SimpleToolNodeMapping": "llama_index.core.objects",
+  "SimpleQueryToolNodeMapping": "llama_index.core.objects",
+  "SQLTableNodeMapping": "llama_index.core.objects",
+  "SQLTableSchema": "llama_index.core.objects",
+  "ChainableOutputParser": "llama_index.core.output_parsers",
+  "LangchainOutputParser": "llama_index.core.output_parsers",
+  "PydanticOutputParser": "llama_index.core.output_parsers",
+  "SelectionOutputParser": "llama_index.core.output_parsers",
+  "Playground": "llama_index.core.playground",
+  "DEFAULT_INDEX_CLASSES": "llama_index.core.playground",
+  "DEFAULT_MODES": "llama_index.core.playground",
+  "SimilarityPostprocessor": "llama_index.core.postprocessor",
+  "KeywordNodePostprocessor": "llama_index.core.postprocessor",
+  "PrevNextNodePostprocessor": "llama_index.core.postprocessor",
+  "AutoPrevNextNodePostprocessor": "llama_index.core.postprocessor",
+  "FixedRecencyPostprocessor": "llama_index.core.postprocessor",
+  "EmbeddingRecencyPostprocessor": "llama_index.core.postprocessor",
+  "TimeWeightedPostprocessor": "llama_index.core.postprocessor",
+  "PIINodePostprocessor": "llama_index.core.postprocessor",
+  "NERPIINodePostprocessor": "llama_index.core.postprocessor",
+  "LLMRerank": "llama_index.core.postprocessor",
+  "SentenceEmbeddingOptimizer": "llama_index.core.postprocessor",
+  "SentenceTransformerRerank": "llama_index.core.postprocessor",
+  "MetadataReplacementPostProcessor": "llama_index.core.postprocessor",
+  "LongContextReorder": "llama_index.core.postprocessor",
+  "BasePydanticProgram": "llama_index.core.program",
+  "LLMTextCompletionProgram": "llama_index.core.program",
+  "MultiModalLLMCompletionProgram": "llama_index.core.program",
+  "LangchainPromptTemplate": "llama_index.core.prompts",
+  "PromptType": "llama_index.core.prompts",
+  "display_prompt_dict": "llama_index.core.prompts",
+  "CitationQueryEngine": "llama_index.core.query_engine",
+  "CogniswitchQueryEngine": "llama_index.core.query_engine",
+  "ComposableGraphQueryEngine": "llama_index.core.query_engine",
+  "RetrieverQueryEngine": "llama_index.core.query_engine",
+  "TransformQueryEngine": "llama_index.core.query_engine",
+  "MultiStepQueryEngine": "llama_index.core.query_engine",
+  "RouterQueryEngine": "llama_index.core.query_engine",
+  "RetrieverRouterQueryEngine": "llama_index.core.query_engine",
+  "ToolRetrieverRouterQueryEngine": "llama_index.core.query_engine",
+  "SubQuestionQueryEngine": "llama_index.core.query_engine",
+  "SubQuestionAnswerPair": "llama_index.core.query_engine",
+  "SQLJoinQueryEngine": "llama_index.core.query_engine",
+  "SQLAutoVectorQueryEngine": "llama_index.core.query_engine",
+  "RetryQueryEngine": "llama_index.core.query_engine",
+  "RetrySourceQueryEngine": "llama_index.core.query_engine",
+  "RetryGuidelineQueryEngine": "llama_index.core.query_engine",
+  "FLAREInstructQueryEngine": "llama_index.core.query_engine",
+  "PandasQueryEngine": "llama_index.core.query_engine",
+  "JSONalyzeQueryEngine": "llama_index.core.query_engine",
+  "KnowledgeGraphQueryEngine": "llama_index.core.query_engine",
+  "BaseQueryEngine": "llama_index.core.query_engine",
+  "CustomQueryEngine": "llama_index.core.query_engine",
+  "# multimodalSimpleMultiModalQueryEngine": "llama_index.core.query_engine",
+  "# SQLSQLTableRetrieverQueryEngine": "llama_index.core.query_engine",
+  "NLSQLTableQueryEngine": "llama_index.core.query_engine",
+  "PGVectorSQLQueryEngine": "llama_index.core.query_engine",
+  "AgentFnComponent": "llama_index.core.query_pipeline",
+  "AgentInputComponent": "llama_index.core.query_pipeline",
+  "ArgPackComponent": "llama_index.core.query_pipeline",
+  "FnComponent": "llama_index.core.query_pipeline",
+  "InputComponent": "llama_index.core.query_pipeline",
+  "RouterComponent": "llama_index.core.query_pipeline",
+  "ToolRunnerComponent": "llama_index.core.query_pipeline",
+  "QueryPipeline": "llama_index.core.query_pipeline",
+  "LLMQuestionGenerator": "llama_index.core.question_gen",
+  "SubQuestionOutputParser": "llama_index.core.question_gen",
+  "ReaderConfig": "llama_index.core.readers",
+  "PDFReader": "llama_index.readers.file",
+  "HTMLTagReader": "llama_index.readers.file",
+  "StringIterableReader": "llama_index.core.readers",
+  "ResponseMode": "llama_index.core.response_synthesizers",
+  "BaseSynthesizer": "llama_index.core.response_synthesizers",
+  "Refine": "llama_index.core.response_synthesizers",
+  "SimpleSummarize": "llama_index.core.response_synthesizers",
+  "TreeSummarize": "llama_index.core.response_synthesizers",
+  "Generation": "llama_index.core.response_synthesizers",
+  "CompactAndRefine": "llama_index.core.response_synthesizers",
+  "Accumulate": "llama_index.core.response_synthesizers",
+  "VectorIndexRetriever": "llama_index.core.retrievers",
+  "VectorIndexAutoRetriever": "llama_index.core.retrievers",
+  "SummaryIndexRetriever": "llama_index.core.retrievers",
+  "SummaryIndexEmbeddingRetriever": "llama_index.core.retrievers",
+  "SummaryIndexLLMRetriever": "llama_index.core.retrievers",
+  "KGTableRetriever": "llama_index.core.retrievers",
+  "KnowledgeGraphRAGRetriever": "llama_index.core.retrievers",
+  "EmptyIndexRetriever": "llama_index.core.retrievers",
+  "TreeAllLeafRetriever": "llama_index.core.retrievers",
+  "TreeSelectLeafEmbeddingRetriever": "llama_index.core.retrievers",
+  "TreeSelectLeafRetriever": "llama_index.core.retrievers",
+  "TreeRootRetriever": "llama_index.core.retrievers",
+  "TransformRetriever": "llama_index.core.retrievers",
+  "KeywordTableSimpleRetriever": "llama_index.core.retrievers",
+  "BaseRetriever": "llama_index.core.retrievers",
+  "RecursiveRetriever": "llama_index.core.retrievers",
+  "AutoMergingRetriever": "llama_index.core.retrievers",
+  "RouterRetriever": "llama_index.core.retrievers",
+  "BM25Retriever": "llama_index.core.retrievers",
+  "QueryFusionRetriever": "llama_index.core.retrievers",
+  "# SQLSQLRetriever": "llama_index.core.retrievers",
+  "NLSQLRetriever": "llama_index.core.retrievers",
+  "SQLParserMode": "llama_index.core.retrievers",
+  "# legacyListIndexEmbeddingRetriever": "llama_index.core.retrievers",
+  "ListIndexRetriever": "llama_index.core.retrievers",
+  "# imageBaseImageRetriever": "llama_index.core.retrievers",
+  "LLMSingleSelector": "llama_index.core.selectors",
+  "LLMMultiSelector": "llama_index.core.selectors",
+  "EmbeddingSingleSelector": "llama_index.core.selectors",
+  "PydanticSingleSelector": "llama_index.core.selectors",
+  "PydanticMultiSelector": "llama_index.core.selectors",
+  "BaseTool": "llama_index.core.tools",
+  "adapt_to_async_tool": "llama_index.core.tools",
+  "AsyncBaseTool": "llama_index.core.tools",
+  "QueryEngineTool": "llama_index.core.tools",
+  "RetrieverTool": "llama_index.core.tools",
+  "ToolMetadata": "llama_index.core.tools",
+  "ToolOutput": "llama_index.core.tools",
+  "FunctionTool": "llama_index.core.tools",
+  "QueryPlanTool": "llama_index.core.tools",
+  "download_tool": "llama_index.core.tools",
+  "VectorStoreQuery": "llama_index.core.vector_stores",
+  "VectorStoreQueryResult": "llama_index.core.vector_stores",
+  "MetadataFilters": "llama_index.core.vector_stores",
+  "MetadataFilter": "llama_index.core.vector_stores",
+  "ExactMatchFilter": "llama_index.core.vector_stores",
+  "FilterCondition": "llama_index.core.vector_stores",
+  "FilterOperator": "llama_index.core.vector_stores",
+  "SimpleVectorStore": "llama_index.core.vector_stores",
+  "BaseParamTuner": "llama_index.experimental.param_tuner",
+  "ParamTuner": "llama_index.experimental.param_tuner",
+  "AsyncParamTuner": "llama_index.experimental.param_tuner",
+  "RayTuneParamTuner": "llama_index.experimental.param_tuner",
+  "OpenAIFinetuneEngine": "llama_index.finetuning",
+  "generate_qa_embedding_pairs": "llama_index.finetuning",
+  "SentenceTransformersFinetuneEngine": "llama_index.finetuning",
+  "EmbeddingAdapterFinetuneEngine": "llama_index.finetuning",
+  "GradientFinetuneEngine": "llama_index.finetuning",
+  "generate_cohere_reranker_finetuning_dataset": "llama_index.finetuning",
+  "CohereRerankerFinetuneEngine": "llama_index.finetuning",
+  "BaseFinetuningHandler": "llama_index.finetuning.callbacks",
+  "OpenAIFineTuningHandler": "llama_index.finetuning.callbacks",
+  "CrossEncoderFinetuneEngine": "llama_index.finetuning.cross_encoders",
+  "CohereRerankerFinetuneDataset": "llama_index.finetuning.rerankers",
+  "SingleStoreVectorStore": "llama_index.vector_stores.singlestoredb",
+  "QdrantVectorStore": "llama_index.vector_stores.qdrant",
+  "PineconeVectorStore": "llama_index.vector_stores.pinecone",
+  "SupabaseVectorStore": "llama_index.vector_stores.supabase",
+  "AstraDBVectorStore": "llama_index.vector_stores.astra",
+  "LanceDBVectorStore": "llama_index.vector_stores.lancedb",
+  "ElasticsearchStore": "llama_index.vector_stores.elasticsearch",
+  "PGVectorStore": "llama_index.vector_stores.postgres",
+  "CassandraVectorStore": "llama_index.vector_stores.cassandra",
+  "ZepVectorStore": "llama_index.vector_stores.zep",
+  "RocksetVectorStore": "llama_index.vector_stores.rocksetdb",
+  "MyScaleVectorStore": "llama_index.vector_stores.myscale",
+  "TencentVectorDB": "llama_index.vector_stores.tencentvectordb",
+  "MilvusVectorStore": "llama_index.vector_stores.milvus",
+  "Neo4jVectorStore": "llama_index.vector_stores.neo4jvector",
+  "DeepLakeVectorStore": "llama_index.vector_stores.deeplake",
+  "WeaviateVectorStore": "llama_index.vector_stores.weaviate",
+  "TimescaleVectorStore": "llama_index.vector_stores.timescalevector",
+  "DashVectorStore": "llama_index.vector_stores.dashvector",
+  "JaguarVectorStore": "llama_index.vector_stores.jaguar",
+  "FaissVectorStore": "llama_index.vector_stores.faiss",
+  "MongoDBAtlasVectorSearch": "llama_index.vector_stores.mongodb",
+  "ChromaVectorStore": "llama_index.vector_stores.chroma",
+  "BagelVectorStore": "llama_index.vector_stores.bagel",
+  "TxtaiVectorStore": "llama_index.vector_stores.txtai",
+  "EpsillaVectorStore": "llama_index.vector_stores.epsilla",
+  "LanternVectorStore": "llama_index.vector_stores.lantern",
+  "AwaDBVectorStore": "llama_index.vector_stores.awadb",
+  "AzureCosmosDBMongoDBVectorSearch": "llama_index.vector_stores.azurecosmosmongo",
+  "TypesenseVectorStore": "llama_index.vector_stores.typesense",
+  "PGVectoRsStore": "llama_index.vector_stores.pgvecto_rs",
+  "OpensearchVectorStore": "llama_index.vector_stores.opensearch",
+  "DocArrayInMemoryVectorStore": "llama_index.vector_stores.docarray",
+  "DocArrayHnswVectorStore": "llama_index.vector_stores.docarray",
+  "DynamoDBVectorStore": "llama_index.vector_stores.dynamodb",
+  "ChatGPTRetrievalPluginClient": "llama_index.vector_stores.chatgpt_plugin",
+  "TairVectorStore": "llama_index.vector_stores.tair",
+  "CognitiveSearchVectorStore": "llama_index.vector_stores.cogsearch",
+  "RedisVectorStore": "llama_index.vector_stores.redis",
+  "set_google_config": "llama_index.vector_stores.google",
+  "GoogleVectorStore": "llama_index.vector_stores.google",
+  "MetalVectorStore": "llama_index.vector_stores.metal",
+  "PathwayRetriever": "llama_index.retrievers.pathway",
+  "YouRetriever": "llama_index.retrievers.you",
+  "ZillizCloudPipelineIndex": "llama_index.indices.managed.zilliz",
+  "ZillizCloudPipelineRetriever": "llama_index.indices.managed.zilliz",
+  "ColbertIndex": "llama_index.indices.managed.colbert",
+  "VectaraIndex": "llama_index.indices.managed.vectara",
+  "VectaraRetriever": "llama_index.indices.managed.vectara",
+  "VectaraAutoRetriever": "llama_index.indices.managed.vectara",
+  "GoogleIndex": "llama_index.indices.managed.google",
+  "SalesforceToolSpec": "llama_index.tools.salesforce",
+  "PythonFileToolSpec": "llama_index.tools.python_file",
+  "TextToImageToolSpec": "llama_index.tools.text_to_image",
+  "OpenAPIToolSpec": "llama_index.tools.openapi",
+  "IonicShoppingToolSpec": "llama_index.tools.ionic_shopping",
+  "ShopifyToolSpec": "llama_index.tools.shopify",
+  "MetaphorToolSpec": "llama_index.tools.metaphor",
+  "ACTION_URL_TMPL": "llama_index.tools.zapier",
+  "ExaToolSpec": "llama_index.tools.exa",
+  "ZapierToolSpec": "llama_index.tools.zapier",
+  "WikipediaToolSpec": "llama_index.tools.wikipedia",
+  "GoogleCalendarToolSpec": "llama_index.tools.google",
+  "GmailToolSpec": "llama_index.tools.google",
+  "GoogleSearchToolSpec": "llama_index.tools.google",
+  "QUERY_URL_TMPL": "llama_index.tools.google",
+  "AzureTranslateToolSpec": "llama_index.tools.azure_translate",
+  "ENDPOINT_BASE_URL": "llama_index.tools.azure_translate",
+  "MultionToolSpec": "llama_index.tools.multion",
+  "DatabaseToolSpec": "llama_index.tools.database",
+  "ChatGPTPluginToolSpec": "llama_index.tools.chatgpt_plugin",
+  "Neo4jQueryToolSpec": "llama_index.tools.neo4j",
+  "BingSearchToolSpec": "llama_index.tools.bing_search",
+  "CogniswitchToolSpec": "llama_index.tools.cogniswitch",
+  "AzureCVToolSpec": "llama_index.tools.azure_cv",
+  "CV_URL_TMPL": "llama_index.tools.azure_cv",
+  "NotionToolSpec": "llama_index.tools.notion",
+  "YelpToolSpec": "llama_index.tools.yelp",
+  "OpenWeatherMapToolSpec": "llama_index.tools.weather",
+  "AzureSpeechToolSpec": "llama_index.tools.azure_speech",
+  "WolframAlphaToolSpec": "llama_index.tools.wolfram_alpha",
+  "SlackToolSpec": "llama_index.tools.slack",
+  "TavilyToolSpec": "llama_index.tools.tavily_research",
+  "ArxivToolSpec": "llama_index.tools.arxiv",
+  "VectorDB": "llama_index.tools.vector_db",
+  "VectorDBToolSpec": "llama_index.tools.vector_db",
+  "CodeInterpreterToolSpec": "llama_index.tools.code_interpreter",
+  "WaiiToolSpec": "llama_index.tools.waii",
+  "INVALID_URL_PROMPT": "llama_index.tools.requests",
+  "RequestsToolSpec": "llama_index.tools.requests",
+  "OpenAIImageGenerationToolSpec": "llama_index.tools.openai",
+  "GraphQLToolSpec": "llama_index.tools.graphql",
+  "PlaygroundsSubgraphConnectorToolSpec": "llama_index.tools.playgrounds",
+  "PlaygroundsSubgraphInspectorToolSpec": "llama_index.tools.playgrounds",
+  "ClipEmbedding": "llama_index.embeddings.clip",
+  "AnyscaleEmbedding": "llama_index.embeddings.anyscale",
+  "LLMRailsEmbedding": "llama_index.embeddings.llm_rails",
+  "LLMRailsEmbeddings": "llama_index.embeddings.llm_rails",
+  "AdapterEmbeddingModel": "llama_index.embeddings.adapter",
+  "TogetherEmbedding": "llama_index.embeddings.together",
+  "VoyageEmbedding": "llama_index.embeddings.voyageai",
+  "GradientEmbedding": "llama_index.embeddings.gradient",
+  "HuggingFaceEmbedding": "llama_index.embeddings.huggingface",
+  "HuggingFaceInferenceAPIEmbedding": "llama_index.embeddings.huggingface",
+  "HuggingFaceInferenceAPIEmbeddings": "llama_index.embeddings.huggingface",
+  "OllamaEmbedding": "llama_index.embeddings.ollama",
+  "SageMakerEmbedding": "llama_index.embeddings.sagemaker_endpoint",
+  "OpenAIEmbedding": "llama_index.embeddings.openai",
+  "OpenAIEmbeddingMode": "llama_index.embeddings.openai",
+  "OpenAIEmbeddingModelType": "llama_index.embeddings.openai",
+  "OpenAIEmbeddingModeModel": "llama_index.embeddings.openai",
+  "CohereEmbedding": "llama_index.embeddings.cohere",
+  "JinaEmbedding": "llama_index.embeddings.jinaai",
+  "NomicEmbedding": "llama_index.embeddings.nomic",
+  "GeminiEmbedding": "llama_index.embeddings.gemini",
+  "FastEmbedEmbedding": "llama_index.embeddings.fastembed",
+  "InstructorEmbedding": "llama_index.embeddings.instructor",
+  "OptimumEmbedding": "llama_index.embeddings.huggingface_optimum",
+  "LangchainEmbedding": "llama_index.embeddings.langchain",
+  "GooglePaLMEmbedding": "llama_index.embeddings.google",
+  "GoogleUnivSentEncoderEmbedding": "llama_index.embeddings.google",
+  "MistralAIEmbedding": "llama_index.embeddings.mistralai",
+  "BedrockEmbedding": "llama_index.embeddings.bedrock",
+  "ClarifaiEmbedding": "llama_index.embeddings.clarifai",
+  "ElasticsearchEmbedding": "llama_index.embeddings.elasticsearch",
+  "AzureOpenAIEmbedding": "llama_index.embeddings.azure_openai",
+  "TextEmbeddingsInference": "llama_index.embeddings.text_embeddings_inference",
+  "LongLLMLinguaPostprocessor": "llama_index.postprocessor.longllmlingua",
+  "RankGPTRerank": "llama_index.postprocessor.rankgpt_rerank",
+  "CohereRerank": "llama_index.postprocessor.cohere_rerank",
+  "FlagEmbeddingReranker": "llama_index.postprocessor.flag_embedding_reranker",
+  "Neo4jGraphStore": "llama_index.graph_stores.neo4j",
+  "FalkorDBGraphStore": "llama_index.graph_stores.falkordb",
+  "KuzuGraphStore": "llama_index.graph_stores.kuzu",
+  "NebulaGraphStore": "llama_index.graph_stores.nebula",
+  "OpenAIMultiModal": "llama_index.multi_modal_llms.openai",
+  "AzureOpenAIMultiModal": "llama_index.multi_modal_llms.azure_openai",
+  "ReplicateMultiModal": "llama_index.multi_modal_llms.replicate",
+  "GeminiMultiModal": "llama_index.multi_modal_llms.gemini",
+  "OllamaMultiModal": "llama_index.multi_modal_llms.ollama",
+  "DashScopeMultiModal": "llama_index.multi_modal_llms.dashscope",
+  "DashScopeMultiModalModels": "llama_index.multi_modal_llms.dashscope",
+  "OpenAIAgent": "llama_index.agent.openai",
+  "OpenAIAgentWorker": "llama_index.agent.openai",
+  "OpenAIAssistantAgent": "llama_index.agent.openai",
+  "BaseOpenAIAgent": "llama_index.agent.openai_legacy",
+  "FnRetrieverOpenAIAgent": "llama_index.agent.openai_legacy",
+  "ContextRetrieverOpenAIAgent": "llama_index.agent.openai_legacy",
+  "PostgresKVStore": "llama_index.storage.kvstore.postgres",
+  "RedisKVStore": "llama_index.storage.kvstore.redis",
+  "FirestoreKVStore": "llama_index.storage.kvstore.firestore",
+  "MongoDBKVStore": "llama_index.storage.kvstore.mongodb",
+  "S3DBKVStore": "llama_index.storage.kvstore.s3",
+  "DynamoDBKVStore": "llama_index.storage.kvstore.dynamodb",
+  "DynamoDBDocumentStore": "llama_index.storage.docstore.dynamodb",
+  "MongoDocumentStore": "llama_index.storage.docstore.mongodb",
+  "FirestoreDocumentStore": "llama_index.storage.docstore.firestore",
+  "RedisDocumentStore": "llama_index.storage.docstore.redis",
+  "PostgresDocumentStore": "llama_index.storage.docstore.postgres",
+  "PostgresIndexStore": "llama_index.storage.index_store.postgres",
+  "DynamoDBIndexStore": "llama_index.storage.index_store.dynamodb",
+  "FirestoreIndexStore": "llama_index.storage.index_store.firestore",
+  "MongoIndexStore": "llama_index.storage.index_store.mongodb",
+  "RedisIndexStore": "llama_index.storage.index_store.redis",
+  "RedisChatStore": "llama_index.storage.chat_store.redis",
+  "GuardrailsOutputParser": "llama_index.output_parsers.guardrails",
+  "OpenAIPydanticProgram": "llama_index.program.openai",
+  "LMFormatEnforcerPydanticProgram": "llama_index.program.lmformatenforcer",
+  "GuidancePydanticProgram": "llama_index.program.guidance",
+  "BaseEvaporateProgram": "llama_index.program.evaporate",
+  "DFEvaporateProgram": "llama_index.program.evaporate",
+  "GoogleTextSynthesizer": "llama_index.response_synthesizers.google",
+  "SynthesizedResponse": "llama_index.response_synthesizers.google",
+  "AnswerConsistencyEvaluator": "llama_index.evaluation.tonic_validate",
+  "AnswerConsistencyBinaryEvaluator": "llama_index.evaluation.tonic_validate",
+  "AnswerSimilarityEvaluator": "llama_index.evaluation.tonic_validate",
+  "AugmentationAccuracyEvaluator": "llama_index.evaluation.tonic_validate",
+  "AugmentationPrecisionEvaluator": "llama_index.evaluation.tonic_validate",
+  "RetrievalPrecisionEvaluator": "llama_index.evaluation.tonic_validate",
+  "TonicValidateEvaluator": "llama_index.evaluation.tonic_validate",
+  "BaseReader": "llama_index.core.readers.base",
+  "DocugamiReader": "llama_index.readers.docugami",
+  "SlackReader": "llama_index.readers.slack",
+  "GeniusReader": "llama_index.readers.genius",
+  "YoutubeTranscriptReader": "llama_index.readers.youtube_transcript",
+  "MboxReader": "llama_index.readers.mbox",
+  "StackoverflowReader": "llama_index.readers.stackoverflow",
+  "PdbAbstractReader": "llama_index.readers.pdb",
+  "SnowflakeReader": "llama_index.readers.snowflake",
+  "DiscordReader": "llama_index.readers.discord",
+  "EarningsCallTranscript": "llama_index.readers.earnings_call_transcript",
+  "SimpleCouchDBReader": "llama_index.readers.couchdb",
+  "CouchbaseReader": "llama_index.readers.couchbase",
+  "SingleStoreReader": "llama_index.readers.singlestore",
+  "JSONReader": "llama_index.readers.json",
+  "TrelloReader": "llama_index.readers.trello",
+  "JaguarReader": "llama_index.readers.jaguar",
+  "JiraReader": "llama_index.readers.jira",
+  "PDFTableReader": "llama_index.readers.pdf_table",
+  "KibelaReader": "llama_index.readers.kibela",
+  "DashVectorReader": "llama_index.readers.dashvector",
+  "BilibiliTranscriptReader": "llama_index.readers.bilibili",
+  "SmartPDFLoader": "llama_index.readers.smart_pdf_loader",
+  "AgentSearchReader": "llama_index.readers.agent_search",
+  "MacrometaGDNReader": "llama_index.readers.macrometa_gdn",
+  "TwitterTweetReader": "llama_index.readers.twitter",
+  "AstraDBReader": "llama_index.readers.astra_db",
+  "OpendalReader": "llama_index.readers.opendal",
+  "OpendalAzblobReader": "llama_index.readers.opendal",
+  "OpendalGcsReader": "llama_index.readers.opendal",
+  "OpendalS3Reader": "llama_index.readers.opendal",
+  "AzStorageBlobReader": "llama_index.readers.azstorage_blob",
+  "ReadwiseReader": "llama_index.readers.readwise",
+  "ApifyActor": "llama_index.readers.apify",
+  "ApifyDataset": "llama_index.readers.apify",
+  "SimpleArangoDBReader": "llama_index.readers.arango_db",
+  "AthenaReader": "llama_index.readers.athena",
+  "DatabaseReader": "llama_index.readers.database",
+  "RemoteReader": "llama_index.readers.remote",
+  "AsanaReader": "llama_index.readers.asana",
+  "HiveReader": "llama_index.readers.hive",
+  "DocstringWalker": "llama_index.readers.docstring_walker",
+  "AirbyteSalesforceReader": "llama_index.readers.airbyte_salesforce",
+  "StripeDocsReader": "llama_index.readers.stripe_docs",
+  "MilvusReader": "llama_index.readers.milvus",
+  "PDFNougatOCR": "llama_index.readers.nougat_ocr",
+  "AssemblyAIAudioTranscriptReader": "llama_index.readers.assemblyai",
+  "GraphDBCypherReader": "llama_index.readers.graphdb_cypher",
+  "ConfluenceReader": "llama_index.readers.confluence",
+  "LilacReader": "llama_index.readers.lilac",
+  "GithubClient": "llama_index.readers.github",
+  "GithubRepositoryReader": "llama_index.readers.github",
+  "GitHubRepositoryCollaboratorsReader": "llama_index.readers.github",
+  "GitHubRepositoryIssuesReader": "llama_index.readers.github",
+  "GitHubIssuesClient": "llama_index.readers.github",
+  "WikipediaReader": "llama_index.readers.wikipedia",
+  "SimpleMongoReader": "llama_index.readers.mongodb",
+  "NotionPageReader": "llama_index.readers.notion",
+  "WordpressReader": "llama_index.readers.wordpress",
+  "XMLReader": "llama_index.readers.file",
+  "PagedCSVReader": "llama_index.readers.file",
+  "AirbyteTypeformReader": "llama_index.readers.airbyte_typeform",
+  "AirbyteZendeskSupportReader": "llama_index.readers.airbyte_zendesk_support",
+  "FirestoreReader": "llama_index.readers.firestore",
+  "OutlookLocalCalendarReader": "llama_index.readers.microsoft_outlook",
+  "S3Reader": "llama_index.readers.s3",
+  "SemanticScholarReader": "llama_index.readers.semanticscholar",
+  "WordLiftLoader": "llama_index.readers.wordlift",
+  "SpotifyReader": "llama_index.readers.spotify",
+  "AirbyteCDKReader": "llama_index.readers.airbyte_cdk",
+  "QdrantReader": "llama_index.readers.qdrant",
+  "FeedlyRssReader": "llama_index.readers.feedly_rss",
+  "AirbyteShopifyReader": "llama_index.readers.airbyte_shopify",
+  "ElasticsearchReader": "llama_index.readers.elasticsearch",
+  "RayyanReader": "llama_index.readers.rayyan",
+  "FirebaseRealtimeDatabaseReader": "llama_index.readers.firebase_realtimedb",
+  "RemoteDepthReader": "llama_index.readers.remote_depth",
+  "MakeWrapper": "llama_index.readers.make_com",
+  "MangaDexReader": "llama_index.readers.mangadex",
+  "IntercomReader": "llama_index.readers.intercom",
+  "AirbyteGongReader": "llama_index.readers.airbyte_gong",
+  "RedditReader": "llama_index.readers.reddit",
+  "FaissReader": "llama_index.readers.faiss",
+  "DadJokesReader": "llama_index.readers.dad_jokes",
+  "PatentsviewReader": "llama_index.readers.patentsview",
+  "MyScaleReader": "llama_index.readers.myscale",
+  "escape_str": "llama_index.readers.myscale",
+  "format_list_to_string": "llama_index.readers.myscale",
+  "GuruReader": "llama_index.readers.guru",
+  "LinearReader": "llama_index.readers.linear",
+  "TelegramReader": "llama_index.readers.telegram",
+  "SteamshipFileReader": "llama_index.readers.steamship",
+  "OpenMap": "llama_index.readers.maps",
+  "PathwayReader": "llama_index.readers.pathway",
+  "AirbyteHubspotReader": "llama_index.readers.airbyte_hubspot",
+  "HatenaBlogReader": "llama_index.readers.hatena_blog",
+  "SECFilingsLoader": "llama_index.readers.sec_filings",
+  "JoplinReader": "llama_index.readers.joplin",
+  "LINK_NOTE_TEMPLATE": "llama_index.readers.joplin",
+  "GraphQLReader": "llama_index.readers.graphql",
+  "BagelReader": "llama_index.readers.bagel",
+  "PreprocessReader": "llama_index.readers.preprocess",
+  "GoogleDocsReader": "llama_index.readers.google",
+  "GoogleSheetsReader": "llama_index.readers.google",
+  "GoogleCalendarReader": "llama_index.readers.google",
+  "GoogleDriveReader": "llama_index.readers.google",
+  "GmailReader": "llama_index.readers.google",
+  "GoogleKeepReader": "llama_index.readers.google",
+  "FeishuDocsReader": "llama_index.readers.feishu_docs",
+  "OpenAlexReader": "llama_index.readers.openalex",
+  "TxtaiReader": "llama_index.readers.txtai",
+  "AzCognitiveSearchReader": "llama_index.readers.azcognitive_search",
+  "PineconeReader": "llama_index.readers.pinecone",
+  "PandasAIReader": "llama_index.readers.pandas_ai",
+  "AirtableReader": "llama_index.readers.airtable",
+  "ZulipReader": "llama_index.readers.zulip",
+  "ZendeskReader": "llama_index.readers.zendesk",
+  "BitbucketReader": "llama_index.readers.bitbucket",
+  "AsyncWebPageReader": "llama_index.readers.web",
+  "BeautifulSoupWebReader": "llama_index.readers.web",
+  "KnowledgeBaseWebReader": "llama_index.readers.web",
+  "MainContentExtractorReader": "llama_index.readers.web",
+  "NewsArticleReader": "llama_index.readers.web",
+  "ReadabilityWebPageReader": "llama_index.readers.web",
+  "RssReader": "llama_index.readers.web",
+  "RssNewsReader": "llama_index.readers.web",
+  "SimpleWebPageReader": "llama_index.readers.web",
+  "SitemapReader": "llama_index.readers.web",
+  "TrafilaturaWebReader": "llama_index.readers.web",
+  "UnstructuredURLLoader": "llama_index.readers.web",
+  "WholeSiteReader": "llama_index.readers.web",
+  "HubspotReader": "llama_index.readers.hubspot",
+  "DocxReader": "llama_index.readers.file",
+  "HWPReader": "llama_index.readers.file",
+  "EpubReader": "llama_index.readers.file",
+  "FlatReader": "llama_index.readers.file",
+  "ImageCaptionReader": "llama_index.readers.file",
+  "ImageReader": "llama_index.readers.file",
+  "ImageVisionLLMReader": "llama_index.readers.file",
+  "IPYNBReader": "llama_index.readers.file",
+  "MarkdownReader": "llama_index.readers.file",
+  "PptxReader": "llama_index.readers.file",
+  "PandasCSVReader": "llama_index.readers.file",
+  "VideoAudioReader": "llama_index.readers.file",
+  "UnstructuredReader": "llama_index.readers.file",
+  "PyMuPDFReader": "llama_index.readers.file",
+  "ImageTabularChartReader": "llama_index.readers.file",
+  "CSVReader": "llama_index.readers.file.tabular",
+  "KalturaESearchReader": "llama_index.readers.kaltura_esearch",
+  "AwadbReader": "llama_index.readers.awadb",
+  "IMDBReviews": "llama_index.readers.imdb_review",
+  "OpensearchReader": "llama_index.readers.opensearch",
+  "SharePointReader": "llama_index.readers.microsoft_sharepoint",
+  "MangoppsGuidesReader": "llama_index.readers.mangoapps_guides",
+  "GPTRepoReader": "llama_index.readers.gpt_repo",
+  "get_ignore_list": "llama_index.readers.gpt_repo",
+  "process_repository": "llama_index.readers.gpt_repo",
+  "should_ignore": "llama_index.readers.gpt_repo",
+  "OneDriveReader": "llama_index.readers.microsoft_onedrive",
+  "HuggingFaceFSReader": "llama_index.readers.huggingface_fs",
+  "WeaviateReader": "llama_index.readers.weaviate",
+  "DeepLakeReader": "llama_index.readers.deeplake",
+  "WhatsappChatLoader": "llama_index.readers.whatsapp",
+  "MondayReader": "llama_index.readers.mondaydotcom",
+  "AirbyteStripeReader": "llama_index.readers.airbyte_stripe",
+  "SnscrapeTwitterReader": "llama_index.readers.snscrape_twitter",
+  "ArxivReader": "llama_index.readers.papers",
+  "PubmedReader": "llama_index.readers.papers",
+  "ObsidianReader": "llama_index.readers.obsidian",
+  "ZepReader": "llama_index.readers.zep",
+  "MemosReader": "llama_index.readers.memos",
+  "PsychicReader": "llama_index.readers.psychic",
+  "ChromaReader": "llama_index.readers.chroma",
+  "WeatherReader": "llama_index.readers.weather",
+  "ChatGPTRetrievalPluginReader": "llama_index.readers.chatgpt_plugin",
+  "MetalReader": "llama_index.readers.metal",
+  "BoardDocsReader": "llama_index.readers.boarddocs",
+  "GuidanceQuestionGenerator": "llama_index.question_gen.guidance",
+  "OpenAIQuestionGenerator": "llama_index.question_gen.openai",
+  "PaLM": "llama_index.llms.palm",
+  "DashScope": "llama_index.llms.dashscope",
+  "DashScopeGenerationModels": "llama_index.llms.dashscope",
+  "WatsonX": "llama_index.llms.watsonx",
+  "Cohere": "llama_index.llms.cohere",
+  "NvidiaTriton": "llama_index.llms.nvidia_triton",
+  "AI21": "llama_index.llms.ai21",
+  "Bedrock": "llama_index.llms.bedrock",
+  "HuggingFaceLLM": "llama_index.llms.huggingface",
+  "HuggingFaceInferenceAPI": "llama_index.llms.huggingface",
+  "AzureOpenAI": "llama_index.llms.azure_openai",
+  "LocalTensorRTLLM": "llama_index.llms.nvidia_tensorrt",
+  "Anthropic": "llama_index.llms.anthropic",
+  "Gemini": "llama_index.llms.gemini",
+  "Clarifai": "llama_index.llms.clarifai",
+  "LlamaAPI": "llama_index.llms.llama_api",
+  "LlamaCPP": "llama_index.llms.llama_cpp",
+  "Perplexity": "llama_index.llms.perplexity",
+  "RunGptLLM": "llama_index.llms.rungpt",
+  "Replicate": "llama_index.llms.replicate",
+  "OpenAILike": "llama_index.llms.openai_like",
+  "Konko": "llama_index.llms.konko",
+  "OpenLLM": "llama_index.llms.openllm",
+  "OpenLLMAPI": "llama_index.llms.openllm",
+  "LiteLLM": "llama_index.llms.litellm",
+  "SageMakerLLM": "llama_index.llms.sagemaker_endpoint",
+  "Portkey": "llama_index.llms.portkey",
+  "Vllm": "llama_index.llms.vllm",
+  "Neutrino": "llama_index.llms.neutrino",
+  "MonsterLLM": "llama_index.llms.monsterapi",
+  "PredibaseLLM": "llama_index.llms.predibase",
+  "Xinference": "llama_index.llms.xinference",
+  "MistralAI": "llama_index.llms.mistralai",
+  "Anyscale": "llama_index.llms.anyscale",
+  "Vertex": "llama_index.llms.vertex",
+  "LocalAI": "llama_index.llms.localai",
+  "TogetherLLM": "llama_index.llms.together",
+  "Ollama": "llama_index.llms.ollama",
+  "LangChainLLM": "llama_index.llms.langchain",
+  "EverlyAI": "llama_index.llms.everlyai",
+  "OpenRouter": "llama_index.llms.openrouter",
+  "OpenAI": "llama_index.llms.openai",
+  "Tokenizer": "llama_index.llms.openai",
+  "GradientBaseModelLLM": "llama_index.llms.gradient",
+  "GradientModelAdapterLLM": "llama_index.llms.gradient",
+  "EntityExtractor": "llama_index.extractors.entity",
+  "MarvinMetadataExtractor": "llama_index.extractors.marvin",
+  "WeaviateRetryEnginePack": "llama_index.packs.retry_engine_weaviate",
+  "LlavaCompletionPack": "llama_index.packs.llava_completion",
+  "VannaPack": "llama_index.packs.vanna",
+  "VannaQueryEngine": "llama_index.packs.vanna",
+  "ZephyrQueryEnginePack": "llama_index.packs.zephyr_query_engine",
+  "TimescaleVectorAutoretrievalPack": "llama_index.packs.timescale_vector_autoretrieval",
+  "MultiDocumentAgentsPack": "llama_index.packs.multi_document_agents",
+  "MultiDocAutoRetrieverPack": "llama_index.packs.multidoc_autoretrieval",
+  "GmailOpenAIAgentPack": "llama_index.packs.gmail_openai_agent",
+  "Neo4jQueryEnginePack": "llama_index.packs.neo4j_query_engine",
+  "ChromaAutoretrievalPack": "llama_index.packs.chroma_autoretrieval",
+  "ResumeScreenerPack": "llama_index.packs.resume_screener",
+  "TruLensRAGTriadPack": "llama_index.packs.trulens_eval_packs",
+  "TruLensHarmlessPack": "llama_index.packs.trulens_eval_packs",
+  "TruLensHelpfulPack": "llama_index.packs.trulens_eval_packs",
+  "EvaluatorBenchmarkerPack": "llama_index.packs.evaluator_benchmarker",
+  "RAGFusionPipelinePack": "llama_index.packs.rag_fusion_query_pipeline",
+  "LlamaGuardModeratorPack": "llama_index.packs.llama_guard_moderator",
+  "SnowflakeQueryEnginePack": "llama_index.packs.snowflake_query_engine",
+  "LlamaDatasetMetadataPack": "llama_index.packs.llama_dataset_metadata",
+  "StockMarketDataQueryEnginePack": "llama_index.packs.stock_market_data_query_engine",
+  "RagEvaluatorPack": "llama_index.packs.rag_evaluator",
+  "ArizePhoenixQueryEnginePack": "llama_index.packs.arize_phoenix_query_engine",
+  "PanelChatPack": "llama_index.packs.panel_chatbot",
+  "MultiTenancyRAGPack": "llama_index.packs.multi_tenancy_rag",
+  "StreamlitChatPack": "llama_index.packs.streamlit_chatbot",
+  "VectaraRagPack": "llama_index.packs.vectara_rag",
+  "ChainOfTablePack": "llama_index.packs.tables",
+  "MixSelfConsistencyPack": "llama_index.packs.tables",
+  "SelfRAGPack": "llama_index.packs.self_rag",
+  "SelfRAGQueryEngine": "llama_index.packs.self_rag",
+  "SemanticChunkingQueryEnginePack": "llama_index.packs.node_parser_semantic_chunking",
+  "RedisIngestionPipelinePack": "llama_index.packs.redis_ingestion_pipeline",
+  "DenseXRetrievalPack": "llama_index.packs.dense_x_retrieval",
+  "LocalRAGCLIPack": "llama_index.packs.rag_cli_local",
+  "InferRetrieveRerankPack": "llama_index.packs.infer_retrieve_rerank",
+  "AutoMergingRetrieverPack": "llama_index.packs.auto_merging_retriever",
+  "LLMCompilerAgentPack": "llama_index.packs.agents_llm_compiler",
+  "GradioReActAgentPack": "llama_index.packs.gradio_react_agent_chatbot",
+  "WeaviateSubQuestionPack": "llama_index.packs.sub_question_weaviate",
+  "DeepMemoryRetrieverPack": "llama_index.packs.deeplake_deepmemory_retriever",
+  "NebulaGraphQueryEnginePack": "llama_index.packs.nebulagraph_query_engine",
+  "VoyageQueryEnginePack": "llama_index.packs.voyage_query_engine",
+  "SentenceWindowRetrieverPack": "llama_index.packs.sentence_window_retriever",
+  "EmbeddedTablesUnstructuredRetrieverPack": "llama_index.packs.recursive_retriever",
+  "RecursiveRetrieverSmallToBigPack": "llama_index.packs.recursive_retriever",
+  "AmazonProductExtractionPack": "llama_index.packs.amazon_product_extraction",
+  "CogniswitchAgentPack": "llama_index.packs.cogniswitch_agent",
+  "OllamaQueryEnginePack": "llama_index.packs.ollama_query_engine",
+  "RAGatouilleRetrieverPack": "llama_index.packs.ragatouille_retriever",
+  "FuzzyCitationEnginePack": "llama_index.packs.fuzzy_citation",
+  "DeepLakeMultimodalRetrieverPack": "llama_index.packs.deeplake_multimodal_retrieval",
+  "GradioAgentChatPack": "llama_index.packs.gradio_agent_chat",
+  "AgentSearchRetriever": "llama_index.packs.agent_search_retriever",
+  "AgentSearchRetrieverPack": "llama_index.packs.agent_search_retriever",
+  "HybridFusionRetrieverPack": "llama_index.packs.fusion_retriever",
+  "QueryRewritingRetrieverPack": "llama_index.packs.fusion_retriever",
+  "BaseNode": "llama_index.core.schema",
+  "TextNode": "llama_index.core.schema",
+  "ImageNode": "llama_index.core.schema",
+  "ImageDocument": "llama_index.core.schema",
+  "NodeWithScore": "llama_index.core.schema",
+  "run_jobs": "llama_index.core.async_utils",
+  "DecomposeQueryTransform": "llama_index.core.query.query_transform.base",
+  "get_eval_results": "llama_index.core.evaluation.eval_utils",
+  "VectorStoreInfo": "llama_index.core.vector_stores",
+  "MetadataInfo": "llama_index.core.vector_stores",
+  "UpstashVectorStore": "llama_index.vector_stores.upstash",
+  "AzureAISearchVectorStore": "llama_index.vector_stores.azureaisearch",
+  "CognitiveSearchVectorStore": "llama_index.vector_stores.azureaisearch",
+  "IndexManagement": "llama_index.vector_stores.azureaisearch",
+  "REPLICATE_MULTI_MODAL_LLM_MODELS": "llama_index.multi_modal_llms.replicate.base"
+}
diff --git a/llama-index-cli/poetry.lock b/llama-index-cli/poetry.lock
new file mode 100644
index 0000000000000..3ed6c4dc07ba2
--- /dev/null
+++ b/llama-index-cli/poetry.lock
@@ -0,0 +1,6002 @@
+# This file is automatically @generated by Poetry 1.7.1 and should not be changed by hand.
+
+[[package]]
+name = "aiohttp"
+version = "3.9.3"
+description = "Async http client/server framework (asyncio)"
+optional = false
+python-versions = ">=3.8"
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+[package.dependencies]
+idna = ">=2.0"
+multidict = ">=4.0"
+
+[[package]]
+name = "zipp"
+version = "3.17.0"
+description = "Backport of pathlib-compatible object wrapper for zip files"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "zipp-3.17.0-py3-none-any.whl", hash = "sha256:0e923e726174922dce09c53c59ad483ff7bbb8e572e00c7f7c46b88556409f31"},
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+]
+
+[package.extras]
+docs = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (<7.2.5)", "sphinx (>=3.5)", "sphinx-lint"]
+testing = ["big-O", "jaraco.functools", "jaraco.itertools", "more-itertools", "pytest (>=6)", "pytest-black (>=0.3.7)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=2.2)", "pytest-ignore-flaky", "pytest-mypy (>=0.9.1)", "pytest-ruff"]
+
+[metadata]
+lock-version = "2.0"
+python-versions = ">=3.8.1,<3.12"
+content-hash = "a0c6f7be872d5ca99b5cbba9da4916e5b54805026cdebbda71f7320e0a0f03df"
diff --git a/llama-index-cli/pyproject.toml b/llama-index-cli/pyproject.toml
new file mode 100644
index 0000000000000..ea9fda4493b1e
--- /dev/null
+++ b/llama-index-cli/pyproject.toml
@@ -0,0 +1,63 @@
+[build-system]
+build-backend = "poetry.core.masonry.api"
+requires = ["poetry-core"]
+
+[tool.codespell]
+check-filenames = true
+check-hidden = true
+# Feel free to un-skip examples, and experimental, you will just need to
+# work through many typos (--write-changes and --interactive will help)
+skip = "*.csv,*.html,*.json,*.jsonl,*.pdf,*.txt,*.ipynb"
+
+[tool.mypy]
+disallow_untyped_defs = true
+# Remove venv skip when integrated with pre-commit
+exclude = ["_static", "build", "examples", "notebooks", "venv"]
+ignore_missing_imports = true
+python_version = "3.8"
+
+[tool.poetry]
+authors = ["llamaindex"]
+description = "llama-index cli"
+license = "MIT"
+maintainers = [
+    "Andrei Fajardo <andrei@runllama.ai>",
+    "Haotian Zhang <ht@runllama.ai>",
+    "Jerry Liu <jerry@llamaindex.ai>",
+    "Logan Markewich <logan@llamaindex.ai>",
+    "Simon Suo <simon@llamaindex.ai>",
+    "Sourabh Desai <sourabh@llamaindex.ai>",
+]
+name = "llama-index-cli"
+packages = [{include = "llama_index/"}]
+readme = "README.md"
+version = "0.1.0"
+
+[tool.poetry.dependencies]
+python = ">=3.8.1,<3.12"
+llama-index-core = "^0.10.3"
+llama-index-vector-stores-chroma = "^0.1.1"
+llama-index-embeddings-openai = "^0.1.1"
+llama-index-llms-openai = "^0.1.1"
+
+[tool.poetry.group.dev.dependencies]
+black = {extras = ["jupyter"], version = "<=23.9.1,>=23.7.0"}
+codespell = {extras = ["toml"], version = ">=v2.2.6"}
+ipython = "8.10.0"
+jupyter = "^1.0.0"
+mypy = "0.991"
+pre-commit = "3.2.0"
+pylint = "2.15.10"
+pytest = "7.2.1"
+pytest-mock = "3.11.1"
+ruff = "0.0.292"
+tree-sitter-languages = "^1.8.0"
+types-Deprecated = ">=0.1.0"
+types-PyYAML = "^6.0.12.12"
+types-protobuf = "^4.24.0.4"
+types-redis = "4.5.5.0"
+types-requests = "2.28.11.8"  # TODO: unpin when mypy>0.991
+types-setuptools = "67.1.0.0"
+
+[tool.poetry.scripts]
+llamaindex-cli = 'llama_index.cli.command_line:main'
diff --git a/llama-index-cli/tests/BUILD b/llama-index-cli/tests/BUILD
new file mode 100644
index 0000000000000..41045da0d0fa5
--- /dev/null
+++ b/llama-index-cli/tests/BUILD
@@ -0,0 +1,3 @@
+python_tests(
+    skip_tests=True,
+)
diff --git a/llama-index-cli/tests/__init__.py b/llama-index-cli/tests/__init__.py
new file mode 100644
index 0000000000000..e69de29bb2d1d
diff --git a/llama-index-cli/tests/test_cli.py b/llama-index-cli/tests/test_cli.py
new file mode 100644
index 0000000000000..e69de29bb2d1d