From 55f71fe2b65d365104ce6d44398521698bf3e079 Mon Sep 17 00:00:00 2001
From: konrad-czarnota-ds <konrad.czarnota@deepsense.ai>
Date: Tue, 15 Oct 2024 14:36:39 +0200
Subject: [PATCH 1/4] example: create e2e rag application

---
 .../examples/documents_chat.py                | 171 ++++++++++++++++++
 1 file changed, 171 insertions(+)
 create mode 100644 packages/ragbits-document-search/examples/documents_chat.py

diff --git a/packages/ragbits-document-search/examples/documents_chat.py b/packages/ragbits-document-search/examples/documents_chat.py
new file mode 100644
index 00000000..b5d4121d
--- /dev/null
+++ b/packages/ragbits-document-search/examples/documents_chat.py
@@ -0,0 +1,171 @@
+# /// script
+# requires-python = ">=3.10"
+# dependencies = [
+#     "gradio",
+#     "ragbits-document-search",
+#     "ragbits-core[chromadb, litellm]",
+# ]
+# ///
+from pathlib import Path
+from typing import AsyncIterator
+
+import chromadb
+import gradio as gr
+from pydantic import BaseModel
+
+from ragbits.core.embeddings.litellm import LiteLLMEmbeddings
+from ragbits.core.llms.litellm import LiteLLM
+from ragbits.core.prompt import Prompt
+from ragbits.core.vector_store.chromadb_store import ChromaDBStore
+from ragbits.document_search import DocumentSearch
+from ragbits.document_search.documents.document import DocumentMeta
+from ragbits.document_search.documents.element import TextElement
+
+
+class QueryWithContext(BaseModel):
+    """
+    Input format for the QueryWithContext.
+    """
+
+    query: str
+    context: list[str]
+
+
+class ChatAnswer(BaseModel):
+    """
+    Output format for the ChatAnswer.
+    """
+
+    answer: str
+
+
+class RAGPrompt(Prompt[QueryWithContext, ChatAnswer]):
+    """
+    A simple prompt for RAG system.
+    """
+
+    system_prompt = """
+    You are a helpful assistant. Answer the QUESTION that will be provided using CONTEXT.
+    If in the given CONTEXT there is not enough information refuse to answer.
+    """
+
+    user_prompt = """
+    QUESTION:
+    {{ query }}
+
+    CONTEXT:
+    {% for item in context %}
+        {{ item }}
+    {% endfor %}
+    """
+
+
+class RAGSystemWithUI:
+    """
+    Simple RAG application
+    """
+
+    DATABASE_CREATED_MESSAGE = "Database created and saved at: "
+    DATABASE_LOADED_MESSAGE = "Database loaded"
+    NO_DOCUMENTS_INGESTED_MESSAGE = (
+        "Before making queries you need to select documents and create database or "
+        "provide a path to an existing database"
+    )
+    DOCUMENT_PICKER_LABEL = "Documents"
+    DATABASE_TEXT_BOX_LABEL = "Database path"
+    DATABASE_CREATE_BUTTON_LABEL = "Create Database"
+    DATABASE_LOAD_BUTTON_LABEL = "Load Database"
+    DATABASE_CREATION_STATUS_LABEL = "Database creation status"
+    DATABASE_CREATION_STATUS_PLACEHOLDER = "Upload files and click 'Create Database' to start..."
+    DATABASE_LOADING_STATUS_LABEL = "Database loading status"
+    DATABASE_LOADING_STATUS_PLACEHOLDER = "Click 'Load Database' to start..."
+
+    def __init__(
+        self,
+        database_path: str = "chroma",
+        index_name: str = "documents",
+        model_name: str = "gpt-4o-2024-08-06",
+        columns_ratios: tuple[int, int] = (1, 5),
+        chatbot_height_vh: int = 90,
+    ) -> None:
+        self._database_path = database_path
+        self._index_name = index_name
+        self._columns_ratios = columns_ratios
+        self._chatbot_height_vh = chatbot_height_vh
+        self._documents_ingested = False
+        self._prepare_document_search(self._database_path, self._index_name)
+        self._llm = LiteLLM(model_name, use_structured_output=True)
+
+    def _prepare_document_search(self, database_path: str, index_name: str) -> None:
+        chroma_client = chromadb.PersistentClient(path=database_path)
+        embedding_client = LiteLLMEmbeddings()
+
+        vector_store = ChromaDBStore(
+            index_name=index_name,
+            chroma_client=chroma_client,
+            embedding_function=embedding_client,
+        )
+        self.document_search = DocumentSearch(embedder=vector_store.embedding_function, vector_store=vector_store)
+
+    async def _create_database(self, document_paths: list[str]) -> str:
+        for path in document_paths:
+            await self.document_search.ingest_document(DocumentMeta.from_local_path(Path(path)))
+        self._documents_ingested = True
+        return self.DATABASE_CREATED_MESSAGE + self._database_path
+
+    def _load_database(self, database_path: str) -> str:
+        self._prepare_document_search(database_path, self._index_name)
+        self._documents_ingested = True
+        return self.DATABASE_LOADED_MESSAGE
+
+    async def _handle_message(
+        self, message: str, history: list[dict]  # pylint: disable=unused-argument
+    ) -> AsyncIterator[str]:
+        if not self._documents_ingested:
+            yield self.NO_DOCUMENTS_INGESTED_MESSAGE
+        results = await self.document_search.search(message[-1])
+        prompt = RAGPrompt(
+            QueryWithContext(query=message, context=[i.content for i in results if isinstance(i, TextElement)])
+        )
+        response = await self._llm.generate(prompt)
+        yield response.answer
+
+    def prepare_layout(self) -> gr.Blocks:
+        """
+        Crates gradio layout as gr.Blocks and connects component events with proper handlers
+
+        Returns:
+            gradio layout
+        """
+        with gr.Blocks(fill_height=True, fill_width=True) as app:
+            with gr.Row():
+                with gr.Column(scale=self._columns_ratios[0]):
+                    with gr.Group():
+                        documents_picker = gr.File(file_count="multiple", label=self.DOCUMENT_PICKER_LABEL)
+                        create_btn = gr.Button(self.DATABASE_CREATE_BUTTON_LABEL)
+                        creating_status_display = gr.Textbox(
+                            label=self.DATABASE_CREATION_STATUS_LABEL,
+                            interactive=False,
+                            placeholder=self.DATABASE_CREATION_STATUS_PLACEHOLDER,
+                        )
+
+                    with gr.Group():
+                        database_path = gr.Textbox(label=self.DATABASE_TEXT_BOX_LABEL)
+                        load_btn = gr.Button(self.DATABASE_LOAD_BUTTON_LABEL)
+                        loading_status_display = gr.Textbox(
+                            label=self.DATABASE_LOADING_STATUS_LABEL,
+                            interactive=False,
+                            placeholder=self.DATABASE_LOADING_STATUS_PLACEHOLDER,
+                        )
+                    load_btn.click(fn=self._load_database, inputs=database_path, outputs=loading_status_display)
+                    create_btn.click(fn=self._create_database, inputs=documents_picker, outputs=creating_status_display)
+
+                with gr.Column(scale=self._columns_ratios[1]):
+                    chat_interface = gr.ChatInterface(self._handle_message, type="messages")
+                    chat_interface.chatbot.height = f"{self._chatbot_height_vh}vh"
+        return app
+
+
+if __name__ == "__main__":
+    rag_system = RAGSystemWithUI()
+    rag_system.prepare_layout().launch()

From 02b800c78514c387d1414e38b25ec65553bb73b3 Mon Sep 17 00:00:00 2001
From: Ludwik Trammer <ludwik.trammer@deepsense.ai>
Date: Tue, 15 Oct 2024 15:26:18 +0200
Subject: [PATCH 2/4] feat(llms): option to set a default LLM factory (#101)

---
 .../ragbits-core/src/ragbits/core/config.py   |  3 +
 .../src/ragbits/core/llms/factory.py          | 60 +++++++++++++++++++
 .../src/ragbits/core/prompt/lab/app.py        | 35 +++++------
 .../tests/unit/llms/factory/__init__.py       |  5 ++
 .../unit/llms/factory/test_get_default_llm.py | 15 +++++
 .../llms/factory/test_get_llm_from_factory.py | 22 +++++++
 .../unit/llms/factory/test_has_default_llm.py | 20 +++++++
 uv.lock                                       | 14 +----
 8 files changed, 145 insertions(+), 29 deletions(-)
 create mode 100644 packages/ragbits-core/src/ragbits/core/llms/factory.py
 create mode 100644 packages/ragbits-core/tests/unit/llms/factory/__init__.py
 create mode 100644 packages/ragbits-core/tests/unit/llms/factory/test_get_default_llm.py
 create mode 100644 packages/ragbits-core/tests/unit/llms/factory/test_get_llm_from_factory.py
 create mode 100644 packages/ragbits-core/tests/unit/llms/factory/test_has_default_llm.py

diff --git a/packages/ragbits-core/src/ragbits/core/config.py b/packages/ragbits-core/src/ragbits/core/config.py
index 49c0b12b..830dfc9f 100644
--- a/packages/ragbits-core/src/ragbits/core/config.py
+++ b/packages/ragbits-core/src/ragbits/core/config.py
@@ -11,5 +11,8 @@ class CoreConfig(BaseModel):
     # Pattern used to search for prompt files
     prompt_path_pattern: str = "**/prompt_*.py"
 
+    # Path to a function that returns an LLM object, e.g. "my_project.llms.get_llm"
+    default_llm_factory: str | None = None
+
 
 core_config = get_config_instance(CoreConfig, subproject="core")
diff --git a/packages/ragbits-core/src/ragbits/core/llms/factory.py b/packages/ragbits-core/src/ragbits/core/llms/factory.py
new file mode 100644
index 00000000..02bd4704
--- /dev/null
+++ b/packages/ragbits-core/src/ragbits/core/llms/factory.py
@@ -0,0 +1,60 @@
+import importlib
+
+from ragbits.core.config import core_config
+from ragbits.core.llms.base import LLM
+from ragbits.core.llms.litellm import LiteLLM
+
+
+def get_llm_from_factory(factory_path: str) -> LLM:
+    """
+    Get an instance of an LLM using a factory function specified by the user.
+
+    Args:
+        factory_path (str): The path to the factory function.
+
+    Returns:
+        LLM: An instance of the LLM.
+    """
+    module_name, function_name = factory_path.rsplit(".", 1)
+    module = importlib.import_module(module_name)
+    function = getattr(module, function_name)
+    return function()
+
+
+def has_default_llm() -> bool:
+    """
+    Check if the default LLM factory is set in the configuration.
+
+    Returns:
+        bool: Whether the default LLM factory is set.
+    """
+    return core_config.default_llm_factory is not None
+
+
+def get_default_llm() -> LLM:
+    """
+    Get an instance of the default LLM using the factory function
+    specified in the configuration.
+
+    Returns:
+        LLM: An instance of the default LLM.
+
+    Raises:
+        ValueError: If the default LLM factory is not set.
+    """
+    factory = core_config.default_llm_factory
+    if factory is None:
+        raise ValueError("Default LLM factory is not set")
+
+    return get_llm_from_factory(factory)
+
+
+def simple_litellm_factory() -> LLM:
+    """
+    A basic LLM factory that creates an LiteLLM instance with the default model,
+    default options, and assumes that the API key is set in the environment.
+
+    Returns:
+        LLM: An instance of the LiteLLM.
+    """
+    return LiteLLM()
diff --git a/packages/ragbits-core/src/ragbits/core/prompt/lab/app.py b/packages/ragbits-core/src/ragbits/core/prompt/lab/app.py
index 9b6a7dc4..05648b01 100644
--- a/packages/ragbits-core/src/ragbits/core/prompt/lab/app.py
+++ b/packages/ragbits-core/src/ragbits/core/prompt/lab/app.py
@@ -14,8 +14,8 @@
 from rich.console import Console
 
 from ragbits.core.config import core_config
-from ragbits.core.llms import LiteLLM
-from ragbits.core.llms.clients import LiteLLMOptions
+from ragbits.core.llms import LLM
+from ragbits.core.llms.factory import get_llm_from_factory
 from ragbits.core.prompt import Prompt
 from ragbits.core.prompt.discovery import PromptDiscovery
 
@@ -30,14 +30,12 @@ class PromptState:
     Attributes:
         prompts (list): A list containing discovered prompts.
         rendered_prompt (Prompt): The most recently rendered Prompt instance.
-        llm_model_name (str): The name of the selected LLM model.
-        llm_api_key (str | None): The API key for the chosen LLM model.
+        llm (LLM): The LLM instance to be used for generating responses.
     """
 
     prompts: list = field(default_factory=list)
     rendered_prompt: Prompt | None = None
-    llm_model_name: str | None = None
-    llm_api_key: str | None = None
+    llm: LLM | None = None
 
 
 def render_prompt(index: int, system_prompt: str, user_prompt: str, state: PromptState, *args: Any) -> PromptState:
@@ -99,15 +97,17 @@ def send_prompt_to_llm(state: PromptState) -> str:
 
     Returns:
         str: The response generated by the LLM.
-    """
-    assert state.llm_model_name is not None, "LLM model name is not set."
-    llm_client = LiteLLM(model_name=state.llm_model_name, api_key=state.llm_api_key)
 
+    Raises:
+        ValueError: If the LLM model is not configured.
+    """
     assert state.rendered_prompt is not None, "Prompt has not been rendered yet."
+
+    if state.llm is None:
+        raise ValueError("LLM model is not configured.")
+
     try:
-        response = asyncio.run(
-            llm_client.client.call(conversation=state.rendered_prompt.chat, options=LiteLLMOptions())
-        )
+        response = asyncio.run(state.llm.generate_raw(prompt=state.rendered_prompt))
     except Exception as e:  # pylint: disable=broad-except
         response = str(e)
 
@@ -136,7 +136,8 @@ def get_input_type_fields(obj: BaseModel | None) -> list[dict]:
 
 
 def lab_app(  # pylint: disable=missing-param-doc
-    file_pattern: str = core_config.prompt_path_pattern, llm_model: str | None = None, llm_api_key: str | None = None
+    file_pattern: str = core_config.prompt_path_pattern,
+    llm_factory: str | None = core_config.default_llm_factory,
 ) -> None:
     """
     Launches the interactive application for listing, rendering, and testing prompts
@@ -163,9 +164,8 @@ def lab_app(  # pylint: disable=missing-param-doc
     with gr.Blocks() as gr_app:
         prompts_state = gr.State(
             PromptState(
-                llm_model_name=llm_model,
-                llm_api_key=llm_api_key,
                 prompts=list(prompts),
+                llm=get_llm_from_factory(llm_factory) if llm_factory else None,
             )
         )
 
@@ -220,14 +220,15 @@ def show_split(index: int, state: gr.State) -> None:
                                 )
                                 gr.Textbox(label="Rendered User Prompt", value=rendered_user_prompt, interactive=False)
 
-            llm_enabled = state.llm_model_name is not None
+            llm_enabled = state.llm is not None
             prompt_ready = state.rendered_prompt is not None
             llm_request_button = gr.Button(
                 value="Send to LLM",
                 interactive=llm_enabled and prompt_ready,
             )
             gr.Markdown(
-                "To enable this button, select an LLM model when starting the app in CLI.", visible=not llm_enabled
+                "To enable this button set an LLM factory function in CLI options or your pyproject.toml",
+                visible=not llm_enabled,
             )
             gr.Markdown("To enable this button, render a prompt first.", visible=llm_enabled and not prompt_ready)
             llm_prompt_response = gr.Textbox(lines=10, label="LLM response")
diff --git a/packages/ragbits-core/tests/unit/llms/factory/__init__.py b/packages/ragbits-core/tests/unit/llms/factory/__init__.py
new file mode 100644
index 00000000..a3559f0c
--- /dev/null
+++ b/packages/ragbits-core/tests/unit/llms/factory/__init__.py
@@ -0,0 +1,5 @@
+import sys
+from pathlib import Path
+
+# Add "llms" to sys.path
+sys.path.append(str(Path(__file__).parent.parent))
diff --git a/packages/ragbits-core/tests/unit/llms/factory/test_get_default_llm.py b/packages/ragbits-core/tests/unit/llms/factory/test_get_default_llm.py
new file mode 100644
index 00000000..c07272fb
--- /dev/null
+++ b/packages/ragbits-core/tests/unit/llms/factory/test_get_default_llm.py
@@ -0,0 +1,15 @@
+from ragbits.core.config import core_config
+from ragbits.core.llms.factory import get_default_llm
+from ragbits.core.llms.litellm import LiteLLM
+
+
+def test_get_default_llm(monkeypatch):
+    """
+    Test the get_llm_from_factory function.
+    """
+
+    monkeypatch.setattr(core_config, "default_llm_factory", "factory.test_get_llm_from_factory.mock_llm_factory")
+
+    llm = get_default_llm()
+    assert isinstance(llm, LiteLLM)
+    assert llm.model_name == "mock_model"
diff --git a/packages/ragbits-core/tests/unit/llms/factory/test_get_llm_from_factory.py b/packages/ragbits-core/tests/unit/llms/factory/test_get_llm_from_factory.py
new file mode 100644
index 00000000..8d2a948c
--- /dev/null
+++ b/packages/ragbits-core/tests/unit/llms/factory/test_get_llm_from_factory.py
@@ -0,0 +1,22 @@
+from ragbits.core.llms.factory import get_llm_from_factory
+from ragbits.core.llms.litellm import LiteLLM
+
+
+def mock_llm_factory() -> LiteLLM:
+    """
+    A mock LLM factory that creates a LiteLLM instance with a mock model name.
+
+    Returns:
+        LiteLLM: An instance of the LiteLLM.
+    """
+    return LiteLLM(model_name="mock_model")
+
+
+def test_get_llm_from_factory():
+    """
+    Test the get_llm_from_factory function.
+    """
+    llm = get_llm_from_factory("factory.test_get_llm_from_factory.mock_llm_factory")
+
+    assert isinstance(llm, LiteLLM)
+    assert llm.model_name == "mock_model"
diff --git a/packages/ragbits-core/tests/unit/llms/factory/test_has_default_llm.py b/packages/ragbits-core/tests/unit/llms/factory/test_has_default_llm.py
new file mode 100644
index 00000000..59c86483
--- /dev/null
+++ b/packages/ragbits-core/tests/unit/llms/factory/test_has_default_llm.py
@@ -0,0 +1,20 @@
+from ragbits.core.config import core_config
+from ragbits.core.llms.factory import has_default_llm
+
+
+def test_has_default_llm(monkeypatch):
+    """
+    Test the has_default_llm function when the default LLM factory is not set.
+    """
+    monkeypatch.setattr(core_config, "default_llm_factory", None)
+
+    assert has_default_llm() is False
+
+
+def test_has_default_llm_false(monkeypatch):
+    """
+    Test the has_default_llm function when the default LLM factory is set.
+    """
+    monkeypatch.setattr(core_config, "default_llm_factory", "my_project.llms.get_llm")
+
+    assert has_default_llm() is True
diff --git a/uv.lock b/uv.lock
index f685d643..6156c1af 100644
--- a/uv.lock
+++ b/uv.lock
@@ -617,7 +617,7 @@ wheels = [
 
 [package.optional-dependencies]
 toml = [
-    { name = "tomli", marker = "python_full_version == '3.11'" },
+    { name = "tomli", marker = "python_full_version <= '3.11'" },
 ]
 
 [[package]]
@@ -2038,7 +2038,6 @@ version = "12.1.3.1"
 source = { registry = "https://pypi.org/simple" }
 wheels = [
     { url = "https://files.pythonhosted.org/packages/37/6d/121efd7382d5b0284239f4ab1fc1590d86d34ed4a4a2fdb13b30ca8e5740/nvidia_cublas_cu12-12.1.3.1-py3-none-manylinux1_x86_64.whl", hash = "sha256:ee53ccca76a6fc08fb9701aa95b6ceb242cdaab118c3bb152af4e579af792728", size = 410594774 },
-    { url = "https://files.pythonhosted.org/packages/c5/ef/32a375b74bea706c93deea5613552f7c9104f961b21df423f5887eca713b/nvidia_cublas_cu12-12.1.3.1-py3-none-win_amd64.whl", hash = "sha256:2b964d60e8cf11b5e1073d179d85fa340c120e99b3067558f3cf98dd69d02906", size = 439918445 },
 ]
 
 [[package]]
@@ -2047,7 +2046,6 @@ version = "12.1.105"
 source = { registry = "https://pypi.org/simple" }
 wheels = [
     { url = "https://files.pythonhosted.org/packages/7e/00/6b218edd739ecfc60524e585ba8e6b00554dd908de2c9c66c1af3e44e18d/nvidia_cuda_cupti_cu12-12.1.105-py3-none-manylinux1_x86_64.whl", hash = "sha256:e54fde3983165c624cb79254ae9818a456eb6e87a7fd4d56a2352c24ee542d7e", size = 14109015 },
-    { url = "https://files.pythonhosted.org/packages/d0/56/0021e32ea2848c24242f6b56790bd0ccc8bf99f973ca790569c6ca028107/nvidia_cuda_cupti_cu12-12.1.105-py3-none-win_amd64.whl", hash = "sha256:bea8236d13a0ac7190bd2919c3e8e6ce1e402104276e6f9694479e48bb0eb2a4", size = 10154340 },
 ]
 
 [[package]]
@@ -2056,7 +2054,6 @@ version = "12.1.105"
 source = { registry = "https://pypi.org/simple" }
 wheels = [
     { url = "https://files.pythonhosted.org/packages/b6/9f/c64c03f49d6fbc56196664d05dba14e3a561038a81a638eeb47f4d4cfd48/nvidia_cuda_nvrtc_cu12-12.1.105-py3-none-manylinux1_x86_64.whl", hash = "sha256:339b385f50c309763ca65456ec75e17bbefcbbf2893f462cb8b90584cd27a1c2", size = 23671734 },
-    { url = "https://files.pythonhosted.org/packages/ad/1d/f76987c4f454eb86e0b9a0e4f57c3bf1ac1d13ad13cd1a4da4eb0e0c0ce9/nvidia_cuda_nvrtc_cu12-12.1.105-py3-none-win_amd64.whl", hash = "sha256:0a98a522d9ff138b96c010a65e145dc1b4850e9ecb75a0172371793752fd46ed", size = 19331863 },
 ]
 
 [[package]]
@@ -2065,7 +2062,6 @@ version = "12.1.105"
 source = { registry = "https://pypi.org/simple" }
 wheels = [
     { url = "https://files.pythonhosted.org/packages/eb/d5/c68b1d2cdfcc59e72e8a5949a37ddb22ae6cade80cd4a57a84d4c8b55472/nvidia_cuda_runtime_cu12-12.1.105-py3-none-manylinux1_x86_64.whl", hash = "sha256:6e258468ddf5796e25f1dc591a31029fa317d97a0a94ed93468fc86301d61e40", size = 823596 },
-    { url = "https://files.pythonhosted.org/packages/9f/e2/7a2b4b5064af56ea8ea2d8b2776c0f2960d95c88716138806121ae52a9c9/nvidia_cuda_runtime_cu12-12.1.105-py3-none-win_amd64.whl", hash = "sha256:dfb46ef84d73fababab44cf03e3b83f80700d27ca300e537f85f636fac474344", size = 821226 },
 ]
 
 [[package]]
@@ -2085,7 +2081,6 @@ version = "11.0.2.54"
 source = { registry = "https://pypi.org/simple" }
 wheels = [
     { url = "https://files.pythonhosted.org/packages/86/94/eb540db023ce1d162e7bea9f8f5aa781d57c65aed513c33ee9a5123ead4d/nvidia_cufft_cu12-11.0.2.54-py3-none-manylinux1_x86_64.whl", hash = "sha256:794e3948a1aa71fd817c3775866943936774d1c14e7628c74f6f7417224cdf56", size = 121635161 },
-    { url = "https://files.pythonhosted.org/packages/f7/57/7927a3aa0e19927dfed30256d1c854caf991655d847a4e7c01fe87e3d4ac/nvidia_cufft_cu12-11.0.2.54-py3-none-win_amd64.whl", hash = "sha256:d9ac353f78ff89951da4af698f80870b1534ed69993f10a4cf1d96f21357e253", size = 121344196 },
 ]
 
 [[package]]
@@ -2094,7 +2089,6 @@ version = "10.3.2.106"
 source = { registry = "https://pypi.org/simple" }
 wheels = [
     { url = "https://files.pythonhosted.org/packages/44/31/4890b1c9abc496303412947fc7dcea3d14861720642b49e8ceed89636705/nvidia_curand_cu12-10.3.2.106-py3-none-manylinux1_x86_64.whl", hash = "sha256:9d264c5036dde4e64f1de8c50ae753237c12e0b1348738169cd0f8a536c0e1e0", size = 56467784 },
-    { url = "https://files.pythonhosted.org/packages/5c/97/4c9c7c79efcdf5b70374241d48cf03b94ef6707fd18ea0c0f53684931d0b/nvidia_curand_cu12-10.3.2.106-py3-none-win_amd64.whl", hash = "sha256:75b6b0c574c0037839121317e17fd01f8a69fd2ef8e25853d826fec30bdba74a", size = 55995813 },
 ]
 
 [[package]]
@@ -2108,7 +2102,6 @@ dependencies = [
 ]
 wheels = [
     { url = "https://files.pythonhosted.org/packages/bc/1d/8de1e5c67099015c834315e333911273a8c6aaba78923dd1d1e25fc5f217/nvidia_cusolver_cu12-11.4.5.107-py3-none-manylinux1_x86_64.whl", hash = "sha256:8a7ec542f0412294b15072fa7dab71d31334014a69f953004ea7a118206fe0dd", size = 124161928 },
-    { url = "https://files.pythonhosted.org/packages/b8/80/8fca0bf819122a631c3976b6fc517c1b10741b643b94046bd8dd451522c5/nvidia_cusolver_cu12-11.4.5.107-py3-none-win_amd64.whl", hash = "sha256:74e0c3a24c78612192a74fcd90dd117f1cf21dea4822e66d89e8ea80e3cd2da5", size = 121643081 },
 ]
 
 [[package]]
@@ -2120,7 +2113,6 @@ dependencies = [
 ]
 wheels = [
     { url = "https://files.pythonhosted.org/packages/65/5b/cfaeebf25cd9fdec14338ccb16f6b2c4c7fa9163aefcf057d86b9cc248bb/nvidia_cusparse_cu12-12.1.0.106-py3-none-manylinux1_x86_64.whl", hash = "sha256:f3b50f42cf363f86ab21f720998517a659a48131e8d538dc02f8768237bd884c", size = 195958278 },
-    { url = "https://files.pythonhosted.org/packages/0f/95/48fdbba24c93614d1ecd35bc6bdc6087bd17cbacc3abc4b05a9c2a1ca232/nvidia_cusparse_cu12-12.1.0.106-py3-none-win_amd64.whl", hash = "sha256:b798237e81b9719373e8fae8d4f091b70a0cf09d9d85c95a557e11df2d8e9a5a", size = 195414588 },
 ]
 
 [[package]]
@@ -2138,7 +2130,6 @@ source = { registry = "https://pypi.org/simple" }
 wheels = [
     { url = "https://files.pythonhosted.org/packages/11/8c/386018fdffdce2ff8d43fedf192ef7d14cab7501cbf78a106dd2e9f1fc1f/nvidia_nvjitlink_cu12-12.6.77-py3-none-manylinux2014_aarch64.whl", hash = "sha256:3bf10d85bb1801e9c894c6e197e44dd137d2a0a9e43f8450e9ad13f2df0dd52d", size = 19270432 },
     { url = "https://files.pythonhosted.org/packages/fe/e4/486de766851d58699bcfeb3ba6a3beb4d89c3809f75b9d423b9508a8760f/nvidia_nvjitlink_cu12-12.6.77-py3-none-manylinux2014_x86_64.whl", hash = "sha256:9ae346d16203ae4ea513be416495167a0101d33d2d14935aa9c1829a3fb45142", size = 19745114 },
-    { url = "https://files.pythonhosted.org/packages/1a/aa/7b5d8e22d73e03f941293ae62c993642fa41e6525f3213292e007621aa8e/nvidia_nvjitlink_cu12-12.6.77-py3-none-win_amd64.whl", hash = "sha256:410718cd44962bed862a31dd0318620f6f9a8b28a6291967bcfcb446a6516771", size = 161917250 },
 ]
 
 [[package]]
@@ -2147,7 +2138,6 @@ version = "12.1.105"
 source = { registry = "https://pypi.org/simple" }
 wheels = [
     { url = "https://files.pythonhosted.org/packages/da/d3/8057f0587683ed2fcd4dbfbdfdfa807b9160b809976099d36b8f60d08f03/nvidia_nvtx_cu12-12.1.105-py3-none-manylinux1_x86_64.whl", hash = "sha256:dc21cf308ca5691e7c04d962e213f8a4aa9bbfa23d95412f452254c2caeb09e5", size = 99138 },
-    { url = "https://files.pythonhosted.org/packages/b8/d7/bd7cb2d95ac6ac6e8d05bfa96cdce69619f1ef2808e072919044c2d47a8c/nvidia_nvtx_cu12-12.1.105-py3-none-win_amd64.whl", hash = "sha256:65f4d98982b31b60026e0e6de73fbdfc09d08a96f4656dd3665ca616a11e1e82", size = 66307 },
 ]
 
 [[package]]
@@ -3210,7 +3200,7 @@ dev = [
 [[package]]
 name = "ragbits-workspace"
 version = "0.1.0"
-source = { editable = "." }
+source = { virtual = "." }
 dependencies = [
     { name = "ragbits-cli" },
     { name = "ragbits-core", extra = ["chromadb", "lab", "litellm", "local"] },

From f8771b39cb6b8a3c372a06a3646583db591dc9e0 Mon Sep 17 00:00:00 2001
From: Ludwik Trammer <ludwik.trammer@deepsense.ai>
Date: Wed, 16 Oct 2024 12:06:02 +0200
Subject: [PATCH 3/4] chore: Add project-level README (#103)

---
 CONTRIBUTING.md | 28 +++++++++++++++
 README.md       | 90 ++++++++++++++++++++++++++++++++++++++++---------
 2 files changed, 102 insertions(+), 16 deletions(-)
 create mode 100644 CONTRIBUTING.md

diff --git a/CONTRIBUTING.md b/CONTRIBUTING.md
new file mode 100644
index 00000000..5a4ce435
--- /dev/null
+++ b/CONTRIBUTING.md
@@ -0,0 +1,28 @@
+# Installation
+
+## Build from source
+
+To build and run Ragbits from the source code:
+
+1. Requirements: [**uv**](https://docs.astral.sh/uv/getting-started/installation/) & [**python**](https://docs.astral.sh/uv/guides/install-python/) 3.10 or higher
+2. Install dependencies and run venv in editable mode:
+
+```bash
+$ source ./setup_dev_env.sh
+```
+
+## Install pre-commit
+
+To ensure code quality we use pre-commit hook with several checks. Setup it by:
+
+```
+pre-commit install
+```
+
+All updated files will be reformatted and linted before the commit.
+
+To reformat and lint all files in the project, use:
+
+`pre-commit run --all-files`
+
+The used linters are configured in `.pre-commit-config.yaml`. You can use `pre-commit autoupdate` to bump tools to the latest versions.
diff --git a/README.md b/README.md
index 2a2d8255..c47afb68 100644
--- a/README.md
+++ b/README.md
@@ -1,32 +1,90 @@
-# Ragbits
+<div align="center">
 
-Repository for internal experiment with our upcoming LLM framework.
+<h1>Ragbits</h1>
 
-# Installation
+*Building blocks for rapid development of GenAI applications*
 
-## Build from source
+[Documentation](https://ragbits.deepsense.ai) | [Contact](https://deepsense.ai/contact/)
 
-To build and run Ragbits from the source code:
+[![PyPI - License](https://img.shields.io/pypi/l/ragbits)](https://pypi.org/project/ragbits)
+[![PyPI - Version](https://img.shields.io/pypi/v/ragbits)](https://pypi.org/project/ragbits)
+[![PyPI - Python Version](https://img.shields.io/pypi/pyversions/ragbits)](https://pypi.org/project/ragbits)
 
-1. Requirements: [**uv**](https://docs.astral.sh/uv/getting-started/installation/) & [**python**](https://docs.astral.sh/uv/guides/install-python/) 3.10 or higher
-2. Install dependencies and run venv in editable mode:
+</div>
 
-```bash
-$ source ./setup_dev_env.sh
+---
+
+## What's Included?
+
+- [X] **[Core](packages/ragbits-core)** - Fundamental tools for working with prompts and LLMs.
+- [X] **[Document Search](packages/ragbits-document-search)** - Handles vector search to retrieve relevant documents.
+- [X] **[CLI](packages/ragbits-cli)** - The `ragbits` shell command, enabling tools such as GUI prompt management.
+- [ ] **Flow Controls** - Manages multi-stage chat flows for performing advanced actions *(coming soon)*.
+- [ ] **Structured Querying** - Queries structured data sources in a predictable manner *(coming soon)*.
+- [ ] **Caching** - Adds a caching layer to reduce costs and response times *(coming soon)*.
+- [ ] **Observability & Audit** - Tracks user queries and events for easier troubleshooting *(coming soon)*.
+- [ ] **Guardrails** - Ensures response safety and relevance *(coming soon)*.
+
+## Installation
+
+To use the complete Ragbits stack, install the `ragbits` package:
+
+```sh
+pip install ragbits
+```
+
+Alternatively, you can use individual components of the stack by installing their respective packages: `ragbits-core`, `ragbits-document-search`, `ragbits-cli`.
+
+## Quickstart
+
+First, create a prompt and a model for the data used in the prompt:
+
+```python
+from pydantic import BaseModel
+from ragbits.core.prompt import Prompt
+
+class Dog(BaseModel):
+    breed: str
+    age: int
+    temperament: str
+
+class DogNamePrompt(Prompt[Dog, str]):
+    system_prompt = """
+    You are a dog name generator. You come up with funny names for dogs given the dog details.
+    """
+
+    user_prompt = """
+    The dog is a {breed} breed, {age} years old, and has a {temperament} temperament.
+    """
 ```
 
-## Install pre-commit
+Next, create an instance of the LLM and the prompt:
 
-To ensure code quality we use pre-commit hook with several checks. Setup it by:
+```python
+from ragbits.core.llms.litellm import LiteLLM
 
+llm = LiteLLM("gpt-4o")
+example_dog = Dog(breed="Golden Retriever", age=3, temperament="friendly")
+prompt = DogNamePrompt(example_dog)
 ```
-pre-commit install
+
+Finally, generate a response from the LLM using the prompt:
+
+```python
+response = await llm.generate(prompt)
+print(f"Generated dog name: {response}")
 ```
 
-All updated files will be reformatted and linted before the commit.
+<!--
+TODO:
+Add links to quickstart guides for individual packages, demonstrating how to extend this with their functionality.
+Add a link to the full tutorial.
+-->
+
+## License
 
-To reformat and lint all files in the project, use:
+Ragbits is licensed under the [MIT License](LICENSE).
 
-`pre-commit run --all-files`
+## Contributing
 
-The used linters are configured in `.pre-commit-config.yaml`. You can use `pre-commit autoupdate` to bump tools to the latest versions.
+We welcome contributions! Please read [CONTRIBUTING.md](CONTRIBUTING.md) for more information.

From d61725fc14961607e254657904bc3cf2f165fd75 Mon Sep 17 00:00:00 2001
From: akotyla <79326805+akotyla@users.noreply.github.com>
Date: Wed, 16 Oct 2024 12:06:25 +0200
Subject: [PATCH 4/4] feat(document-search): determine document type
 automatically (#99)

---
 .../src/ragbits/document_search/_main.py      | 14 ++++++--
 .../document_search/documents/document.py     | 18 +++++++++++
 .../tests/unit/test_document_search.py        | 32 ++++++++++++++++++-
 3 files changed, 61 insertions(+), 3 deletions(-)

diff --git a/packages/ragbits-document-search/src/ragbits/document_search/_main.py b/packages/ragbits-document-search/src/ragbits/document_search/_main.py
index fe3f826c..dd92caee 100644
--- a/packages/ragbits-document-search/src/ragbits/document_search/_main.py
+++ b/packages/ragbits-document-search/src/ragbits/document_search/_main.py
@@ -6,6 +6,7 @@
 from ragbits.core.vector_store import VectorStore, get_vector_store
 from ragbits.document_search.documents.document import Document, DocumentMeta
 from ragbits.document_search.documents.element import Element
+from ragbits.document_search.documents.sources import GCSSource, LocalFileSource, Source
 from ragbits.document_search.ingestion.document_processor import DocumentProcessorRouter
 from ragbits.document_search.ingestion.providers.base import BaseProvider
 from ragbits.document_search.retrieval.rephrasers import get_rephraser
@@ -104,7 +105,9 @@ async def search(self, query: str, search_config: SearchConfig = SearchConfig())
         return self.reranker.rerank(elements)
 
     async def ingest_document(
-        self, document: Union[DocumentMeta, Document], document_processor: Optional[BaseProvider] = None
+        self,
+        document: Union[DocumentMeta, Document, Union[LocalFileSource, GCSSource]],
+        document_processor: Optional[BaseProvider] = None,
     ) -> None:
         """
         Ingest a document.
@@ -114,7 +117,14 @@ async def ingest_document(
             document_processor: The document processor to use. If not provided, the document processor will be
                 determined based on the document metadata.
         """
-        document_meta = document if isinstance(document, DocumentMeta) else document.metadata
+
+        if isinstance(document, Source):
+            document_meta = await DocumentMeta.from_source(document)
+        elif isinstance(document, DocumentMeta):
+            document_meta = document
+        else:
+            document_meta = document.metadata
+
         if document_processor is None:
             document_processor = self.document_processor_router.get_provider(document_meta)
 
diff --git a/packages/ragbits-document-search/src/ragbits/document_search/documents/document.py b/packages/ragbits-document-search/src/ragbits/document_search/documents/document.py
index 2ca2ec9a..0d43df91 100644
--- a/packages/ragbits-document-search/src/ragbits/document_search/documents/document.py
+++ b/packages/ragbits-document-search/src/ragbits/document_search/documents/document.py
@@ -97,6 +97,24 @@ def from_local_path(cls, local_path: Path) -> "DocumentMeta":
             source=LocalFileSource(path=local_path),
         )
 
+    @classmethod
+    async def from_source(cls, source: Union[LocalFileSource, GCSSource]) -> "DocumentMeta":
+        """
+        Create a document metadata from a source.
+
+        Args:
+            source: The source from which the document is fetched.
+
+        Returns:
+            The document metadata.
+        """
+        path = await source.fetch()
+
+        return cls(
+            document_type=DocumentType(path.suffix[1:]),
+            source=source,
+        )
+
 
 class Document(BaseModel):
     """
diff --git a/packages/ragbits-document-search/tests/unit/test_document_search.py b/packages/ragbits-document-search/tests/unit/test_document_search.py
index 76743c89..ba8695b1 100644
--- a/packages/ragbits-document-search/tests/unit/test_document_search.py
+++ b/packages/ragbits-document-search/tests/unit/test_document_search.py
@@ -1,3 +1,4 @@
+import tempfile
 from pathlib import Path
 from typing import Union
 from unittest.mock import AsyncMock
@@ -7,8 +8,10 @@
 from ragbits.core.vector_store.in_memory import InMemoryVectorStore
 from ragbits.document_search import DocumentSearch
 from ragbits.document_search._main import SearchConfig
-from ragbits.document_search.documents.document import Document, DocumentMeta
+from ragbits.document_search.documents.document import Document, DocumentMeta, DocumentType
 from ragbits.document_search.documents.element import TextElement
+from ragbits.document_search.documents.sources import LocalFileSource
+from ragbits.document_search.ingestion.document_processor import DocumentProcessorRouter
 from ragbits.document_search.ingestion.providers.dummy import DummyProvider
 
 CONFIG = {
@@ -46,6 +49,33 @@ async def test_document_search_from_config(document, expected):
     assert first_result.content == expected
 
 
+async def test_document_search_ingest_document_from_source():
+    embeddings_mock = AsyncMock()
+    embeddings_mock.embed_text.return_value = [[0.1, 0.1]]
+
+    providers = {DocumentType.TXT: DummyProvider()}
+    router = DocumentProcessorRouter.from_config(providers)
+
+    document_search = DocumentSearch(
+        embedder=embeddings_mock, vector_store=InMemoryVectorStore(), document_processor_router=router
+    )
+
+    with tempfile.NamedTemporaryFile(suffix=".txt") as f:
+        f.write(b"Name of Peppa's brother is George")
+        f.seek(0)
+
+        source = LocalFileSource(path=Path(f.name))
+
+        await document_search.ingest_document(source)
+
+        results = await document_search.search("Peppa's brother")
+
+    first_result = results[0]
+
+    assert isinstance(first_result, TextElement)
+    assert first_result.content == "Name of Peppa's brother is George"
+
+
 @pytest.mark.parametrize(
     "document",
     [