Merge pull request #300 from zjffdu/minor_rename

[MINOR] Rename from lightrag to adalflow

Author: fm1320

adalflow/adalflow/components/output_parsers/outputs.py

@@ -75,7 +75,7 @@ class OutputParser(Component):
     This interface helps users customize output parsers with consistent interfaces for the Generator.
     Even though you don't always need to subclass it.
 
-    LightRAG uses two core components:
+    AdalFlow uses two core components:
     1. the Prompt to format output instruction
     2. A string parser component from core.string_parser for response parsing.
     """

adalflow/adalflow/core/__init__.py

@@ -3,7 +3,7 @@
 from .component import Component, FunComponent, fun_to_component
 from .container import Sequential
 from .db import LocalDB
-from .default_prompt_template import DEFAULT_LIGHTRAG_SYSTEM_PROMPT
+from .default_prompt_template import DEFAULT_ADALFLOW_SYSTEM_PROMPT
 from .embedder import Embedder, BatchEmbedder
 from .generator import Generator, BackwardEngine
 from .model_client import ModelClient
@@ -58,7 +58,7 @@
     "Generator",
     "BackwardEngine",
     "Prompt",
-    "DEFAULT_LIGHTRAG_SYSTEM_PROMPT",
+    "DEFAULT_ADALFLOW_SYSTEM_PROMPT",
     # "Parameter",
     "required_field",
     "ModelClient",

adalflow/adalflow/core/default_prompt_template.py

@@ -1,16 +1,16 @@
-"""This is the default system prompt template used in the LightRAG.
+"""This is the default system prompt template used in the AdalFlow.
 
 Use :ref:`Prompt <core-prompt_builder>` class  to manage it.
 """
 
 __all__ = [
-    "LIGHTRAG_DEFAULT_PROMPT_ARGS",
-    "LIGHTRAG_DEFAULT_PROMPT_TRAINABLE_PARAMS",
-    "SIMPLE_DEFAULT_LIGHTRAG_SYSTEM_PROMPT",
-    "DEFAULT_LIGHTRAG_SYSTEM_PROMPT",
+    "ADALFLOW_DEFAULT_PROMPT_ARGS",
+    "ADALFLOW_DEFAULT_PROMPT_TRAINABLE_PARAMS",
+    "SIMPLE_DEFAULT_ADALFLOW_SYSTEM_PROMPT",
+    "DEFAULT_ADALFLOW_SYSTEM_PROMPT",
 ]
 # TODO: potentially make a data class for this
-LIGHTRAG_DEFAULT_PROMPT_ARGS = [
+ADALFLOW_DEFAULT_PROMPT_ARGS = [
     "task_desc_str",  # task description
     "output_format_str",  # output format of the task
     "tools_str",  # tools used in the task
@@ -21,17 +21,17 @@
     "input_str",  # user query or input
 ]
 
-LIGHTRAG_DEFAULT_PROMPT_TRAINABLE_PARAMS = [
+ADALFLOW_DEFAULT_PROMPT_TRAINABLE_PARAMS = [
     "task_desc_str",
     # "output_format_str",
     "examples_str",
 ]
 
-SIMPLE_DEFAULT_LIGHTRAG_SYSTEM_PROMPT = r"""<SYS>{{task_desc_str}}</SYS>
+SIMPLE_DEFAULT_ADALFLOW_SYSTEM_PROMPT = r"""<SYS>{{task_desc_str}}</SYS>
 User: {{input_str}}
 You:"""
 
-DEFAULT_LIGHTRAG_SYSTEM_PROMPT = r"""<START_OF_SYSTEM_PROMPT>
+DEFAULT_ADALFLOW_SYSTEM_PROMPT = r"""<START_OF_SYSTEM_PROMPT>
 {# task desc #}
 {% if task_desc_str %}
 {{task_desc_str}}
@@ -87,7 +87,7 @@
 <END_OF_ASSISTANT_STEPS>
 {% endif %}
 """
-"""This is the default system prompt template used in the LightRAG.
+"""This is the default system prompt template used in the AdalFlow.
 
 Use :ref:`Prompt <core-prompt_builder>` class  to manage it.
 """

adalflow/adalflow/core/generator.py

@@ -26,7 +26,7 @@
 from adalflow.core.prompt_builder import Prompt
 from adalflow.core.functional import compose_model_kwargs
 from adalflow.core.model_client import ModelClient
-from adalflow.core.default_prompt_template import DEFAULT_LIGHTRAG_SYSTEM_PROMPT
+from adalflow.core.default_prompt_template import DEFAULT_ADALFLOW_SYSTEM_PROMPT
 from adalflow.optim.function import BackwardContext
 from adalflow.utils.cache import CachedEngine
 from adalflow.tracing.callback_manager import CallbackManager
@@ -113,7 +113,7 @@ def __init__(
                     Got {model_client} instead."
             )
 
-        template = template or DEFAULT_LIGHTRAG_SYSTEM_PROMPT
+        template = template or DEFAULT_ADALFLOW_SYSTEM_PROMPT
 
         # create the cache path and initialize the cache engine
 

adalflow/adalflow/core/model_client.py

@@ -25,15 +25,15 @@ class ModelClient(Component):
 
 (1) Initialize the client, including both sync and async.
 
-(2) Convert the standard LightRAG components inputs to the API-specific format.
+(2) Convert the standard AdalFlow components inputs to the API-specific format.
 
 (3) Call the API and parse the response.
 
 (4) Handle API specific exceptions and errors to retry the call.
 
 Check the subclasses in `components/model_client/` directory for the functional API clients we have.
 
-    This interface is designed to bridge the gap between LightRAG components inputs and model APIs.
+    This interface is designed to bridge the gap between AdalFlow components inputs and model APIs.
 
     You can see examples of the subclasses in components/model_client/ directory.
     """
@@ -103,7 +103,7 @@ def track_completion_usage(self, *args, **kwargs) -> "CompletionUsage":
         )
 
     def parse_embedding_response(self, response: Any) -> "EmbedderOutput":
-        r"""Parse the embedding response to a structure LightRAG components can understand."""
+        r"""Parse the embedding response to a structure AdalFlow components can understand."""
         raise NotImplementedError(
             f"{type(self).__name__} must implement parse_embedding_response method"
         )

adalflow/adalflow/core/prompt_builder.py

@@ -8,7 +8,7 @@
 
 
 from adalflow.core.component import Component
-from adalflow.core.default_prompt_template import DEFAULT_LIGHTRAG_SYSTEM_PROMPT
+from adalflow.core.default_prompt_template import DEFAULT_ADALFLOW_SYSTEM_PROMPT
 from adalflow.optim.parameter import Parameter
 
 
@@ -56,7 +56,7 @@ def __init__(
     ):
         super().__init__()
 
-        self.template = template or DEFAULT_LIGHTRAG_SYSTEM_PROMPT
+        self.template = template or DEFAULT_ADALFLOW_SYSTEM_PROMPT
         self.__create_jinja2_template()
         self.prompt_variables: List[str] = []
         for var in self._find_template_variables(self.template):

docs/source/tutorials/generator.rst

@@ -55,7 +55,7 @@ An Orchestrator
 It orchestrates three components:
 
 - `Prompt`: by taking in ``template`` (string) and ``prompt_kwargs`` (dict) to format the prompt at initialization.
-  When the ``template`` is not provided, it defaults to :const:`DEFAULT_LIGHTRAG_SYSTEM_PROMPT<core.default_prompt_template.DEFAULT_LIGHTRAG_SYSTEM_PROMPT>`.
+  When the ``template`` is not provided, it defaults to :const:`DEFAULT_ADALFLOW_SYSTEM_PROMPT<core.default_prompt_template.DEFAULT_ADALFLOW_SYSTEM_PROMPT>`.
 
 - `ModelClient`: by taking in an already instantiated ``model_client`` and ``model_kwargs`` to call the model.
   Switching out the model client allows you to call any LLM model using the same prompt and output parsing.
@@ -485,7 +485,7 @@ It will require users to define ``Parameter`` and pass it to the ``prompt_kwargs
 
    - :class:`core.generator.Generator`
    - :class:`core.types.GeneratorOutput`
-   - :class:`core.default_prompt_template.DEFAULT_LIGHTRAG_SYSTEM_PROMPT`
+   - :class:`core.default_prompt_template.DEFAULT_ADALFLOW_SYSTEM_PROMPT`
    - :class:`core.types.ModelClientType`
    - :class:`core.types.ModelType`
    - :class:`core.string_parser.JsonParser`

docs/source/tutorials/prompt.rst

@@ -6,7 +6,7 @@
       <a href="https://colab.research.google.com/drive/1_sGeHaKrwpI9RiL01g3cKyI2_5PJqZtr?usp=sharing" target="_blank" style="margin-right: 10px;">
          <img alt="Try Quickstart in Colab" src="https://colab.research.google.com/assets/colab-badge.svg" style="vertical-align: middle;">
       </a>
-      <a href="https://github.com/SylphAI-Inc/LightRAG/blob/main/tutorials/prompt_note.py" target="_blank" style="display: flex; align-items: center;">
+      <a href="https://github.com/SylphAI-Inc/AdalFlow/blob/main/tutorials/prompt_note.py" target="_blank" style="display: flex; align-items: center;">
          <img src="https://github.githubassets.com/images/modules/logos_page/GitHub-Mark.png" alt="GitHub" style="height: 20px; width: 20px; margin-right: 5px;">
          <span style="vertical-align: middle;"> Open Source Code</span>
       </a>
@@ -206,13 +206,13 @@ As with all components, you can use ``to_dict`` and ``from_dict`` to serialize a
 Default Prompt Template
 -------------------------
 
-In default, the ``Prompt`` class uses the :const:`DEFAULT_LIGHTRAG_SYSTEM_PROMPT<core.default_prompt_template.DEFAULT_LIGHTRAG_SYSTEM_PROMPT>` as its string template if no template is provided.
+In default, the ``Prompt`` class uses the :const:`DEFAULT_ADALFLOW_SYSTEM_PROMPT<core.default_prompt_template.DEFAULT_ADALFLOW_SYSTEM_PROMPT>` as its string template if no template is provided.
 This default template allows you to conditionally passing seven important variables designed from the data flow diagram above.
 These varaibles are:
 
 .. code-block:: python
 
-   LIGHTRAG_DEFAULT_PROMPT_ARGS = [
+   ADALFLOW_DEFAULT_PROMPT_ARGS = [
       "task_desc_str",  # task description
       "output_format_str",  # output format of the task
       "tools_str",  # tools used in the task
@@ -266,4 +266,4 @@ The output will be the bare minimum with only the user query and a prefix for as
    :class: highlight
 
    - :class:`core.prompt_builder.Prompt`
-   - :const:`core.default_prompt_template.DEFAULT_LIGHTRAG_SYSTEM_PROMPT`
+   - :const:`core.default_prompt_template.DEFAULT_ADALFLOW_SYSTEM_PROMPT`