Best docs Cinnamon will probably ever have (#105)

knowledgehub/llms/__init__.py

@@ -4,6 +4,7 @@ from .base import BaseLLM
 from .branching import GatedBranchingPipeline, SimpleBranchingPipeline
 from .chats import AzureChatOpenAI, ChatLLM
 from .completions import LLM, AzureOpenAI, OpenAI
+from .cot import ManualSequentialChainOfThought, Thought
 from .linear import GatedLinearPipeline, SimpleLinearPipeline
 from .prompts import BasePromptComponent, PromptTemplate
 
@@ -28,4 +29,7 @@ __all__ = [
     "GatedLinearPipeline",
     "SimpleBranchingPipeline",
     "GatedBranchingPipeline",
+    # chain-of-thoughts
+    "ManualSequentialChainOfThought",
+    "Thought",
 ]

knowledgehub/llms/branching.py

@@ -12,7 +12,8 @@ class SimpleBranchingPipeline(BaseComponent):
     Attributes:
         branches (List[BaseComponent]): The list of branches to be executed.
 
-    Example Usage:
+    Example:
+        ```python
         from kotaemon.llms import (
             AzureChatOpenAI,
             BasePromptComponent,
@@ -45,6 +46,7 @@ class SimpleBranchingPipeline(BaseComponent):
         print(pipeline(condition_text="1"))
         print(pipeline(condition_text="2"))
         print(pipeline(condition_text="12"))
+        ```
     """
 
     branches: List[BaseComponent] = Param(default_callback=lambda *_: [])
@@ -87,7 +89,8 @@ class GatedBranchingPipeline(SimpleBranchingPipeline):
     Attributes:
         branches (List[BaseComponent]): The list of branches to be executed.
 
-    Example Usage:
+    Example:
+        ```python
         from kotaemon.llms import (
             AzureChatOpenAI,
             BasePromptComponent,
@@ -119,6 +122,7 @@ class GatedBranchingPipeline(SimpleBranchingPipeline):
             )
         print(pipeline(condition_text="1"))
         print(pipeline(condition_text="2"))
+        ```
     """
 
     def run(self, *, condition_text: Optional[str] = None, **prompt_kwargs):
@@ -135,7 +139,7 @@ class GatedBranchingPipeline(SimpleBranchingPipeline):
             Union[OutputType, None]: The output of the first branch that satisfies the
             condition, or None if no branch satisfies the condition.
 
-        Raise:
+        Raises:
             ValueError: If condition_text is None
         """
         if condition_text is None:

knowledgehub/llms/cot.py

@@ -1,7 +1,9 @@
 from copy import deepcopy
 from typing import Callable, List
 
-from kotaemon.base import BaseComponent, Document, Node, Param
+from theflow import Function, Node, Param
+
+from kotaemon.base import BaseComponent, Document
 
 from .chats import AzureChatOpenAI
 from .completions import LLM
@@ -66,13 +68,13 @@ class Thought(BaseComponent):
 
     prompt: str = Param(
         help=(
-            "The prompt template string. This prompt template has Python-like "
-            "variable placeholders, that then will be subsituted with real values when "
-            "this component is executed"
+            "The prompt template string. This prompt template has Python-like variable"
+            " placeholders, that then will be substituted with real values when this"
+            " component is executed"
         )
     )
     llm: LLM = Node(AzureChatOpenAI, help="The LLM model to execute the input prompt")
-    post_process: BaseComponent = Node(
+    post_process: Function = Node(
         help=(
             "The function post-processor that post-processes LLM output prediction ."
             "It should take a string as input (this is the LLM output text) and return "
@@ -83,7 +85,7 @@ class Thought(BaseComponent):
     @Node.auto(depends_on="prompt")
     def prompt_template(self):
         """Automatically wrap around param prompt. Can ignore"""
-        return BasePromptComponent(template=self.prompt)
+        return BasePromptComponent(self.prompt)
 
     def run(self, **kwargs) -> Document:
         """Run the chain of thought"""
@@ -113,20 +115,19 @@ class ManualSequentialChainOfThought(BaseComponent):
 
     **Create and run a chain of thought without "+" operator:**
 
-    ```python
-    >> from kotaemon.pipelines.cot import Thought, ManualSequentialChainOfThought
-
-    >> llm = AzureChatOpenAI(...)
-    >> thought1 = Thought(
-           prompt="Word {word} in {language} is ",
-           post_process=lambda string: {"translated": string},
-       )
-    >> thought2 = Thought(
-            prompt="Translate {translated} to Japanese",
-            post_process=lambda string: {"output": string},
-       )
-    >> thought = ManualSequentialChainOfThought(thoughts=[thought1, thought2], llm=llm)
-    >> thought(word="hello", language="French")
+    ```pycon
+    >>> from kotaemon.pipelines.cot import Thought, ManualSequentialChainOfThought
+    >>> llm = AzureChatOpenAI(...)
+    >>> thought1 = Thought(
+    >>>    prompt="Word {word} in {language} is ",
+    >>>    post_process=lambda string: {"translated": string},
+    >>> )
+    >>> thought2 = Thought(
+    >>>     prompt="Translate {translated} to Japanese",
+    >>>     post_process=lambda string: {"output": string},
+    >>> )
+    >>> thought = ManualSequentialChainOfThought(thoughts=[thought1, thought2], llm=llm)
+    >>> thought(word="hello", language="French")
     {'word': 'hello',
      'language': 'French',
      'translated': '"Bonjour"',

knowledgehub/llms/linear.py

@@ -21,6 +21,7 @@ class SimpleLinearPipeline(BaseComponent):
             post-processor component or function.
 
     Example Usage:
+        ```python
         from kotaemon.llms import AzureChatOpenAI, BasePromptComponent
 
         def identity(x):
@@ -41,6 +42,7 @@ class SimpleLinearPipeline(BaseComponent):
             post_processor=identity,
         )
         print(pipeline(word="lone"))
+        ```
     """
 
     prompt: BasePromptComponent
@@ -85,7 +87,8 @@ class GatedLinearPipeline(SimpleLinearPipeline):
         condition (Callable[[IO_Type], Any]): A callable function that represents the
             condition.
 
-    Example Usage:
+    Usage:
+        ```{.py3 title="Example Usage"}
         from kotaemon.llms import AzureChatOpenAI, BasePromptComponent
         from kotaemon.parsers import RegexExtractor
 
@@ -109,6 +112,7 @@ class GatedLinearPipeline(SimpleLinearPipeline):
         )
         print(pipeline(condition_text="some pattern", word="lone"))
         print(pipeline(condition_text="other pattern", word="lone"))
+        ```
     """
 
     condition: Callable[[IO_Type], Any]

knowledgehub/llms/prompts/template.py

@@ -72,7 +72,7 @@ class PromptTemplate:
                 UserWarning,
             )
 
-    def populate(self, **kwargs):
+    def populate(self, **kwargs) -> str:
         """
         Strictly populate the template with the given keyword arguments.
 
@@ -81,7 +81,7 @@ class PromptTemplate:
                       Each keyword corresponds to a placeholder in the template.
 
         Returns:
-            str: The populated template.
+            The populated template.
 
         Raises:
             ValueError: If an unknown placeholder is provided.