Update various docs (#4)

* rename cli tool

* remove redundant docs

* update docs

* update macos instructions

* add badges

docs/development/create-a-component.md

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+# Creating a component
+
+A fundamental concept in kotaemon is "component".
+
+Anything that isn't data or data structure is a "component". A component can be
+thought of as a step within a pipeline. It takes in some input, processes it,
+and returns an output, just the same as a Python function! The output will then
+become an input for the next component in a pipeline. In fact, a pipeline is just
+a component. More appropriately, a nested component: a component that makes use of one or more other components in
+the processing step. So in reality, there isn't a difference between a pipeline
+and a component! Because of that, in kotaemon, we will consider them the
+same as "component".
+
+To define a component, you will:
+
+1. Create a class that subclasses from `kotaemon.base.BaseComponent`
+2. Declare init params with type annotation
+3. Declare nodes (nodes are just other components!) with type annotation
+4. Implement the processing logic in `run`.
+
+The syntax of a component is as follow:
+
+```python
+from kotaemon.base import BaseComponent
+from kotaemon.llms import AzureChatOpenAI
+from kotaemon.parsers import RegexExtractor
+
+
+class FancyPipeline(BaseComponent):
+    param1: str = "This is param1"
+    param2: int = 10
+    param3: float
+
+    node1: BaseComponent    # this is a node because of BaseComponent type annotation
+    node2: AzureChatOpenAI  # this is also a node because AzureChatOpenAI subclasses BaseComponent
+    node3: RegexExtractor   # this is also a node bceause RegexExtractor subclasses BaseComponent
+
+    def run(self, some_text: str):
+        prompt = (self.param1 + some_text) * int(self.param2 + self.param3)
+        llm_pred = self.node2(prompt).text
+        matches = self.node3(llm_pred)
+        return matches
+```
+
+Then this component can be used as follow:
+
+```python
+llm = AzureChatOpenAI(endpoint="some-endpont")
+extractor = RegexExtractor(pattern=["yes", "Yes"])
+
+component = FancyPipeline(
+    param1="Hello"
+    param3=1.5
+    node1=llm,
+    node2=llm,
+    node3=extractor
+)
+component("goodbye")
+```
+
+This way, we can define each operation as a reusable component, and use them to
+compose larger reusable components!
+
+## Benefits of component
+
+By defining a component as above, we formally encapsulate all the necessary
+information inside a single class. This introduces several benefits:
+
+1. Allow tools like promptui to inspect the inner working of a component in
+   order to automatically generate the promptui.
+2. Allow visualizing a pipeline for debugging purpose.