docs: fix docs typos and example issues for issue 725

Correct broken snippets and grammar, fix RST formatting issues, and remove decorative emoji from documentation headers for consistency with project standards.

Author: vaquarkhan

README.md

@@ -40,7 +40,7 @@ pluggable persisters (e.g. for memory) to save & load application state.
 Link to [documentation](https://burr.apache.org/). Quick (<3min) video intro [here](https://www.loom.com/share/a10f163428b942fea55db1a84b1140d8?sid=1512863b-f533-4a42-a2f3-95b13deb07c9).
 Longer [video intro & walkthrough](https://www.youtube.com/watch?v=rEZ4oDN0GdU). Blog post [here](https://blog.dagworks.io/p/burr-develop-stateful-ai-applications). Join discord for help/questions [here](https://discord.gg/6Zy2DwP4f3).
 
-## 🏃Quick start
+## Quick start
 
 Install from `pypi`:
 
@@ -57,7 +57,7 @@ burr
 ```
 
 This will open up Burr's telemetry UI. It comes loaded with some default data so you can click around.
-It also has a demo chat application to help demonstrate what the UI captures enabling you too see things changing in
+It also has a demo chat application to help demonstrate what the UI captures, enabling you to see things changing in
 real-time. Hit the "Demos" side bar on the left and select `chatbot`. To chat it requires the `OPENAI_API_KEY`
 environment variable to be set, but you can still see how it works if you don't have an API key set.
 
@@ -73,7 +73,7 @@ See if you can find it.
 
 For more details see the [getting started guide](https://burr.apache.org/getting_started/simple-example/).
 
-## 🔩 How does Apache Burr work?
+## How does Apache Burr work?
 
 With Apache Burr you express your application as a state machine (i.e. a graph/flowchart).
 You can (and should!) use it for anything in which you have to manage state, track complex decisions, add human feedback, or dictate an idempotent, self-persisting workflow.
@@ -94,7 +94,7 @@ def ai_response(state: State) -> State:
     # query the LLM however you want (or don't use an LLM, up to you...)
     response = _query_llm(state["chat_history"]) # Burr doesn't care how you use LLMs!
     chat_item = {"role" : "system", "content" : response}
-    return state.update(response=content).append(chat_history=chat_item)
+    return state.update(response=response).append(chat_history=chat_item)
 
 app = (
     ApplicationBuilder()
@@ -113,12 +113,12 @@ print("answer:", app.state["response"])
 Apache Burr includes:
 
 1. A (dependency-free) low-abstraction python library that enables you to build and manage state machines with simple python functions
-2. A UI you can use view execution telemetry for introspection and debugging
+2. A UI you can use to view execution telemetry for introspection and debugging
 3. A set of integrations to make it easier to persist state, connect to telemetry, and integrate with other systems
 
 ![Burr at work](https://github.com/apache/burr/blob/main/chatbot.gif)
 
-## 💻️ What can you do with Apache Burr?
+## What can you do with Apache Burr?
 
 Apache Burr can be used to power a variety of applications, including:
 
@@ -139,12 +139,12 @@ Apache Burr will _not_ tell you how to build your models, how to query APIs, or
 in a way that scales with your needs and makes following the logic of your system easy. Burr comes out of the box with a host of integrations
 including tooling to build a UI in streamlit and watch your state machine execute.
 
-## 🏗 Start building
+## Start building
 
 See the documentation for [getting started](https://burr.apache.org/getting_started/simple-example), and follow the example.
 Then read through some of the concepts and write your own application!
 
-## 📃 Comparison against common frameworks
+## Comparison against common frameworks
 
 While Apache Burr is attempting something (somewhat) unique, there are a variety of tools that occupy similar spaces:
 
@@ -157,7 +157,7 @@ While Apache Burr is attempting something (somewhat) unique, there are a variety
 | Open-source user-interface for monitoring/tracing |  ✅  |    ❌     |    ❌    |    ❌     |     ❌     |    ✅    |
 | Works with non-LLM use-cases                      |  ✅  |    ❌     |    ❌    |    ❌     |     ❌     |    ✅    |
 
-## 🌯 Why the name Burr?
+## Why the name Burr?
 
 Apache Burr is named after [Aaron Burr](https://en.wikipedia.org/wiki/Aaron_Burr), founding father, third VP of the United States, and murderer/arch-nemesis of [Alexander Hamilton](https://en.wikipedia.org/wiki/Alexander_Hamilton).
 What's the connection with (Apache) Hamilton? We imagine a world in which Burr and Hamilton lived in harmony and saw through their differences to better the union. Originally Apache Burr was built as a _harness_ to handle state between executions of Apache Hamilton DAGs (because DAGs don't have cycles),
@@ -207,7 +207,7 @@ but realized that it has a wide array of applications and decided to release it
 **Aditya K.**
 *DS Architect, TaskHuman*
 
-## 🛣 Roadmap
+## Roadmap
 
 While Apache Burr is stable and well-tested, we have quite a few tools/features on our roadmap!
 1. FastAPI integration + hosted deployment -- make it really easy to get Apache Burr in an app in production without thinking about REST APIs
@@ -222,11 +222,11 @@ While Apache Burr is stable and well-tested, we have quite a few tools/features
 If you want to avoid self-hosting the above solutions we're building Burr Cloud. To let us know you're interested
 sign up [here](https://forms.gle/w9u2QKcPrztApRedA) for the waitlist to get access.
 
-## 🤲 Contributing
+## Contributing
 
 We welcome contributors! To get started on developing, see the [developer-facing docs](https://burr.apache.org/contributing).
 
-## 👪 Contributors
+## Contributors
 
 ### Code contributions
 
@@ -249,12 +249,12 @@ Users who have contributed small docs fixes, design suggestions, and found bugs
 - [Evans](https://github.com/sudoevans)
 - [Sasmitha Manathunga](https://github.com/mmz-001)
 
-# 📑 License
+# License
 
 Apache Burr is released under the Apache 2.0 License. See [LICENSE](https://github.com/apache/burr/blob/main/LICENSE) for details.
 
-# 🌎 Community
-## 👨‍💻 Contributing
+# Community
+## Contributing
 We're very supportive of changes by new contributors, big or small! Make sure to discuss potential changes by creating an issue or commenting on an existing one before opening a pull request. Good first contributions include creating an example or an integration with your favorite Python library!
 
  To contribute, checkout our [contributing guidelines](https://github.com/apache/burr/blob/main/CONTRIBUTING.rst), our [developer setup guide](https://github.com/apache/burr/blob/main/developer_setup.md), and our [Code of Conduct](https://github.com/apache/burr/blob/main/CODE_OF_CONDUCT.md).

docs/concepts/actions.rst

@@ -26,7 +26,7 @@ Actions
 .. note::
 
     Actions are the core building block of Burr. They read from state and write to state.
-    They can be synchronous and asynchonous, and have both a ``sync`` and ``async`` API.
+    They can be synchronous and asynchronous, and have both a ``sync`` and ``async`` API.
     There are both function and class-based APIs.
 
 
@@ -96,7 +96,7 @@ above is equivalent to returning an empty dictionary instead of the results.
     from burr.core import action, State
 
     @action(reads=["var_from_state"], writes=["var_to_update"])
-    def custom_action(state: State) -> State
+    def custom_action(state: State) -> State:
         return results, state.update(var_to_update=var_from_state + 1)
 
     app = ApplicationBuilder().with_actions(

docs/concepts/state-persistence.rst

@@ -271,7 +271,7 @@ tracked runs. This is useful for debugging, or building an application that enab
             tracker,
             resume_at_next_action=True,
             default_state={"chat_history" : []},
-            default_entrypoint="human_converse
+            default_entrypoint="human_converse"
         )
         .with_tracker(tracker)
         .with_identifiers(app_id=app_id)

docs/concepts/tracking.rst

@@ -93,7 +93,7 @@ For example, to debug your Burr Application, you'd have some control flow like t
             fork_from_sequence_id=sequence_id,
             fork_from_partition_key=partition_key
         )
-        .with_tracker(tracker)  # tracking + checkpointing; one line 🪄.
+        .with_tracker(tracker)  # tracking + checkpointing in one line.
         .build()
     )
 

docs/examples/deployment/index.rst

@@ -17,9 +17,9 @@
    under the License.
 
 
-=============
-✈ Deployment
-=============
+==========
+Deployment
+==========
 
 Burr is specifically meant to make getting your product in production easier and faster.
 This section covers examples of getting Burr to production, as well as a brief overview of approaches/requirements.

docs/getting_started/install.rst

@@ -33,7 +33,8 @@ along with a fully built server.
 This will give you tools to visualize, track, and interact with the UI. You can explore the UI (including some sample projects)
 simply by running the command ``burr``. Up next we'll write our own application and follow it in the UI.
 
-If you're using poetry, you can't install the ``start`` target directly, due to [this issue](https://github.com/python-poetry/poetry/issues/3369).
+If you're using poetry, you can't install the ``start`` target directly, due to
+`this issue <https://github.com/python-poetry/poetry/issues/3369>`_.
 Instead, please install manually using the following command:
 
 .. code-block:: bash

docs/getting_started/simple-example.rst

@@ -48,7 +48,7 @@ So hold tight! This gets you started with the basics but there's a lot more you
 
     If you want to skip ahead to the cool stuff (chatbots, ML training, simulations, etc...) feel free to jump into the deep end and start with the :ref:`examples <examples>`.
 
-🤔 If you prefer to learn by video, check out
+If you prefer to learn by video, check out
 `this video walkthrough <https://www.youtube.com/watch?v=rEZ4oDN0GdU>`_
 using `this notebook <https://github.com/apache/burr/blob/main/examples/simple-chatbot-intro/notebook.ipynb>`_.
 
@@ -222,4 +222,4 @@ Now that we've built a basic application, we can do the following with only a fe
 2. :ref:`Persist state to a database + reload <state-persistence>` -- add a ``initialize_from`` line to the builder and select a pre-existing/implement a custom persistence method.
 3. :ref:`Add monitoring to track application data <tracking>` -- leverage ``with_tracker`` to track to the Burr UI and visualize your application live.
 4. :ref:`Stream results back <streaming>` -- minimize time to first token by streaming results back to the user.
-5. `Generate test cases from prior runs <https://github.com/apache/burr/tree/main/examples/test-case-creation>`_ -- use the ``burr-testburr-test-case create`` command to automatically generate test cases for your LLM app.
+5. `Generate test cases from prior runs <https://github.com/apache/burr/tree/main/examples/test-case-creation>`_ -- use the ``burr-test-case create`` command to automatically generate test cases for your LLM app.

docs/getting_started/up-next.rst

@@ -88,7 +88,7 @@ Once you're comfortable with the UI, you may want to get a sense of a few of the
 of the Burr library and where you can go to learn more about them:
 
 - :ref:`Creating custom actions <actions>` and calling out to integrated frameworks
-- :ref:`Running applications <applications>`, managing their lifeycyle, and inspecting the results
+- :ref:`Running applications <applications>`, managing their lifecycle, and inspecting the results
 - :ref:`Managing state <state>` -- persisting, inspecting, and updating
 - :ref:`Handling transition between nodes <transitions>` and managing the flow of your application
 - :ref:`Adding hooks to customize execution <hooks>` and integrate with other systems

examples/simple-chatbot-intro/README.md

@@ -19,7 +19,7 @@
 
 Example that goes with [introductory blog post](https://blog.dagworks.io/p/burr-develop-stateful-ai-applications).
 
-## 🏃Quick start
+## Quick start
 
 ```bash
 pip install "apache-burr[start]" jupyter