initial readme

Author: kvey

LICENSE

@@ -0,0 +1,21 @@
+MIT License
+
+Copyright (c) 2023 Thousand Birds Inc
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.

README.md

@@ -1,31 +1,90 @@
-# Thousand Birds - Chidori: A Reactive Runtime for AI Systems
+<div align="center">
 
-Thousand Birds offers a reactive environment to build AI systems seamlessly. Inspired by the notion of ["agents"](https://en.wikipedia.org/wiki/Intelligent_agent), Thousand Birds combines the strength of AI with the regularity of software development. Our goal is to create an environment where AI can operate smoothly and humans can interact efficiently with AI during its creation and maintenance.
+# &nbsp; Chidori &nbsp;
 
-### Important
+**A Reactive Runtime for AI Systems.**
 
-This is alpha software under active development. Breaking changes can happen anytime, without prior notice. You are welcome to experiment with the software, but please understand that we can't provide support at this time.
+<p>
+<a href="https://github.com/ThousandBirdsInc/chidori/commits"><img alt="GitHub Last Commit" src="https://img.shields.io/github/last-commit/ThousandBirdsInc/chidori" /></a>
+<a href="https://github.com/ThousandBirdsInc/chidori/issues"><img alt="GitHub Issues" src="https://img.shields.io/github/issues/ThousandBirdsInc/chidori" /></a>
+<a href="https://github.com/ThousandBirdsInc/chidori/pulls"><img alt="GitHub Pull Requests" src="https://img.shields.io/github/issues-pr/ThousandBirdsInc/chidori" /></a>
+<a href="https://github.com/ThousandBirdsInc/chidori/blob/main/LICENSE"><img alt="Github License" src="https://img.shields.io/badge/License-MIT-green.svg" /></a>
+<a href="https://github.com/ThousandBirdsInc/chidori"><img alt="GitHub Repo stars" src="https://img.shields.io/github/stars/ThousandBirdsInc/chidori?style=social" /></a>
+</p>
 
-For questions, issues and bug reports, please open an issue on Github.
+<br />
 
-### Why Another AI Framework?
+</div>
 
-Thousand Birds pushes to be more than a simple wrapper around LLMs. Our effort is to resolve as much of the accidental complexity of building systems in the category of long running agents as possible, helping the broader developer community build successful systems.
 
 ### Quick Links
-- [Example Agents](https://www.notion.so/Example-Agents-d2c4164cb0f64f7ab6716a6f6e55577d?pvs=21)
+- [Getting Started](https://github.com/ThousandBirdsInc/chidori/tree/main#-getting-started)
 - [Documentation](https://www.notion.so/Documentation-3fe20a82965148c7a0b480f7daf0aff6?pvs=21)
-- [Roadmap](https://www.notion.so/Roadmap-98b73a3aab9e48dcb2e51f87d9752c1c?pvs=21)
-- [About](https://www.notion.so/About-da11db5a115444f68c5d912dc077daee?pvs=21)
-- [Blog](https://www.notion.so/Blog-4a284fcb736d4e5e8ce2309303c272a2?pvs=21)
+- [About](https://github.com/ThousandBirdsInc/chidori/tree/main#-about)
+- [Roadmap](https://github.com/ThousandBirdsInc/chidori/tree/main#-roadmap)
+
+## ⚡️ Getting Started
+
+
+### Installation
+```bash
+npm i @1kbirds/chidori
+yarn add @1kbirds/chidori
+```
+```bash
+pip install chidori
+```
+```bash
+cargo install chidori
+```
+
+### Environment Variables
+```bash
+OPENAI_API_KEY=...
+```
+
+### Example
+```python
+chidori = Chidori("100", "http://localhost:9800")
+
+# Generate an inspirational quote
+iq = await self.client.prompt_node(
+    name="InspirationalQuote",
+    template="""Come up with a novel and interesting quote. Something that will make them
+    want to seize the day. Do not wrap the quote in quotes.
+    """
+)
+
+# Get the current date
+(await self.client.deno_code_node(
+    name="CurrentDate",
+    code=""" return {"output": "" + new Date() } """,
+)).run_when(iq)
+
+
+# Format the date in a fun way
+await self.client.prompt_node(
+    name="FunFormat",
+    queries=[""" query Q { CurrentDate { output } } """],
+    template="""Format the following in a fun and more informal way: {{CodeNode.output}} """
+)
+
+# Return the quote with the date
+await self.client.deno_code_node(
+    name="ResultingQuote",
+    queries=[""" query Q { FunFormat { promptResult } } """],
+    code=""" return {"output": "Your quote: " + "{{FunFormat.promptResult}}" } """
+)
+```
+
+## 🤔 About
 
 ### Reactive Runtime
-At its core, Thousand Birds brings a reactive runtime that orchestrates interactions between different agents and their components. The runtime comprises of "nodes", which react to system changes they subscribe to, providing dynamic and responsive behavior to your AI systems.
-
-Nodes can encompass code, prompts, vector databases, custom code, services, or even complete systems. The runtime was designed around the principles discussed in the paper ["Out of the Tar Pit"](https://github.com/papers-we-love/papers-we-love/blob/master/design/out-of-the-tar-pit.pdf), leveraging its concepts to help you create more dynamic, robust, and controlled agents.
+At its core, Thousand Birds brings a reactive runtime that orchestrates interactions between different agents and their components. The runtime is comprised of "nodes", which react to system changes they subscribe to, providing dynamic and responsive behavior in your AI systems.
+Nodes can encompass code, prompts, vector databases, custom code, services, or even complete systems. 
 
 ### Monitoring and Observability
-Thousand Birds ensures comprehensive monitoring and observability of your agents. We record all the changes emitted by nodes, enabling us to explain precisely what led to what, enhancing your debugging experience and understanding of the system’s production behavior.
+Thousand Birds ensures comprehensive monitoring and observability of your agents. We record all the inputs and outputs emitted by nodes, enabling us to explain precisely what led to what, enhancing your debugging experience and understanding of the system’s production behavior.
 
 ### Branching and Time-Travel
 With Thousand Birds, you can take snapshots of your system and explore different possible outcomes from that point (branching), or rewind the system to a previous state (time-travel). This functionality improves error handling, debugging, and system robustness by offering alternative pathways and do-overs.
@@ -36,10 +95,31 @@ Vector databases, akin to an AI’s brain, help your AI remember and understand
 ### Code Interpreter Environments
 Thousand Birds comes with first-class support for code interpreter environments like [Deno](https://deno.land/) or [Starlark](https://github.com/bazelbuild/starlark/blob/master/spec.md). You can execute code directly within your system, providing quick startup, ease of use, and secure execution. We're continually working on additional safeguards against running untrusted code, with containerized nodes support coming soon.
 
+## 🛣️ Roadmap
+
+### Short term
+* [ ] Improving the ergonomics of time travel and branching
+* [ ] Improving the ergonomics of subscribing nodes and constructing graphs
+* [ ] Adding support for containerized nodes
+* [ ] Allowing filtering in node queries
+
+### Med term
+* [ ] Analysis tools for comparing executions
+* [ ] Agent re-evaluation with feedback
+* [ ] Definitive patterns for human in the loop agents
+* [ ] Adding support for more vector databases 
+* [ ] Adding support for other LLM sources
+* [ ] Adding support for more code interpreter environments
+
+
 ## Contributing
 We look forward to future contributions from the community. For now it will be difficult to contribute, as we are still in the process of setting up our development environment. We will update this section as soon as we have a more stable development environment.
 If you have feedback or would like to chat with us, please add to the discussion on our Github issues!
 
+
+### Why Another AI Framework?
+Thousand Birds pushes to be more than a simple wrapper around LLMs. Our effort is to resolve as much of the accidental complexity of building systems in the category of long running agents as possible, helping the broader developer community build successful systems.
+
 ## Inspiration
 Our framework is inspired by the work of many others, including:
 * https://temporal.io/ - providing reliability and durability to workflows

toolchain/chidori/README.md

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+# Chidori
+
+## Generating Python Client
+- maturin develop --features python
+
+## Generating Nodejs Client
+- npm run build-release

toolchain/prompt-graph-core/README.md

@@ -2,11 +2,3 @@
 
 This implements an interface for constructing prompt graphs.
 This can be used to annotate existing implementations with graph definitions as well.
-
-Lambda definitions should include an endpoint to return the serialized prompt graph.
-
-## Generating Python Client
-- maturin develop --features python
-
-## Generating Nodejs Client
-- npm run build -- --release