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[](https://crates.io/crates/air-interpreter-wasm)
[](https://www.npmjs.com/package/@fluencelabs/avm)
-# Aquamarine
+# AquaVM
- - composability medium
- - allows developers to express network choreography in a script
- - moves script & data from peer to peer in a single-use logical network with checking merkle proofs and signatures.
+AquaVM executes compiled [Aqua](https://github.com/fluencelabs/aqua), i.e., Aqua Intermediate Representation (AIR) scripts, and plays an integral part in the implementation of the Fluence peer-to-peer compute protocol. Specifically, AquaVM allows expressing network choreography in scripts and composing distributed, peer-to-peer hosted services. Moreover, AquaVM plays a significant role in facilitating *function addressability* in the Fluence network. Figure 1.
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+**Figure 1: Stylized AquaVM And AIR Model**
-## Fluence stack
+
-Fluence [nodes](https://github.com/fluencelabs/fluence) uses AIR to coordinate requests between different services run by [Marine](https://github.com/fluencelabs/marine):
+Since AquaVM compiles to Wasm, it can run in both client, such as browsers and nodejs apps, and server environments.
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+## AquaVM: Interpreter Execution Model
-## Aquamarine Intermediate Representation
+AquaVM's execution model facilitates Fluence protocol's data push model implemented as a *particle*, i.e., a smart packet comprised of data, AIR, and some metadata. In this context, AquaVM can be viewed as a pure state transition function that facilitates particle updates, which includes state management of particle data by taking previous and current state to produce a new state and an updated list of peers and call requests in the remaining AIR workflow. In addition to local service call execution, AquaVM handles requests from remote peers, e.g. as part of a parallel execution block, to call local services and handle the future response. See Figure 2.
-### AIR: What is it?
+**Figure 2: AquaVM Interpreter Execution Model**
-- S-expression-based low-level language
-- Controls Fluence network and its peers
-- Inspired by WAT (WebAssembly Text Format)
-- Meant to be a compile target
-- Development meant to happen in a higher-level language
-- Syntax is in flux, will change
+
-Scripts written in AIR look like this:
+In summary, the AquaVM execution model handles the topological hops for simple and advanced composition patters, such as (async) parallel service execution on one or multiple peers.
-
+## Aquamarine Intermediate Representation (AIR): IR For P2P Systems
-1. Gather chat members by calling chat.members
-2. Iterate through elements in members array, m = element
-3. Each m is an object, represented as array; [0] is the first field
-4. `(next m)` triggers next iteration
+AIR scripts control the Fluence peer-to-peer network, its peers and, through Marine adapter services, even resources on other (p2p) networks, such as IPFS and Filecoin, e.g., [Fluence IPFS library](https://doc.fluence.dev/aqua-book/libraries/aqua-ipfs).
+
+### What is AIR?
+
+- S-expression-based low-level language with binary form to come
+- Consists of twelve (12) instructions with more instructions to come
+- Semantics are inspired by [π-calculus](https://en.wikipedia.org/wiki/%CE%A0-calculus), [λ-calculus](https://en.wikipedia.org/wiki/Lambda_calculus) and [category theory](https://en.wikipedia.org/wiki/Category_theory)
+- Syntax is inspired by [Wasm Text Format](https://developer.mozilla.org/en-US/docs/WebAssembly/Understanding_the_text_format) (WAT) and [Lisp](https://en.wikipedia.org/wiki/Lisp_(programming_language))
### AIR: Instructions
-#### call: execution
-
-- `call` commands the execution
-- moves execution to a peer, specified by `location`
-- peer is expected to have specified WASM `service`
-- the `service` must have specified `function` available to be called
-- `argument list` is given to the `function`
-- result of the `function` is saved and available under `output name`
-- example call could be thought of as `data.result = dht.put(key, value)`
+#### call
-#### seq: sequential
-
+```wasm
+(call ( ) []