feat(helexa-acp): scaffold ACP bridge with provider trait + OpenAI chat

Adds a new workspace crate `helexa-acp` (binary, Apache-2.0) — the
start of "the missing ACP binary" for multi-endpoint LLM setups
mixing public APIs, private LAN deployments, and various wire
formats. Today it speaks OpenAI /v1/chat/completions; the
Provider trait is the seam that lets OpenAI Responses, Anthropic
/v1/messages, and other wire formats slot in later without touching
the agent loop.

The crate is intentionally self-contained — no dependencies on the
other workspace crates (cortex-core, cortex-gateway, neuron) — so a
future migration to a dedicated GitHub repo is a Cargo.toml-only
change. All deps come from crates.io.

This commit lands:

  * `config.rs` — TOML config at $XDG_CONFIG_HOME/helexa-acp/config.toml
    with multi-endpoint support (each `[[endpoints]]` declares its
    name, base_url, wire_api, default_model, optional API key /
    api_key_env). Falls back to env-only single-endpoint config when
    no TOML exists (HELEXA_ACP_BASE_URL, HELEXA_ACP_MODEL, etc.). The
    `endpoint:model` selector syntax is validated and tested.

  * `provider/mod.rs` — `Provider` trait + provider-agnostic types
    (`CompletionRequest`, `CompletionEvent`, `Message`, `ToolCall`,
    `ToolSpec`, `Role`, `UsageStats`). Agent loop consumes these
    without knowing the wire format on the other side.

  * `provider/openai_chat.rs` — `OpenAIChatProvider` impl. Compatible
    with cortex, LM Studio, Ollama (compat mode), OpenRouter, OpenAI
    itself. Streams via reqwest + eventsource-stream + async-stream.
    Surfaces text deltas, reasoning deltas (for models that emit
    `reasoning_content`), tool-call lifecycle (start, args-delta,
    completion), usage, finish reason. Cancellation-token aware.

  * `main.rs` — tokio + stderr-only tracing-subscriber + Stdio
    transport. Builds a provider per configured endpoint at startup,
    surfacing config mistakes before the editor even initializes.
    Currently responds to `initialize`; everything else stubs to
    `not implemented yet` until the agent loop lands in the next
    commit.

12 unit tests pass — encoder shape, decoder shape (text-only,
tool-call progressive, cancellation, malformed-chunk recovery),
config parsing (multi-endpoint TOML, env fallback, validation).

The `#![allow(dead_code)]` on `provider/mod.rs` is temporary — the
agent loop in the next commit reads every field. It's noted in the
module-level docstring so the next reader knows.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
This commit is contained in:
2026-05-28 08:13:47 +03:00
parent 249b2e5c98
commit e23d5011d0
7 changed files with 2123 additions and 15 deletions

View File

@@ -0,0 +1,645 @@
//! OpenAI `/v1/chat/completions` provider.
//!
//! Covers cortex, LM Studio, Ollama (compat mode), OpenRouter, and
//! OpenAI itself. The wire format is well-documented and stable;
//! tool calls follow the `tools` request param + `tool_calls`
//! response delta convention shared by every reasonably-modern
//! OpenAI-compatible server.
use async_trait::async_trait;
use eventsource_stream::Eventsource;
use futures::{Stream, StreamExt, stream::BoxStream};
use serde::{Deserialize, Serialize};
use serde_json::{Value, json};
use tokio_util::sync::CancellationToken;
use super::{
CompletionEvent, CompletionRequest, Message, MessageContent, ModelInfo, Provider, Role,
ToolCall, ToolSpec, UsageStats,
};
use crate::config::EndpointConfig;
// Several fields and types in this module are only used through the
// async HTTP path in `complete()` and `list_models()`. Tests don't
// stand up a mock HTTP server (we'd be over-engineering for the
// payoff), so clippy's dead-code pass under `--tests` flags them.
// Each `allow(dead_code)` below names exactly what's exercised only
// at runtime, with a one-line rationale so the next reader can tell
// it's intentional.
pub struct OpenAIChatProvider {
endpoint: EndpointConfig,
/// Read by `list_models` and `complete` (bearer auth header).
#[allow(dead_code)]
api_key: Option<String>,
/// Read by `list_models` and `complete` (request builder).
#[allow(dead_code)]
http: reqwest::Client,
}
impl OpenAIChatProvider {
pub fn new(endpoint: EndpointConfig) -> anyhow::Result<Self> {
let api_key = endpoint.resolve_api_key()?;
let http = reqwest::Client::builder()
// Generous timeout: cortex may need to cold-load a model
// before serving the first chunk, which can be tens of
// seconds. We rely on cancellation for early termination,
// not on timeout.
.timeout(std::time::Duration::from_secs(600))
.build()?;
Ok(Self {
endpoint,
api_key,
http,
})
}
}
#[async_trait]
impl Provider for OpenAIChatProvider {
fn name(&self) -> &str {
&self.endpoint.name
}
async fn list_models(&self) -> anyhow::Result<Vec<ModelInfo>> {
let mut req = self.http.get(self.endpoint.models_url());
if let Some(key) = &self.api_key {
req = req.bearer_auth(key);
}
let resp = req
.send()
.await
.map_err(|e| anyhow::anyhow!("{} list_models: {e}", self.endpoint.name))?;
let status = resp.status();
if !status.is_success() {
let body = resp.text().await.unwrap_or_default();
anyhow::bail!(
"{} list_models returned {}: {}",
self.endpoint.name,
status,
body
);
}
let body: WireModelsResponse = resp.json().await?;
Ok(body
.data
.into_iter()
.map(|m| ModelInfo {
id: m.id,
display_name: None,
})
.collect())
}
async fn complete(
&self,
request: CompletionRequest,
cancel: CancellationToken,
) -> anyhow::Result<BoxStream<'static, anyhow::Result<CompletionEvent>>> {
let body = encode_request(&request);
let mut req = self
.http
.post(self.endpoint.chat_completions_url())
.json(&body);
if let Some(key) = &self.api_key {
req = req.bearer_auth(key);
}
let resp = req
.send()
.await
.map_err(|e| anyhow::anyhow!("{} chat_completion send: {e}", self.endpoint.name))?;
let status = resp.status();
if !status.is_success() {
let body = resp.text().await.unwrap_or_default();
anyhow::bail!(
"{} chat_completion returned {}: {}",
self.endpoint.name,
status,
body
);
}
let sse = resp.bytes_stream().eventsource();
let stream = decode_stream(sse, cancel);
Ok(Box::pin(stream))
}
}
#[cfg(test)]
mod tests {
use super::*;
use futures::stream;
use url::Url;
fn ep() -> EndpointConfig {
EndpointConfig {
name: "test".into(),
base_url: Url::parse("http://localhost:9999/v1").unwrap(),
wire_api: crate::config::WireApi::OpenAiChat,
default_model: None,
api_key: None,
api_key_env: None,
}
}
#[test]
fn encodes_text_only_request() {
let req = CompletionRequest {
model: "helexa/large".into(),
messages: vec![
Message {
role: Role::System,
content: MessageContent::Text("you are helpful".into()),
},
Message {
role: Role::User,
content: MessageContent::Text("hi".into()),
},
],
tools: vec![],
temperature: Some(0.7),
top_p: None,
max_tokens: Some(256),
};
let body = encode_request(&req);
assert_eq!(body["model"], "helexa/large");
assert_eq!(body["stream"], true);
assert_eq!(body["temperature"], 0.7);
assert_eq!(body["max_tokens"], 256);
assert!(body.get("top_p").is_none(), "absent options are omitted");
let messages = body["messages"].as_array().unwrap();
assert_eq!(messages.len(), 2);
assert_eq!(messages[0]["role"], "system");
assert_eq!(messages[1]["role"], "user");
assert_eq!(messages[1]["content"], "hi");
assert!(body.get("tools").is_none(), "empty tools omitted");
assert_eq!(body["stream_options"]["include_usage"], true);
}
#[test]
fn encodes_tool_call_round_trip() {
let req = CompletionRequest {
model: "x".into(),
messages: vec![
Message {
role: Role::Assistant,
content: MessageContent::ToolCalls {
text: Some("calling read_file".into()),
calls: vec![ToolCall {
id: "call_1".into(),
name: "read_file".into(),
arguments: "{\"path\":\"/tmp/a.txt\"}".into(),
}],
},
},
Message {
role: Role::Tool,
content: MessageContent::ToolResult {
tool_call_id: "call_1".into(),
content: "file contents".into(),
},
},
],
tools: vec![ToolSpec {
name: "read_file".into(),
description: "Read a file".into(),
parameters: json!({"type": "object", "properties": {"path": {"type": "string"}}}),
}],
temperature: None,
top_p: None,
max_tokens: None,
};
let body = encode_request(&req);
// Tool defs flow through:
let tools = body["tools"].as_array().unwrap();
assert_eq!(tools[0]["function"]["name"], "read_file");
// Assistant tool_calls flow through:
let asst = &body["messages"][0];
assert_eq!(asst["role"], "assistant");
assert_eq!(asst["tool_calls"][0]["id"], "call_1");
assert_eq!(asst["tool_calls"][0]["function"]["name"], "read_file");
// Tool result flows through:
let tool = &body["messages"][1];
assert_eq!(tool["role"], "tool");
assert_eq!(tool["tool_call_id"], "call_1");
assert_eq!(tool["content"], "file contents");
}
/// Build a fake eventsource stream from canned SSE `data:` lines.
fn fake_sse(
lines: Vec<&'static str>,
) -> impl Stream<
Item = std::result::Result<
eventsource_stream::Event,
eventsource_stream::EventStreamError<reqwest::Error>,
>,
> {
stream::iter(lines.into_iter().map(|data| {
Ok(eventsource_stream::Event {
event: "message".into(),
data: data.into(),
id: String::new(),
retry: None,
})
}))
}
#[tokio::test]
async fn decodes_text_then_finish() {
let sse = fake_sse(vec![
r#"{"choices":[{"delta":{"content":"hel"},"finish_reason":null}]}"#,
r#"{"choices":[{"delta":{"content":"lo"},"finish_reason":null}]}"#,
r#"{"choices":[{"delta":{},"finish_reason":"stop"}]}"#,
r#"{"choices":[],"usage":{"prompt_tokens":5,"completion_tokens":2,"total_tokens":7}}"#,
"[DONE]",
]);
let stream = decode_stream(sse, CancellationToken::new());
let events: Vec<_> = stream.collect().await;
let events: Vec<_> = events.into_iter().map(|r| r.unwrap()).collect();
assert!(matches!(&events[0], CompletionEvent::TextDelta(s) if s == "hel"));
assert!(matches!(&events[1], CompletionEvent::TextDelta(s) if s == "lo"));
assert!(
matches!(&events[2], CompletionEvent::Finish { reason } if reason.as_deref() == Some("stop"))
);
assert!(matches!(&events[3], CompletionEvent::Usage(u) if u.total_tokens == 7));
assert_eq!(events.len(), 4);
}
#[tokio::test]
async fn decodes_tool_call_progressively() {
let sse = fake_sse(vec![
r#"{"choices":[{"delta":{"tool_calls":[{"index":0,"id":"c1","function":{"name":"read_file"}}]}}]}"#,
r#"{"choices":[{"delta":{"tool_calls":[{"index":0,"function":{"arguments":"{\"pa"}}]}}]}"#,
r#"{"choices":[{"delta":{"tool_calls":[{"index":0,"function":{"arguments":"th\":\"/tmp/a\"}"}}]}}]}"#,
r#"{"choices":[{"delta":{},"finish_reason":"tool_calls"}]}"#,
"[DONE]",
]);
let events: Vec<_> = decode_stream(sse, CancellationToken::new())
.collect::<Vec<_>>()
.await
.into_iter()
.map(|r| r.unwrap())
.collect();
assert!(matches!(
&events[0],
CompletionEvent::ToolCallStart { index: 0, id, name }
if id == "c1" && name == "read_file"
));
assert!(matches!(
&events[1],
CompletionEvent::ToolCallArgsDelta { index: 0, args_delta }
if args_delta == "{\"pa"
));
assert!(matches!(
&events[2],
CompletionEvent::ToolCallArgsDelta { index: 0, args_delta }
if args_delta == "th\":\"/tmp/a\"}"
));
assert!(matches!(
&events[3],
CompletionEvent::Finish { reason } if reason.as_deref() == Some("tool_calls")
));
}
#[tokio::test]
async fn cancellation_ends_stream() {
let sse = fake_sse(vec![
r#"{"choices":[{"delta":{"content":"hello"}}]}"#,
// These chunks should NOT be consumed once we cancel.
r#"{"choices":[{"delta":{"content":" world"}}]}"#,
]);
let cancel = CancellationToken::new();
cancel.cancel(); // pre-cancel so the first select! arm wins.
let events: Vec<_> = decode_stream(sse, cancel).collect().await;
assert!(events.is_empty(), "cancelled stream yields nothing");
}
#[tokio::test]
async fn skips_malformed_chunks() {
let sse = fake_sse(vec![
r#"{"choices":[{"delta":{"content":"before"}}]}"#,
r#"not valid json"#,
r#"{"choices":[{"delta":{"content":"after"}}]}"#,
"[DONE]",
]);
let events: Vec<_> = decode_stream(sse, CancellationToken::new())
.collect::<Vec<_>>()
.await
.into_iter()
.map(|r| r.unwrap())
.collect();
// The bad chunk is skipped with a warn; the bracketing
// chunks both come through.
assert!(matches!(&events[0], CompletionEvent::TextDelta(s) if s == "before"));
assert!(matches!(&events[1], CompletionEvent::TextDelta(s) if s == "after"));
assert_eq!(events.len(), 2);
}
#[test]
fn provider_construction_is_cheap() {
// Ensures construction doesn't accidentally make any HTTP calls
// — important because helexa-acp builds a provider per
// configured endpoint at startup, before the editor has
// necessarily connected.
let p = OpenAIChatProvider::new(ep()).expect("construction");
assert_eq!(p.name(), "test");
}
}
// ── Request encoding ────────────────────────────────────────────────
fn encode_request(req: &CompletionRequest) -> Value {
let messages: Vec<Value> = req.messages.iter().map(encode_message).collect();
let mut body = json!({
"model": req.model,
"messages": messages,
"stream": true,
});
if let Value::Object(map) = &mut body {
if let Some(t) = req.temperature {
map.insert("temperature".into(), json!(t));
}
if let Some(p) = req.top_p {
map.insert("top_p".into(), json!(p));
}
if let Some(m) = req.max_tokens {
map.insert("max_tokens".into(), json!(m));
}
if !req.tools.is_empty() {
map.insert("tools".into(), encode_tools(&req.tools));
}
// Some servers (cortex via neuron, OpenAI) report usage at the
// end of the stream only when explicitly requested.
map.insert("stream_options".into(), json!({ "include_usage": true }));
}
body
}
fn encode_message(m: &Message) -> Value {
match (m.role, &m.content) {
(Role::System, MessageContent::Text(s)) => json!({"role": "system", "content": s}),
(Role::User, MessageContent::Text(s)) => json!({"role": "user", "content": s}),
(Role::Assistant, MessageContent::Text(s)) => json!({"role": "assistant", "content": s}),
(Role::Assistant, MessageContent::ToolCalls { text, calls }) => {
let calls_json: Vec<Value> = calls
.iter()
.map(|c| {
json!({
"id": c.id,
"type": "function",
"function": {
"name": c.name,
"arguments": c.arguments,
}
})
})
.collect();
json!({
"role": "assistant",
"content": text.clone().unwrap_or_default(),
"tool_calls": calls_json,
})
}
(
Role::Tool,
MessageContent::ToolResult {
tool_call_id,
content,
},
) => json!({
"role": "tool",
"tool_call_id": tool_call_id,
"content": content,
}),
// Mismatched (role, content) combinations shouldn't happen
// — the agent constructs them in pairs. If they do, degrade
// gracefully to a plain text turn so the request still goes
// out rather than crashing the conversation.
(role, content) => {
tracing::warn!(
?role,
?content,
"encode_message: unexpected (role, content) shape"
);
json!({"role": role_str(role), "content": content_as_text(content)})
}
}
}
fn role_str(r: Role) -> &'static str {
match r {
Role::System => "system",
Role::User => "user",
Role::Assistant => "assistant",
Role::Tool => "tool",
}
}
fn content_as_text(c: &MessageContent) -> String {
match c {
MessageContent::Text(s) => s.clone(),
MessageContent::ToolCalls { text, .. } => text.clone().unwrap_or_default(),
MessageContent::ToolResult { content, .. } => content.clone(),
}
}
fn encode_tools(tools: &[ToolSpec]) -> Value {
let arr: Vec<Value> = tools
.iter()
.map(|t| {
json!({
"type": "function",
"function": {
"name": t.name,
"description": t.description,
"parameters": t.parameters,
}
})
})
.collect();
Value::Array(arr)
}
// ── Response decoding ───────────────────────────────────────────────
// Both types are deserialised through `list_models()`. Tests don't
// exercise that path (no mock HTTP server), so clippy --tests reports
// them as dead; in real use they're hit on every Zed model-picker
// refresh.
#[allow(dead_code)]
#[derive(Debug, Deserialize)]
struct WireModelsResponse {
data: Vec<WireModelObject>,
}
#[allow(dead_code)]
#[derive(Debug, Deserialize)]
struct WireModelObject {
id: String,
}
#[derive(Debug, Deserialize)]
struct WireChunk {
#[serde(default)]
choices: Vec<WireChunkChoice>,
#[serde(default)]
usage: Option<WireUsage>,
}
#[derive(Debug, Deserialize)]
struct WireChunkChoice {
#[serde(default)]
delta: WireDelta,
#[serde(default)]
finish_reason: Option<String>,
}
#[derive(Debug, Default, Deserialize)]
struct WireDelta {
#[serde(default)]
content: Option<String>,
/// Some servers expose chain-of-thought text via this field
/// (mirroring OpenAI's reasoning-model schema). When present we
/// surface it as `ReasoningDelta`.
#[serde(default)]
reasoning_content: Option<String>,
#[serde(default)]
tool_calls: Vec<WireToolCallDelta>,
}
#[derive(Debug, Deserialize)]
struct WireToolCallDelta {
#[serde(default)]
index: usize,
#[serde(default)]
id: Option<String>,
#[serde(default)]
function: Option<WireFunctionDelta>,
}
#[derive(Debug, Default, Deserialize)]
struct WireFunctionDelta {
#[serde(default)]
name: Option<String>,
#[serde(default)]
arguments: Option<String>,
}
#[derive(Debug, Deserialize, Serialize)]
struct WireUsage {
prompt_tokens: u64,
completion_tokens: u64,
total_tokens: u64,
}
/// Convert the eventsource-stream byte SSE into provider-agnostic
/// events. Bails the stream on the first parse failure with a logged
/// warning — partial state is preferable to silently corrupting a
/// conversation by skipping bad events.
fn decode_stream<S>(
sse: S,
cancel: CancellationToken,
) -> impl Stream<Item = anyhow::Result<CompletionEvent>>
where
S: Stream<
Item = Result<
eventsource_stream::Event,
eventsource_stream::EventStreamError<reqwest::Error>,
>,
> + Send
+ 'static,
{
async_stream::stream! {
// Track which (index) tool calls we've already announced. The
// OpenAI stream emits the id and name only on the first delta
// for each tool call; later deltas just carry argument bytes.
let mut announced: std::collections::HashSet<usize> = Default::default();
let mut sse = Box::pin(sse);
loop {
tokio::select! {
// `biased;` checks `cancel.cancelled()` first on every
// poll — without it, a pre-cancelled token loses to a
// ready SSE chunk, and a mid-stream cancellation could
// still consume one more chunk before noticing.
biased;
_ = cancel.cancelled() => {
tracing::debug!("openai_chat: cancellation requested, ending stream");
break;
}
next = sse.next() => {
let Some(event) = next else { break };
let event = match event {
Ok(e) => e,
Err(e) => {
yield Err(anyhow::anyhow!("SSE transport: {e}"));
break;
}
};
let data = event.data;
if data == "[DONE]" {
break;
}
let chunk: WireChunk = match serde_json::from_str(&data) {
Ok(c) => c,
Err(e) => {
tracing::warn!(
error = %e,
raw = %data,
"openai_chat: failed to parse SSE chunk; skipping"
);
continue;
}
};
for choice in chunk.choices {
if let Some(text) = choice.delta.content
&& !text.is_empty()
{
yield Ok(CompletionEvent::TextDelta(text));
}
if let Some(reasoning) = choice.delta.reasoning_content
&& !reasoning.is_empty()
{
yield Ok(CompletionEvent::ReasoningDelta(reasoning));
}
for tc in choice.delta.tool_calls {
let idx = tc.index;
if announced.insert(idx) {
let id = tc.id.unwrap_or_default();
let name = tc
.function
.as_ref()
.and_then(|f| f.name.clone())
.unwrap_or_default();
yield Ok(CompletionEvent::ToolCallStart {
index: idx,
id,
name,
});
}
if let Some(f) = tc.function
&& let Some(args) = f.arguments
&& !args.is_empty()
{
yield Ok(CompletionEvent::ToolCallArgsDelta {
index: idx,
args_delta: args,
});
}
}
if let Some(reason) = choice.finish_reason {
yield Ok(CompletionEvent::Finish { reason: Some(reason) });
}
}
if let Some(u) = chunk.usage {
yield Ok(CompletionEvent::Usage(UsageStats {
prompt_tokens: u.prompt_tokens,
completion_tokens: u.completion_tokens,
total_tokens: u.total_tokens,
}));
}
}
}
}
}
}