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cortex/crates/helexa-acp/src/provider/mod.rs
rob thijssen 8fa1d1962e
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feat(helexa-acp): anthropic-messages provider
Stage 6b. Third provider impl, completing the wire-format trio
(openai-chat, openai-responses, anthropic-messages). Lets a
helexa-acp endpoint configured with `wire_api = "anthropic-messages"`
drive Claude models — either against Anthropic directly or via
cortex's /v1/messages translation surface.

## Encoder (CompletionRequest → Anthropic body)

- System messages flatten to the top-level `system` field
  (concatenated with blank lines when there are multiple).
- User text → `{role:"user", content:"..."}`.
- User MultiPart (text + images) → `content` array with Anthropic's
  distinct image shape: `{type:"image", source:{type:"base64",
  media_type, data}}` — structurally different from OpenAI's
  `image_url` data URI.
- Assistant text → `{role:"assistant", content:"..."}`.
- Assistant tool_calls → `content` array with optional `{type:"text"}`
  block plus one `{type:"tool_use", id, name, input:<parsed json>}`
  per call. The internal arguments JSON string is parsed back to a
  Value before encoding (Anthropic requires the parsed form);
  malformed JSON falls back to a String input so the request body
  still serialises.
- Tool result → `{role:"user", content:[{type:"tool_result",
  tool_use_id, content}]}` per Anthropic's convention (no separate
  `tool` role).
- `max_tokens` is required by Anthropic; defaults to 8192 when the
  request doesn't specify.

## Decoder (Anthropic SSE → CompletionEvent)

Named SSE events:

- `message_start` → captures input_tokens from `usage` for the
  eventual UsageStats.
- `content_block_start` (type=text) → TextDelta (initial text, if any).
- `content_block_start` (type=tool_use) → ToolCallStart; if a
  pre-buffered `input` is present, also emits a single
  ToolCallArgsDelta.
- `content_block_start` (type=thinking, for extended-thinking
  models) → ReasoningDelta.
- `content_block_delta` (text_delta) → TextDelta.
- `content_block_delta` (input_json_delta) → ToolCallArgsDelta,
  correlated by block index.
- `content_block_delta` (thinking_delta) → ReasoningDelta.
- `message_delta` → Usage (final output_tokens) + Finish with
  stop_reason mapped: end_turn/stop_sequence → "stop", max_tokens
  → "length", tool_use → "tool_calls".
- `message_stop` → stream terminates.
- `ping` ignored (Anthropic's keep-alive).
- `error` → yields Err and ends the stream.

## Wiring

- Authentication: `x-api-key` + `anthropic-version: 2023-06-01`
  headers (not Bearer). Both ship when api_key is configured;
  servers that don't care (cortex) ignore them.
- `WireApi::AnthropicMessages` in build_provider now constructs
  the provider instead of erroring "reserved for future".
- `provider::mod.rs` registers the new module.

18 new unit tests: encoder (system collapse, multi-system concat,
default max_tokens, multipart with image, tool_use blocks, tool
results, malformed JSON arg fallback), decoder (text streaming,
tool_use lifecycle, max_tokens→length mapping, empty deltas, ping
events, error events, cancellation, malformed payload skip,
thinking blocks).

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
2026-05-31 14:01:59 +03:00

231 lines
8.8 KiB
Rust

//! Provider trait — the seam between the ACP-side agent loop and
//! whatever wire protocol an endpoint actually speaks.
//!
//! Every concrete provider (OpenAI chat completions, OpenAI Responses,
//! Anthropic /v1/messages, Ollama native, …) implements
//! [`Provider`]. The agent constructs a [`CompletionRequest`] using
//! provider-agnostic types and consumes a stream of
//! [`CompletionEvent`]s — neither end knows which wire format is on
//! the other side of the trait.
//!
//! Day-1 provider: [`openai_chat::OpenAIChatProvider`]. Day-N
//! providers slot in without touching `agent.rs`.
use async_trait::async_trait;
use futures::stream::BoxStream;
use serde::{Deserialize, Serialize};
use serde_json::Value;
use tokio_util::sync::CancellationToken;
pub mod anthropic_messages;
pub mod openai_chat;
pub mod openai_responses;
/// Provider-agnostic LLM endpoint. Implementations translate between
/// [`CompletionRequest`] / [`CompletionEvent`] and whatever wire
/// format their endpoint speaks.
#[async_trait]
pub trait Provider: Send + Sync {
/// Endpoint name as configured by the user (e.g. `"helexa"`,
/// `"openrouter"`). Used in logs and in the `endpoint:model`
/// selector.
fn name(&self) -> &str;
/// List models available at this endpoint. Used to build the
/// model-picker dropdown in editor clients (Stage 4). Should
/// return quickly (cache if necessary).
#[allow(dead_code)]
async fn list_models(&self) -> anyhow::Result<Vec<ModelInfo>>;
/// Run a chat completion. Returns a stream of provider-agnostic
/// events. The stream stops when the upstream finishes, when
/// `cancel` is fired, or when the stream is dropped.
async fn complete(
&self,
request: CompletionRequest,
cancel: CancellationToken,
) -> anyhow::Result<BoxStream<'static, anyhow::Result<CompletionEvent>>>;
}
/// One model exposed by a provider. Constructed by `list_models` —
/// Stage 4 is when the agent loop starts consuming it for the
/// model-picker dropdown.
#[allow(dead_code)]
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct ModelInfo {
pub id: String,
/// Human-friendly name, if the endpoint exposes one. Otherwise
/// `id` is used as the display name.
#[serde(default)]
pub display_name: Option<String>,
}
/// Inputs to a completion. Provider-agnostic — concrete providers
/// translate this into their wire format.
#[derive(Debug, Clone)]
pub struct CompletionRequest {
/// Endpoint-local model id (without the `endpoint:` prefix).
pub model: String,
pub messages: Vec<Message>,
/// Tools the model is allowed to call. Empty list means no tool
/// support advertised.
pub tools: Vec<ToolSpec>,
pub temperature: Option<f64>,
pub top_p: Option<f64>,
pub max_tokens: Option<u64>,
}
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct Message {
pub role: Role,
pub content: MessageContent,
}
#[derive(Debug, Clone, Copy, PartialEq, Eq, Serialize, Deserialize)]
#[serde(rename_all = "snake_case")]
pub enum Role {
System,
User,
Assistant,
/// Tool result message. Provider impls turn this into whatever
/// shape the upstream wire format wants (OpenAI uses
/// `role: "tool"` + `tool_call_id`; Anthropic uses content blocks).
/// Stage 3 (tools) constructs this; Stage 2 never does.
Tool,
}
#[derive(Debug, Clone, Serialize, Deserialize)]
#[serde(tag = "type", rename_all = "snake_case")]
pub enum MessageContent {
/// Plain text turn (system / user / assistant). Struct variant
/// rather than newtype so the persisted JSON has an explicit
/// `text` field — that lets us use internal tagging on the
/// enum, which is incompatible with newtype-of-primitive
/// variants.
Text { text: String },
/// Mixed text + image user turn. Stage 5 introduces this when
/// Zed sends an `ImageContent` block alongside the user's prompt.
/// Providers that don't support vision should down-convert by
/// dropping image parts and concatenating text parts.
MultiPart { parts: Vec<MessagePart> },
/// Assistant turn that called one or more tools. Stage 3 starts
/// constructing this when the provider stream yields a
/// `ToolCallStart` / `ToolCallArgsDelta` sequence.
ToolCalls {
/// Optional text the assistant said alongside the tool calls.
text: Option<String>,
calls: Vec<ToolCall>,
},
/// Tool result. `tool_call_id` matches the assistant's call id.
/// Stage 3 constructs this after the tool runner finishes.
ToolResult {
tool_call_id: String,
content: String,
},
}
/// One part of a [`MessageContent::MultiPart`] message.
#[derive(Debug, Clone, Serialize, Deserialize)]
#[serde(tag = "type", rename_all = "snake_case")]
pub enum MessagePart {
Text { text: String },
Image(ImageData),
}
/// Inline image attachment. `data` is base64-encoded raw image
/// bytes; the encoder constructs an `image_url` data URI from it
/// at request time. `uri` carries any pointer the client supplied
/// (e.g. `file:///tmp/x.png`) — we keep it on the message for
/// debugging / future providers but the OpenAI encoder ignores it
/// when `data` is present (data wins, since it round-trips through
/// every wire format).
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct ImageData {
pub mime_type: String,
/// Base64-encoded image bytes (no `data:` prefix, no padding
/// stripped — exactly what `ImageContent.data` carried).
pub data: String,
#[serde(default, skip_serializing_if = "Option::is_none")]
pub uri: Option<String>,
}
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct ToolCall {
/// Provider-assigned id that ties the call to its result. The
/// Qwen3 wire format we use today doesn't carry this on the
/// model side (calls and results are matched positionally inside
/// a turn), so the field looks unused in the prod build — but it
/// flows through to `MessageContent::ToolResult.tool_call_id` for
/// history bookkeeping and a future strict-OpenAI backend will
/// consume it directly.
#[allow(dead_code)]
pub id: String,
pub name: String,
/// JSON-encoded arguments. Kept as a string because providers
/// stream argument bytes incrementally and only validate at the
/// end; the agent decodes once the call is complete.
pub arguments: String,
}
#[derive(Debug, Clone)]
pub struct ToolSpec {
pub name: String,
pub description: String,
/// JSON Schema of the arguments object.
pub parameters: Value,
}
/// Events emitted by a provider during a streaming completion.
#[derive(Debug, Clone)]
pub enum CompletionEvent {
/// Incremental visible text from the assistant.
TextDelta(String),
/// Incremental "reasoning" / thought text, if the model emits one
/// (e.g. Qwen3 with `<think>` tags surfaced as a separate stream,
/// or OpenAI reasoning models).
ReasoningDelta(String),
/// A new tool call has started. Stage 2 ignores the payload; the
/// agent loop in Stage 3 reads `index` to correlate with
/// [`Self::ToolCallArgsDelta`], `id` for the eventual tool-result
/// turn, and `name` to dispatch the runner.
#[allow(dead_code)]
ToolCallStart {
index: usize,
id: String,
name: String,
},
/// More argument bytes for a tool call already announced via
/// [`Self::ToolCallStart`]. Stage 2 ignores; Stage 3 accumulates
/// the bytes by `index` until the call's arguments are complete.
#[allow(dead_code)]
ToolCallArgsDelta { index: usize, args_delta: String },
/// A `<tool_call>` block whose JSON couldn't be parsed even with
/// the qwen3 module's repair attempts. The agent surfaces this
/// as a Failed `SessionUpdate::ToolCall` card with the raw body
/// visible (so the editor renders structured failure UI rather
/// than dumping the body inline in the message pane), and feeds
/// a synthetic tool-error message back into history so the
/// model can self-correct on the next round.
MalformedToolCall { raw: String },
/// Stream finished. Carries the upstream `finish_reason` if it
/// gave one (`"stop"`, `"length"`, `"tool_calls"`, …).
Finish { reason: Option<String> },
/// Final usage stats, if the provider supplied them. Stage 2
/// matches the variant to drop it; Stage 6b (token metrics) is
/// when the payload starts being read.
#[allow(dead_code)]
Usage(UsageStats),
}
/// Token accounting reported by the provider at the end of a stream.
/// Stage 2 doesn't surface usage anywhere — the stable `PromptResponse`
/// has no usage field, and the unstable variant is gated. Stage 6b
/// turns these on with Prometheus metrics.
#[allow(dead_code)]
#[derive(Debug, Clone, Copy, Default)]
pub struct UsageStats {
pub prompt_tokens: u64,
pub completion_tokens: u64,
pub total_tokens: u64,
}