tftsr-devops_investigation/src-tauri/src/ai/anthropic.rs

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feat: initial implementation of TFTSR IT Triage & RCA application Implements Phases 1-8 of the TFTSR implementation plan. Rust backend (Tauri 2.x, src-tauri/): - Multi-provider AI: OpenAI-compatible, Anthropic, Gemini, Mistral, Ollama - PII detection engine: 11 regex patterns with overlap resolution - SQLCipher AES-256 encrypted database with 10 versioned migrations - 28 Tauri IPC commands for triage, analysis, document, and system ops - Ollama: hardware probe, model recommendations, pull/delete with events - RCA and blameless post-mortem Markdown document generators - PDF export via printpdf - Audit log: SHA-256 hash of every external data send - Integration stubs for Confluence, ServiceNow, Azure DevOps (v0.2) Frontend (React 18 + TypeScript + Vite, src/): - 9 pages: full triage workflow NewIssue→LogUpload→Triage→Resolution→RCA→Postmortem→History+Settings - 7 components: ChatWindow, TriageProgress, PiiDiffViewer, DocEditor, HardwareReport, ModelSelector, UI primitives - 3 Zustand stores: session, settings (persisted), history - Type-safe tauriCommands.ts matching Rust backend types exactly - 8 IT domain system prompts (Linux, Windows, Network, K8s, DB, Virt, HW, Obs) DevOps: - .woodpecker/test.yml: rustfmt, clippy, cargo test, tsc, vitest on every push - .woodpecker/release.yml: linux/amd64 + linux/arm64 builds, Gogs release upload Verified: - cargo check: zero errors - tsc --noEmit: zero errors - vitest run: 13/13 unit tests passing Co-Authored-By: Claude Sonnet 4.6 (1M context) <noreply@anthropic.com>
2026-03-15 03:36:25 +00:00
use async_trait::async_trait;
use crate::ai::provider::Provider;
use crate::ai::{ChatResponse, Message, ProviderInfo, TokenUsage};
use crate::state::ProviderConfig;
pub struct AnthropicProvider;
#[async_trait]
impl Provider for AnthropicProvider {
fn name(&self) -> &str {
"anthropic"
}
fn info(&self) -> ProviderInfo {
ProviderInfo {
name: "Anthropic".to_string(),
supports_streaming: true,
models: vec![
"claude-sonnet-4-20250514".to_string(),
"claude-haiku-4-20250414".to_string(),
"claude-3-5-sonnet-20241022".to_string(),
],
}
}
async fn chat(
&self,
messages: Vec<Message>,
config: &ProviderConfig,
) -> anyhow::Result<ChatResponse> {
let client = reqwest::Client::new();
let url = format!(
"{}/v1/messages",
config
.api_url
.trim_end_matches('/')
.trim_end_matches("/v1/messages")
);
// Extract system message if the first message has role "system"
let (system_text, chat_messages): (Option<String>, Vec<&Message>) = {
let mut sys = None;
let mut msgs = Vec::new();
for msg in &messages {
if msg.role == "system" && sys.is_none() {
sys = Some(msg.content.clone());
} else {
msgs.push(msg);
}
}
(sys, msgs)
};
// Build Anthropic messages format
let api_messages: Vec<serde_json::Value> = chat_messages
.iter()
.map(|m| {
serde_json::json!({
"role": if m.role == "assistant" { "assistant" } else { "user" },
"content": m.content,
})
})
.collect();
let mut body = serde_json::json!({
"model": config.model,
"messages": api_messages,
"max_tokens": 4096,
});
if let Some(sys) = &system_text {
body["system"] = serde_json::Value::String(sys.clone());
}
let resp = client
.post(&url)
.header("x-api-key", &config.api_key)
.header("anthropic-version", "2023-06-01")
.header("Content-Type", "application/json")
.json(&body)
.send()
.await?;
if !resp.status().is_success() {
let status = resp.status();
let text = resp.text().await?;
anyhow::bail!("Anthropic API error {}: {}", status, text);
}
let json: serde_json::Value = resp.json().await?;
// Parse content from response.content[0].text
let content = json["content"]
.as_array()
.and_then(|arr| arr.first())
.and_then(|block| block["text"].as_str())
.ok_or_else(|| anyhow::anyhow!("No text content in Anthropic response"))?
.to_string();
let usage = json.get("usage").and_then(|u| {
Some(TokenUsage {
prompt_tokens: u["input_tokens"].as_u64()? as u32,
completion_tokens: u["output_tokens"].as_u64()? as u32,
total_tokens: (u["input_tokens"].as_u64()? + u["output_tokens"].as_u64()?) as u32,
})
});
let model = json["model"]
.as_str()
.unwrap_or(&config.model)
.to_string();
Ok(ChatResponse {
content,
model,
usage,
})
}
}