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
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use async_trait::async_trait;
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use crate::ai::provider::Provider;
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use crate::ai::{ChatResponse, Message, ProviderInfo, TokenUsage};
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use crate::state::ProviderConfig;
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pub struct OpenAiProvider;
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#[async_trait]
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impl Provider for OpenAiProvider {
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fn name(&self) -> &str {
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"openai"
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}
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fn info(&self) -> ProviderInfo {
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ProviderInfo {
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name: "OpenAI Compatible".to_string(),
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supports_streaming: true,
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models: vec![
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"gpt-4o".to_string(),
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"gpt-4o-mini".to_string(),
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"gpt-4-turbo".to_string(),
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],
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}
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}
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async fn chat(
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&self,
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messages: Vec<Message>,
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config: &ProviderConfig,
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2026-04-03 20:45:42 +00:00
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) -> anyhow::Result<ChatResponse> {
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// Check if using MSI GenAI format
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let api_format = config.api_format.as_deref().unwrap_or("openai");
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if api_format == "msi_genai" {
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self.chat_msi_genai(messages, config).await
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} else {
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self.chat_openai(messages, config).await
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}
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}
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}
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impl OpenAiProvider {
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/// OpenAI-compatible API format (default)
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async fn chat_openai(
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&self,
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messages: Vec<Message>,
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config: &ProviderConfig,
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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
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) -> anyhow::Result<ChatResponse> {
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let client = reqwest::Client::new();
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2026-04-03 20:45:42 +00:00
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// Use custom endpoint path if provided, otherwise default to /chat/completions
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let endpoint_path = config
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.custom_endpoint_path
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.as_deref()
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.unwrap_or("/chat/completions");
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let url = format!("{}{}", config.api_url.trim_end_matches('/'), endpoint_path);
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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
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let body = serde_json::json!({
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"model": config.model,
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"messages": messages,
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"max_tokens": 4096,
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});
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2026-04-03 20:45:42 +00:00
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// Use custom auth header and prefix if provided
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let auth_header = config.custom_auth_header.as_deref().unwrap_or("Authorization");
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let auth_prefix = config.custom_auth_prefix.as_deref().unwrap_or("Bearer ");
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let auth_value = format!("{}{}", auth_prefix, config.api_key);
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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
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let resp = client
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.post(&url)
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2026-04-03 20:45:42 +00:00
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.header(auth_header, auth_value)
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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
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.header("Content-Type", "application/json")
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.json(&body)
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.send()
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.await?;
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if !resp.status().is_success() {
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let status = resp.status();
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let text = resp.text().await?;
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2026-03-15 18:28:59 +00:00
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anyhow::bail!("OpenAI API error {status}: {text}");
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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
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}
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let json: serde_json::Value = resp.json().await?;
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let content = json["choices"][0]["message"]["content"]
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.as_str()
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.ok_or_else(|| anyhow::anyhow!("No content in response"))?
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.to_string();
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let usage = json.get("usage").and_then(|u| {
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Some(TokenUsage {
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prompt_tokens: u["prompt_tokens"].as_u64()? as u32,
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completion_tokens: u["completion_tokens"].as_u64()? as u32,
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total_tokens: u["total_tokens"].as_u64()? as u32,
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})
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});
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Ok(ChatResponse {
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content,
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model: config.model.clone(),
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usage,
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})
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}
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2026-04-03 20:45:42 +00:00
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/// MSI GenAI custom format
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async fn chat_msi_genai(
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&self,
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messages: Vec<Message>,
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config: &ProviderConfig,
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) -> anyhow::Result<ChatResponse> {
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let client = reqwest::Client::new();
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// Use custom endpoint path, default to empty (API URL already includes /api/v2/chat)
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let endpoint_path = config.custom_endpoint_path.as_deref().unwrap_or("");
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let url = format!("{}{}", config.api_url.trim_end_matches('/'), endpoint_path);
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// Extract system message if present
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let system_message = messages
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.iter()
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.find(|m| m.role == "system")
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.map(|m| m.content.clone());
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// Get last user message as prompt
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let prompt = messages
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.iter()
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.rev()
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.find(|m| m.role == "user")
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.map(|m| m.content.clone())
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.ok_or_else(|| anyhow::anyhow!("No user message found"))?;
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// Build request body
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let mut body = serde_json::json!({
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"model": config.model,
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"prompt": prompt,
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});
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2026-04-03 21:34:00 +00:00
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// Add userId if provided (CORE ID email)
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if let Some(user_id) = &config.user_id {
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body["userId"] = serde_json::Value::String(user_id.clone());
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}
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2026-04-03 20:45:42 +00:00
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// Add optional system message
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if let Some(system) = system_message {
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body["system"] = serde_json::Value::String(system);
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}
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// Add session ID if available (for conversation continuity)
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if let Some(session_id) = &config.session_id {
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body["sessionId"] = serde_json::Value::String(session_id.clone());
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}
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// Use custom auth header and prefix (no prefix for MSI GenAI)
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let auth_header = config
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.custom_auth_header
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.as_deref()
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.unwrap_or("x-msi-genai-api-key");
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let auth_prefix = config.custom_auth_prefix.as_deref().unwrap_or("");
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let auth_value = format!("{}{}", auth_prefix, config.api_key);
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let resp = client
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.post(&url)
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.header(auth_header, auth_value)
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.header("Content-Type", "application/json")
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2026-04-03 21:34:00 +00:00
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.header("X-msi-genai-client", "tftsr-devops-investigation")
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2026-04-03 20:45:42 +00:00
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.json(&body)
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.send()
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.await?;
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if !resp.status().is_success() {
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let status = resp.status();
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let text = resp.text().await?;
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anyhow::bail!("MSI GenAI API error {status}: {text}");
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}
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let json: serde_json::Value = resp.json().await?;
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// Extract response content from "msg" field
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let content = json["msg"]
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.as_str()
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.ok_or_else(|| anyhow::anyhow!("No 'msg' field in response"))?
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.to_string();
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// Note: sessionId from response should be stored back to config.session_id
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// This would require making config mutable or returning it as part of ChatResponse
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// For now, the caller can extract it from the response if needed
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// TODO: Consider adding session_id to ChatResponse struct
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Ok(ChatResponse {
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content,
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model: config.model.clone(),
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usage: None, // MSI GenAI doesn't provide token usage in response
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})
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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
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}
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