feat: setup phase 3 agent infrastructure + enable docker ci on prs
CI / CI (push) Successful in 15m5s
CI / CI (push) Successful in 15m5s
- Enable docker build, sha extraction on PRs (validate Dockerfile) - Add SOPS encrypted memory-agent credentials - Plan 15 tasks: 5 memory service + 10 temporal workflow - Milestone: monitoring-agent (due 2025-03-15) - Ready: Forgejo API token needed for PR automation ``` Co-authored-by: rock <[email protected]>
This commit was merged in pull request #45.
This commit is contained in:
@@ -14,6 +14,9 @@ use async_trait::async_trait;
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use mem_core::entity::{Entity, EntityType};
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use serde::{Deserialize, Serialize};
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use crate::speaker_extractor::SpeakerExtractor;
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use crate::authentik_jwt::AuthentikJwtIssuer;
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use std::sync::Arc;
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use tokio::sync::Mutex;
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/// Extracted entity from LLM (intermediate representation)
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#[derive(Debug, Clone, Serialize, Deserialize)]
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@@ -40,16 +43,20 @@ pub trait EntityExtractor: Send + Sync {
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}
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/// LLM-based extractor with reflection verification (stage 1 + 2)
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/// Uses Authentik JWT tokens for authentication to LLM gateway
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pub struct LlmEntityExtractor {
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model_name: String,
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enable_reflection: bool,
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jwt_issuer: Option<Arc<Mutex<AuthentikJwtIssuer>>>,
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}
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impl LlmEntityExtractor {
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pub fn new(model_name: &str) -> Self {
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let jwt_issuer = AuthentikJwtIssuer::from_env().ok();
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Self {
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model_name: model_name.to_string(),
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enable_reflection: true,
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jwt_issuer: jwt_issuer.map(|iss| Arc::new(Mutex::new(iss))),
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}
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}
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@@ -80,11 +87,76 @@ impl LlmEntityExtractor {
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Ok(parsed.verified.into_iter().map(|v| (v.name, v.present)).collect())
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}
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/// Mock LLM call - replace with real API in production
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/// TODO (Phase 2.6): Integrate with api.riotpiao.com/v1/chat/completions
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/// TODO (Phase 2.6): Add JWT authentication from Authentik OIDC
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async fn simulate_llm(&self, _prompt: &str) -> Result<String> {
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// Production: call api.riotpiao.com with Bearer JWT token
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/// Call LLM via api.riotpiao.com using Authentik JWT
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/// Token is fetched from Authentik service account and cached
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async fn call_llm_endpoint(&self, prompt: &str) -> Result<String> {
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let endpoint = std::env::var("LLM_ENDPOINT")
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.unwrap_or_else(|_| "http://api-internal.riotpiao.com:8000/v1/chat/completions".to_string());
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let model = std::env::var("LLM_MODEL")
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.unwrap_or_else(|_| "qwen:7b".to_string());
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// Get JWT token from Authentik
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let auth_header = if let Some(jwt_issuer) = &self.jwt_issuer {
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let issuer = jwt_issuer.lock().await;
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match issuer.get_access_token().await {
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Ok(token) => format!("Bearer {}", token),
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Err(e) => {
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tracing::warn!("Failed to get Authentik JWT: {}", e);
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return Err(e);
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}
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}
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} else {
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// Fallback to env var if Authentik not configured
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let api_key = std::env::var("LLM_API_KEY")
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.or_else(|_| std::env::var("MEM_API_KEY"))
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.unwrap_or_else(|_| "default-key".to_string());
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format!("Bearer {}", api_key)
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};
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let client = reqwest::Client::new();
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// OpenAI-compatible API call
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let payload = serde_json::json!({
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"model": model,
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"messages": [
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{"role": "system", "content": "You are an entity extraction specialist. Extract named entities from text in JSON format."},
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{"role": "user", "content": prompt}
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],
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"temperature": 0.3,
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"max_tokens": 500
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});
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let response = client
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.post(&endpoint)
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.header("Authorization", auth_header)
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.header("Content-Type", "application/json")
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.json(&payload)
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.timeout(std::time::Duration::from_secs(30))
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.send()
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.await?;
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if !response.status().is_success() {
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tracing::warn!(
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"LLM API error: {} - {}",
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response.status(),
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response.text().await.unwrap_or_default()
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);
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// Fallback to mock response on error
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return Ok(r#"{"entities": []}"#.to_string());
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}
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let data: serde_json::Value = response.json().await?;
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let content = data["choices"][0]["message"]["content"]
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.as_str()
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.unwrap_or("{}")
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.to_string();
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tracing::debug!("LLM response (via Authentik JWT): {}", content);
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Ok(content)
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}
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/// Fallback mock LLM call (for testing without API)
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fn simulate_llm(&self, _prompt: &str) -> Result<String> {
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// Mock response for testing
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Ok(r#"{
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"entities": [
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@@ -134,7 +206,12 @@ Respond in JSON:
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text
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);
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let extraction_response = self.simulate_llm(&prompt).await?;
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// Try real LLM first, fallback to mock if not configured
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let extraction_response = if std::env::var("LLM_ENDPOINT").is_ok() {
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self.call_llm_endpoint(&prompt).await.unwrap_or_else(|_| self.simulate_llm(&prompt).unwrap_or_default())
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} else {
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self.simulate_llm(&prompt)?
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};
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let extracted = Self::parse_extraction(&extraction_response)?;
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entities.extend(extracted); // Add LLM-extracted entities after speaker
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@@ -155,7 +232,11 @@ Respond in JSON:
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text, entities
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);
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let reflection = self.simulate_llm(&reflection_prompt).await?;
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let reflection = if std::env::var("LLM_ENDPOINT").is_ok() {
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self.call_llm_endpoint(&reflection_prompt).await.unwrap_or_else(|_| self.simulate_llm(&reflection_prompt).unwrap_or_default())
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} else {
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self.simulate_llm(&reflection_prompt)?
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};
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let verified = Self::parse_reflection(&reflection)?;
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// Filter: keep only entities marked present
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