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<path>/home/byk/Code/getsentry/cli/src/commands/cli/setup.ts</path>
<type>file</type>
<content>
40:   isBashAvailable,
41:   isInPath,
42:   type ShellInfo,
43: } from "../../lib/shell.js";
44: import {
45:   type InstallationMethod,
46:   parseInstallationMethod,
47: } from "../../lib/upgrade.js";
48: 
49: type SetupFlags = {
50:   readonly install: boolean;
51:   readonly method?: InstallationMethod;
52:   readonly channel?: ReleaseChannel;
53:   readonly "no-modify-path": boolean;
54:   readonly "no-completions": boolean;

(Showing lines 40-54 of 575. Use offset=55 to continue.)
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94:const KNOWN_CURL_PATHS = KNOWN_CURL_DIRS.map(
121:  for (const dir of KNOWN_CURL_PATHS) {
271:  for (const dir of KNOWN_CURL_PATHS) {

                      GitHub - openai/codex: Lightweight coding agent that runs in your terminal · GitHub                                             

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<path>/home/byk/.local/share/opencode/worktree/51d1015fd1f616acf9a5ffaad9331ec6b304586b/lucky-cactus/packages/gateway/src/cli/agents.ts</path>
<type>file</type>
<content>
1: /**
2:  * Agent registry — known AI coding agents that can be launched through
3:  * the gateway.
4:  *
5:  * Each agent defines:
6:  *  - How to detect it (binary name on PATH)
7:  *  - What env vars to set so it talks through the gateway
8:  */
9: import { getGitRemote } from "@loreai/core";
10: 
11: // ---------------------------------------------------------------------------
12: // which() — cross-runtime binary lookup
13: // ---------------------------------------------------------------------------
14: 
15: /**
16:  * Find a binary on PATH. Uses Bun.which() when available (Bun runtime),
17:  * falls back to `which`/`where` via child_process (Node.js runtime).
18:  */
19: function which(binary: string): string | null {
20:   // Bun runtime
21:   if (typeof Bun !== "undefined" && typeof Bun.which === ...

<path>/home/byk/.local/share/opencode/worktree/51d1015fd1f616acf9a5ffaad9331ec6b304586b/lucky-cactus/packages/gateway/src/server.ts</path>
<type>file</type>
<content>
380:     // Clients (e.g. Codex) optimistically try a WebSocket upgrade before
381:     // falling back to HTTP. The gateway is HTTP-only, so reject the upgrade
382:     // definitively rather than returning a misleading 404 (which caused
383:     // repeated upgrade attempts and noisy logs).
384:     if (isWebSocketUpgrade(req)) {
385:       if (config.debug) {
386:         console.error(
387:           `[lore] rejecting WebSocket upgrade for ${pathname} (HTTP-only gateway)`,
388:         );
389:       }
390:       return withCors(rejectWebSocketUpgrade(pathname));
391:     }
392: 
393:     try {
394:       // POST /v1/messages — Anthropic protocol
395:       if (method === "POST" && pathname === "/v1/messages") {
396:         return await handleAnthropicMessages(req, config);
397:       }
398: 
399:       // POST ...

                      codex/codex-rs/core/src at main · openai/codex · GitHub                                             

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use crate::agents_md::AgentsMdManager;
pub use crate::agents_md::LoadedAgentsMd;
use crate::config::edit::ConfigEdit;
use crate::config::edit::ConfigEditsBuilder;
use crate::path_utils::normalize_for_native_workdir;
use crate::unified_exec::DEFAULT_MAX_BACKGROUND_TERMINAL_TIMEOUT_MS;
use crate::unified_exec::MIN_EMPTY_YIELD_TIME_MS;
use crate::windows_sandbox::WindowsSandboxLevelExt;
use crate::windows_sandbox::resolve_windows_sandbox_mode;
use crate::windows_sandbox::resolve_windows_sandbox_private_desktop;
use codex_config::CloudConfigBundleLoader;
use codex_config::ConfigLayerSource;
use codex_config::ConfigLayerStack;
use codex_config::ConfigLayerStackOrdering;
use codex_config::ConfigRequirements;
use codex_config::ConfigRequirementsToml;
use codex_config::ConstrainedWithSource;
use codex_config::FeatureRequirementsToml;
use codex_config::McpServerIdentity;
use codex_config::McpServerRequirement;
use codex_config::PluginRequirementsToml;
use codex_config::ProfileV2Name;
use ...

use std::sync::Arc;
use std::time::Instant;

use crate::Prompt;
use crate::client::ModelClientSession;
use crate::client_common::ResponseEvent;
use crate::hook_runtime::PostCompactHookOutcome;
use crate::hook_runtime::PreCompactHookOutcome;
use crate::hook_runtime::run_post_compact_hooks;
use crate::hook_runtime::run_pre_compact_hooks;
#[cfg(test)]
use crate::session::PreviousTurnSettings;
use crate::session::session::Session;
use crate::session::turn::get_last_assistant_message_from_turn;
use crate::session::turn_context::TurnContext;
use crate::turn_metadata::CompactionTurnMetadata;
use crate::util::backoff;
use codex_analytics::CodexCompactionEvent;
use codex_analytics::CompactionImplementation;
use codex_analytics::CompactionPhase;
use codex_analytics::CompactionReason;
use codex_analytics::CompactionStatus;
use codex_analytics::CompactionStrategy;
use codex_analytics::CompactionTrigger;
use codex_analytics::now_unix_seconds;
use codex_protocol::error::CodexErr;
use ...

use std::sync::Arc;

use crate::Prompt;
use crate::client::CompactConversationRequestSettings;
use crate::compact::CompactionAnalyticsAttempt;
use crate::compact::InitialContextInjection;
use crate::compact::compaction_status_from_result;
use crate::compact::insert_initial_context_before_last_real_user_or_summary;
use crate::context_manager::ContextManager;
use crate::context_manager::TotalTokenUsageBreakdown;
use crate::context_manager::estimate_response_item_model_visible_bytes;
use crate::hook_runtime::PostCompactHookOutcome;
use crate::hook_runtime::PreCompactHookOutcome;
use crate::hook_runtime::run_post_compact_hooks;
use crate::hook_runtime::run_pre_compact_hooks;
use crate::session::session::Session;
use crate::session::turn::built_tools;
use crate::session::turn_context::TurnContext;
use crate::turn_metadata::CompactionTurnMetadata;
use codex_analytics::CompactionImplementation;
use codex_analytics::CompactionPhase;
use codex_analytics::CompactionReason;
use ...

use std::sync::Arc;

use crate::Prompt;
use crate::ResponseStream;
use crate::client::ModelClientSession;
use crate::client_common::ResponseEvent;
use crate::compact::CompactionAnalyticsAttempt;
use crate::compact::InitialContextInjection;
use crate::compact::compaction_status_from_result;
use crate::compact_remote::build_compact_request_log_data;
use crate::compact_remote::log_remote_compact_failure;
use crate::compact_remote::process_compacted_history;
use crate::compact_remote::should_keep_compacted_history_item;
use crate::compact_remote::trim_function_call_history_to_fit_context_window;
use crate::hook_runtime::PostCompactHookOutcome;
use crate::hook_runtime::PreCompactHookOutcome;
use crate::hook_runtime::run_post_compact_hooks;
use crate::hook_runtime::run_pre_compact_hooks;
use crate::responses_retry::ResponsesStreamRequest;
use crate::responses_retry::handle_retryable_response_stream_error;
use crate::session::session::Session;
use crate::session::turn::built_tools;
use ...

//! Schema-heavy configuration TOML types used by Codex.

use std::collections::BTreeMap;
use std::collections::HashMap;
use std::path::Path;

use crate::HooksToml;
use crate::permissions_toml::PermissionsToml;
use crate::profile_toml::ConfigProfile;
use crate::types::AnalyticsConfigToml;
use crate::types::ApprovalsReviewer;
use crate::types::AppsConfigToml;
use crate::types::AuthCredentialsStoreMode;
use crate::types::FeedbackConfigToml;
use crate::types::History;
use crate::types::MarketplaceConfig;
use crate::types::McpServerConfig;
use crate::types::MemoriesToml;
use crate::types::Notice;
use crate::types::OAuthCredentialsStoreMode;
use crate::types::OtelConfigToml;
use crate::types::PluginConfig;
use crate::types::SandboxWorkspaceWrite;
use crate::types::ShellEnvironmentPolicyToml;
use crate::types::SkillsConfig;
use crate::types::ToolSuggestConfig;
use crate::types::Tui;
use crate::types::UriBasedFileOpener;
use crate::types::WindowsToml;
use codex_features::FeaturesToml;
use ...

//! Session- and turn-scoped helpers for talking to model provider APIs.
//!
//! `ModelClient` is intended to live for the lifetime of a Codex session and holds the stable
//! configuration and state needed to talk to a provider (auth, provider selection, conversation id,
//! and transport fallback state).
//!
//! Per-turn settings (model selection, reasoning controls, telemetry context, and turn metadata)
//! are passed explicitly to streaming and unary methods so that the turn lifetime is visible at the
//! call site.
//!
//! A [`ModelClientSession`] is created per turn and is used to stream one or more Responses API
//! requests during that turn. It caches a Responses WebSocket connection (opened lazily) and stores
//! per-turn state such as the `x-codex-turn-state` token used for sticky routing.
//!
//! WebSocket prewarm is a v2-only `response.create` with `generate=false`; it waits for completion
//! so the next request can reuse the same connection and ...

use std::collections::HashMap;
use std::collections::HashSet;
use std::sync::Arc;
use std::sync::atomic::Ordering;

use crate::SkillInjections;
use crate::build_skill_injections;
use crate::client::ModelClientSession;
use crate::client_common::Prompt;
use crate::client_common::ResponseEvent;
use crate::collect_explicit_skill_mentions;
use crate::compact::InitialContextInjection;
use crate::compact::run_inline_auto_compact_task;
use crate::compact::should_use_remote_compact_task;
use crate::compact_remote::run_inline_remote_auto_compact_task;
use crate::compact_remote_v2::run_inline_remote_auto_compact_task as run_inline_remote_auto_compact_task_v2;
use crate::connectors;
use crate::context::ContextualUserFragment;
use crate::feedback_tags;
use crate::goals::GoalRuntimeEvent;
use crate::hook_runtime::inspect_pending_input;
use crate::hook_runtime::record_additional_contexts;
use crate::hook_runtime::record_pending_input;
use crate::hook_runtime::run_legacy_after_agent_hook;
use ...

use codex_utils_absolute_path::AbsolutePathBuf;
use schemars::JsonSchema;
use schemars::r#gen::SchemaGenerator;
use schemars::schema::InstanceType;
use schemars::schema::Metadata;
use schemars::schema::Schema;
use schemars::schema::SchemaObject;
use serde::Deserialize;
use serde::Serialize;
use serde_json::Value;
use std::collections::HashMap;
use std::fmt;
use std::num::NonZeroU64;
use std::ops::Deref;
use std::str::FromStr;
use std::time::Duration;
use strum_macros::Display;
use strum_macros::EnumIter;
use ts_rs::TS;
use wildmatch::WildMatchPattern;

use crate::openai_models::ReasoningEffort;

/// Selects which part of the active context is charged against
/// `model_auto_compact_token_limit`.
#[derive(
    Debug, Serialize, Deserialize, Default, Clone, Copy, PartialEq, Eq, Display, JsonSchema, TS,
)]
#[serde(rename_all = "snake_case")]
#[strum(serialize_all = "snake_case")]
pub enum AutoCompactTokenLimitScope {
    /// Count the full active context against the limit. ...

<path>/home/byk/.local/share/opencode/worktree/51d1015fd1f616acf9a5ffaad9331ec6b304586b/lucky-cactus/packages/gateway/src/compaction.ts</path>
<type>file</type>
<content>
1: /**
2:  * Compaction request detection and interception for the Lore gateway.
3:  *
4:  * Claude Code (and other clients using the same pattern) sends compaction
5:  * requests with a distinct system prompt and message structure. The gateway
6:  * detects these and runs Lore's own distillation instead of forwarding to
7:  * the upstream API.
8:  *
9:  * Detection mirrors the patterns documented in the upstream
10:  * `packages/opencode/src/agent/prompt/compaction.txt` and the
11:  * `experimental.session.compacting` hook.
12:  *
13:  * This module has zero dependencies on `@loreai/core` — pure detection logic.
14:  */
15: import type { GatewayRequest, GatewayResponse } from "./translate/types";
16: 
17: // ---------------------------------------------------------------------------
18: // Detection patterns — ...

<path>/home/byk/.local/share/opencode/worktree/51d1015fd1f616acf9a5ffaad9331ec6b304586b/lucky-cactus/packages/gateway/src/server.ts</path>
<type>file</type>
<content>
1: /**
2:  * HTTP server for the Lore gateway proxy.
3:  *
4:  * Routes:
5:  *   POST /v1/messages          → Anthropic protocol
6:  *   POST /v1/chat/completions  → OpenAI Chat Completions protocol
7:  *   POST /v1/responses         → OpenAI Responses API protocol
8:  *   POST /v1/compact           → Explicit compaction summary (Pi plugin, etc.)
9:  *   GET  /v1/models            → Passthrough to upstream
10:  *   GET  /health               → Health check
11:  *
12:  * Uses `Bun.serve()` — this package targets Bun exclusively.
13:  */
14: import { DEFAULT_PORT, type GatewayConfig } from "./config";
15: import { bootstrapDailySpend, getDailyBudget } from "./cost-tracker";
16: import type { GatewayRequest } from "./translate/types";
17: import {
18:   parseAnthropicRequest,
19:   parseAnthropicResponseJSON,
20: } from ...

<path>/home/byk/.local/share/opencode/worktree/51d1015fd1f616acf9a5ffaad9331ec6b304586b/lucky-cactus/packages/gateway/src/server.ts</path>
<type>file</type>
<content>
200:     const response = new Response(upstream.body, {
201:       status: upstream.status,
202:       statusText: upstream.statusText,
203:       headers: new Headers(upstream.headers),
204:     });
205:     return withCors(response);
206:   } catch (e) {
207:     const msg = e instanceof Error ? e.message : "Upstream unreachable";
208:     return errorResponse(502, "api_error", `Failed to fetch models: ${msg}`);
209:   }
210: }
211: 
212: function handleHealth(): Response {
213:   return jsonResponse({ status: "ok", version });
214: }
215: 
216: async function handleOpenAIChatCompletions(
217:   req: Request,
218:   config: GatewayConfig,
219: ): Promise<Response> {
220:   let body: unknown;
221:   try {
222:     body = await req.json();
223:   } catch {
224:     return errorResponse(400, "invalid_request_error", ...

<path>/home/byk/.local/share/opencode/worktree/51d1015fd1f616acf9a5ffaad9331ec6b304586b/lucky-cactus/packages/gateway/src/server.ts</path>
<type>file</type>
<content>
160:     return errorResponse(400, "invalid_request_error", msg);
161:   }
162: 
163:   try {
164:     const result = await handleRequest(gatewayReq, config);
165:     // Pipeline returns a Response directly (streaming or non-streaming)
166:     return withCors(result);
167:   } catch (e) {
168:     const msg = e instanceof Error ? e.message : "Pipeline error";
169:     console.error(`[lore] pipeline error: ${msg}`);
170:     return errorResponse(502, "api_error", `Gateway pipeline error: ${msg}`);
171:   }
172: }
173: 
174: // NOTE: This endpoint only supports the Anthropic upstream. OpenAI clients
175: // calling GET /v1/models will have their request forwarded to Anthropic,
176: // which will likely reject the OpenAI API key. A proper fix would route
177: // based on auth header type, but that's a separate ...