chore: devops upstream

docs/community/Streams/12-2024/2024-12-10.md

@@ -1,12 +1,12 @@
 ---
 sidebar_position: 4
 title: "AI Agent Dev School Part 4"
-description: "AI Pizza: Hacking Eliza for Domino's Delivery (plus TEE Deep Dive)"
+description: "AI Pizza: Hacking OKai for Domino's Delivery (plus TEE Deep Dive)"
 ---
 
 # AI Agent Dev School Part 4
 
-**AI Pizza: Hacking Eliza for Domino's Delivery (plus TEE Deep Dive)**
+**AI Pizza: Hacking OKai for Domino's Delivery (plus TEE Deep Dive)**
 
 Date: 2024-12-10
 YouTube Link: https://www.youtube.com/watch?v=6I9e9pJprDI
@@ -16,7 +16,7 @@ YouTube Link: https://www.youtube.com/watch?v=6I9e9pJprDI
 Part 1: Trusted Execution Environments (TEEs) with Agent Joshua
 - **00:00:09** - Stream starts, initial setup issues.
 - **00:01:58** - Intro to Trusted Execution Environments (TEEs).
-- **00:08:03** - Agent Joshua begins explaining TEEs and the Eliza plugin.
+- **00:08:03** - Agent Joshua begins explaining TEEs and the OKai plugin.
 - **00:19:15** - Deeper dive into remote attestation.
 - **00:24:50** - Discussion of derived keys.
 - **00:37:00** - Deploying to a real TEE, Phala Network's TEE cloud.
@@ -26,7 +26,7 @@ Part 2: Building a Domino's pizza ordering agent
 - **01:04:37** - Transition to building a Domino's pizza ordering agent.
 - **01:14:20** - Discussion of the pizza ordering agent’s order flow and state machine.
 - **01:22:07** - Using Claude to generate a state machine diagram.
-- **01:32:17** - Creating the Domino's plugin in Eliza.
+- **01:32:17** - Creating the Domino's plugin in OKai.
 - **01:54:15** - Working on the pizza order provider.
 - **02:16:46** - Pizza provider code completed.
 - **02:28:50** - Discussion of caching customer and order data.
@@ -39,11 +39,11 @@ Part 2: Building a Domino's pizza ordering agent
 
 ## Summary
 
-This is a livestream titled "AI Agent Dev School Part 4" from the ai16z project, featuring Shaw. The stream is divided into two main parts: a technical discussion on Trusted Execution Environments (TEEs) and a coding session where Shaw attempts to build a pizza-ordering agent using the Domino's API.
+This is a livestream titled "AI Agent Dev School Part 4" from the okcashpro project, featuring Shaw. The stream is divided into two main parts: a technical discussion on Trusted Execution Environments (TEEs) and a coding session where Shaw attempts to build a pizza-ordering agent using the Domino's API.
 
 **Part 1: Trusted Execution Environments (TEEs) with Agent Joshua**
 
-This segment begins with Shaw introducing the concept of TEEs and their importance for running autonomous agents securely. He emphasizes the need to protect private keys and ensure that code execution is tamper-proof. Joshua from the Phala Network is brought on to explain TEEs in more detail and demonstrate how to use the TEE plugin he built for Eliza.
+This segment begins with Shaw introducing the concept of TEEs and their importance for running autonomous agents securely. He emphasizes the need to protect private keys and ensure that code execution is tamper-proof. Joshua from the Phala Network is brought on to explain TEEs in more detail and demonstrate how to use the TEE plugin he built for OKai.
 
 *   **Key Concepts:**
     *   **Trusted Execution Environments (TEEs):** Secure areas within a processor that isolate code and data, protecting them from unauthorized access and tampering.
@@ -53,7 +53,7 @@ This segment begins with Shaw introducing the concept of TEEs and their importan
     *   **Derived Key Provider:** A component that generates cryptographic keys based on a secret salt, ensuring that private keys are not exposed to humans.
 
 *   **Demonstration:**
-    *   Joshua walks through the process of setting up and deploying an Eliza agent in a TEE simulator, demonstrating how to generate remote attestations and derive keys.
+    *   Joshua walks through the process of setting up and deploying an OKai agent in a TEE simulator, demonstrating how to generate remote attestations and derive keys.
     *   He shows how to use the remote attestation explorer to verify the authenticity of the agent running inside the TEE.
     *   He explains how to build a Docker image of the agent and deploy it to the Phala Network's TEE cloud solution.
 

docs/community/components/Contributions.tsx

@@ -81,7 +81,7 @@ const Contributions = ({
     const fetchCommits = async (page: number) => {
         try {
             const commitResponse = await fetch(
-                `https://api.github.com/repos/ai16z/eliza/commits?author=${contributor.login}&page=${page}`,
+                `https://api.github.com/repos/okcashpro/okai/commits?author=${contributor.login}&page=${page}`,
                 {
                     method: "GET",
                     headers: {
@@ -109,7 +109,7 @@ const Contributions = ({
     const fetchPRs = async (page: number) => {
         try {
             const prResponse = await fetch(
-                `https://api.github.com/search/issues?q=type:pr+author:${contributor.login}+repo:ai16z/eliza&page=${page}`,
+                `https://api.github.com/search/issues?q=type:pr+author:${contributor.login}+repo:okcashpro/okai&page=${page}`,
                 {
                     method: "GET",
                     headers: {
@@ -144,7 +144,7 @@ const Contributions = ({
     const fetchIssues = async (page: number) => {
         try {
             const issueResponse = await fetch(
-                `https://api.github.com/search/issues?q=type:issue+author:${contributor.login}+repo:ai16z/eliza&page=${page}`,
+                `https://api.github.com/search/issues?q=type:issue+author:${contributor.login}+repo:okcashpro/okai&page=${page}`,
                 {
                     method: "GET",
                     headers: {

docs/community/components/Contributors.tsx

@@ -68,7 +68,7 @@ const Contributors: React.FC = () => {
         loadingRef.current = true;
         try {
             const response = await fetch(
-                `https://api.github.com/repos/ai16z/eliza/contributors?per_page=${GITHUB_PAGE_LIMIT}&page=${page}`,
+                `https://api.github.com/repos/okcashpro/okai/contributors?per_page=${GITHUB_PAGE_LIMIT}&page=${page}`,
                 {
                     method: "GET",
                     headers: {
@@ -101,7 +101,7 @@ const Contributors: React.FC = () => {
         const fetchActivitySummaries = async () => {
             try {
                 const response = await fetch(
-                    "https://ai16z.github.io/data/contributors.json",
+                    "https://okcashpro.github.io/data/contributors.json",
                 );
                 if (!response.ok) {
                     throw new Error(

packages/client-twitter/src/base.ts

@@ -272,7 +272,7 @@ export class ClientBase extends EventEmitter {
     }
 
     async fetchFeedTimeline(count: number): Promise<string> {
-        elizaLogger.debug("fetching home timeline");
+        okaiLogger.debug("fetching home timeline");
         const homeTimeline = await this.twitterClient.fetchHomeTimeline(count, []);
         return homeTimeline
             .filter(tweet => tweet.text || tweet.legacy?.full_text)
@@ -289,7 +289,7 @@ export class ClientBase extends EventEmitter {
     }
 
     async fetchTimelineForActions(count: number): Promise<Tweet[]> {
-        elizaLogger.debug("fetching timeline for actions");
+        okaiLogger.debug("fetching timeline for actions");
         const homeTimeline = await this.twitterClient.fetchHomeTimeline(count, []);
 
         return homeTimeline.map(tweet => ({

packages/client-twitter/src/index.ts

@@ -16,11 +16,11 @@ class TwitterManager {
 
         if (enableSearch) {
           // this searches topics from character file
-          elizaLogger.warn('Twitter/X client running in a mode that:')
-          elizaLogger.warn('1. violates consent of random users')
-          elizaLogger.warn('2. burns your rate limit')
-          elizaLogger.warn('3. can get your account banned')
-          elizaLogger.warn('use at your own risk')
+          okaiLogger.warn('Twitter/X client running in a mode that:')
+          okaiLogger.warn('1. violates consent of random users')
+          okaiLogger.warn('2. burns your rate limit')
+          okaiLogger.warn('3. can get your account banned')
+          okaiLogger.warn('use at your own risk')
           this.search = new TwitterSearchClient(this.client, runtime); // don't start the search client by default
         }
         this.interaction = new TwitterInteractionClient(this.client, runtime);

packages/core/src/generation.ts

@@ -1522,20 +1522,20 @@ export async function generateTweetActions({
                 console.debug("Parsed tweet actions:", actions);
                 return actions;
             } else {
-                elizaLogger.debug("generateTweetActions no valid response");
+                okaiLogger.debug("generateTweetActions no valid response");
             }
         } catch (error) {
-            elizaLogger.error("Error in generateTweetActions:", error);
+            okaiLogger.error("Error in generateTweetActions:", error);
             if (
                 error instanceof TypeError &&
                 error.message.includes("queueTextCompletion")
             ) {
-                elizaLogger.error(
+                okaiLogger.error(
                     "TypeError: Cannot read properties of null (reading 'queueTextCompletion')"
                 );
             }
         }
-        elizaLogger.log(`Retrying in ${retryDelay}ms...`);
+        okaiLogger.log(`Retrying in ${retryDelay}ms...`);
         await new Promise((resolve) => setTimeout(resolve, retryDelay));
         retryDelay *= 2;
     }

tests/README.md

@@ -1,6 +1,6 @@
 # Integration tests
 
-This directory contains smoke and integration tests for Eliza project.
+This directory contains smoke and integration tests for OKai project.
 
 ## Smoke tests
 - Should always be run on a freshly cloned project (i.e. no local changes)