add folder contacts2

8-skill-in-shell.mjs

@@ -4,89 +4,89 @@ import shell from 'shelljs'
 
 const client = new OpenAI();
 
-// const responseHosted = await client.responses.create({
-//   model: "gpt-5.2",
-//   tools: [
-//     {
-//       type: "shell",
-//       environment: {
-//         type: "container_auto",
-//         skills: [
-//           { type: "skill_reference", skill_id: "skill_69b7aab7a0988191afca6ad2c530326b07c9ae27b6429c7c" },
-//         ],
-//       },
-//     },
-//   ],
-//   input: "Use the skills to find phone number of Qiaozhen.",
-// });
-
-// console.log('Hosted shell response:', responseHosted.output_text);
-
-const conversation = [{
-    role: 'user',
-    content: "Use the mycontacts skill and run locally to find the phone number of Qiaozhen."
-  }]
-
-let hasShellCall = true
-let round = 0
-
-while(hasShellCall) {
-  hasShellCall = false
-  round++
-
-const responseLocal = await client.responses.create({
+const responseHosted = await client.responses.create({
   model: "gpt-5.2",
   tools: [
     {
       type: "shell",
       environment: {
-        type: "local",
+        type: "container_auto",
         skills: [
-          {
-            name: "mycontacts",
-            description: "My contacts info",
-            path: path.resolve("./skills/mycontacts"),
-          },
+          { type: "skill_reference", skill_id: "skill_69b7c456a9408193856b890836fcd1950fd5b0453b8a6018" },
         ],
       },
     },
   ],
-  input: conversation,
+  input: "Use the skills to find phone number of Qiaozhen.",
 });
 
-console.log('Local shell response output:', JSON.stringify(responseLocal.output, null, 2));
+console.log('Hosted shell response:', responseHosted.output_text);
 
-conversation.push(...responseLocal.output)
+// const conversation = [{
+//     role: 'user',
+//     content: "Use the mycontacts skill and run locally to find the phone number of Qiaozhen."
+//   }]
 
-responseLocal.output.forEach(item => {
-  if (item.type == 'shell_call') {
-    hasShellCall = true
-    console.log('shell call item =', item)
-    let shell_call_output = []
-    item.action.commands.forEach(command => {
+// let hasShellCall = true
+// let round = 0
 
-      console.log('$', command, '\n')
+// while(hasShellCall) {
+//   hasShellCall = false
+//   round++
+
+// const responseLocal = await client.responses.create({
+//   model: "gpt-5.2",
+//   tools: [
+//     {
+//       type: "shell",
+//       environment: {
+//         type: "local",
+//         skills: [
+//           {
+//             name: "mycontacts",
+//             description: "My contacts info",
+//             path: path.resolve("./skills/mycontacts"),
+//           },
+//         ],
+//       },
+//     },
+//   ],
+//   input: conversation,
+// });
+
+// console.log('Local shell response output:', JSON.stringify(responseLocal.output, null, 2));
+
+// conversation.push(...responseLocal.output)
+
+// responseLocal.output.forEach(item => {
+//   if (item.type == 'shell_call') {
+//     hasShellCall = true
+//     console.log('shell call item =', item)
+//     let shell_call_output = []
+//     item.action.commands.forEach(command => {
+
+//       console.log('$', command, '\n')
 
 
-      let { stdout, stderr } = shell.exec(command, {
-        silent: true
-      })
-      shell_call_output.push({
-        stdout,
-        stderr,
-        outcome: { type: 'exit', exit_code: 0 }
-      })
-    })
+//       let { stdout, stderr } = shell.exec(command, {
+//         silent: true
+//       })
+//       shell_call_output.push({
+//         stdout,
+//         stderr,
+//         outcome: { type: 'exit', exit_code: 0 }
+//       })
+//     })
 
-    conversation.push({
-      type: 'shell_call_output',
-      call_id: item.call_id,
-      output: shell_call_output
-    })
-  }
-})
+//     conversation.push({
+//       type: 'shell_call_output',
+//       call_id: item.call_id,
+//       output: shell_call_output
+//     })
+//   }
+// })
 
-console.log('Local shell response of round ' + round + ':', JSON.stringify(responseLocal.output_text, null, 2));
+// console.log('Local shell response of round ' + round + ':', JSON.stringify(responseLocal.output_text, null, 2));
 
 
-}
+// }

8-skill.md

@@ -1,5 +1,5 @@
 ```
-curl -X POST 'https://api.openai.com/v1/skills' -H "Authorization: Bearer $OPENAI_API_KEY" -F 'files[]=@./contacts/SKILL.md;filename=contacts/SKILL.md;type=text/markdown''
+$ curl -X POST 'https://api.openai.com/v1/skills' -H "Authorization: Bearer $OPENAI_API_KEY" -F 'files[]=@./contacts/SKILL.md;filename=contacts/SKILL.md;type=text/markdown''
 {
   "id": "skill_69b7aab7a0988191afca6ad2c530326b07c9ae27b6429c7c",
   "object": "skill",
@@ -9,10 +9,11 @@ curl -X POST 'https://api.openai.com/v1/skills' -H "Authorization: Bearer $OPENA
   "latest_version": "1",
   "name": "contacts"
 }
-<07:01:11#root@codespaces-5a7969=23.97.62.113^x86_64,Linux,Debtrixie/sid:/workspaces/my-default-codespace/aitest>#
 ```
 
-注意，必须只有一级目录，不能有子目录 （skills/contacts/skill.md），否则会报错：
+会被上传到 OpenAI，可以在个人中心的 Storage 里的 Skills 标签下找到。
+
+注意，通过curl上传，必须只有一级目录，不能有子目录 （skills/contacts/skill.md），否则会报错：
 
 ```
 {
@@ -24,3 +25,8 @@ curl -X POST 'https://api.openai.com/v1/skills' -H "Authorization: Bearer $OPENA
   }
 }
 ```
+
+curl -X POST 'https://api.openai.com/v1/skills' \
+ -H "Authorization: Bearer $OPENAI_API_KEY" \
+ -F 'files[]=@./contacts2/skill.md;filename=contacts2/skill.md;type=text/markdown' \
+ -F 'files[]=@./contacts2/contacts.csv;filename=contacts2/contacts.csv;type=text/csv'

contacts2/contacts.csv

@@ -0,0 +1,3 @@
+Xue Hua, 18617591633
+Luk Lu, 15295439901
+Zong Qiaozhen, 13585016982

contacts2/skill.md

@@ -0,0 +1,6 @@
+---
+name: contacts2
+description: My contact list
+---
+
+Use this skill when you need to find details of a contact of mine. The skill provides a list of contacts in CSV format: "name, phone" in contacts.csv.