🥊

readme.md

@@ -243,52 +243,28 @@ const messages: OpenAI.ChatCompletionMessageParam[] = [
   { role: 'user', content: 'What is the weather in San Francisco?' }
 ]
 
-{
-  // First call to OpenAI to invoke the weather tool
-  const res = await openai.chat.completions.create({
-    messages,
-    model: 'gpt-4o-mini',
-    temperature: 0,
-    tools: weather.functions.toolSpecs,
-    tool_choice: 'required'
-  })
-  const message = res.choices[0]?.message!
-  console.log(JSON.stringify(message, null, 2))
-  assert(message.tool_calls?.[0]?.function?.name === 'get_current_weather')
+const res = await openai.chat.completions.create({
+  messages,
+  model: 'gpt-4o-mini',
+  temperature: 0,
+  tools: weather.functions.toolSpecs,
+  tool_choice: 'required'
+})
+const message = res.choices[0]?.message!
+console.log(JSON.stringify(message, null, 2))
+assert(message.tool_calls?.[0]?.function?.name === 'get_current_weather')
 
-  const fn = weather.functions.get('get_current_weather')!
-  assert(fn)
+const fn = weather.functions.get('get_current_weather')!
 
-  const toolParams = message.tool_calls[0].function.arguments
-  const toolResult = await fn(toolParams)
-
-  messages.push(message)
-  messages.push({
-    role: 'tool',
-    tool_call_id: message.tool_calls[0].id,
-    content: JSON.stringify(toolResult)
-  })
-}
-
-{
-  // Second call to OpenAI to generate a text response
-  const res = await openai.chat.completions.create({
-    messages,
-    model: 'gpt-4o-mini',
-    temperature: 0,
-    tools: weather.functions.toolSpecs
-  })
-  const message = res.choices?.[0]?.message
-  console.log(JSON.stringify(message, null, 2))
-}
+const toolParams = message.tool_calls[0].function.arguments
+const toolResult = await fn(toolParams)
+console.log(JSON.stringify(toolResult, null, 2))
 ```
 
 See [examples/openai](./examples/openai) for a full example.
 
 </details>
 
-See the [examples](./examples) directory for working examples of how to use each of these adapters.
-
 ### Optimized Imports
 
 `@agentic/stdlib` is just a convenience wrapper which re-exports all of the built-in AI tool packages. If you want to optimize your imports, you can replace `@agentic/stdlib` with the specific AI tools you want. For example: