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#!/usr/bin/env ruby
# GPT-5 Action-Oriented Agent - pure stdlib
require "net/http"
require "json"
require "uri"
API_KEY = ENV["OPENAI_API_KEY"] or abort("Set OPENAI_API_KEY")
MODEL = "gpt-5-mini"
# Tools GPT-5 can use
TOOLS = [
{
type: "function",
function: {
name: "read_file",
description: "Read contents of a file",
parameters: {
type: "object",
properties: { path: { type: "string" } },
required: ["path"]
}
}
},
{
type: "function",
function: {
name: "write_file",
description: "Write contents to a file",
parameters: {
type: "object",
properties: { path: { type: "string" }, content: { type: "string" } },
required: ["path","content"]
}
}
},
{
type: "function",
function: {
name: "run_command",
description: "Run a shell command and return output",
parameters: {
type: "object",
properties: { command: { type: "string" } },
required: ["command"]
}
}
}
]
# Execute tools
def run_tool(name, args)
case name
when "read_file"
begin
{ content: File.read(args["path"]) }
rescue => e
{ error: e.message }
end
when "write_file"
begin
File.write(args["path"], args["content"])
{ status: "ok" }
rescue => e
{ error: e.message }
end
when "run_command"
begin
{ output: `#{args["command"]}`.strip }
rescue => e
{ error: e.message }
end
else
{ error: "unknown tool #{name}" }
end
end
# Call OpenAI
def openai_chat(messages, tools)
uri = URI("https://api.openai.com/v1/chat/completions")
req = Net::HTTP::Post.new(uri)
req["Authorization"] = "Bearer #{API_KEY}"
req["Content-Type"] = "application/json"
req.body = {
model: MODEL,
messages: messages,
tools: tools,
tool_choice: "auto"
}.to_json
res = Net::HTTP.start(uri.hostname, uri.port, use_ssl: true) { |h| h.request(req) }
raise "HTTP #{res.code}: #{res.body}" unless res.is_a?(Net::HTTPSuccess)
JSON.parse(res.body)
end
# Conversation with bias-for-action
messages = [
{ role: "system", content: <<~MSG
You are a reasoning coding and system agent. Prioritize taking practical actions whenever possible.
Use read_file, write_file, and run_command proactively to achieve user goals.
Explain your reasoning briefly in content. Avoid unnecessary delays; act whenever sufficient info is available.
MSG
}
]
puts ">> Type instructions (or 'exit')"
loop do
print "\nUser> "
input = STDIN.gets&.strip
break if input.nil? || input.downcase == "exit"
messages << { role: "user", content: input }
loop do
resp = openai_chat(messages, TOOLS)
msg = resp.dig("choices", 0, "message")
messages << msg
# Print reasoning content immediately
if msg["content"] && !msg["content"].empty?
puts "\nAssistant> #{msg['content']}"
end
# Execute any tool calls
if msg["tool_calls"]
msg["tool_calls"].each do |call|
name = call.dig("function","name")
args = JSON.parse(call.dig("function","arguments"))
result = run_tool(name, args)
messages << { role: "tool", tool_call_id: call["id"], content: JSON.dump(result) }
end
next # continue reasoning on tool results
end
break # no tool calls left, turn is done
end
end
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