Responses API

type ResponsesRequest = {
  model: string;                    // Listed id or alias from GET /v1/models
  input: string | InputItem[];      // string or multi-turn array

  // Optional
  instructions?: string;            // System-level message
  stream?: boolean;                 // Default: false
  max_output_tokens?: number;
  temperature?: number;
  top_p?: number;
  tools?: Tool[];
  tool_choice?: "auto" | "none" | "required" | object;
  parallel_tool_calls?: boolean;    // Default: true
  previous_response_id?: string;    // Not supported — use full input array
};

type InputItem =
  | { type?: "message"; role: "user" | "assistant" | "system" | "developer"; content: string | ContentBlock[] }
  | { type: "function_call_output"; call_id: string; output: string }   // tool result
  | { type: "function_call"; call_id: string; name: string; arguments: string };

type ContentBlock =
  | { type: "input_text"; text: string }
  | { type: "input_image"; image_url: string; detail?: "auto" | "low" | "high" };

// Non-streaming response object
type ResponsesResponse = {
  id: string;             // Opaque BazaarLink request id; format may change
  object: "response";
  created_at: number;
  completed_at: number;
  status: "completed" | "failed" | "incomplete";
  model: string;
  output: OutputItem[];
  usage: {
    input_tokens: number;   // equivalent to prompt_tokens
    output_tokens: number;  // equivalent to completion_tokens
    total_tokens: number;
    cost?: number;          // USD amount charged to the customer for this request
  } | null;
  error: null | { code: string; message: string };
};

type OutputItem =
  | {
      type: "message";
      id: string;
      role: "assistant";
      status: "completed";
      content: Array<{ type: "output_text"; text: string; annotations: [] }>;
    }
  | { type: "function_call"; id: string; call_id: string; name: string; arguments: string; status: "completed" };

# Chat Completions (before)
response = client.chat.completions.create(
    model="openai/gpt-5.4-mini",
    messages=[
        {"role": "system", "content": "You are helpful."},
        {"role": "user",   "content": "Hello"},
    ]
)
text = response.choices[0].message.content

# Responses API (after)
response = client.responses.create(
    model="openai/gpt-5.4-mini",
    instructions="You are helpful.",
    input="Hello"
)
text = response.output[0].content[0].text