feat(ai): Implement unified AI API with Anthropic provider

- Define clean API with complete() method and callbacks for streaming
- Add comprehensive type system for messages, tools, and usage
- Implement AnthropicAI provider with full feature support:
  - Thinking/reasoning with signatures
  - Tool calling with parallel execution
  - Streaming via callbacks (onText, onThinking)
  - Proper error handling and stop reasons
  - Cache tracking for input/output tokens
- Add working test/example demonstrating tool execution flow
- Support for system prompts, temperature, max tokens
- Proper message role types: user, assistant, toolResult

packages/ai/test/examples/anthropic.ts

@@ -0,0 +1,63 @@
+import Anthropic from "@anthropic-ai/sdk";
+import { MessageCreateParamsBase } from "@anthropic-ai/sdk/resources/messages.mjs";
+import chalk from "chalk";
+import { AnthropicAI } from "../../src/providers/anthropic";
+import { Request, Message, Tool } from "../../src/types";
+
+const anthropic = new Anthropic();
+
+// Define a simple calculator tool
+const tools: Tool[] = [
+    {
+        name: "calculate",
+        description: "Perform a mathematical calculation",
+        parameters: {
+            type: "object" as const,
+            properties: {
+                expression: {
+                    type: "string",
+                    description: "The mathematical expression to evaluate"
+                }
+            },
+            required: ["expression"]
+        }
+    }
+];
+
+const ai = new AnthropicAI("claude-sonnet-4-0");
+const context: Request = {
+        messages: [
+        {
+            role: "user",
+            content: "Think about birds briefly. Then give me a list of 10 birds. Finally, calculate 42 * 17 + 123 and 453 + 434 in parallel using the calculator tool.",
+        }
+    ],
+    tools,
+    onText: (t) => process.stdout.write(t),
+    onThinking: (t) => process.stdout.write(chalk.dim(t))
+}
+
+const options = {thinking: { enabled: true }};
+let msg = await ai.complete(context, options)
+context.messages.push(msg);
+console.log(JSON.stringify(msg, null, 2));
+
+for (const toolCall of msg.toolCalls || []) {
+    if (toolCall.name === "calculate") {
+        const expression = toolCall.arguments.expression;
+        const result = eval(expression);
+        context.messages.push({
+            role: "toolResult",
+            content: `The result of ${expression} is ${result}.`,
+            toolCallId: toolCall.id,
+            isError: false
+        });
+    }
+}
+
+msg = await ai.complete(context, options);
+console.log(JSON.stringify(msg, null, 2));
+
+
+
+