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afarntrogafarntrog
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add deprecated and proof that the LLM will retry
1 parent 5050320 commit aacc01f

2 files changed

Lines changed: 212 additions & 5 deletions

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‎examples/og_test.ipynb‎

Lines changed: 198 additions & 3 deletions
Original file line numberDiff line numberDiff line change
@@ -2,7 +2,7 @@
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"cells": [
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{
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"cell_type": "code",
5-
"execution_count": 1,
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"execution_count": 11,
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"id": "7fad2095",
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"metadata": {},
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"outputs": [],
@@ -16,9 +16,10 @@
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"import asyncio\n",
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"from datetime import datetime\n",
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"from typing import List, Optional\n",
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"from pydantic import BaseModel, Field\n",
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"from pydantic import BaseModel, Field, field_validator\n",
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"import base64\n",
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"import os\n",
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"from pydantic import validator\n",
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"\n",
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"\n",
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"# Example models for different use cases\n",
@@ -79,9 +80,57 @@
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" due_date: str\n",
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" estimated_hours: int\n",
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"\n",
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"# Example functions demonstrating different usage patterns\n"
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"# Example functions demonstrating different usage patterns\n",
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"\n",
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"\n",
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"class Name(BaseModel):\n",
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" first_name: str\n",
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"\n",
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" @field_validator(\"first_name\")\n",
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" @classmethod\n",
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" def validate_first_name(cls, value: str) -> str:\n",
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" if not value.endswith('abc'):\n",
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" raise ValueError(\"You must append 'abc' to the end of my name\")\n",
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" return value "
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]
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},
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{
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"cell_type": "code",
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"execution_count": 10,
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"id": "ea338493",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"Name(first_name='John Doeabc')"
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]
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},
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"execution_count": 10,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"Name(first_name=\"John Doeabc\")"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "4813b35f",
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"metadata": {},
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"outputs": [],
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"source": []
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "ec503329",
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"metadata": {},
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"outputs": [],
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"source": []
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},
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{
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"cell_type": "code",
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"execution_count": 2,
@@ -2074,6 +2123,152 @@
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"metadata": {},
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"outputs": [],
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"source": []
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "b764df06",
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"metadata": {},
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"outputs": [],
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"source": []
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},
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{
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"cell_type": "markdown",
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"id": "74e4e938",
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"metadata": {},
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"source": [
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"### Test the LLM calls it again if it fails on the first try (for example validation issue)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 14,
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"id": "ca9a8b59",
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"metadata": {},
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"outputs": [
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"Structured output validation failed for Name: Validation failed for Name. Please fix the following errors:\n",
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"- Field 'first_name': Value error, You must append 'abc' to the end of my name\n",
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"Structured output tool Name returned error status: error\n"
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]
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},
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"inside _validate_structured_output_result inside _validate_structured_output_result inside _validate_structured_output_result inside _validate_structured_output_result inside _validate_structured_output_result inside _validate_structured_output_result inside _validate_structured_output_result inside _validate_structured_output_result inside _validate_structured_output_result inside _validate_structured_output_result inside _validate_structured_output_result inside _validate_structured_output_result inside _validate_structured_output_result inside _validate_structured_output_result inside _validate_structured_output_result inside _validate_structured_output_result inside _validate_structured_output_result inside _validate_structured_output_result inside _validate_structured_output_result inside _validate_structured_output_result inside _validate_structured_output_result inside _validate_structured_output_result inside _validate_structured_output_result inside _validate_structured_output_result inside _validate_structured_output_result inside _validate_structured_output_result inside _validate_structured_output_result inside _validate_structured_output_result inside _validate_structured_output_result inside _validate_structured_output_result \n",
2163+
"inside _validate_structured_output_result inside _validate_structured_output_result inside _validate_structured_output_result inside _validate_structured_output_result inside _validate_structured_output_result inside _validate_structured_output_result inside _validate_structured_output_result inside _validate_structured_output_result inside _validate_structured_output_result inside _validate_structured_output_result inside _validate_structured_output_result inside _validate_structured_output_result inside _validate_structured_output_result inside _validate_structured_output_result inside _validate_structured_output_result inside _validate_structured_output_result inside _validate_structured_output_result inside _validate_structured_output_result inside _validate_structured_output_result inside _validate_structured_output_result inside _validate_structured_output_result inside _validate_structured_output_result inside _validate_structured_output_result inside _validate_structured_output_result inside _validate_structured_output_result inside _validate_structured_output_result inside _validate_structured_output_result inside _validate_structured_output_result inside _validate_structured_output_result inside _validate_structured_output_result \n"
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]
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}
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],
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"source": [
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"from strands.agent import Agent\n",
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"class Name(BaseModel):\n",
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" first_name: str\n",
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"\n",
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" @field_validator(\"first_name\")\n",
2173+
" @classmethod\n",
2174+
" def validate_first_name(cls, value: str) -> str:\n",
2175+
" if not value.endswith('abc'):\n",
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" raise ValueError(\"You must append 'abc' to the end of my name\")\n",
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" return value \n",
2178+
"\n",
2179+
"agent = Agent(callback_handler=None) \n",
2180+
"result = agent(\"Whats Aaron's name?\", output_type=Name)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 15,
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"id": "0b590625",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"AgentResult(stop_reason='tool_use', message={'role': 'assistant', 'content': [{'text': \"I see there's a validation requirement. Let me correct that:\"}, {'toolUse': {'toolUseId': 'tooluse_IuwQTcWYQNezNb7Y-LKt_A', 'name': 'Name', 'input': {'first_name': 'Aaronabc'}}}]}, metrics=EventLoopMetrics(cycle_count=2, tool_metrics={'Name': ToolMetrics(tool={'toolUseId': 'tooluse_IuwQTcWYQNezNb7Y-LKt_A', 'name': 'Name', 'input': {'first_name': 'Aaronabc'}}, call_count=2, success_count=1, error_count=1, total_time=0.002743959426879883)}, cycle_durations=[2.4125640392303467], traces=[<strands.telemetry.metrics.Trace object at 0x10bd58190>, <strands.telemetry.metrics.Trace object at 0x10bd58220>], accumulated_usage={'inputTokens': 921, 'outputTokens': 139, 'totalTokens': 1060}, accumulated_metrics={'latencyMs': 4217}), state={}, structured_output=Name(first_name='Aaronabc'))"
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]
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},
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"execution_count": 15,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"result"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 16,
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"id": "1c8e761c",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"Name(first_name='Aaronabc')"
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]
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},
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"execution_count": 16,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"result.structured_output"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 17,
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"id": "0b084666",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"[{'role': 'user', 'content': [{'text': \"Whats Aaron's name?\"}]},\n",
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" {'role': 'assistant',\n",
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" 'content': [{'text': \"I can help you extract Aaron's name using the available tool.\"},\n",
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" {'toolUse': {'toolUseId': 'tooluse_Jz272gvUQqmLQZCttasupA',\n",
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" 'name': 'Name',\n",
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" 'input': {'first_name': 'Aaron'}}}]},\n",
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" {'role': 'user',\n",
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" 'content': [{'toolResult': {'toolUseId': 'tooluse_Jz272gvUQqmLQZCttasupA',\n",
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" 'status': 'error',\n",
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" 'content': [{'text': \"Validation failed for Name. Please fix the following errors:\\n- Field 'first_name': Value error, You must append 'abc' to the end of my name\"}]}}]},\n",
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" {'role': 'assistant',\n",
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" 'content': [{'text': \"I see there's a validation requirement. Let me correct that:\"},\n",
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" {'toolUse': {'toolUseId': 'tooluse_IuwQTcWYQNezNb7Y-LKt_A',\n",
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" 'name': 'Name',\n",
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" 'input': {'first_name': 'Aaronabc'}}}]},\n",
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" {'role': 'user',\n",
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" 'content': [{'toolResult': {'toolUseId': 'tooluse_IuwQTcWYQNezNb7Y-LKt_A',\n",
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" 'status': 'success',\n",
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" 'content': [{'text': 'Successfully validated Name structured output'}],\n",
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" '_validated_object': Name(first_name='Aaronabc')}}]}]"
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]
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},
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"execution_count": 17,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"agent.messages"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "88437e72",
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"metadata": {},
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"outputs": [],
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"source": []
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}
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],
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"metadata": {

‎src/strands/agent/agent.py‎

Lines changed: 14 additions & 2 deletions
Original file line numberDiff line numberDiff line change
@@ -27,7 +27,7 @@
2727
Union,
2828
cast,
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)
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from typing_extensions import deprecated
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from opentelemetry import trace as trace_api
3232
from pydantic import BaseModel
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@@ -505,6 +505,12 @@ async def invoke_async(self, prompt: AgentInput = None, output_type: Optional[Ty
505505

506506
return cast(AgentResult, event["result"])
507507

508+
@deprecated(
509+
'Agent.structured_output method is deprecated.'
510+
' You should pass in `output_type` directly into the agent invocation.'
511+
' see the <LINK> for more details',
512+
category=None,
513+
)
508514
def structured_output(self, output_model: Type[T], prompt: AgentInput = None) -> T:
509515
"""This method allows you to get structured output from the agent.
510516
@@ -534,6 +540,12 @@ def execute() -> T:
534540
future = executor.submit(execute)
535541
return future.result()
536542

543+
@deprecated(
544+
'Agent.structured_output_async method is deprecated.'
545+
' You should pass in `output_type` directly into the agent invocation.'
546+
' see the <LINK> for more details',
547+
category=None,
548+
)
537549
async def structured_output_async(self, output_model: Type[T], prompt: AgentInput = None) -> T:
538550
"""This method allows you to get structured output from the agent.
539551
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639651
"""
640652
callback_handler = kwargs.get("callback_handler", self.callback_handler)
641653

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# Resolve output schema (runtime override or agent default)
654+
# Resolve output schema (runtime override or agent default) TODO we should allow for halfway configuration. for example, the user should be able to define `output_mode` on the Agent level but `output_type` on the `output_mode`
643655
if output_schema is None:
644656
output_schema = self._resolve_output_schema(output_type, output_mode) or self.default_output_schema
645657

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