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new templates; use qwen; and quasi working agent (#52)
* new templates; use qwen; and quasi working agent * fix broken test
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‎docs/notebooks/first_llm_agent.ipynb‎

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{
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"cells": [
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{
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"cell_type": "markdown",
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"id": "93a2ace1-2f96-4bf0-9c7f-55e37799ad09",
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"metadata": {},
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"source": [
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"# Our First LLM Agent"
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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": 1,
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"id": "1c074c89-e290-4f16-b4c3-80dbcb2541a2",
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"metadata": {},
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"outputs": [],
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"source": [
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"from logging import DEBUG\n",
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"\n",
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"from llm_agents_from_scratch import LLMAgent\n",
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"from llm_agents_from_scratch.logger import get_logger, set_log_level\n",
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"\n",
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"set_log_level(DEBUG)\n",
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"nb_logger = get_logger(\"notebook\")"
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]
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},
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{
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"cell_type": "markdown",
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"id": "37a14d79-bd26-4b19-966d-4f29047cebb5",
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"metadata": {},
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"source": [
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"## Create an `LLMAgent`"
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]
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},
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{
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"cell_type": "markdown",
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"id": "d48e30aa-caa8-4984-9c98-048c86880586",
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"metadata": {},
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"source": [
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"### Define the backbone LLM"
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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": 2,
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"id": "578979fe-3de7-4eec-acd6-fb90c876481b",
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"metadata": {},
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"outputs": [],
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"source": [
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"from llm_agents_from_scratch.llms import OllamaLLM"
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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": 3,
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"id": "65f3a83d-b3bc-4e76-ba47-7e24120d33b3",
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"metadata": {},
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"outputs": [],
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"source": [
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"llm = OllamaLLM(model=\"qwen2.5:3b\")"
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]
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},
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{
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"cell_type": "markdown",
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"id": "e173fe6d-239e-4129-a97a-10999f2a0732",
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"metadata": {},
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"source": [
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"### Define Tools"
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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": 4,
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"id": "7477b302-af47-49de-a7e3-741586d90261",
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"metadata": {},
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"outputs": [],
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"source": [
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"from llm_agents_from_scratch import (\n",
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" SimpleFunctionTool,\n",
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")"
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]
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},
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{
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"cell_type": "markdown",
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"id": "eb5cd91c-2123-48f4-9548-4d4cfa960bda",
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"metadata": {},
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"source": [
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"#### Simple function tools\n",
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"\n",
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"These tools use manual and simple conversions from Python types to valid JSON schema types."
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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": 5,
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"id": "823e9414-2c20-4c33-8205-08bd162e7da2",
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"metadata": {},
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"outputs": [],
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"source": [
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"def add_one(x: str) -> float:\n",
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" \"\"\"Adds one to a given number.\"\"\"\n",
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" return float(x) + 1"
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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": 6,
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"id": "6d6dc843-df79-415a-b87c-d6d7e01df77f",
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"metadata": {},
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"outputs": [],
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"source": [
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"add_one_tool = SimpleFunctionTool(func=add_one)"
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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": 7,
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"id": "0ac20ebb-d9e7-4fc8-92cc-326950c6cb9c",
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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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"ToolCallResult(tool_call=ToolCall(tool_name='add_one', arguments={'x': '3.15'}), content='4.15', error=False)"
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]
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},
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"execution_count": 7,
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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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"from llm_agents_from_scratch.data_structures.tool import ToolCall\n",
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"\n",
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"# test the tool\n",
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"tool_call = ToolCall(\n",
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" tool_name=add_one_tool.name,\n",
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" arguments={\"x\": \"3.15\"},\n",
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")\n",
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"add_one_tool(tool_call)"
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]
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},
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{
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"cell_type": "markdown",
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"id": "3dff626b-eab2-4b44-8220-ad2b19f502c3",
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"metadata": {},
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"source": [
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"### Define the LLM Agent"
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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": 8,
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"id": "7ebe27bb-de33-4406-9e11-a5f427ef7ac7",
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"metadata": {},
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"outputs": [],
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"source": [
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"agent = LLMAgent(\n",
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" llm=llm,\n",
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" tools=[add_one_tool],\n",
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")"
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]
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},
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{
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"cell_type": "markdown",
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"id": "fcbe332e-5a33-4f1e-b111-ca84e02596ee",
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"metadata": {},
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"source": [
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"## Run a simple task"
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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": 9,
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"id": "4d09a484-9eb7-4525-923e-d00ebfe0434a",
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"metadata": {},
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"outputs": [],
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"source": [
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"from llm_agents_from_scratch.data_structures.agent import Task"
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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": "1d5d512e-d400-4398-980f-a4142d367add",
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"metadata": {},
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"outputs": [],
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"source": [
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"task = Task(\n",
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" instruction=\"Add one to fifty-five point three. Use an appropriate tool!\",\n",
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")"
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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": 11,
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"id": "e99cca54-0d21-4c9d-9a17-bf595d110fe5",
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"metadata": {},
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"outputs": [
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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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"INFO (llm_agents_fs.LLMAgent) : 🚀 Starting task: Add one to fifty-five point three. Use an appropriate tool!\n",
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"DEBUG (llm_agents_fs.TaskHandler) : 🧵 Rollout: \n",
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"INFO (llm_agents_fs.TaskHandler) : 🧠 New Step: Add one to fifty-five point three. Use an appropriate tool!\n",
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"INFO (llm_agents_fs.TaskHandler) : ⚙️ Processing Step: Add one to fifty-five point three. Use an appropriate tool!\n",
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"DEBUG (llm_agents_fs.TaskHandler) : 🧵 Rollout: \n",
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"DEBUG (llm_agents_fs.TaskHandler) : 💬 SYSTEM: You are a helpful assistant.\n",
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"DEBUG (llm_agents_fs.TaskHandler) : 💬 USER: Add one to fifty-five point three. Use an appropriate tool!\n",
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"DEBUG (llm_agents_fs.TaskHandler) : 💬 ASSISTANT: \n",
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"INFO (llm_agents_fs.TaskHandler) : 🛠️ Executing Tool Call: add_one\n",
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"INFO (llm_agents_fs.TaskHandler) : ✅ Successful Tool Call: 56.3\n",
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"INFO (llm_agents_fs.TaskHandler) : ✅ Step Result: After adding one to fifty-five point three, the result is 56.3.\n",
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"DEBUG (llm_agents_fs.TaskHandler) : 🧵 Rollout: user: Add one to fifty-five point three. Use an appropriate tool!\n",
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"assistant: I need to make a tool call(s) to add_one\n",
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"tool: \n",
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"The below is a tool call response for a given tool call.\n",
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"<tool-call>\n",
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"tool name: add_one\n",
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"arguments: {'x': '55.3'}\n",
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"</tool-call>\n",
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"\n",
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"<result>\n",
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"56.3\n",
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"</result>\n",
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"\n",
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"assistant: After adding one to fifty-five point three, the result is 56.3.\n",
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"INFO (llm_agents_fs.TaskHandler) : 🧠 New Step: There is sufficient context to complete the task within the provided history — another tool call may not even be necessary! Proceed with completion and mark this as the last step. NOTE: that the real user has not seen this dialogue, and so just provide the final task result without referencing it.\n",
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"INFO (llm_agents_fs.TaskHandler) : ⚙️ Processing Step: There is sufficient context to complete the task within the provided history — another tool call may not even be necessary! Proceed with completion and mark this as the last step. NOTE: that the real user has not seen this dialogue, and so just provide the final task result without referencing it.\n",
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"DEBUG (llm_agents_fs.TaskHandler) : 🧵 Rollout: user: Add one to fifty-five point three. Use an appropriate tool!\n",
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"assistant: I need to make a tool call(s) to add_one\n",
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"tool: \n",
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"The below is a tool call response for a given tool call.\n",
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"<tool-call>\n",
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"tool name: add_one\n",
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"arguments: {'x': '55.3'}\n",
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"</tool-call>\n",
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"\n",
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"<result>\n",
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"56.3\n",
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"</result>\n",
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"\n",
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"assistant: After adding one to fifty-five point three, the result is 56.3.\n",
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"DEBUG (llm_agents_fs.TaskHandler) : 💬 SYSTEM: You are a helpful assistant.\n",
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"\n",
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"Here is some past dialogue and context, where another assistant was working\n",
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"towards completing the task.\n",
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"\n",
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"<history>\n",
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"user: Add one to fifty-five point three. Use an appropriate tool!\n",
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"assistant: I need to make a tool call(s) to add_one\n",
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"tool: \n",
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"The below is a tool call response for a given tool call.\n",
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"<tool-call>\n",
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"tool name: add_one\n",
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"arguments: {'x': '55.3'}\n",
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"</tool-call>\n",
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"\n",
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"<result>\n",
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"56.3\n",
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"</result>\n",
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"\n",
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"assistant: After adding one to fifty-five point three, the result is 56.3.\n",
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"</history>\n",
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"\n",
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"DEBUG (llm_agents_fs.TaskHandler) : 💬 USER: There is sufficient context to complete the task within the provided history — another tool call may not even be necessary! Proceed with completion and mark this as the last step. NOTE: that the real user has not seen this dialogue, and so just provide the final task result without referencing it.\n",
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"DEBUG (llm_agents_fs.TaskHandler) : 💬 ASSISTANT: \n",
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"INFO (llm_agents_fs.TaskHandler) : 🛠️ Executing Tool Call: add_one\n",
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"INFO (llm_agents_fs.TaskHandler) : ✅ Successful Tool Call: 56.3\n",
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"INFO (llm_agents_fs.TaskHandler) : ✅ Step Result: After adding one to fifty-five point three, the result is 56.3.\n",
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"INFO (llm_agents_fs.LLMAgent) : 🏁 Task completed: After adding one to fifty-five point three, the result is 56.3.\n"
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]
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}
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],
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"source": [
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"result = await agent.run(task)"
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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": 12,
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"id": "0fde7c61-f0d9-4ef9-b0b6-90386667bbb8",
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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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"TaskResult(task=Task(instruction='Add one to fifty-five point three. Use an appropriate tool!'), content='After adding one to fifty-five point three, the result is 56.3.', rollout=\"user: Add one to fifty-five point three. Use an appropriate tool!\\nassistant: I need to make a tool call(s) to add_one\\ntool: \\nThe below is a tool call response for a given tool call.\\n<tool-call>\\ntool name: add_one\\narguments: {'x': '55.3'}\\n</tool-call>\\n\\n<result>\\n56.3\\n</result>\\n\\nassistant: After adding one to fifty-five point three, the result is 56.3.user: There is sufficient context to complete the task within the provided history — another tool call may not even be necessary! Proceed with completion and mark this as the last step. NOTE: that the real user has not seen this dialogue, and so just provide the final task result without referencing it.\\nassistant: I need to make a tool call(s) to add_one\\ntool: \\nThe below is a tool call response for a given tool call.\\n<tool-call>\\ntool name: add_one\\narguments: {'x': '55.3'}\\n</tool-call>\\n\\n<result>\\n56.3\\n</result>\\n\\nassistant: After adding one to fifty-five point three, the result is 56.3.\", error=False)"
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]
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},
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"execution_count": 12,
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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": null,
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"id": "93b1cfa1-1ac0-420d-b36e-007de5cdfc7f",
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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": {
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"kernelspec": {
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"display_name": "Python 3 (ipykernel)",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.13.5"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}

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