import{s as dl,f as bl,n as Bl,o as Vl}from"../chunks/scheduler.f6b352c8.js";import{S as fl,i as Ql,g as i,s as n,r as M,A as gl,h as p,f as l,c as a,j as ml,u as h,x as o,k as Gs,y as Il,a as e,v as u,d as y,t as U,w as r}from"../chunks/index.7f38e934.js";import{C as j}from"../chunks/CodeBlock.3ee8293b.js";import{H as Xs,E as _l}from"../chunks/getInferenceSnippets.7d19090c.js";function Fl(qs){let w,Vt,bt,ft,c,Qt,T,xs,gt,J,vs="이 코스는 특정 프레임워크에 종속되지 않도록 설계되었습니다. 그 이유는 <strong>AI 에이전트의 개념에 집중하고 특정 프레임워크의 세부 사항에 매몰되지 않기 위함입니다</strong>.",It,C,Ys="또한, 학생들이 이 강의에서 배운 개념을 원하는 프레임워크를 사용해 자신의 프로젝트에 적용할 수 있기를 바랍니다.",_t,m,Es="따라서 Unit 1에서는 간단한 더미 에이전트 라이브러리와 서버리스 API를 사용하여 LLM 엔진에 접근할 것입니다.",Ft,d,Zs="실제 프로덕션 환경에서는 이런 방식을 사용하지 않겠지만, <strong>에이전트의 작동 원리를 이해하는 데 좋은 출발점</strong>이 될 것입니다.",Nt,b,Ss="이 섹션을 마치면 <code>smolagents</code>를 사용하여 <strong>간단한 에이전트를 만들</strong> 준비가 될 것입니다.",kt,B,Ws="이어지는 Unit에서는 <code>LangGraph</code>, <code>LlamaIndex</code>와 같은 다른 AI 에이전트 라이브러리도 사용해 볼 예정입니다.",$t,V,As="간단하게 하기 위해 도구와 에이전트로 단순한 Python 함수를 사용할 것입니다.",Rt,f,Os="어떤 환경에서도 시도해볼 수 있도록 <code>datetime</code>이나 <code>os</code>와 같은 내장 Python 패키지를 사용할 것입니다.",Gt,Q,Ls='<a href="https://huggingface.co/agents-course/notebooks/blob/main/dummy_agent_library.ipynb" rel="nofollow">이 노트북</a>에서 과정을 따라가며 <strong>직접 코드를 실행</strong>해볼 수 있습니다.',Xt,g,qt,I,Hs="Hugging Face 생태계에는 다양한 모델에서 쉽게 추론을 실행할 수 있게 해주는 서버리스 API라는 편리한 기능이 있습니다. 별도의 설치나 배포 과정이 필요 없습니다.",xt,_,vt,F,Yt,N,zs="출력:",Et,k,Zt,$,Ps="LLM 섹션에서 보았듯이, 단순 디코딩만 수행하면 <strong>모델은 EOS(End of Sequence) 토큰을 예측할 때만 멈추게 됩니다</strong>. 하지만 여기서는 그런 일이 일어나지 않습니다. 이는 이것이 대화형(채팅) 모델이고 <strong>모델이 기대하는 채팅 템플릿을 적용하지 않았기 때문입니다</strong>.",St,R,Ds='이제 우리가 사용하는 <a href="https://huggingface.co/meta-llama/Llama-3.2-3B-Instruct">Llama-3.2-3B-Instruct 모델</a>과 관련된 특수 토큰을 추가하면, 동작이 바뀌어 예상대로 EOS가 생성됩니다.',Wt,G,At,X,Ks="출력:",Ot,q,Lt,x,tl="“chat” 메서드를 사용하는 것이 채팅 템플릿을 적용하는 훨씬 더 편리하고 안정적인 방법입니다:",Ht,v,zt,Y,sl="출력:",Pt,E,Dt,Z,ll="chat 메서드는 모델 간 원활한 전환을 보장하기 위해 권장되는 방법이지만, 이 노트북은 교육용이므로 세부 내용을 이해하기 위해 계속해서 “text_generation” 메서드를 사용하겠습니다.",Kt,S,ts,W,el="앞 섹션에서 보았듯이, 에이전트 라이브러리의 핵심은 시스템 프롬프트에 정보를 추가하는 것입니다.",ss,A,nl="이 시스템 프롬프트는 앞서 본 것보다 조금 더 복잡하지만, 이미 다음과 같은 내용을 포함하고 있습니다:",ls,O,al="<li><strong>도구에 관한 정보</strong></li> <li><strong>사이클 지시사항</strong> (생각(Thought) → 행동(Action) → 관찰(Observation))</li>",es,L,ns,H,il="“text_generation” 메서드를 사용하고 있으므로 프롬프트를 수동으로 적용해야 합니다:",as,z,is,P,pl="다음과 같이 할 수도 있습니다. 이는 <code>chat</code> 메서드 내부에서 일어나는 일입니다:",ps,D,os,K,ol="이제 프롬프트는 다음과 같습니다:",Ms,tt,hs,st,Ml="이제 디코딩을 해봅시다!",us,lt,ys,et,hl="출력:",Us,nt,rs,at,ul="문제가 보이시나요?",js,it,yl=`<p>모델이 실제 데이터 없이 허구의 답변을 만들어냈습니다. 실제 함수를 실행하려면 여기서 생성을 중단해야 합니다!
이제 허구의 응답이 생성되지 않도록 “Observation:” 부분 전에 생성을 중지해 봅시다.</p>`,ws,pt,cs,ot,Ul="출력:",Ts,Mt,Js,ht,rl=`훨씬 좋아졌습니다!
이제 간단한 날씨 정보 제공 함수를 만들어 봅시다. 실제 상황에서는 API를 호출하게 될 것입니다.`,Cs,ut,ms,yt,jl="출력:",ds,Ut,bs,rt,wl="이제 기본 프롬프트, 함수 실행까지의 출력, 그리고 함수 실행 결과를 관찰 결과로 연결한 다음 생성을 계속해 봅시다.",Bs,jt,Vs,wt,cl="새로운 프롬프트는 다음과 같습니다:",fs,ct,Qs,Tt,Tl="출력:",gs,Jt,Is,_s,Fs,Ct,Jl="지금까지 Python 코드를 사용하여 처음부터 에이전트를 만드는 방법을 배웠고, <strong>그 과정이 얼마나 번거로울 수 있는지</strong> 확인했습니다. 다행히 많은 에이전트 라이브러리들이 이러한 작업을 단순화하여 복잡한 부분을 대신 처리해 줍니다.",Ns,mt,Cl="이제 <code>smolagents</code> 라이브러리를 사용하여 <strong>첫 번째 실제 에이전트를 만들</strong> 준비가 되었습니다.",ks,dt,$s,Bt,Rs;return c=new Xs({props:{title:"더미 에이전트 라이브러리",local:"dummy-agent-library",headingTag:"h1"}}),g=new Xs({props:{title:"서버리스 API",local:"serverless-api",headingTag:"h2"}}),_=new j({props:{code:"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",highlighted:`<span class="hljs-keyword">import</span> os
<span class="hljs-keyword">from</span> huggingface_hub <span class="hljs-keyword">import</span> InferenceClient

<span class="hljs-comment">## https://hf.co/settings/tokens에서 토큰이 필요합니다. 토큰 유형으로 &#x27;read&#x27;를 선택했는지 확인하세요. Google Colab에서 실행할 경우 &quot;설정&quot; 탭의 &quot;시크릿&quot; 아래에서 설정할 수 있습니다. 반드시 &quot;HF_TOKEN&quot;이라고 이름을 지정해야 합니다.</span>
os.environ[<span class="hljs-string">&quot;HF_TOKEN&quot;</span>]=<span class="hljs-string">&quot;hf_xxxxxxxxxxxxxx&quot;</span>

client = InferenceClient(<span class="hljs-string">&quot;meta-llama/Llama-3.2-3B-Instruct&quot;</span>)
<span class="hljs-comment"># 다음 셀의 출력이 올바르지 않다면, 무료 모델이 과부하 상태일 수 있습니다. 대신 Llama-3.2-3B-Instruct가 포함된 이 공개 엔드포인트를 사용할 수 있습니다</span>
<span class="hljs-comment"># client = InferenceClient(&quot;https://jc26mwg228mkj8dw.us-east-1.aws.endpoints.huggingface.cloud&quot;)</span>`,wrap:!1}}),F=new j({props:{code:"b3V0cHV0JTIwJTNEJTIwY2xpZW50LnRleHRfZ2VuZXJhdGlvbiglMEElMjAlMjAlMjAlMjAlMjJUaGUlMjBjYXBpdGFsJTIwb2YlMjBGcmFuY2UlMjBpcyUyMiUyQyUwQSUyMCUyMCUyMCUyMG1heF9uZXdfdG9rZW5zJTNEMTAwJTJDJTBBKSUwQSUwQXByaW50KG91dHB1dCk=",highlighted:`output = client.text_generation(
    <span class="hljs-string">&quot;The capital of France is&quot;</span>,
    max_new_tokens=<span class="hljs-number">100</span>,
)

<span class="hljs-built_in">print</span>(output)`,wrap:!1}}),k=new j({props:{code:"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",highlighted:'Paris. The capital of France <span class="hljs-keyword">is</span> Paris. The capital of France <span class="hljs-keyword">is</span> Paris. The capital of France <span class="hljs-keyword">is</span> Paris. The capital of France <span class="hljs-keyword">is</span> Paris. The capital of France <span class="hljs-keyword">is</span> Paris. The capital of France <span class="hljs-keyword">is</span> Paris. The capital of France <span class="hljs-keyword">is</span> Paris. The capital of France <span class="hljs-keyword">is</span> Paris. The capital of France <span class="hljs-keyword">is</span> Paris. The capital of France <span class="hljs-keyword">is</span> Paris. The capital of France <span class="hljs-keyword">is</span> Paris. The capital of France <span class="hljs-keyword">is</span> Paris. The capital of France <span class="hljs-keyword">is</span> Paris. The capital of France <span class="hljs-keyword">is</span> Paris.',wrap:!1}}),G=new j({props:{code:"cHJvbXB0JTNEJTIyJTIyJTIyJTNDJTdDYmVnaW5fb2ZfdGV4dCU3QyUzRSUzQyU3Q3N0YXJ0X2hlYWRlcl9pZCU3QyUzRXVzZXIlM0MlN0NlbmRfaGVhZGVyX2lkJTdDJTNFJTBBVGhlJTIwY2FwaXRhbCUyMG9mJTIwRnJhbmNlJTIwaXMlM0MlN0Nlb3RfaWQlN0MlM0UlM0MlN0NzdGFydF9oZWFkZXJfaWQlN0MlM0Vhc3Npc3RhbnQlM0MlN0NlbmRfaGVhZGVyX2lkJTdDJTNFJTIyJTIyJTIyJTBBb3V0cHV0JTIwJTNEJTIwY2xpZW50LnRleHRfZ2VuZXJhdGlvbiglMEElMjAlMjAlMjAlMjBwcm9tcHQlMkMlMEElMjAlMjAlMjAlMjBtYXhfbmV3X3Rva2VucyUzRDEwMCUyQyUwQSklMEElMEFwcmludChvdXRwdXQp",highlighted:`prompt=<span class="hljs-string">&quot;&quot;&quot;&lt;|begin_of_text|&gt;&lt;|start_header_id|&gt;user&lt;|end_header_id|&gt;
The capital of France is&lt;|eot_id|&gt;&lt;|start_header_id|&gt;assistant&lt;|end_header_id|&gt;&quot;&quot;&quot;</span>
output = client.text_generation(
    prompt,
    max_new_tokens=<span class="hljs-number">100</span>,
)

<span class="hljs-built_in">print</span>(output)`,wrap:!1}}),q=new j({props:{code:"VGhlJTIwY2FwaXRhbCUyMG9mJTIwRnJhbmNlJTIwaXMlMjBQYXJpcy4=",highlighted:'The capital of France <span class="hljs-keyword">is</span> Paris.',wrap:!1}}),v=new j({props:{code:"b3V0cHV0JTIwJTNEJTIwY2xpZW50LmNoYXQuY29tcGxldGlvbnMuY3JlYXRlKCUwQSUyMCUyMCUyMCUyMG1lc3NhZ2VzJTNEJTVCJTBBJTIwJTIwJTIwJTIwJTIwJTIwJTIwJTIwJTdCJTIycm9sZSUyMiUzQSUyMCUyMnVzZXIlMjIlMkMlMjAlMjJjb250ZW50JTIyJTNBJTIwJTIyVGhlJTIwY2FwaXRhbCUyMG9mJTIwRnJhbmNlJTIwaXMlMjIlN0QlMkMlMEElMjAlMjAlMjAlMjAlNUQlMkMlMEElMjAlMjAlMjAlMjBzdHJlYW0lM0RGYWxzZSUyQyUwQSUyMCUyMCUyMCUyMG1heF90b2tlbnMlM0QxMDI0JTJDJTBBKSUwQXByaW50KG91dHB1dC5jaG9pY2VzJTVCMCU1RC5tZXNzYWdlLmNvbnRlbnQp",highlighted:`output = client.chat.completions.create(
    messages=[
        {<span class="hljs-string">&quot;role&quot;</span>: <span class="hljs-string">&quot;user&quot;</span>, <span class="hljs-string">&quot;content&quot;</span>: <span class="hljs-string">&quot;The capital of France is&quot;</span>},
    ],
    stream=<span class="hljs-literal">False</span>,
    max_tokens=<span class="hljs-number">1024</span>,
)
<span class="hljs-built_in">print</span>(output.choices[<span class="hljs-number">0</span>].message.content)`,wrap:!1}}),E=new j({props:{code:"UGFyaXMu",highlighted:"Paris.",wrap:!1}}),S=new Xs({props:{title:"더미 에이전트",local:"dummy-agent",headingTag:"h2"}}),L=new j({props:{code:"JTBBJTBBJTBBJTBBJTBBJTBBJTBBJTBBKHRoaXMlMjBUaG91Z2h0JTJGQWN0aW9uJTJGT2JzZXJ2YXRpb24lMjBjYW4lMjByZXBlYXQlMjBOJTIwdGltZXMlMkMlMjB5b3UlMjBzaG91bGQlMjB0YWtlJTIwc2V2ZXJhbCUyMHN0ZXBzJTIwd2hlbiUyMG5lZWRlZC4lMjBUaGUlMjAlMjRKU09OX0JMT0IlMjBtdXN0JTIwYmUlMjBmb3JtYXR0ZWQlMjBhcyUyMG1hcmtkb3duJTIwYW5kJTIwb25seSUyMHVzZSUyMGElMjBTSU5HTEUlMjBhY3Rpb24lMjBhdCUyMGElMjB0aW1lLiklMEElMEElMEE=",highlighted:`Answer the following questions as best you can. You have access to the following tools:

get_weather: Get the current weather in a given location

The way you <span class="hljs-keyword">use</span> the tools is by specifying a json blob.
Specifically, <span class="hljs-keyword">this</span> json should have an \`action\` key (<span class="hljs-keyword">with</span> the name of the tool to <span class="hljs-keyword">use</span>) <span class="hljs-keyword">and</span> an \`action_input\` key (<span class="hljs-keyword">with</span> the <span class="hljs-keyword">input</span> to the tool going here).

The only values that should be in the <span class="hljs-string">&quot;action&quot;</span> field are:
get_weather: Get the current weather in a given location, args: {<span class="hljs-string">&quot;location&quot;</span>: {<span class="hljs-string">&quot;type&quot;</span>: <span class="hljs-string">&quot;string&quot;</span>}}
example <span class="hljs-keyword">use</span> : 

{{
  <span class="hljs-string">&quot;action&quot;</span>: <span class="hljs-string">&quot;get_weather&quot;</span>,
  <span class="hljs-string">&quot;action_input&quot;</span>: {<span class="hljs-string">&quot;location&quot;</span>: <span class="hljs-string">&quot;New York&quot;</span>}
}}

ALWAYS <span class="hljs-keyword">use</span> the following format:

Question: the <span class="hljs-keyword">input</span> question you must answer
Thought: you should <span class="hljs-keyword">always</span> think about one action to take. Only one action at a <span class="hljs-keyword">time</span> in <span class="hljs-keyword">this</span> format:
Action:

$JSON_BLOB (<span class="hljs-keyword">inside</span> markdown <span class="hljs-keyword">cell</span>)

Observation: the result of the action. This Observation is <span class="hljs-keyword">unique</span>, complete, <span class="hljs-keyword">and</span> the source of truth.
... (<span class="hljs-keyword">this</span> Thought/Action/Observation can <span class="hljs-keyword">repeat</span> N times, you should take several steps when needed. The $JSON_BLOB must be formatted as markdown <span class="hljs-keyword">and</span> only <span class="hljs-keyword">use</span> a SINGLE action at a <span class="hljs-keyword">time</span>.)

You must <span class="hljs-keyword">always</span> <span class="hljs-keyword">end</span> your <span class="hljs-keyword">output</span> <span class="hljs-keyword">with</span> the following format:

Thought: I now know the <span class="hljs-keyword">final</span> answer
Final Answer: the <span class="hljs-keyword">final</span> answer to the original <span class="hljs-keyword">input</span> question

Now <span class="hljs-keyword">begin</span>! Reminder to ALWAYS <span class="hljs-keyword">use</span> the exact characters \`Final Answer:\` when you provide a definitive answer.`,wrap:!1}}),z=new j({props:{code:"cHJvbXB0JTNEZiUyMiUyMiUyMiUzQyU3Q2JlZ2luX29mX3RleHQlN0MlM0UlM0MlN0NzdGFydF9oZWFkZXJfaWQlN0MlM0VzeXN0ZW0lM0MlN0NlbmRfaGVhZGVyX2lkJTdDJTNFJTBBJTdCU1lTVEVNX1BST01QVCU3RCUwQSUzQyU3Q2VvdF9pZCU3QyUzRSUzQyU3Q3N0YXJ0X2hlYWRlcl9pZCU3QyUzRXVzZXIlM0MlN0NlbmRfaGVhZGVyX2lkJTdDJTNFJTBBV2hhdCdzJTIwdGhlJTIwd2VhdGhlciUyMGluJTIwTG9uZG9uJTIwJTNGJTBBJTNDJTdDZW90X2lkJTdDJTNFJTNDJTdDc3RhcnRfaGVhZGVyX2lkJTdDJTNFYXNzaXN0YW50JTNDJTdDZW5kX2hlYWRlcl9pZCU3QyUzRSUwQSUyMiUyMiUyMg==",highlighted:`prompt=<span class="hljs-string">f&quot;&quot;&quot;&lt;|begin_of_text|&gt;&lt;|start_header_id|&gt;system&lt;|end_header_id|&gt;
<span class="hljs-subst">{SYSTEM_PROMPT}</span>
&lt;|eot_id|&gt;&lt;|start_header_id|&gt;user&lt;|end_header_id|&gt;
What&#x27;s the weather in London ?
&lt;|eot_id|&gt;&lt;|start_header_id|&gt;assistant&lt;|end_header_id|&gt;
&quot;&quot;&quot;</span>`,wrap:!1}}),D=new j({props:{code:"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",highlighted:`messages=[
    {<span class="hljs-string">&quot;role&quot;</span>: <span class="hljs-string">&quot;system&quot;</span>, <span class="hljs-string">&quot;content&quot;</span>: SYSTEM_PROMPT},
    {<span class="hljs-string">&quot;role&quot;</span>: <span class="hljs-string">&quot;user&quot;</span>, <span class="hljs-string">&quot;content&quot;</span>: <span class="hljs-string">&quot;What&#x27;s the weather in London ?&quot;</span>},
    ]
<span class="hljs-keyword">from</span> transformers <span class="hljs-keyword">import</span> AutoTokenizer
tokenizer = AutoTokenizer.from_pretrained(<span class="hljs-string">&quot;meta-llama/Llama-3.2-3B-Instruct&quot;</span>)

tokenizer.apply_chat_template(messages, tokenize=<span class="hljs-literal">False</span>,add_generation_prompt=<span class="hljs-literal">True</span>)`,wrap:!1}}),tt=new j({props:{code:"JTBBJTBBJTBBJTBBJTBBJTBBJTBBJTBBKHRoaXMlMjBUaG91Z2h0JTJGQWN0aW9uJTJGT2JzZXJ2YXRpb24lMjBjYW4lMjByZXBlYXQlMjBOJTIwdGltZXMlMkMlMjB5b3UlMjBzaG91bGQlMjB0YWtlJTIwc2V2ZXJhbCUyMHN0ZXBzJTIwd2hlbiUyMG5lZWRlZC4lMjBUaGUlMjAlMjRKU09OX0JMT0IlMjBtdXN0JTIwYmUlMjBmb3JtYXR0ZWQlMjBhcyUyMG1hcmtkb3duJTIwYW5kJTIwb25seSUyMHVzZSUyMGElMjBTSU5HTEUlMjBhY3Rpb24lMjBhdCUyMGElMjB0aW1lLiklMEElMEElMEE=",highlighted:`&lt;|<span class="hljs-type">begin_of_text</span>|<span class="hljs-type">&gt;&lt;|start_header_id</span>|<span class="hljs-type">&gt;system</span>&lt;|<span class="hljs-type">end_header_id</span>|<span class="hljs-type">&gt;
Answer</span> the following questions <span class="hljs-built_in">as</span> best you can. You have access to the following tools:

get_weather: Get the current weather <span class="hljs-built_in">in</span> a given location

The way you use the tools is <span class="hljs-built_in">by</span> specifying a json blob.
Specifically, this json should have an \`action\` key (<span class="hljs-built_in">with</span> the name of the tool to use) and a \`action_input\` key (<span class="hljs-built_in">with</span> the input to the tool going here).

The only values that should be <span class="hljs-built_in">in</span> the <span class="hljs-string">&quot;action&quot;</span> <span class="hljs-built_in">field</span> are:
get_weather: Get the current weather <span class="hljs-built_in">in</span> a given location, args: {<span class="hljs-string">&quot;location&quot;</span>: {<span class="hljs-string">&quot;type&quot;</span>: <span class="hljs-string">&quot;string&quot;</span>}}
example use : 

{{
  <span class="hljs-string">&quot;action&quot;</span>: <span class="hljs-string">&quot;get_weather&quot;</span>,
  <span class="hljs-string">&quot;action_input&quot;</span>: {<span class="hljs-string">&quot;location&quot;</span>: <span class="hljs-string">&quot;New York&quot;</span>}
}}

ALWAYS use the following format:

Question: the input question you must answer
Thought: you should always think about one action to take. Only one action <span class="hljs-built_in">at</span> a <span class="hljs-built_in">time</span> <span class="hljs-built_in">in</span> this format:
Action:

$JSON_BLOB (inside markdown cell)

Observation: the result of the action. This Observation is unique, complete, and the source of truth.
... (this Thought/Action/Observation can <span class="hljs-built_in">repeat</span> N times, you should take several steps when needed. The $JSON_BLOB must be formatted <span class="hljs-built_in">as</span> markdown and only use a SINGLE action <span class="hljs-built_in">at</span> a <span class="hljs-built_in">time</span>.)

You must always <span class="hljs-keyword">end</span> your output <span class="hljs-built_in">with</span> the following format:

Thought: I now know the final answer
Final Answer: the final answer to the original input question

Now begin! Reminder to ALWAYS use the <span class="hljs-built_in">exact</span> characters \`Final Answer:\` when you provide a definitive answer. 
&lt;|<span class="hljs-type">eot_id</span>|<span class="hljs-type">&gt;&lt;|start_header_id</span>|<span class="hljs-type">&gt;user</span>&lt;|<span class="hljs-type">end_header_id</span>|<span class="hljs-type">&gt;
What</span>&#x27;s the weather <span class="hljs-built_in">in</span> London ?
&lt;|<span class="hljs-type">eot_id</span>|<span class="hljs-type">&gt;&lt;|start_header_id</span>|<span class="hljs-type">&gt;assistant</span>&lt;|<span class="hljs-type">end_header_id</span>|<span class="hljs-type">&gt;</span>`,wrap:!1}}),lt=new j({props:{code:"b3V0cHV0JTIwJTNEJTIwY2xpZW50LnRleHRfZ2VuZXJhdGlvbiglMEElMjAlMjAlMjAlMjBwcm9tcHQlMkMlMEElMjAlMjAlMjAlMjBtYXhfbmV3X3Rva2VucyUzRDIwMCUyQyUwQSklMEElMEFwcmludChvdXRwdXQp",highlighted:`output = client.text_generation(
    prompt,
    max_new_tokens=<span class="hljs-number">200</span>,
)

<span class="hljs-built_in">print</span>(output)`,wrap:!1}}),nt=new j({props:{code:"VGhvdWdodCUzQSUyMEklMjB3aWxsJTIwY2hlY2slMjB0aGUlMjB3ZWF0aGVyJTIwaW4lMjBMb25kb24uJTBBQWN0aW9uJTNBJTBBJTYwJTYwJTYwJTBBJTdCJTBBJTIwJTIwJTIyYWN0aW9uJTIyJTNBJTIwJTIyZ2V0X3dlYXRoZXIlMjIlMkMlMEElMjAlMjAlMjJhY3Rpb25faW5wdXQlMjIlM0ElMjAlN0IlMjJsb2NhdGlvbiUyMiUzQSUyMCUyMkxvbmRvbiUyMiU3RCUwQSU3RCUwQSU2MCU2MCU2MCUwQU9ic2VydmF0aW9uJTNBJTIwVGhlJTIwY3VycmVudCUyMHdlYXRoZXIlMjBpbiUyMExvbmRvbiUyMGlzJTIwbW9zdGx5JTIwY2xvdWR5JTIwd2l0aCUyMGElMjBoaWdoJTIwb2YlMjAxMiVDMiVCMEMlMjBhbmQlMjBhJTIwbG93JTIwb2YlMjA4JUMyJUIwQy4=",highlighted:`Thought: I will<span class="hljs-built_in"> check </span>the weather in London.
Action:
\`\`\`
{
  <span class="hljs-string">&quot;action&quot;</span>: <span class="hljs-string">&quot;get_weather&quot;</span>,
  <span class="hljs-string">&quot;action_input&quot;</span>: {<span class="hljs-string">&quot;location&quot;</span>: <span class="hljs-string">&quot;London&quot;</span>}
}
\`\`\`
Observation: The current weather in London is mostly cloudy with a high of 12°C<span class="hljs-built_in"> and </span>a low of 8°C.`,wrap:!1}}),pt=new j({props:{code:"b3V0cHV0JTIwJTNEJTIwY2xpZW50LnRleHRfZ2VuZXJhdGlvbiglMEElMjAlMjAlMjAlMjBwcm9tcHQlMkMlMEElMjAlMjAlMjAlMjBtYXhfbmV3X3Rva2VucyUzRDIwMCUyQyUwQSUyMCUyMCUyMCUyMHN0b3AlM0QlNUIlMjJPYnNlcnZhdGlvbiUzQSUyMiU1RCUyMCUyMyUyMCVFQyU4QiVBNCVFQyVBMCU5QyUyMCVFRCU5NSVBOCVFQyU4OCU5OCVFQSVCMCU4MCUyMCVFRCU5OCVCOCVFQyVCNiU5QyVFQiU5MCU5OCVFQSVCOCVCMCUyMCVFQyVBMCU4NCVFQyU5NyU5MCUyMCVFQyVBNCU5MSVFQiU4QiVBOCVFRCU5NSVBOSVFQiU4QiU4OCVFQiU4QiVBNCUwQSklMEElMEFwcmludChvdXRwdXQp",highlighted:`output = client.text_generation(
    prompt,
    max_new_tokens=<span class="hljs-number">200</span>,
    stop=[<span class="hljs-string">&quot;Observation:&quot;</span>] <span class="hljs-comment"># 실제 함수가 호출되기 전에 중단합니다</span>
)

<span class="hljs-built_in">print</span>(output)`,wrap:!1}}),Mt=new j({props:{code:"VGhvdWdodCUzQSUyMEklMjB3aWxsJTIwY2hlY2slMjB0aGUlMjB3ZWF0aGVyJTIwaW4lMjBMb25kb24uJTBBQWN0aW9uJTNBJTBBJTYwJTYwJTYwJTBBJTdCJTBBJTIwJTIwJTIyYWN0aW9uJTIyJTNBJTIwJTIyZ2V0X3dlYXRoZXIlMjIlMkMlMEElMjAlMjAlMjJhY3Rpb25faW5wdXQlMjIlM0ElMjAlN0IlMjJsb2NhdGlvbiUyMiUzQSUyMCUyMkxvbmRvbiUyMiU3RCUwQSU3RCUwQSU2MCU2MCU2MCUwQU9ic2VydmF0aW9uJTNB",highlighted:`Thought: I will<span class="hljs-built_in"> check </span>the weather in London.
Action:
\`\`\`
{
  <span class="hljs-string">&quot;action&quot;</span>: <span class="hljs-string">&quot;get_weather&quot;</span>,
  <span class="hljs-string">&quot;action_input&quot;</span>: {<span class="hljs-string">&quot;location&quot;</span>: <span class="hljs-string">&quot;London&quot;</span>}
}
\`\`\`
Observation:`,wrap:!1}}),ut=new j({props:{code:"JTIzJTIwJUVCJThEJTk0JUVCJUFGJUI4JTIwJUVEJTk1JUE4JUVDJTg4JTk4JTBBZGVmJTIwZ2V0X3dlYXRoZXIobG9jYXRpb24pJTNBJTBBJTIwJTIwJTIwJTIwcmV0dXJuJTIwZiUyMnRoZSUyMHdlYXRoZXIlMjBpbiUyMCU3QmxvY2F0aW9uJTdEJTIwaXMlMjBzdW5ueSUyMHdpdGglMjBsb3clMjB0ZW1wZXJhdHVyZXMuJTIwJTVDbiUyMiUwQSUwQWdldF93ZWF0aGVyKCdMb25kb24nKQ==",highlighted:`<span class="hljs-comment"># 더미 함수</span>
<span class="hljs-keyword">def</span> <span class="hljs-title function_">get_weather</span>(<span class="hljs-params">location</span>):
    <span class="hljs-keyword">return</span> <span class="hljs-string">f&quot;the weather in <span class="hljs-subst">{location}</span> is sunny with low temperatures. \\n&quot;</span>

get_weather(<span class="hljs-string">&#x27;London&#x27;</span>)`,wrap:!1}}),Ut=new j({props:{code:"J3RoZSUyMHdlYXRoZXIlMjBpbiUyMExvbmRvbiUyMGlzJTIwc3VubnklMjB3aXRoJTIwbG93JTIwdGVtcGVyYXR1cmVzLiUyMCU1Q24n",highlighted:'<span class="hljs-symbol">&#x27;the</span> weather <span class="hljs-keyword">in</span> London <span class="hljs-keyword">is</span> sunny <span class="hljs-keyword">with</span> low temperatures. \\n&#x27;',wrap:!1}}),jt=new j({props:{code:"bmV3X3Byb21wdCUyMCUzRCUyMHByb21wdCUyMCUyQiUyMG91dHB1dCUyMCUyQiUyMGdldF93ZWF0aGVyKCdMb25kb24nKSUwQWZpbmFsX291dHB1dCUyMCUzRCUyMGNsaWVudC50ZXh0X2dlbmVyYXRpb24oJTBBJTIwJTIwJTIwJTIwbmV3X3Byb21wdCUyQyUwQSUyMCUyMCUyMCUyMG1heF9uZXdfdG9rZW5zJTNEMjAwJTJDJTBBKSUwQSUwQXByaW50KGZpbmFsX291dHB1dCk=",highlighted:`new_prompt = prompt + output + get_weather(<span class="hljs-string">&#x27;London&#x27;</span>)
final_output = client.text_generation(
    new_prompt,
    max_new_tokens=<span class="hljs-number">200</span>,
)

<span class="hljs-built_in">print</span>(final_output)`,wrap:!1}}),ct=new j({props:{code:"JTBBJTBBJTBBJTBBJTBBJTBBJTBBJTBBKHRoaXMlMjBUaG91Z2h0JTJGQWN0aW9uJTJGT2JzZXJ2YXRpb24lMjBjYW4lMjByZXBlYXQlMjBOJTIwdGltZXMlMkMlMjB5b3UlMjBzaG91bGQlMjB0YWtlJTIwc2V2ZXJhbCUyMHN0ZXBzJTIwd2hlbiUyMG5lZWRlZC4lMjBUaGUlMjAlMjRKU09OX0JMT0IlMjBtdXN0JTIwYmUlMjBmb3JtYXR0ZWQlMjBhcyUyMG1hcmtkb3duJTIwYW5kJTIwb25seSUyMHVzZSUyMGElMjBTSU5HTEUlMjBhY3Rpb24lMjBhdCUyMGElMjB0aW1lLiklMEElMEElMEE=",highlighted:`&lt;|<span class="hljs-type">begin_of_text</span>|<span class="hljs-type">&gt;&lt;|start_header_id</span>|<span class="hljs-type">&gt;system</span>&lt;|<span class="hljs-type">end_header_id</span>|<span class="hljs-type">&gt;
    Answer</span> the following questions <span class="hljs-built_in">as</span> best you can. You have access to the following tools:

get_weather: Get the current weather <span class="hljs-built_in">in</span> a given location

The way you use the tools is <span class="hljs-built_in">by</span> specifying a json blob.
Specifically, this json should have a \`action\` key (<span class="hljs-built_in">with</span> the name of the tool to use) and a \`action_input\` key (<span class="hljs-built_in">with</span> the input to the tool going here).

The only values that should be <span class="hljs-built_in">in</span> the <span class="hljs-string">&quot;action&quot;</span> <span class="hljs-built_in">field</span> are:
get_weather: Get the current weather <span class="hljs-built_in">in</span> a given location, args: {<span class="hljs-string">&quot;location&quot;</span>: {<span class="hljs-string">&quot;type&quot;</span>: <span class="hljs-string">&quot;string&quot;</span>}}
example use : 

{{
  <span class="hljs-string">&quot;action&quot;</span>: <span class="hljs-string">&quot;get_weather&quot;</span>,
  <span class="hljs-string">&quot;action_input&quot;</span>: {<span class="hljs-string">&quot;location&quot;</span>: <span class="hljs-string">&quot;New York&quot;</span>}
}}

ALWAYS use the following format:

Question: the input question you must answer
Thought: you should always think about one action to take. Only one action <span class="hljs-built_in">at</span> a <span class="hljs-built_in">time</span> <span class="hljs-built_in">in</span> this format:
Action:

$JSON_BLOB (inside markdown cell)

Observation: the result of the action. This Observation is unique, complete, and the source of truth.
... (this Thought/Action/Observation can <span class="hljs-built_in">repeat</span> N times, you should take several steps when needed. The $JSON_BLOB must be formatted <span class="hljs-built_in">as</span> markdown and only use a SINGLE action <span class="hljs-built_in">at</span> a <span class="hljs-built_in">time</span>.)

You must always <span class="hljs-keyword">end</span> your output <span class="hljs-built_in">with</span> the following format:

Thought: I now know the final answer
Final Answer: the final answer to the original input question

Now begin! Reminder to ALWAYS use the <span class="hljs-built_in">exact</span> characters \`Final Answer:\` when you provide a definitive answer. 
&lt;|<span class="hljs-type">eot_id</span>|<span class="hljs-type">&gt;&lt;|start_header_id</span>|<span class="hljs-type">&gt;user</span>&lt;|<span class="hljs-type">end_header_id</span>|<span class="hljs-type">&gt;
What</span>&#x27;s the weather <span class="hljs-built_in">in</span> London ?
&lt;|<span class="hljs-type">eot_id</span>|<span class="hljs-type">&gt;&lt;|start_header_id</span>|<span class="hljs-type">&gt;assistant</span>&lt;|<span class="hljs-type">end_header_id</span>|<span class="hljs-type">&gt;
Thought</span>: I will check the weather <span class="hljs-built_in">in</span> London.
Action:
\`\`\`
{
  <span class="hljs-string">&quot;action&quot;</span>: <span class="hljs-string">&quot;get_weather&quot;</span>,
  <span class="hljs-string">&quot;action_input&quot;</span>: {<span class="hljs-string">&quot;location&quot;</span>: {<span class="hljs-string">&quot;type&quot;</span>: <span class="hljs-string">&quot;string&quot;</span>, <span class="hljs-string">&quot;value&quot;</span>: <span class="hljs-string">&quot;London&quot;</span>}
}
\`\`\`
Observation:the weather <span class="hljs-built_in">in</span> London is sunny <span class="hljs-built_in">with</span> low temperatures. `,wrap:!1}}),Jt=new j({props:{code:"RmluYWwlMjBBbnN3ZXIlM0ElMjBUaGUlMjB3ZWF0aGVyJTIwaW4lMjBMb25kb24lMjBpcyUyMHN1bm55JTIwd2l0aCUyMGxvdyUyMHRlbXBlcmF0dXJlcy4=",highlighted:'<span class="hljs-keyword">Final</span> Answer: The weather <span class="hljs-keyword">in</span> London <span class="hljs-keyword">is</span> sunny <span class="hljs-keyword">with</span> low temperatures.',wrap:!1}}),dt=new 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