import{s as Ot,f as Kt,o as es,n as _}from"../chunks/scheduler.37c15a92.js";import{S as ts,i as ss,g as T,s as d,r as U,A as ls,h,f as s,c as m,j as yt,u as I,x as y,k as G,y as ns,a as l,v as g,d as b,t as Z,w as $,m as R,n as x}from"../chunks/index.2bf4358c.js";import{T as $e}from"../chunks/Tip.363c041f.js";import{C as W}from"../chunks/CodeBlock.4e987730.js";import{H as V}from"../chunks/Heading.8ada512a.js";import{H as ft,a as Q}from"../chunks/HfOption.02c8e375.js";import{E as as}from"../chunks/getInferenceSnippets.d4d07d1e.js";function is(C){let a,u="You can choose any of the frameworks covered in the course for this use case. Select your preferred option from the code tabs.";return{c(){a=T("p"),a.textContent=u},l(c){a=h(c,"P",{"data-svelte-h":!0}),y(a)!=="svelte-1846727"&&(a.textContent=u)},m(c,M){l(c,a,M)},p:_,d(c){c&&s(a)}}}function os(C){let a;return{c(){a=R("In a real-world scenario, this dataset could be expanded to include dietary preferences, gift interests, conversation topics to avoid, and other helpful details for a host.")},l(u){a=x(u,"In a real-world scenario, this dataset could be expanded to include dietary preferences, gift interests, conversation topics to avoid, and other helpful details for a host.")},m(u,c){l(u,a,c)},d(u){u&&s(a)}}}function rs(C){let a,u="We will use the Hugging Face <code>datasets</code> library to load the dataset and convert it into a list of <code>Document</code> objects from the <code>langchain.docstore.document</code> module.",c,M,p;return M=new W({props:{code:"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",highlighted:`<span class="hljs-keyword">import</span> datasets
<span class="hljs-keyword">from</span> langchain_core.documents <span class="hljs-keyword">import</span> Document

<span class="hljs-comment"># Load the dataset</span>
guest_dataset = datasets.load_dataset(<span class="hljs-string">&quot;agents-course/unit3-invitees&quot;</span>, split=<span class="hljs-string">&quot;train&quot;</span>)

<span class="hljs-comment"># Convert dataset entries into Document objects</span>
docs = [
    Document(
        page_content=<span class="hljs-string">&quot;\\n&quot;</span>.join([
            <span class="hljs-string">f&quot;Name: <span class="hljs-subst">{guest[<span class="hljs-string">&#x27;name&#x27;</span>]}</span>&quot;</span>,
            <span class="hljs-string">f&quot;Relation: <span class="hljs-subst">{guest[<span class="hljs-string">&#x27;relation&#x27;</span>]}</span>&quot;</span>,
            <span class="hljs-string">f&quot;Description: <span class="hljs-subst">{guest[<span class="hljs-string">&#x27;description&#x27;</span>]}</span>&quot;</span>,
            <span class="hljs-string">f&quot;Email: <span class="hljs-subst">{guest[<span class="hljs-string">&#x27;email&#x27;</span>]}</span>&quot;</span>
        ]),
        metadata={<span class="hljs-string">&quot;name&quot;</span>: guest[<span class="hljs-string">&quot;name&quot;</span>]}
    )
    <span class="hljs-keyword">for</span> guest <span class="hljs-keyword">in</span> guest_dataset
]
`,wrap:!1}}),{c(){a=T("p"),a.innerHTML=u,c=d(),U(M.$$.fragment)},l(o){a=h(o,"P",{"data-svelte-h":!0}),y(a)!=="svelte-1vrqwzz"&&(a.innerHTML=u),c=m(o),I(M.$$.fragment,o)},m(o,n){l(o,a,n),l(o,c,n),g(M,o,n),p=!0},p:_,i(o){p||(b(M.$$.fragment,o),p=!0)},o(o){Z(M.$$.fragment,o),p=!1},d(o){o&&(s(a),s(c)),$(M,o)}}}function ps(C){let a,u="We will use the Hugging Face <code>datasets</code> library to load the dataset and convert it into a list of <code>Document</code> objects from the <code>llama_index.core.schema</code> module.",c,M,p;return M=new W({props:{code:"aW1wb3J0JTIwZGF0YXNldHMlMEFmcm9tJTIwbGxhbWFfaW5kZXguY29yZS5zY2hlbWElMjBpbXBvcnQlMjBEb2N1bWVudCUwQSUwQSUyMyUyMExvYWQlMjB0aGUlMjBkYXRhc2V0JTBBZ3Vlc3RfZGF0YXNldCUyMCUzRCUyMGRhdGFzZXRzLmxvYWRfZGF0YXNldCglMjJhZ2VudHMtY291cnNlJTJGdW5pdDMtaW52aXRlZXMlMjIlMkMlMjBzcGxpdCUzRCUyMnRyYWluJTIyKSUwQSUwQSUyMyUyMENvbnZlcnQlMjBkYXRhc2V0JTIwZW50cmllcyUyMGludG8lMjBEb2N1bWVudCUyMG9iamVjdHMlMEFkb2NzJTIwJTNEJTIwJTVCJTBBJTIwJTIwJTIwJTIwRG9jdW1lbnQoJTBBJTIwJTIwJTIwJTIwJTIwJTIwJTIwJTIwdGV4dCUzRCUyMiU1Q24lMjIuam9pbiglNUIlMEElMjAlMjAlMjAlMjAlMjAlMjAlMjAlMjAlMjAlMjAlMjAlMjBmJTIyTmFtZSUzQSUyMCU3Qmd1ZXN0X2RhdGFzZXQlNUInbmFtZSclNUQlNUJpJTVEJTdEJTIyJTJDJTBBJTIwJTIwJTIwJTIwJTIwJTIwJTIwJTIwJTIwJTIwJTIwJTIwZiUyMlJlbGF0aW9uJTNBJTIwJTdCZ3Vlc3RfZGF0YXNldCU1QidyZWxhdGlvbiclNUQlNUJpJTVEJTdEJTIyJTJDJTBBJTIwJTIwJTIwJTIwJTIwJTIwJTIwJTIwJTIwJTIwJTIwJTIwZiUyMkRlc2NyaXB0aW9uJTNBJTIwJTdCZ3Vlc3RfZGF0YXNldCU1QidkZXNjcmlwdGlvbiclNUQlNUJpJTVEJTdEJTIyJTJDJTBBJTIwJTIwJTIwJTIwJTIwJTIwJTIwJTIwJTIwJTIwJTIwJTIwZiUyMkVtYWlsJTNBJTIwJTdCZ3Vlc3RfZGF0YXNldCU1QidlbWFpbCclNUQlNUJpJTVEJTdEJTIyJTBBJTIwJTIwJTIwJTIwJTIwJTIwJTIwJTIwJTVEKSUyQyUwQSUyMCUyMCUyMCUyMCUyMCUyMCUyMCUyMG1ldGFkYXRhJTNEJTdCJTIybmFtZSUyMiUzQSUyMGd1ZXN0X2RhdGFzZXQlNUInbmFtZSclNUQlNUJpJTVEJTdEJTBBJTIwJTIwJTIwJTIwKSUwQSUyMCUyMCUyMCUyMGZvciUyMGklMjBpbiUyMHJhbmdlKGxlbihndWVzdF9kYXRhc2V0KSklMEElNUQ=",highlighted:`<span class="hljs-keyword">import</span> datasets
<span class="hljs-keyword">from</span> llama_index.core.schema <span class="hljs-keyword">import</span> Document

<span class="hljs-comment"># Load the dataset</span>
guest_dataset = datasets.load_dataset(<span class="hljs-string">&quot;agents-course/unit3-invitees&quot;</span>, split=<span class="hljs-string">&quot;train&quot;</span>)

<span class="hljs-comment"># Convert dataset entries into Document objects</span>
docs = [
    Document(
        text=<span class="hljs-string">&quot;\\n&quot;</span>.join([
            <span class="hljs-string">f&quot;Name: <span class="hljs-subst">{guest_dataset[<span class="hljs-string">&#x27;name&#x27;</span>][i]}</span>&quot;</span>,
            <span class="hljs-string">f&quot;Relation: <span class="hljs-subst">{guest_dataset[<span class="hljs-string">&#x27;relation&#x27;</span>][i]}</span>&quot;</span>,
            <span class="hljs-string">f&quot;Description: <span class="hljs-subst">{guest_dataset[<span class="hljs-string">&#x27;description&#x27;</span>][i]}</span>&quot;</span>,
            <span class="hljs-string">f&quot;Email: <span class="hljs-subst">{guest_dataset[<span class="hljs-string">&#x27;email&#x27;</span>][i]}</span>&quot;</span>
        ]),
        metadata={<span class="hljs-string">&quot;name&quot;</span>: guest_dataset[<span class="hljs-string">&#x27;name&#x27;</span>][i]}
    )
    <span class="hljs-keyword">for</span> i <span class="hljs-keyword">in</span> <span class="hljs-built_in">range</span>(<span class="hljs-built_in">len</span>(guest_dataset))
]`,wrap:!1}}),{c(){a=T("p"),a.innerHTML=u,c=d(),U(M.$$.fragment)},l(o){a=h(o,"P",{"data-svelte-h":!0}),y(a)!=="svelte-ag3ykm"&&(a.innerHTML=u),c=m(o),I(M.$$.fragment,o)},m(o,n){l(o,a,n),l(o,c,n),g(M,o,n),p=!0},p:_,i(o){p||(b(M.$$.fragment,o),p=!0)},o(o){Z(M.$$.fragment,o),p=!1},d(o){o&&(s(a),s(c)),$(M,o)}}}function cs(C){let a,u="We will use the Hugging Face <code>datasets</code> library to load the dataset and convert it into a list of <code>Document</code> objects from the <code>langchain.docstore.document</code> module.",c,M,p;return M=new W({props:{code:"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",highlighted:`<span class="hljs-keyword">import</span> datasets
<span class="hljs-keyword">from</span> langchain_core.documents <span class="hljs-keyword">import</span> Document

<span class="hljs-comment"># Load the dataset</span>
guest_dataset = datasets.load_dataset(<span class="hljs-string">&quot;agents-course/unit3-invitees&quot;</span>, split=<span class="hljs-string">&quot;train&quot;</span>)

<span class="hljs-comment"># Convert dataset entries into Document objects</span>
docs = [
    Document(
        page_content=<span class="hljs-string">&quot;\\n&quot;</span>.join([
            <span class="hljs-string">f&quot;Name: <span class="hljs-subst">{guest[<span class="hljs-string">&#x27;name&#x27;</span>]}</span>&quot;</span>,
            <span class="hljs-string">f&quot;Relation: <span class="hljs-subst">{guest[<span class="hljs-string">&#x27;relation&#x27;</span>]}</span>&quot;</span>,
            <span class="hljs-string">f&quot;Description: <span class="hljs-subst">{guest[<span class="hljs-string">&#x27;description&#x27;</span>]}</span>&quot;</span>,
            <span class="hljs-string">f&quot;Email: <span class="hljs-subst">{guest[<span class="hljs-string">&#x27;email&#x27;</span>]}</span>&quot;</span>
        ]),
        metadata={<span class="hljs-string">&quot;name&quot;</span>: guest[<span class="hljs-string">&quot;name&quot;</span>]}
    )
    <span class="hljs-keyword">for</span> guest <span class="hljs-keyword">in</span> guest_dataset
]`,wrap:!1}}),{c(){a=T("p"),a.innerHTML=u,c=d(),U(M.$$.fragment)},l(o){a=h(o,"P",{"data-svelte-h":!0}),y(a)!=="svelte-1vrqwzz"&&(a.innerHTML=u),c=m(o),I(M.$$.fragment,o)},m(o,n){l(o,a,n),l(o,c,n),g(M,o,n),p=!0},p:_,i(o){p||(b(M.$$.fragment,o),p=!0)},o(o){Z(M.$$.fragment,o),p=!1},d(o){o&&(s(a),s(c)),$(M,o)}}}function Ms(C){let a,u,c,M,p,o;return a=new Q({props:{id:"agents-frameworks",option:"smolagents",$$slots:{default:[rs]},$$scope:{ctx:C}}}),c=new Q({props:{id:"agents-frameworks",option:"llama-index",$$slots:{default:[ps]},$$scope:{ctx:C}}}),p=new Q({props:{id:"agents-frameworks",option:"langgraph",$$slots:{default:[cs]},$$scope:{ctx:C}}}),{c(){U(a.$$.fragment),u=d(),U(c.$$.fragment),M=d(),U(p.$$.fragment)},l(n){I(a.$$.fragment,n),u=m(n),I(c.$$.fragment,n),M=m(n),I(p.$$.fragment,n)},m(n,i){g(a,n,i),l(n,u,i),g(c,n,i),l(n,M,i),g(p,n,i),o=!0},p(n,i){const f={};i&2&&(f.$$scope={dirty:i,ctx:n}),a.$set(f);const j={};i&2&&(j.$$scope={dirty:i,ctx:n}),c.$set(j);const w={};i&2&&(w.$$scope={dirty:i,ctx:n}),p.$set(w)},i(n){o||(b(a.$$.fragment,n),b(c.$$.fragment,n),b(p.$$.fragment,n),o=!0)},o(n){Z(a.$$.fragment,n),Z(c.$$.fragment,n),Z(p.$$.fragment,n),o=!1},d(n){n&&(s(u),s(M)),$(a,n),$(c,n),$(p,n)}}}function us(C){let a,u,c="BM25Retriever",M,p,o="sentence-transformers",n;return{c(){a=R("The "),u=T("code"),u.textContent=c,M=R(" is a great starting point for retrieval, but for more advanced semantic search, you might consider using embedding-based retrievers like those from "),p=T("a"),p.textContent=o,n=R("."),this.h()},l(i){a=x(i,"The "),u=h(i,"CODE",{"data-svelte-h":!0}),y(u)!=="svelte-13pi4gc"&&(u.textContent=c),M=x(i," is a great starting point for retrieval, but for more advanced semantic search, you might consider using embedding-based retrievers like those from "),p=h(i,"A",{href:!0,"data-svelte-h":!0}),y(p)!=="svelte-8vrx36"&&(p.textContent=o),n=x(i,"."),this.h()},h(){G(p,"href","https://www.sbert.net/")},m(i,f){l(i,a,f),l(i,u,f),l(i,M,f),l(i,p,f),l(i,n,f)},p:_,d(i){i&&(s(a),s(u),s(M),s(p),s(n))}}}function ds(C){let a,u="We will use the <code>BM25Retriever</code> from the <code>langchain_community.retrievers</code> module to create a retriever tool.",c,M,p,o,n,i,f="Let’s understand this tool step-by-step:",j,w,v="<li>The <code>name</code> and <code>description</code> help the agent understand when and how to use this tool</li> <li>The <code>inputs</code> define what parameters the tool expects (in this case, a search query)</li> <li>We’re using a <code>BM25Retriever</code>, which is a powerful text retrieval algorithm that doesn’t require embeddings</li> <li>The <code>forward</code> method processes the query and returns the most relevant guest information</li>",B;return M=new $e({props:{$$slots:{default:[us]},$$scope:{ctx:C}}}),o=new W({props:{code:"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",highlighted:`<span class="hljs-keyword">from</span> smolagents <span class="hljs-keyword">import</span> Tool
<span class="hljs-keyword">from</span> langchain_community.retrievers <span class="hljs-keyword">import</span> BM25Retriever

<span class="hljs-keyword">class</span> <span class="hljs-title class_">GuestInfoRetrieverTool</span>(<span class="hljs-title class_ inherited__">Tool</span>):
    name = <span class="hljs-string">&quot;guest_info_retriever&quot;</span>
    description = <span class="hljs-string">&quot;Retrieves detailed information about gala guests based on their name or relation.&quot;</span>
    inputs = {
        <span class="hljs-string">&quot;query&quot;</span>: {
            <span class="hljs-string">&quot;type&quot;</span>: <span class="hljs-string">&quot;string&quot;</span>,
            <span class="hljs-string">&quot;description&quot;</span>: <span class="hljs-string">&quot;The name or relation of the guest you want information about.&quot;</span>
        }
    }
    output_type = <span class="hljs-string">&quot;string&quot;</span>

    <span class="hljs-keyword">def</span> <span class="hljs-title function_">__init__</span>(<span class="hljs-params">self, docs</span>):
        self.is_initialized = <span class="hljs-literal">False</span>
        self.retriever = BM25Retriever.from_documents(docs)

    <span class="hljs-keyword">def</span> <span class="hljs-title function_">forward</span>(<span class="hljs-params">self, query: <span class="hljs-built_in">str</span></span>):
        results = self.retriever.get_relevant_documents(query)
        <span class="hljs-keyword">if</span> results:
            <span class="hljs-keyword">return</span> <span class="hljs-string">&quot;\\n\\n&quot;</span>.join([doc.page_content <span class="hljs-keyword">for</span> doc <span class="hljs-keyword">in</span> results[:<span class="hljs-number">3</span>]])
        <span class="hljs-keyword">else</span>:
            <span class="hljs-keyword">return</span> <span class="hljs-string">&quot;No matching guest information found.&quot;</span>

<span class="hljs-comment"># Initialize the tool</span>
guest_info_tool = GuestInfoRetrieverTool(docs)`,wrap:!1}}),{c(){a=T("p"),a.innerHTML=u,c=d(),U(M.$$.fragment),p=d(),U(o.$$.fragment),n=d(),i=T("p"),i.textContent=f,j=d(),w=T("ul"),w.innerHTML=v},l(t){a=h(t,"P",{"data-svelte-h":!0}),y(a)!=="svelte-1weris3"&&(a.innerHTML=u),c=m(t),I(M.$$.fragment,t),p=m(t),I(o.$$.fragment,t),n=m(t),i=h(t,"P",{"data-svelte-h":!0}),y(i)!=="svelte-xficc2"&&(i.textContent=f),j=m(t),w=h(t,"UL",{"data-svelte-h":!0}),y(w)!=="svelte-14ztz3k"&&(w.innerHTML=v)},m(t,J){l(t,a,J),l(t,c,J),g(M,t,J),l(t,p,J),g(o,t,J),l(t,n,J),l(t,i,J),l(t,j,J),l(t,w,J),B=!0},p(t,J){const k={};J&2&&(k.$$scope={dirty:J,ctx:t}),M.$set(k)},i(t){B||(b(M.$$.fragment,t),b(o.$$.fragment,t),B=!0)},o(t){Z(M.$$.fragment,t),Z(o.$$.fragment,t),B=!1},d(t){t&&(s(a),s(c),s(p),s(n),s(i),s(j),s(w)),$(M,t),$(o,t)}}}function ms(C){let a,u,c="BM25Retriever",M,p,o="sentence-transformers",n;return{c(){a=R("The "),u=T("code"),u.textContent=c,M=R(" is a great starting point for retrieval, but for more advanced semantic search, you might consider using embedding-based retrievers like those from "),p=T("a"),p.textContent=o,n=R("."),this.h()},l(i){a=x(i,"The "),u=h(i,"CODE",{"data-svelte-h":!0}),y(u)!=="svelte-13pi4gc"&&(u.textContent=c),M=x(i," is a great starting point for retrieval, but for more advanced semantic search, you might consider using embedding-based retrievers like those from "),p=h(i,"A",{href:!0,"data-svelte-h":!0}),y(p)!=="svelte-8vrx36"&&(p.textContent=o),n=x(i,"."),this.h()},h(){G(p,"href","https://www.sbert.net/")},m(i,f){l(i,a,f),l(i,u,f),l(i,M,f),l(i,p,f),l(i,n,f)},p:_,d(i){i&&(s(a),s(u),s(M),s(p),s(n))}}}function Js(C){let a,u="We will use the <code>BM25Retriever</code> from the <code>llama_index.retrievers.bm25</code> module to create a retriever tool.",c,M,p,o,n,i,f="Let’s understand this tool step-by-step.",j,w,v="<li>The docstring helps the agent understand when and how to use this tool</li> <li>The type decorators define what parameters the tool expects (in this case, a search query)</li> <li>We’re using a <code>BM25Retriever</code>, which is a powerful text retrieval algorithm that doesn’t require embeddings</li> <li>The method processes the query and returns the most relevant guest information</li>",B;return M=new $e({props:{$$slots:{default:[ms]},$$scope:{ctx:C}}}),o=new W({props:{code:"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",highlighted:`<span class="hljs-keyword">from</span> llama_index.core.tools <span class="hljs-keyword">import</span> FunctionTool
<span class="hljs-keyword">from</span> llama_index.retrievers.bm25 <span class="hljs-keyword">import</span> BM25Retriever

bm25_retriever = BM25Retriever.from_defaults(nodes=docs)

<span class="hljs-keyword">def</span> <span class="hljs-title function_">get_guest_info_retriever</span>(<span class="hljs-params">query: <span class="hljs-built_in">str</span></span>) -&gt; <span class="hljs-built_in">str</span>:
    <span class="hljs-string">&quot;&quot;&quot;Retrieves detailed information about gala guests based on their name or relation.&quot;&quot;&quot;</span>
    results = bm25_retriever.retrieve(query)
    <span class="hljs-keyword">if</span> results:
        <span class="hljs-keyword">return</span> <span class="hljs-string">&quot;\\n\\n&quot;</span>.join([doc.text <span class="hljs-keyword">for</span> doc <span class="hljs-keyword">in</span> results[:<span class="hljs-number">3</span>]])
    <span class="hljs-keyword">else</span>:
        <span class="hljs-keyword">return</span> <span class="hljs-string">&quot;No matching guest information found.&quot;</span>

<span class="hljs-comment"># Initialize the tool</span>
guest_info_tool = FunctionTool.from_defaults(get_guest_info_retriever)`,wrap:!1}}),{c(){a=T("p"),a.innerHTML=u,c=d(),U(M.$$.fragment),p=d(),U(o.$$.fragment),n=d(),i=T("p"),i.textContent=f,j=d(),w=T("ul"),w.innerHTML=v},l(t){a=h(t,"P",{"data-svelte-h":!0}),y(a)!=="svelte-1li0cac"&&(a.innerHTML=u),c=m(t),I(M.$$.fragment,t),p=m(t),I(o.$$.fragment,t),n=m(t),i=h(t,"P",{"data-svelte-h":!0}),y(i)!=="svelte-5xdv72"&&(i.textContent=f),j=m(t),w=h(t,"UL",{"data-svelte-h":!0}),y(w)!=="svelte-1grz3gg"&&(w.innerHTML=v)},m(t,J){l(t,a,J),l(t,c,J),g(M,t,J),l(t,p,J),g(o,t,J),l(t,n,J),l(t,i,J),l(t,j,J),l(t,w,J),B=!0},p(t,J){const k={};J&2&&(k.$$scope={dirty:J,ctx:t}),M.$set(k)},i(t){B||(b(M.$$.fragment,t),b(o.$$.fragment,t),B=!0)},o(t){Z(M.$$.fragment,t),Z(o.$$.fragment,t),B=!1},d(t){t&&(s(a),s(c),s(p),s(n),s(i),s(j),s(w)),$(M,t),$(o,t)}}}function ws(C){let a,u,c="BM25Retriever",M,p,o="sentence-transformers",n;return{c(){a=R("The "),u=T("code"),u.textContent=c,M=R(" is a great starting point for retrieval, but for more advanced semantic search, you might consider using embedding-based retrievers like those from "),p=T("a"),p.textContent=o,n=R("."),this.h()},l(i){a=x(i,"The "),u=h(i,"CODE",{"data-svelte-h":!0}),y(u)!=="svelte-13pi4gc"&&(u.textContent=c),M=x(i," is a great starting point for retrieval, but for more advanced semantic search, you might consider using embedding-based retrievers like those from "),p=h(i,"A",{href:!0,"data-svelte-h":!0}),y(p)!=="svelte-8vrx36"&&(p.textContent=o),n=x(i,"."),this.h()},h(){G(p,"href","https://www.sbert.net/")},m(i,f){l(i,a,f),l(i,u,f),l(i,M,f),l(i,p,f),l(i,n,f)},p:_,d(i){i&&(s(a),s(u),s(M),s(p),s(n))}}}function Ts(C){let a,u="We will use the <code>BM25Retriever</code> from the <code>langchain_community.retrievers</code> module to create a retriever tool.",c,M,p,o,n,i,f="Let’s understand this tool step-by-step.",j,w,v="<li>The <code>name</code> and <code>description</code> help the agent understand when and how to use this tool</li> <li>The type decorators define what parameters the tool expects (in this case, a search query)</li> <li>We’re using a <code>BM25Retriever</code>, which is a powerful text retrieval algorithm that doesn’t require embeddings</li> <li>The method processes the query and returns the most relevant guest information</li>",B;return M=new $e({props:{$$slots:{default:[ws]},$$scope:{ctx:C}}}),o=new W({props:{code:"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",highlighted:`<span class="hljs-keyword">from</span> langchain_community.retrievers <span class="hljs-keyword">import</span> BM25Retriever
<span class="hljs-keyword">from</span> langchain.tools <span class="hljs-keyword">import</span> Tool

bm25_retriever = BM25Retriever.from_documents(docs)

<span class="hljs-keyword">def</span> <span class="hljs-title function_">extract_text</span>(<span class="hljs-params">query: <span class="hljs-built_in">str</span></span>) -&gt; <span class="hljs-built_in">str</span>:
    <span class="hljs-string">&quot;&quot;&quot;Retrieves detailed information about gala guests based on their name or relation.&quot;&quot;&quot;</span>
    results = bm25_retriever.invoke(query)
    <span class="hljs-keyword">if</span> results:
        <span class="hljs-keyword">return</span> <span class="hljs-string">&quot;\\n\\n&quot;</span>.join([doc.page_content <span class="hljs-keyword">for</span> doc <span class="hljs-keyword">in</span> results[:<span class="hljs-number">3</span>]])
    <span class="hljs-keyword">else</span>:
        <span class="hljs-keyword">return</span> <span class="hljs-string">&quot;No matching guest information found.&quot;</span>

guest_info_tool = Tool(
    name=<span class="hljs-string">&quot;guest_info_retriever&quot;</span>,
    func=extract_text,
    description=<span class="hljs-string">&quot;Retrieves detailed information about gala guests based on their name or relation.&quot;</span>
)`,wrap:!1}}),{c(){a=T("p"),a.innerHTML=u,c=d(),U(M.$$.fragment),p=d(),U(o.$$.fragment),n=d(),i=T("p"),i.textContent=f,j=d(),w=T("ul"),w.innerHTML=v},l(t){a=h(t,"P",{"data-svelte-h":!0}),y(a)!=="svelte-1weris3"&&(a.innerHTML=u),c=m(t),I(M.$$.fragment,t),p=m(t),I(o.$$.fragment,t),n=m(t),i=h(t,"P",{"data-svelte-h":!0}),y(i)!=="svelte-5xdv72"&&(i.textContent=f),j=m(t),w=h(t,"UL",{"data-svelte-h":!0}),y(w)!=="svelte-95yww2"&&(w.innerHTML=v)},m(t,J){l(t,a,J),l(t,c,J),g(M,t,J),l(t,p,J),g(o,t,J),l(t,n,J),l(t,i,J),l(t,j,J),l(t,w,J),B=!0},p(t,J){const k={};J&2&&(k.$$scope={dirty:J,ctx:t}),M.$set(k)},i(t){B||(b(M.$$.fragment,t),b(o.$$.fragment,t),B=!0)},o(t){Z(M.$$.fragment,t),Z(o.$$.fragment,t),B=!1},d(t){t&&(s(a),s(c),s(p),s(n),s(i),s(j),s(w)),$(M,t),$(o,t)}}}function hs(C){let a,u,c,M,p,o;return a=new Q({props:{id:"agents-frameworks",option:"smolagents",$$slots:{default:[ds]},$$scope:{ctx:C}}}),c=new Q({props:{id:"agents-frameworks",option:"llama-index",$$slots:{default:[Js]},$$scope:{ctx:C}}}),p=new Q({props:{id:"agents-frameworks",option:"langgraph",$$slots:{default:[Ts]},$$scope:{ctx:C}}}),{c(){U(a.$$.fragment),u=d(),U(c.$$.fragment),M=d(),U(p.$$.fragment)},l(n){I(a.$$.fragment,n),u=m(n),I(c.$$.fragment,n),M=m(n),I(p.$$.fragment,n)},m(n,i){g(a,n,i),l(n,u,i),g(c,n,i),l(n,M,i),g(p,n,i),o=!0},p(n,i){const f={};i&2&&(f.$$scope={dirty:i,ctx:n}),a.$set(f);const j={};i&2&&(j.$$scope={dirty:i,ctx:n}),c.$set(j);const w={};i&2&&(w.$$scope={dirty:i,ctx:n}),p.$set(w)},i(n){o||(b(a.$$.fragment,n),b(c.$$.fragment,n),b(p.$$.fragment,n),o=!0)},o(n){Z(a.$$.fragment,n),Z(c.$$.fragment,n),Z(p.$$.fragment,n),o=!1},d(n){n&&(s(u),s(M)),$(a,n),$(c,n),$(p,n)}}}function ys(C){let a,u,c,M="Expected output:",p,o,n,i,f="What’s happening in this final step:",j,w,v="<li>We initialize a Hugging Face model using the <code>InferenceClientModel</code> class</li> <li>We create our agent (Alfred) as a <code>CodeAgent</code>, which can execute Python code to solve problems</li> <li>We ask Alfred to retrieve information about a guest named “Lady Ada Lovelace”</li>",B;return a=new W({props:{code:"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",highlighted:`<span class="hljs-keyword">from</span> smolagents <span class="hljs-keyword">import</span> CodeAgent, InferenceClientModel

<span class="hljs-comment"># Initialize the Hugging Face model</span>
model = InferenceClientModel()

<span class="hljs-comment"># Create Alfred, our gala agent, with the guest info tool</span>
alfred = CodeAgent(tools=[guest_info_tool], model=model)

<span class="hljs-comment"># Example query Alfred might receive during the gala</span>
response = alfred.run(<span class="hljs-string">&quot;Tell me about our guest named &#x27;Lady Ada Lovelace&#x27;.&quot;</span>)

<span class="hljs-built_in">print</span>(<span class="hljs-string">&quot;🎩 Alfred&#x27;s Response:&quot;</span>)
<span class="hljs-built_in">print</span>(response)`,wrap:!1}}),o=new W({props:{code:"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",highlighted:`🎩 Alfred<span class="hljs-comment">&#x27;s Response:</span>
Based <span class="hljs-keyword">on</span> the information I retrieved, Lady Ada Lovelace <span class="hljs-built_in">is</span> an esteemed mathematician <span class="hljs-built_in">and</span> <span class="hljs-keyword">friend</span>. She <span class="hljs-built_in">is</span> renowned <span class="hljs-keyword">for</span> her pioneering work <span class="hljs-keyword">in</span> mathematics <span class="hljs-built_in">and</span> computing, often celebrated <span class="hljs-keyword">as</span> the first computer programmer due <span class="hljs-keyword">to</span> her work <span class="hljs-keyword">on</span> Charles Babbage<span class="hljs-comment">&#x27;s Analytical Engine. Her email address is ada.lovelace@example.com.</span>`,wrap:!1}}),{c(){U(a.$$.fragment),u=d(),c=T("p"),c.textContent=M,p=d(),U(o.$$.fragment),n=d(),i=T("p"),i.textContent=f,j=d(),w=T("ul"),w.innerHTML=v},l(t){I(a.$$.fragment,t),u=m(t),c=h(t,"P",{"data-svelte-h":!0}),y(c)!=="svelte-15t3xg7"&&(c.textContent=M),p=m(t),I(o.$$.fragment,t),n=m(t),i=h(t,"P",{"data-svelte-h":!0}),y(i)!=="svelte-18avn85"&&(i.textContent=f),j=m(t),w=h(t,"UL",{"data-svelte-h":!0}),y(w)!=="svelte-1mwulne"&&(w.innerHTML=v)},m(t,J){g(a,t,J),l(t,u,J),l(t,c,J),l(t,p,J),g(o,t,J),l(t,n,J),l(t,i,J),l(t,j,J),l(t,w,J),B=!0},p:_,i(t){B||(b(a.$$.fragment,t),b(o.$$.fragment,t),B=!0)},o(t){Z(a.$$.fragment,t),Z(o.$$.fragment,t),B=!1},d(t){t&&(s(u),s(c),s(p),s(n),s(i),s(j),s(w)),$(a,t),$(o,t)}}}function fs(C){let a,u,c,M="Expected output:",p,o,n,i,f="What’s happening in this final step:",j,w,v="<li>We initialize a Hugging Face model using the <code>HuggingFaceInferenceAPI</code> class</li> <li>We create our agent (Alfred) as a <code>AgentWorkflow</code>, including the tool we just created</li> <li>We ask Alfred to retrieve information about a guest named “Lady Ada Lovelace”</li>",B;return a=new W({props:{code:"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",highlighted:`<span class="hljs-keyword">from</span> llama_index.core.agent.workflow <span class="hljs-keyword">import</span> AgentWorkflow
<span class="hljs-keyword">from</span> llama_index.llms.huggingface_api <span class="hljs-keyword">import</span> HuggingFaceInferenceAPI

<span class="hljs-comment"># Initialize the Hugging Face model</span>
llm = HuggingFaceInferenceAPI(model_name=<span class="hljs-string">&quot;Qwen/Qwen2.5-Coder-32B-Instruct&quot;</span>)

<span class="hljs-comment"># Create Alfred, our gala agent, with the guest info tool</span>
alfred = AgentWorkflow.from_tools_or_functions(
    [guest_info_tool],
    llm=llm,
)

<span class="hljs-comment"># Example query Alfred might receive during the gala</span>
response = <span class="hljs-keyword">await</span> alfred.run(<span class="hljs-string">&quot;Tell me about our guest named &#x27;Lady Ada Lovelace&#x27;.&quot;</span>)

<span class="hljs-built_in">print</span>(<span class="hljs-string">&quot;🎩 Alfred&#x27;s Response:&quot;</span>)
<span class="hljs-built_in">print</span>(response)`,wrap:!1}}),o=new W({props:{code:"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",highlighted:`🎩 Alfred<span class="hljs-comment">&#x27;s Response:</span>
Lady Ada Lovelace <span class="hljs-built_in">is</span> an esteemed mathematician <span class="hljs-built_in">and</span> <span class="hljs-keyword">friend</span>, renowned <span class="hljs-keyword">for</span> her pioneering work <span class="hljs-keyword">in</span> mathematics <span class="hljs-built_in">and</span> computing. She <span class="hljs-built_in">is</span> celebrated <span class="hljs-keyword">as</span> the first computer programmer due <span class="hljs-keyword">to</span> her work <span class="hljs-keyword">on</span> Charles Babbage<span class="hljs-comment">&#x27;s Analytical Engine. Her email is ada.lovelace@example.com.</span>`,wrap:!1}}),{c(){U(a.$$.fragment),u=d(),c=T("p"),c.textContent=M,p=d(),U(o.$$.fragment),n=d(),i=T("p"),i.textContent=f,j=d(),w=T("ul"),w.innerHTML=v},l(t){I(a.$$.fragment,t),u=m(t),c=h(t,"P",{"data-svelte-h":!0}),y(c)!=="svelte-15t3xg7"&&(c.textContent=M),p=m(t),I(o.$$.fragment,t),n=m(t),i=h(t,"P",{"data-svelte-h":!0}),y(i)!=="svelte-18avn85"&&(i.textContent=f),j=m(t),w=h(t,"UL",{"data-svelte-h":!0}),y(w)!=="svelte-1xe3pcb"&&(w.innerHTML=v)},m(t,J){g(a,t,J),l(t,u,J),l(t,c,J),l(t,p,J),g(o,t,J),l(t,n,J),l(t,i,J),l(t,j,J),l(t,w,J),B=!0},p:_,i(t){B||(b(a.$$.fragment,t),b(o.$$.fragment,t),B=!0)},o(t){Z(a.$$.fragment,t),Z(o.$$.fragment,t),B=!1},d(t){t&&(s(u),s(c),s(p),s(n),s(i),s(j),s(w)),$(a,t),$(o,t)}}}function js(C){let a,u,c,M="Expected output:",p,o,n,i,f="What’s happening in this final step:",j,w,v="<li>We initialize a Hugging Face model using the <code>HuggingFaceEndpoint</code> class. We also generate a chat interface and append the tools.</li> <li>We create our agent (Alfred) as a <code>StateGraph</code>, that combines 2 nodes (<code>assistant</code>, <code>tools</code>) using an edge</li> <li>We ask Alfred to retrieve information about a guest named “Lady Ada Lovelace”</li>",B;return a=new W({props:{code:"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",highlighted:`<span class="hljs-keyword">from</span> typing <span class="hljs-keyword">import</span> TypedDict, Annotated
<span class="hljs-keyword">from</span> langgraph.graph.message <span class="hljs-keyword">import</span> add_messages
<span class="hljs-keyword">from</span> langchain_core.messages <span class="hljs-keyword">import</span> AnyMessage, HumanMessage, AIMessage
<span class="hljs-keyword">from</span> langgraph.prebuilt <span class="hljs-keyword">import</span> ToolNode
<span class="hljs-keyword">from</span> langgraph.graph <span class="hljs-keyword">import</span> START, StateGraph
<span class="hljs-keyword">from</span> langgraph.prebuilt <span class="hljs-keyword">import</span> tools_condition
<span class="hljs-keyword">from</span> langchain_huggingface <span class="hljs-keyword">import</span> HuggingFaceEndpoint, ChatHuggingFace

<span class="hljs-comment"># Generate the chat interface, including the tools</span>
llm = HuggingFaceEndpoint(
    repo_id=<span class="hljs-string">&quot;Qwen/Qwen2.5-Coder-32B-Instruct&quot;</span>,
    huggingfacehub_api_token=HUGGINGFACEHUB_API_TOKEN,
)

chat = ChatHuggingFace(llm=llm, verbose=<span class="hljs-literal">True</span>)
tools = [guest_info_tool]
chat_with_tools = chat.bind_tools(tools)

<span class="hljs-comment"># Generate the AgentState and Agent graph</span>
<span class="hljs-keyword">class</span> <span class="hljs-title class_">AgentState</span>(<span class="hljs-title class_ inherited__">TypedDict</span>):
    messages: Annotated[<span class="hljs-built_in">list</span>[AnyMessage], add_messages]

<span class="hljs-keyword">def</span> <span class="hljs-title function_">assistant</span>(<span class="hljs-params">state: AgentState</span>):
    <span class="hljs-keyword">return</span> {
        <span class="hljs-string">&quot;messages&quot;</span>: [chat_with_tools.invoke(state[<span class="hljs-string">&quot;messages&quot;</span>])],
    }

<span class="hljs-comment">## The graph</span>
builder = StateGraph(AgentState)

<span class="hljs-comment"># Define nodes: these do the work</span>
builder.add_node(<span class="hljs-string">&quot;assistant&quot;</span>, assistant)
builder.add_node(<span class="hljs-string">&quot;tools&quot;</span>, ToolNode(tools))

<span class="hljs-comment"># Define edges: these determine how the control flow moves</span>
builder.add_edge(START, <span class="hljs-string">&quot;assistant&quot;</span>)
builder.add_conditional_edges(
    <span class="hljs-string">&quot;assistant&quot;</span>,
    <span class="hljs-comment"># If the latest message requires a tool, route to tools</span>
    <span class="hljs-comment"># Otherwise, provide a direct response</span>
    tools_condition,
)
builder.add_edge(<span class="hljs-string">&quot;tools&quot;</span>, <span class="hljs-string">&quot;assistant&quot;</span>)
alfred = builder.<span class="hljs-built_in">compile</span>()

messages = [HumanMessage(content=<span class="hljs-string">&quot;Tell me about our guest named &#x27;Lady Ada Lovelace&#x27;.&quot;</span>)]
response = alfred.invoke({<span class="hljs-string">&quot;messages&quot;</span>: messages})

<span class="hljs-built_in">print</span>(<span class="hljs-string">&quot;🎩 Alfred&#x27;s Response:&quot;</span>)
<span class="hljs-built_in">print</span>(response[<span class="hljs-string">&#x27;messages&#x27;</span>][-<span class="hljs-number">1</span>].content)`,wrap:!1}}),o=new W({props:{code:"JUYwJTlGJThFJUE5JTIwQWxmcmVkJ3MlMjBSZXNwb25zZSUzQSUwQUxhZHklMjBBZGElMjBMb3ZlbGFjZSUyMGlzJTIwYW4lMjBlc3RlZW1lZCUyMG1hdGhlbWF0aWNpYW4lMjBhbmQlMjBwaW9uZWVyJTIwaW4lMjBjb21wdXRpbmclMkMlMjBvZnRlbiUyMGNlbGVicmF0ZWQlMjBhcyUyMHRoZSUyMGZpcnN0JTIwY29tcHV0ZXIlMjBwcm9ncmFtbWVyJTIwZHVlJTIwdG8lMjBoZXIlMjB3b3JrJTIwb24lMjBDaGFybGVzJTIwQmFiYmFnZSdzJTIwQW5hbHl0aWNhbCUyMEVuZ2luZS4=",highlighted:`🎩 Alfred<span class="hljs-comment">&#x27;s Response:</span>
Lady Ada Lovelace <span class="hljs-built_in">is</span> an esteemed mathematician <span class="hljs-built_in">and</span> pioneer <span class="hljs-keyword">in</span> computing, often celebrated <span class="hljs-keyword">as</span> the first computer programmer due <span class="hljs-keyword">to</span> her work <span class="hljs-keyword">on</span> Charles Babbage<span class="hljs-comment">&#x27;s Analytical Engine.</span>`,wrap:!1}}),{c(){U(a.$$.fragment),u=d(),c=T("p"),c.textContent=M,p=d(),U(o.$$.fragment),n=d(),i=T("p"),i.textContent=f,j=d(),w=T("ul"),w.innerHTML=v},l(t){I(a.$$.fragment,t),u=m(t),c=h(t,"P",{"data-svelte-h":!0}),y(c)!=="svelte-15t3xg7"&&(c.textContent=M),p=m(t),I(o.$$.fragment,t),n=m(t),i=h(t,"P",{"data-svelte-h":!0}),y(i)!=="svelte-18avn85"&&(i.textContent=f),j=m(t),w=h(t,"UL",{"data-svelte-h":!0}),y(w)!=="svelte-1gzv19f"&&(w.innerHTML=v)},m(t,J){g(a,t,J),l(t,u,J),l(t,c,J),l(t,p,J),g(o,t,J),l(t,n,J),l(t,i,J),l(t,j,J),l(t,w,J),B=!0},p:_,i(t){B||(b(a.$$.fragment,t),b(o.$$.fragment,t),B=!0)},o(t){Z(a.$$.fragment,t),Z(o.$$.fragment,t),B=!1},d(t){t&&(s(u),s(c),s(p),s(n),s(i),s(j),s(w)),$(a,t),$(o,t)}}}function Us(C){let a,u,c,M,p,o;return a=new Q({props:{id:"agents-frameworks",option:"smolagents",$$slots:{default:[ys]},$$scope:{ctx:C}}}),c=new Q({props:{id:"agents-frameworks",option:"llama-index",$$slots:{default:[fs]},$$scope:{ctx:C}}}),p=new Q({props:{id:"agents-frameworks",option:"langgraph",$$slots:{default:[js]},$$scope:{ctx:C}}}),{c(){U(a.$$.fragment),u=d(),U(c.$$.fragment),M=d(),U(p.$$.fragment)},l(n){I(a.$$.fragment,n),u=m(n),I(c.$$.fragment,n),M=m(n),I(p.$$.fragment,n)},m(n,i){g(a,n,i),l(n,u,i),g(c,n,i),l(n,M,i),g(p,n,i),o=!0},p(n,i){const f={};i&2&&(f.$$scope={dirty:i,ctx:n}),a.$set(f);const j={};i&2&&(j.$$scope={dirty:i,ctx:n}),c.$set(j);const w={};i&2&&(w.$$scope={dirty:i,ctx:n}),p.$set(w)},i(n){o||(b(a.$$.fragment,n),b(c.$$.fragment,n),b(p.$$.fragment,n),o=!0)},o(n){Z(a.$$.fragment,n),Z(c.$$.fragment,n),Z(p.$$.fragment,n),o=!1},d(n){n&&(s(u),s(M)),$(a,n),$(c,n),$(p,n)}}}function Is(C){let a,u,c="When you’re done, implement your guest retriever tool in the <code>retriever.py</code> file.";return{c(){a=R(`Try extending the retriever tool to also return conversation starters based on each guest's interests or background. How would you modify the tool to accomplish this?
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By combining a retrieval system with an LLM, Alfred can access accurate, up-to-date information about your guests on demand.",ve,N,Ge,q,We,L,Ut="In this unit, we’ll develop our agent within a HF Space, as a structured Python project. This approach helps us maintain clean, modular code by organizing different functionalities into separate files.  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    <span class="hljs-attr">&quot;name&quot;</span><span class="hljs-punctuation">:</span> <span class="hljs-string">&quot;Dr. Nikola Tesla&quot;</span><span class="hljs-punctuation">,</span>
    <span class="hljs-attr">&quot;relation&quot;</span><span class="hljs-punctuation">:</span> <span class="hljs-string">&quot;old friend from university days&quot;</span><span class="hljs-punctuation">,</span>  
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    <span class="hljs-attr">&quot;email&quot;</span><span class="hljs-punctuation">:</span> <span class="hljs-string">&quot;nikola.tesla@gmail.com&quot;</span>
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