diff --git a/404.html b/404.html index b85d5d84..ad72b9ac 100644 --- a/404.html +++ b/404.html @@ -7,7 +7,7 @@ - + diff --git a/assets/js/86a88343.24b0994d.js b/assets/js/86a88343.24b0994d.js deleted file mode 100644 index a047de07..00000000 --- a/assets/js/86a88343.24b0994d.js +++ /dev/null @@ -1 +0,0 @@ -"use strict";(self.webpackChunkai_rag_lab=self.webpackChunkai_rag_lab||[]).push([[186],{6742:(e,n,t)=>{t.r(n),t.d(n,{assets:()=>d,contentTitle:()=>c,default:()=>l,frontMatter:()=>o,metadata:()=>s,toc:()=>a});var r=t(4848),i=t(8453);const o={},c="\ud83e\uddb9 Combine pre-filtering with vector search",s={id:"perform-semantic-search/pre-filtering",title:"\ud83e\uddb9 Combine pre-filtering with vector search",description:"Pre-filtering a technique to optimize vector search by only considering documents that match certain criteria during vector search.",source:"@site/docs/60-perform-semantic-search/4-pre-filtering.mdx",sourceDirName:"60-perform-semantic-search",slug:"/perform-semantic-search/pre-filtering",permalink:"/ai-rag-lab/docs/perform-semantic-search/pre-filtering",draft:!1,unlisted:!1,editUrl:"https://github.com/mongodb-developer/ai-rag-lab/blob/main/docs/60-perform-semantic-search/4-pre-filtering.mdx",tags:[],version:"current",sidebarPosition:4,frontMatter:{},sidebar:"tutorialSidebar",previous:{title:"\ud83d\udc50 Perform semantic search",permalink:"/ai-rag-lab/docs/perform-semantic-search/vector-search"},next:{title:"Build the RAG Application",permalink:"/ai-rag-lab/docs/category/build-the-rag-application"}},d={},a=[{value:"Filter for documents where the content type is Video",id:"filter-for-documents-where-the-content-type-is-video",level:2},{value:"Filter on documents which have been updated on or after 2024-05-19 and where the content type is Tutorial",id:"filter-on-documents-which-have-been-updated-on-or-after-2024-05-19-and-where-the-content-type-is-tutorial",level:2}];function h(e){const n={code:"code",h1:"h1",h2:"h2",p:"p",pre:"pre",strong:"strong",...(0,i.R)(),...e.components},{Details:t}=n;return t||function(e,n){throw new Error("Expected "+(n?"component":"object")+" `"+e+"` to be defined: you likely forgot to import, pass, or provide it.")}("Details",!0),(0,r.jsxs)(r.Fragment,{children:[(0,r.jsx)(n.h1,{id:"-combine-pre-filtering-with-vector-search",children:"\ud83e\uddb9 Combine pre-filtering with vector search"}),"\n",(0,r.jsx)(n.p,{children:"Pre-filtering a technique to optimize vector search by only considering documents that match certain criteria during vector search."}),"\n",(0,r.jsxs)(n.h2,{id:"filter-for-documents-where-the-content-type-is-video",children:["Filter for documents where the content type is ",(0,r.jsx)(n.code,{children:"Video"})]}),"\n",(0,r.jsx)(n.p,{children:"To do this, you will first need to modify the vector search index you created previously. The new index definition should look as follows:"}),"\n",(0,r.jsxs)(t,{children:[(0,r.jsx)("summary",{children:"Answer"}),(0,r.jsx)("div",{children:(0,r.jsx)(n.pre,{children:(0,r.jsx)(n.code,{className:"language-python",children:'{\n "fields": [\n {\n "type": "vector",\n "path": "embedding",\n "numDimensions": 384,\n "similarity": "cosine"\n },\n {\n "type":"filter",\n "path":"metadata.contentType"\n }\n ]\n}\n'})})})]}),"\n",(0,r.jsxs)(n.p,{children:["Once you have updated the vector search index, fill in ",(0,r.jsx)(n.code,{children:""})," and run the cells under the ",(0,r.jsx)(n.strong,{children:"Filter for documents where the content type is Video"})," section in the notebook to see how the filter impacts the vector search results."]}),"\n",(0,r.jsx)(n.p,{children:"The answer for this code block is as follows:"}),"\n",(0,r.jsx)(n.p,{children:(0,r.jsx)(n.strong,{children:"CODE_BLOCK_11"})}),"\n",(0,r.jsxs)(t,{children:[(0,r.jsx)("summary",{children:"Answer"}),(0,r.jsx)("div",{children:(0,r.jsx)(n.pre,{children:(0,r.jsx)(n.code,{className:"language-python",children:'[\n {\n "$vectorSearch": {\n "index": "vector_index",\n "path": "embedding",\n "queryVector": query_embedding,\n "numCandidates": 150,\n "limit": 5,\n "filter": {"metadata.contentType": "Video"}\n }\n },\n {\n "$project": {\n "_id": 0,\n "body": 1,\n "score": {"$meta": "vectorSearchScore"}\n }\n }\n]\n'})})})]}),"\n",(0,r.jsxs)(n.h2,{id:"filter-on-documents-which-have-been-updated-on-or-after-2024-05-19-and-where-the-content-type-is-tutorial",children:["Filter on documents which have been updated on or after ",(0,r.jsx)(n.code,{children:"2024-05-19"})," and where the content type is ",(0,r.jsx)(n.code,{children:"Tutorial"})]}),"\n",(0,r.jsx)(n.p,{children:"Again, you will need to modify the vector search index. The new index definition should look as follows:"}),"\n",(0,r.jsxs)(t,{children:[(0,r.jsx)("summary",{children:"Answer"}),(0,r.jsx)("div",{children:(0,r.jsx)(n.pre,{children:(0,r.jsx)(n.code,{className:"language-python",children:'{\n "fields": [\n {\n "type": "vector",\n "path": "embedding",\n "numDimensions": 384,\n "similarity": "cosine"\n },\n {\n "type":"filter",\n "path":"metadata.contentType"\n },\n {\n "type":"filter",\n "path":"updated"\n }\n ]\n}\n'})})})]}),"\n",(0,r.jsxs)(n.p,{children:["Once you have updated the vector search index, fill in ",(0,r.jsx)(n.code,{children:""})," and run the cells under the ",(0,r.jsx)(n.strong,{children:"Filter on documents which have been updated on or after 2024-05-19 and where the content type is Tutorial"})," section in the notebook to see how the filter impacts the vector search results."]}),"\n",(0,r.jsx)(n.p,{children:"The answer for this code block is as follows:"}),"\n",(0,r.jsx)(n.p,{children:(0,r.jsx)(n.strong,{children:"CODE_BLOCK_12"})}),"\n",(0,r.jsxs)(t,{children:[(0,r.jsx)("summary",{children:"Answer"}),(0,r.jsx)("div",{children:(0,r.jsx)(n.pre,{children:(0,r.jsx)(n.code,{className:"language-python",children:'[\n {\n "$vectorSearch": {\n "index": "vector_index",\n "path": "embedding",\n "queryVector": query_embedding,\n "numCandidates": 150,\n "limit": 5,\n "filter": {\n "metadata.contentType": "Tutorial",\n "updated": {"$gte": "2024-05-19"}\n }\n }\n },\n {\n "$project": {\n "_id": 0,\n "body": 1,\n "score": {"$meta": "vectorSearchScore"}\n }\n }\n]\n'})})})]})]})}function l(e={}){const{wrapper:n}={...(0,i.R)(),...e.components};return n?(0,r.jsx)(n,{...e,children:(0,r.jsx)(h,{...e})}):h(e)}},8453:(e,n,t)=>{t.d(n,{R:()=>c,x:()=>s});var r=t(6540);const i={},o=r.createContext(i);function c(e){const n=r.useContext(o);return r.useMemo((function(){return"function"==typeof e?e(n):{...n,...e}}),[n,e])}function s(e){let n;return n=e.disableParentContext?"function"==typeof e.components?e.components(i):e.components||i:c(e.components),r.createElement(o.Provider,{value:n},e.children)}}}]); \ No newline at end of file diff --git a/assets/js/86a88343.be9144b8.js b/assets/js/86a88343.be9144b8.js new file mode 100644 index 00000000..5d3ca2ef --- /dev/null +++ b/assets/js/86a88343.be9144b8.js @@ -0,0 +1 @@ +"use strict";(self.webpackChunkai_rag_lab=self.webpackChunkai_rag_lab||[]).push([[186],{6742:(e,n,t)=>{t.r(n),t.d(n,{assets:()=>d,contentTitle:()=>c,default:()=>l,frontMatter:()=>o,metadata:()=>s,toc:()=>a});var r=t(4848),i=t(8453);const o={},c="\ud83e\uddb9 Combine pre-filtering with vector search",s={id:"perform-semantic-search/pre-filtering",title:"\ud83e\uddb9 Combine pre-filtering with vector search",description:"Pre-filtering is a technique to optimize vector search by only considering documents that match certain criteria during vector search.",source:"@site/docs/60-perform-semantic-search/4-pre-filtering.mdx",sourceDirName:"60-perform-semantic-search",slug:"/perform-semantic-search/pre-filtering",permalink:"/ai-rag-lab/docs/perform-semantic-search/pre-filtering",draft:!1,unlisted:!1,editUrl:"https://github.com/mongodb-developer/ai-rag-lab/blob/main/docs/60-perform-semantic-search/4-pre-filtering.mdx",tags:[],version:"current",sidebarPosition:4,frontMatter:{},sidebar:"tutorialSidebar",previous:{title:"\ud83d\udc50 Perform semantic search",permalink:"/ai-rag-lab/docs/perform-semantic-search/vector-search"},next:{title:"Build the RAG Application",permalink:"/ai-rag-lab/docs/category/build-the-rag-application"}},d={},a=[{value:"Filter for documents where the content type is Video",id:"filter-for-documents-where-the-content-type-is-video",level:2},{value:"Filter on documents which have been updated on or after 2024-05-19 and where the content type is Tutorial",id:"filter-on-documents-which-have-been-updated-on-or-after-2024-05-19-and-where-the-content-type-is-tutorial",level:2}];function h(e){const n={code:"code",h1:"h1",h2:"h2",li:"li",p:"p",pre:"pre",strong:"strong",ul:"ul",...(0,i.R)(),...e.components},{Details:t}=n;return t||function(e,n){throw new Error("Expected "+(n?"component":"object")+" `"+e+"` to be defined: you likely forgot to import, pass, or provide it.")}("Details",!0),(0,r.jsxs)(r.Fragment,{children:[(0,r.jsx)(n.h1,{id:"-combine-pre-filtering-with-vector-search",children:"\ud83e\uddb9 Combine pre-filtering with vector search"}),"\n",(0,r.jsx)(n.p,{children:"Pre-filtering is a technique to optimize vector search by only considering documents that match certain criteria during vector search."}),"\n",(0,r.jsx)(n.p,{children:"In this section, you will learn how to combine filters with vector search. This mainly involves:"}),"\n",(0,r.jsxs)(n.ul,{children:["\n",(0,r.jsx)(n.li,{children:"Updating the vector search index to include the appropriate filter fields"}),"\n",(0,r.jsxs)(n.li,{children:["Updating the ",(0,r.jsx)(n.code,{children:"$vectorSearch"})," stage in the aggregation pipeline definition to include the filters"]}),"\n"]}),"\n",(0,r.jsxs)(n.h2,{id:"filter-for-documents-where-the-content-type-is-video",children:["Filter for documents where the content type is ",(0,r.jsx)(n.code,{children:"Video"})]}),"\n",(0,r.jsx)(n.p,{children:"To do this, you will first need to modify the vector search index you created previously."}),"\n",(0,r.jsx)(n.p,{children:(0,r.jsx)(n.strong,{children:"Updated index definition"})}),"\n",(0,r.jsxs)(t,{children:[(0,r.jsx)("summary",{children:"Answer"}),(0,r.jsx)("div",{children:(0,r.jsx)(n.pre,{children:(0,r.jsx)(n.code,{className:"language-python",children:'{\n "fields": [\n {\n "type": "vector",\n "path": "embedding",\n "numDimensions": 384,\n "similarity": "cosine"\n },\n {\n "type":"filter",\n "path":"metadata.contentType"\n }\n ]\n}\n'})})})]}),"\n",(0,r.jsxs)(n.p,{children:["Once you have updated the vector search index, fill in any ",(0,r.jsx)(n.code,{children:""})," placeholders and run the cells under the ",(0,r.jsx)(n.strong,{children:"Filter for documents where the content type is Video"})," section in the notebook to see how the filter impacts the vector search results."]}),"\n",(0,r.jsx)(n.p,{children:"The answers for code blocks in this section are as follows:"}),"\n",(0,r.jsx)(n.p,{children:(0,r.jsx)(n.strong,{children:"CODE_BLOCK_11"})}),"\n",(0,r.jsxs)(t,{children:[(0,r.jsx)("summary",{children:"Answer"}),(0,r.jsx)("div",{children:(0,r.jsx)(n.pre,{children:(0,r.jsx)(n.code,{className:"language-python",children:'[\n {\n "$vectorSearch": {\n "index": "vector_index",\n "path": "embedding",\n "queryVector": query_embedding,\n "numCandidates": 150,\n "limit": 5,\n "filter": {"metadata.contentType": "Video"}\n }\n },\n {\n "$project": {\n "_id": 0,\n "body": 1,\n "score": {"$meta": "vectorSearchScore"}\n }\n }\n]\n'})})})]}),"\n",(0,r.jsxs)(n.h2,{id:"filter-on-documents-which-have-been-updated-on-or-after-2024-05-19-and-where-the-content-type-is-tutorial",children:["Filter on documents which have been updated on or after ",(0,r.jsx)(n.code,{children:"2024-05-19"})," and where the content type is ",(0,r.jsx)(n.code,{children:"Tutorial"})]}),"\n",(0,r.jsx)(n.p,{children:"Again, you will first need to modify the vector search index."}),"\n",(0,r.jsx)(n.p,{children:(0,r.jsx)(n.strong,{children:"Updated index definition"})}),"\n",(0,r.jsxs)(t,{children:[(0,r.jsx)("summary",{children:"Answer"}),(0,r.jsx)("div",{children:(0,r.jsx)(n.pre,{children:(0,r.jsx)(n.code,{className:"language-python",children:'{\n "fields": [\n {\n "type": "vector",\n "path": "embedding",\n "numDimensions": 384,\n "similarity": "cosine"\n },\n {\n "type":"filter",\n "path":"metadata.contentType"\n },\n {\n "type":"filter",\n "path":"updated"\n }\n ]\n}\n'})})})]}),"\n",(0,r.jsxs)(n.p,{children:["Once you have updated the vector search index, fill in any ",(0,r.jsx)(n.code,{children:""})," placeholders and run the cells under the ",(0,r.jsx)(n.strong,{children:"Filter on documents which have been updated on or after 2024-05-19 and where the content type is Tutorial"})," section in the notebook to see how the filter impacts the vector search results."]}),"\n",(0,r.jsx)(n.p,{children:"The answers for code blocks in this section are as follows:"}),"\n",(0,r.jsx)(n.p,{children:(0,r.jsx)(n.strong,{children:"CODE_BLOCK_12"})}),"\n",(0,r.jsxs)(t,{children:[(0,r.jsx)("summary",{children:"Answer"}),(0,r.jsx)("div",{children:(0,r.jsx)(n.pre,{children:(0,r.jsx)(n.code,{className:"language-python",children:'[\n {\n "$vectorSearch": {\n "index": "vector_index",\n "path": "embedding",\n "queryVector": query_embedding,\n "numCandidates": 150,\n "limit": 5,\n "filter": {\n "metadata.contentType": "Tutorial",\n "updated": {"$gte": "2024-05-19"}\n }\n }\n },\n {\n "$project": {\n "_id": 0,\n "body": 1,\n "score": {"$meta": "vectorSearchScore"}\n }\n }\n]\n'})})})]})]})}function l(e={}){const{wrapper:n}={...(0,i.R)(),...e.components};return n?(0,r.jsx)(n,{...e,children:(0,r.jsx)(h,{...e})}):h(e)}},8453:(e,n,t)=>{t.d(n,{R:()=>c,x:()=>s});var r=t(6540);const i={},o=r.createContext(i);function c(e){const n=r.useContext(o);return r.useMemo((function(){return"function"==typeof e?e(n):{...n,...e}}),[n,e])}function s(e){let n;return n=e.disableParentContext?"function"==typeof e.components?e.components(i):e.components||i:c(e.components),r.createElement(o.Provider,{value:n},e.children)}}}]); \ No newline at end of file diff --git a/assets/js/8be1a27a.32bf80d7.js b/assets/js/8be1a27a.a8147315.js similarity index 60% rename from assets/js/8be1a27a.32bf80d7.js rename to assets/js/8be1a27a.a8147315.js index b9cbc212..f1d55e9b 100644 --- a/assets/js/8be1a27a.32bf80d7.js +++ b/assets/js/8be1a27a.a8147315.js @@ -1 +1 @@ -"use strict";(self.webpackChunkai_rag_lab=self.webpackChunkai_rag_lab||[]).push([[262],{408:(e,t,r)=>{r.r(t),r.d(t,{assets:()=>l,contentTitle:()=>i,default:()=>h,frontMatter:()=>o,metadata:()=>c,toc:()=>d});var s=r(4848),a=r(8453),n=r(1179);const o={},i="\ud83d\udc50 Create an account",c={id:"fireworks-ai/create-account",title:"\ud83d\udc50 Create an account",description:"In this lab, we will use the Llama 3 8B Instruct model hosted by Fireworks AI. Fireworks gives you $1 credit upon sign up which is plenty to experiment with industry-leading models on their platform.",source:"@site/docs/30-fireworks-ai/1-create-account.mdx",sourceDirName:"30-fireworks-ai",slug:"/fireworks-ai/create-account",permalink:"/ai-rag-lab/docs/fireworks-ai/create-account",draft:!1,unlisted:!1,editUrl:"https://github.com/mongodb-developer/ai-rag-lab/blob/main/docs/30-fireworks-ai/1-create-account.mdx",tags:[],version:"current",sidebarPosition:1,frontMatter:{},sidebar:"tutorialSidebar",previous:{title:"Fireworks AI",permalink:"/ai-rag-lab/docs/category/fireworks-ai"},next:{title:"\ud83d\udc50 Create an API key",permalink:"/ai-rag-lab/docs/fireworks-ai/create-api-key"}},l={},d=[];function u(e){const t={a:"a",em:"em",h1:"h1",p:"p",strong:"strong",...(0,a.R)(),...e.components};return(0,s.jsxs)(s.Fragment,{children:[(0,s.jsx)(t.h1,{id:"-create-an-account",children:"\ud83d\udc50 Create an account"}),"\n",(0,s.jsxs)(t.p,{children:["In this lab, we will use the ",(0,s.jsx)(t.em,{children:"Llama 3 8B Instruct"})," model hosted by Fireworks AI. Fireworks gives you $1 credit upon sign up which is plenty to experiment with industry-leading models on their platform."]}),"\n",(0,s.jsxs)(t.p,{children:["The easiest way to use the model is via the Fireworks API. But first, you will need to create a Fireworks account. ",(0,s.jsx)(t.strong,{children:"If you already have an account, you can skip the following steps and move on to the next section."})]}),"\n",(0,s.jsxs)(t.p,{children:["Start by navigating to the ",(0,s.jsx)(t.a,{href:"https://fireworks.ai/",children:"Fireworks AI homepage"})," and click the purple ",(0,s.jsx)(t.strong,{children:"Get Started Free"})," button to create an account."]}),"\n",(0,s.jsx)(n.A,{url:"https://fireworks.ai/",src:"img/screenshots/30-fireworks-ai/1-create-account/1-homepage.png",alt:"Get started"}),"\n",(0,s.jsxs)(t.p,{children:["Click ",(0,s.jsx)(t.strong,{children:"Login With Google"})," and authenticate with your Google account. This will provision a new Fireworks account and API Key for you."]}),"\n",(0,s.jsx)(n.A,{url:"https://fireworks.ai/",src:"img/screenshots/30-fireworks-ai/1-create-account/2-google-login.png",alt:"Login"})]})}function h(e={}){const{wrapper:t}={...(0,a.R)(),...e.components};return t?(0,s.jsx)(t,{...e,children:(0,s.jsx)(u,{...e})}):u(e)}},1179:(e,t,r)=>{r.d(t,{A:()=>o});r(6540);var s=r(4848);function a(e){const t=e.url||"http://localhost:3000";return(0,s.jsxs)("div",{className:"browser container",children:[(0,s.jsxs)("div",{className:"row",children:[(0,s.jsxs)("div",{className:"column left",children:[(0,s.jsx)("span",{className:"dot",style:{background:"#ED594A"}}),(0,s.jsx)("span",{className:"dot",style:{background:"#FDD800"}}),(0,s.jsx)("span",{className:"dot",style:{background:"#5AC05A"}})]}),(0,s.jsx)("div",{className:"column middle",children:(0,s.jsx)("input",{type:"text",value:t})}),(0,s.jsx)("div",{className:"column right",children:(0,s.jsxs)("div",{style:{float:"right"},children:[(0,s.jsx)("span",{className:"bar"}),(0,s.jsx)("span",{className:"bar"}),(0,s.jsx)("span",{className:"bar"})]})})]}),(0,s.jsx)("div",{className:"content",children:e.children})]})}var n=r(8180);function o(e){return(0,s.jsx)(a,{...e,children:(0,s.jsx)("img",{src:(0,n.A)(e.src),alt:e.alt})})}},8453:(e,t,r)=>{r.d(t,{R:()=>o,x:()=>i});var s=r(6540);const a={},n=s.createContext(a);function o(e){const t=s.useContext(n);return s.useMemo((function(){return"function"==typeof e?e(t):{...t,...e}}),[t,e])}function i(e){let t;return t=e.disableParentContext?"function"==typeof e.components?e.components(a):e.components||a:o(e.components),s.createElement(n.Provider,{value:t},e.children)}}}]); \ No newline at end of file +"use strict";(self.webpackChunkai_rag_lab=self.webpackChunkai_rag_lab||[]).push([[262],{408:(e,t,r)=>{r.r(t),r.d(t,{assets:()=>l,contentTitle:()=>i,default:()=>h,frontMatter:()=>o,metadata:()=>c,toc:()=>d});var s=r(4848),a=r(8453),n=r(1179);const o={},i="\ud83d\udc50 Create an account",c={id:"fireworks-ai/create-account",title:"\ud83d\udc50 Create an account",description:"In this lab, we will use the Llama 3 8B Instruct model hosted by Fireworks AI. Fireworks gives you $1 credit upon sign up which is plenty to experiment with industry-leading models on their platform.",source:"@site/docs/30-fireworks-ai/1-create-account.mdx",sourceDirName:"30-fireworks-ai",slug:"/fireworks-ai/create-account",permalink:"/ai-rag-lab/docs/fireworks-ai/create-account",draft:!1,unlisted:!1,editUrl:"https://github.com/mongodb-developer/ai-rag-lab/blob/main/docs/30-fireworks-ai/1-create-account.mdx",tags:[],version:"current",sidebarPosition:1,frontMatter:{},sidebar:"tutorialSidebar",previous:{title:"Fireworks AI",permalink:"/ai-rag-lab/docs/category/fireworks-ai"},next:{title:"\ud83d\udc50 Create an API key",permalink:"/ai-rag-lab/docs/fireworks-ai/create-api-key"}},l={},d=[];function u(e){const t={a:"a",em:"em",h1:"h1",p:"p",strong:"strong",...(0,a.R)(),...e.components};return(0,s.jsxs)(s.Fragment,{children:[(0,s.jsx)(t.h1,{id:"-create-an-account",children:"\ud83d\udc50 Create an account"}),"\n",(0,s.jsxs)(t.p,{children:["In this lab, we will use the ",(0,s.jsx)(t.em,{children:"Llama 3 8B Instruct"})," model hosted by Fireworks AI. Fireworks gives you $1 credit upon sign up which is plenty to experiment with industry-leading models on their platform."]}),"\n",(0,s.jsxs)(t.p,{children:["The easiest way to use the model is via the Fireworks API. But first, you will need to create a Fireworks account. ",(0,s.jsx)(t.strong,{children:"If you already have an account, you can skip the following steps and move on to the next section."})]}),"\n",(0,s.jsxs)(t.p,{children:["Start by navigating to the ",(0,s.jsx)(t.a,{href:"https://fireworks.ai/",children:"Fireworks AI homepage"})," and click the purple ",(0,s.jsx)(t.strong,{children:"Get Started Free"})," button to create an account."]}),"\n",(0,s.jsx)(n.A,{url:"https://fireworks.ai/",src:"img/screenshots/30-fireworks-ai/1-create-account/1-homepage.png",alt:"Get started"}),"\n",(0,s.jsxs)(t.p,{children:["Click ",(0,s.jsx)(t.strong,{children:"Login With Google"})," and authenticate with your Google account. This will provision a new Fireworks account for you."]}),"\n",(0,s.jsx)(n.A,{url:"https://fireworks.ai/",src:"img/screenshots/30-fireworks-ai/1-create-account/2-google-login.png",alt:"Login"})]})}function h(e={}){const{wrapper:t}={...(0,a.R)(),...e.components};return t?(0,s.jsx)(t,{...e,children:(0,s.jsx)(u,{...e})}):u(e)}},1179:(e,t,r)=>{r.d(t,{A:()=>o});r(6540);var s=r(4848);function a(e){const t=e.url||"http://localhost:3000";return(0,s.jsxs)("div",{className:"browser container",children:[(0,s.jsxs)("div",{className:"row",children:[(0,s.jsxs)("div",{className:"column left",children:[(0,s.jsx)("span",{className:"dot",style:{background:"#ED594A"}}),(0,s.jsx)("span",{className:"dot",style:{background:"#FDD800"}}),(0,s.jsx)("span",{className:"dot",style:{background:"#5AC05A"}})]}),(0,s.jsx)("div",{className:"column middle",children:(0,s.jsx)("input",{type:"text",value:t})}),(0,s.jsx)("div",{className:"column right",children:(0,s.jsxs)("div",{style:{float:"right"},children:[(0,s.jsx)("span",{className:"bar"}),(0,s.jsx)("span",{className:"bar"}),(0,s.jsx)("span",{className:"bar"})]})})]}),(0,s.jsx)("div",{className:"content",children:e.children})]})}var n=r(8180);function o(e){return(0,s.jsx)(a,{...e,children:(0,s.jsx)("img",{src:(0,n.A)(e.src),alt:e.alt})})}},8453:(e,t,r)=>{r.d(t,{R:()=>o,x:()=>i});var s=r(6540);const a={},n=s.createContext(a);function o(e){const t=s.useContext(n);return s.useMemo((function(){return"function"==typeof e?e(t):{...t,...e}}),[t,e])}function i(e){let t;return t=e.disableParentContext?"function"==typeof e.components?e.components(a):e.components||a:o(e.components),s.createElement(n.Provider,{value:t},e.children)}}}]); \ No newline at end of file diff --git a/assets/js/935f2afb.8fc15c94.js b/assets/js/935f2afb.5728985f.js similarity index 65% rename from assets/js/935f2afb.8fc15c94.js rename to assets/js/935f2afb.5728985f.js index 536c4cf6..ac3f041d 100644 --- a/assets/js/935f2afb.8fc15c94.js +++ b/assets/js/935f2afb.5728985f.js @@ -1 +1 @@ -"use strict";(self.webpackChunkai_rag_lab=self.webpackChunkai_rag_lab||[]).push([[581],{5610:e=>{e.exports=JSON.parse('{"pluginId":"default","version":"current","label":"Next","banner":null,"badge":false,"noIndex":false,"className":"docs-version-current","isLast":true,"docsSidebars":{"tutorialSidebar":[{"type":"link","label":"Introduction","href":"/ai-rag-lab/docs/intro","docId":"intro","unlisted":false},{"type":"category","label":"Retrieval Augmented Generation","collapsible":true,"collapsed":true,"items":[{"type":"link","label":"\ud83d\udcd8 What is RAG?","href":"/ai-rag-lab/docs/rag/what-is-rag","docId":"rag/what-is-rag","unlisted":false},{"type":"link","label":"\ud83d\udcd8 When to use RAG?","href":"/ai-rag-lab/docs/rag/rag-usecases","docId":"rag/rag-usecases","unlisted":false},{"type":"link","label":"\ud83d\udcd8 Components of a RAG system","href":"/ai-rag-lab/docs/rag/components-of-rag","docId":"rag/components-of-rag","unlisted":false}],"href":"/ai-rag-lab/docs/category/retrieval-augmented-generation"},{"type":"category","label":"MongoDB Atlas","collapsible":true,"collapsed":true,"items":[{"type":"link","label":"\ud83d\udc50 Create your account","href":"/ai-rag-lab/docs/mongodb-atlas/create-account","docId":"mongodb-atlas/create-account","unlisted":false},{"type":"link","label":"\ud83d\udc50 Deploy a database cluster","href":"/ai-rag-lab/docs/mongodb-atlas/create-cluster","docId":"mongodb-atlas/create-cluster","unlisted":false},{"type":"link","label":"\ud83d\udc50 Get your connection string","href":"/ai-rag-lab/docs/mongodb-atlas/get-connection-string","docId":"mongodb-atlas/get-connection-string","unlisted":false}],"href":"/ai-rag-lab/docs/category/mongodb-atlas"},{"type":"category","label":"Fireworks AI","collapsible":true,"collapsed":true,"items":[{"type":"link","label":"\ud83d\udc50 Create an account","href":"/ai-rag-lab/docs/fireworks-ai/create-account","docId":"fireworks-ai/create-account","unlisted":false},{"type":"link","label":"\ud83d\udc50 Create an API key","href":"/ai-rag-lab/docs/fireworks-ai/create-api-key","docId":"fireworks-ai/create-api-key","unlisted":false}],"href":"/ai-rag-lab/docs/category/fireworks-ai"},{"type":"category","label":"Dev Environment","collapsible":true,"collapsed":true,"items":[{"type":"link","label":"\ud83d\udc50 Setup dev environment","href":"/ai-rag-lab/docs/dev-env/dev-setup","docId":"dev-env/dev-setup","unlisted":false},{"type":"link","label":"\ud83d\udc50 Setup prerequisites","href":"/ai-rag-lab/docs/dev-env/setup-pre-reqs","docId":"dev-env/setup-pre-reqs","unlisted":false}],"href":"/ai-rag-lab/docs/category/dev-environment"},{"type":"category","label":"Prepare the Data","collapsible":true,"collapsed":true,"items":[{"type":"link","label":"\ud83d\udcd8 Tools, libraries, and concepts","href":"/ai-rag-lab/docs/prepare-the-data/concepts","docId":"prepare-the-data/concepts","unlisted":false},{"type":"link","label":"\ud83d\udc50 Load the dataset","href":"/ai-rag-lab/docs/prepare-the-data/load-data","docId":"prepare-the-data/load-data","unlisted":false},{"type":"link","label":"\ud83d\udc50 Chunk up the data","href":"/ai-rag-lab/docs/prepare-the-data/chunk-data","docId":"prepare-the-data/chunk-data","unlisted":false},{"type":"link","label":"\ud83d\udc50 Generate embeddings","href":"/ai-rag-lab/docs/prepare-the-data/embed-data","docId":"prepare-the-data/embed-data","unlisted":false},{"type":"link","label":"\ud83d\udc50 Ingest data into MongoDB","href":"/ai-rag-lab/docs/prepare-the-data/ingest-data","docId":"prepare-the-data/ingest-data","unlisted":false}],"href":"/ai-rag-lab/docs/category/prepare-the-data"},{"type":"category","label":"Perform Semantic Search on Your Data","collapsible":true,"collapsed":true,"items":[{"type":"link","label":"\ud83d\udcd8 Semantic search in MongoDB","href":"/ai-rag-lab/docs/perform-semantic-search/concepts","docId":"perform-semantic-search/concepts","unlisted":false},{"type":"link","label":"\ud83d\udc50 Create a vector search index","href":"/ai-rag-lab/docs/perform-semantic-search/create-vector-index","docId":"perform-semantic-search/create-vector-index","unlisted":false},{"type":"link","label":"\ud83d\udc50 Perform semantic search","href":"/ai-rag-lab/docs/perform-semantic-search/vector-search","docId":"perform-semantic-search/vector-search","unlisted":false},{"type":"link","label":"\ud83e\uddb9 Combine pre-filtering with vector search","href":"/ai-rag-lab/docs/perform-semantic-search/pre-filtering","docId":"perform-semantic-search/pre-filtering","unlisted":false}],"href":"/ai-rag-lab/docs/category/perform-semantic-search-on-your-data"},{"type":"category","label":"Build the RAG Application","collapsible":true,"collapsed":true,"items":[{"type":"link","label":"\ud83d\udc50 Build the RAG application","href":"/ai-rag-lab/docs/build-rag-app/build-rag-app","docId":"build-rag-app/build-rag-app","unlisted":false},{"type":"link","label":"\ud83e\uddb9 Re-rank retrieved results","href":"/ai-rag-lab/docs/build-rag-app/add-reranking","docId":"build-rag-app/add-reranking","unlisted":false},{"type":"link","label":"\ud83e\uddb9 Stream responses from the RAG application","href":"/ai-rag-lab/docs/build-rag-app/stream-responses","docId":"build-rag-app/stream-responses","unlisted":false}],"href":"/ai-rag-lab/docs/category/build-the-rag-application"},{"type":"category","label":"Add memory to the RAG application","collapsible":true,"collapsed":true,"items":[{"type":"link","label":"\ud83d\udcd8 Tools, libraries, and concepts","href":"/ai-rag-lab/docs/add-memory/concepts","docId":"add-memory/concepts","unlisted":false},{"type":"link","label":"\ud83d\udc50 Add memory to the RAG application","href":"/ai-rag-lab/docs/add-memory/add-memory","docId":"add-memory/add-memory","unlisted":false}],"href":"/ai-rag-lab/docs/category/add-memory-to-the-rag-application"},{"type":"link","label":"\ud83c\udfaf Summary","href":"/ai-rag-lab/docs/summary","docId":"summary","unlisted":false}]},"docs":{"add-memory/add-memory":{"id":"add-memory/add-memory","title":"\ud83d\udc50 Add memory to the RAG application","description":"In many Q&A applications we want to allow the user to have a back-and-forth conversation with the LLM, meaning the application needs some sort of \\"memory\\" of past questions and answers, and some logic for incorporating those into its current thinking. In this section, you will retrieve chat message history from MongoDB and incorporate it in your RAG application.","sidebar":"tutorialSidebar"},"add-memory/concepts":{"id":"add-memory/concepts","title":"\ud83d\udcd8 Tools, libraries, and concepts","description":"Memory is important for the LLM to have multi-turn conversations with the user.","sidebar":"tutorialSidebar"},"build-rag-app/add-reranking":{"id":"build-rag-app/add-reranking","title":"\ud83e\uddb9 Re-rank retrieved results","description":"Re-rankers are specialized models that are trained to calculate the relevance between query-document pairs. Without re-ranking the order of retrieved results is governed by the embedding model, which isn\'t optimized for relevance and can lead to poor LLM recall in RAG applications.","sidebar":"tutorialSidebar"},"build-rag-app/build-rag-app":{"id":"build-rag-app/build-rag-app","title":"\ud83d\udc50 Build the RAG application","description":"Let\'s create a simple RAG application that takes in a user query, retrieves contextually relevant documents from MongoDB Atlas, and passes the query and retrieved context to the Llama 3 8B Instruct model to generate an answer to the user question.","sidebar":"tutorialSidebar"},"build-rag-app/stream-responses":{"id":"build-rag-app/stream-responses","title":"\ud83e\uddb9 Stream responses from the RAG application","description":"By default, generation results are returned once the generation is completed. Another option is to stream the results as they come, which is useful for chat use cases where the user can incrementally see results as each token is generated.","sidebar":"tutorialSidebar"},"dev-env/dev-setup":{"id":"dev-env/dev-setup","title":"\ud83d\udc50 Setup dev environment","description":"You will be working in a Jupyter Notebook throughout this lab. The easiest and recommended way to run the lab notebook is using Google Colab.","sidebar":"tutorialSidebar"},"dev-env/setup-pre-reqs":{"id":"dev-env/setup-pre-reqs","title":"\ud83d\udc50 Setup prerequisites","description":"Replace any placeholders and run the cells under the Step 1 Setup prerequisites sections in the notebook.","sidebar":"tutorialSidebar"},"fireworks-ai/create-account":{"id":"fireworks-ai/create-account","title":"\ud83d\udc50 Create an account","description":"In this lab, we will use the Llama 3 8B Instruct model hosted by Fireworks AI. Fireworks gives you $1 credit upon sign up which is plenty to experiment with industry-leading models on their platform.","sidebar":"tutorialSidebar"},"fireworks-ai/create-api-key":{"id":"fireworks-ai/create-api-key","title":"\ud83d\udc50 Create an API key","description":"If you just created a new account or want to use an existing API key, skip to the last step to copy the API key.","sidebar":"tutorialSidebar"},"intro":{"id":"intro","title":"Introduction","description":"|Lab goals|Learn how to build a RAG application from scratch|","sidebar":"tutorialSidebar"},"mongodb-atlas/create-account":{"id":"mongodb-atlas/create-account","title":"\ud83d\udc50 Create your account","description":"In this lab, you will learn how to use MongoDB Atlas as a knowledge base as well as a memory provider for RAG applications.","sidebar":"tutorialSidebar"},"mongodb-atlas/create-cluster":{"id":"mongodb-atlas/create-cluster","title":"\ud83d\udc50 Deploy a database cluster","description":"Now that you have a MongoDB Atlas account, you can create your first cluster for free.","sidebar":"tutorialSidebar"},"mongodb-atlas/get-connection-string":{"id":"mongodb-atlas/get-connection-string","title":"\ud83d\udc50 Get your connection string","description":"In order to ingest data into your cluster later in the lab, you will need to get the connection string for your cluster.","sidebar":"tutorialSidebar"},"perform-semantic-search/concepts":{"id":"perform-semantic-search/concepts","title":"\ud83d\udcd8 Semantic search in MongoDB","description":"In MongoDB, you can semantically search through your data using MongoDB Atlas Vector Search.","sidebar":"tutorialSidebar"},"perform-semantic-search/create-vector-index":{"id":"perform-semantic-search/create-vector-index","title":"\ud83d\udc50 Create a vector search index","description":"To retrieve documents from MongoDB using vector search, you must configure a vector search index on the collection into which you ingested your data.","sidebar":"tutorialSidebar"},"perform-semantic-search/pre-filtering":{"id":"perform-semantic-search/pre-filtering","title":"\ud83e\uddb9 Combine pre-filtering with vector search","description":"Pre-filtering a technique to optimize vector search by only considering documents that match certain criteria during vector search.","sidebar":"tutorialSidebar"},"perform-semantic-search/vector-search":{"id":"perform-semantic-search/vector-search","title":"\ud83d\udc50 Perform semantic search","description":"Now let\'s run some vector search queries against our data present in MongoDB.","sidebar":"tutorialSidebar"},"prepare-the-data/chunk-data":{"id":"prepare-the-data/chunk-data","title":"\ud83d\udc50 Chunk up the data","description":"Since we are working with large documents, we first need to break them up into smaller chunks before embedding and storing them in MongoDB.","sidebar":"tutorialSidebar"},"prepare-the-data/concepts":{"id":"prepare-the-data/concepts","title":"\ud83d\udcd8 Tools, libraries, and concepts","description":"datasets","sidebar":"tutorialSidebar"},"prepare-the-data/embed-data":{"id":"prepare-the-data/embed-data","title":"\ud83d\udc50 Generate embeddings","description":"To perform vector search on our data, we need to embed it (i.e. generate embedding vectors) before ingesting it into MongoDB.","sidebar":"tutorialSidebar"},"prepare-the-data/ingest-data":{"id":"prepare-the-data/ingest-data","title":"\ud83d\udc50 Ingest data into MongoDB","description":"The final step to build a MongoDB vector store for our RAG application is to ingest the embedded article chunks into MongoDB.","sidebar":"tutorialSidebar"},"prepare-the-data/load-data":{"id":"prepare-the-data/load-data","title":"\ud83d\udc50 Load the dataset","description":"First, let\'s download the dataset for our lab. We\'ll use a subset of articles from the MongoDB Developer Center as the source data for our RAG application.","sidebar":"tutorialSidebar"},"rag/components-of-rag":{"id":"rag/components-of-rag","title":"\ud83d\udcd8 Components of a RAG system","description":"RAG systems have two main components: Retrieval and Generation.","sidebar":"tutorialSidebar"},"rag/rag-usecases":{"id":"rag/rag-usecases","title":"\ud83d\udcd8 When to use RAG?","description":"RAG is best suited for the following:","sidebar":"tutorialSidebar"},"rag/what-is-rag":{"id":"rag/what-is-rag","title":"\ud83d\udcd8 What is RAG?","description":"RAG, short for Retrieval Augmented Generation, is a technique to enhance the quality of responses generated by a large language model (LLM), by augmenting its pre-trained knowledge with information retrieved from external sources. This results is more accurate responses from the LLM by grounding them in real, contextually relevant data.","sidebar":"tutorialSidebar"},"summary":{"id":"summary","title":"\ud83c\udfaf Summary","description":"Congratulations! Following this lab, you have successfully:","sidebar":"tutorialSidebar"}}}')}}]); \ No newline at end of file +"use strict";(self.webpackChunkai_rag_lab=self.webpackChunkai_rag_lab||[]).push([[581],{5610:e=>{e.exports=JSON.parse('{"pluginId":"default","version":"current","label":"Next","banner":null,"badge":false,"noIndex":false,"className":"docs-version-current","isLast":true,"docsSidebars":{"tutorialSidebar":[{"type":"link","label":"Introduction","href":"/ai-rag-lab/docs/intro","docId":"intro","unlisted":false},{"type":"category","label":"Retrieval Augmented Generation","collapsible":true,"collapsed":true,"items":[{"type":"link","label":"\ud83d\udcd8 What is RAG?","href":"/ai-rag-lab/docs/rag/what-is-rag","docId":"rag/what-is-rag","unlisted":false},{"type":"link","label":"\ud83d\udcd8 When to use RAG?","href":"/ai-rag-lab/docs/rag/rag-usecases","docId":"rag/rag-usecases","unlisted":false},{"type":"link","label":"\ud83d\udcd8 Components of a RAG system","href":"/ai-rag-lab/docs/rag/components-of-rag","docId":"rag/components-of-rag","unlisted":false}],"href":"/ai-rag-lab/docs/category/retrieval-augmented-generation"},{"type":"category","label":"MongoDB Atlas","collapsible":true,"collapsed":true,"items":[{"type":"link","label":"\ud83d\udc50 Create your account","href":"/ai-rag-lab/docs/mongodb-atlas/create-account","docId":"mongodb-atlas/create-account","unlisted":false},{"type":"link","label":"\ud83d\udc50 Deploy a database cluster","href":"/ai-rag-lab/docs/mongodb-atlas/create-cluster","docId":"mongodb-atlas/create-cluster","unlisted":false},{"type":"link","label":"\ud83d\udc50 Get your connection string","href":"/ai-rag-lab/docs/mongodb-atlas/get-connection-string","docId":"mongodb-atlas/get-connection-string","unlisted":false}],"href":"/ai-rag-lab/docs/category/mongodb-atlas"},{"type":"category","label":"Fireworks AI","collapsible":true,"collapsed":true,"items":[{"type":"link","label":"\ud83d\udc50 Create an account","href":"/ai-rag-lab/docs/fireworks-ai/create-account","docId":"fireworks-ai/create-account","unlisted":false},{"type":"link","label":"\ud83d\udc50 Create an API key","href":"/ai-rag-lab/docs/fireworks-ai/create-api-key","docId":"fireworks-ai/create-api-key","unlisted":false}],"href":"/ai-rag-lab/docs/category/fireworks-ai"},{"type":"category","label":"Dev Environment","collapsible":true,"collapsed":true,"items":[{"type":"link","label":"\ud83d\udc50 Setup dev environment","href":"/ai-rag-lab/docs/dev-env/dev-setup","docId":"dev-env/dev-setup","unlisted":false},{"type":"link","label":"\ud83d\udc50 Setup prerequisites","href":"/ai-rag-lab/docs/dev-env/setup-pre-reqs","docId":"dev-env/setup-pre-reqs","unlisted":false}],"href":"/ai-rag-lab/docs/category/dev-environment"},{"type":"category","label":"Prepare the Data","collapsible":true,"collapsed":true,"items":[{"type":"link","label":"\ud83d\udcd8 Tools, libraries, and concepts","href":"/ai-rag-lab/docs/prepare-the-data/concepts","docId":"prepare-the-data/concepts","unlisted":false},{"type":"link","label":"\ud83d\udc50 Load the dataset","href":"/ai-rag-lab/docs/prepare-the-data/load-data","docId":"prepare-the-data/load-data","unlisted":false},{"type":"link","label":"\ud83d\udc50 Chunk up the data","href":"/ai-rag-lab/docs/prepare-the-data/chunk-data","docId":"prepare-the-data/chunk-data","unlisted":false},{"type":"link","label":"\ud83d\udc50 Generate embeddings","href":"/ai-rag-lab/docs/prepare-the-data/embed-data","docId":"prepare-the-data/embed-data","unlisted":false},{"type":"link","label":"\ud83d\udc50 Ingest data into MongoDB","href":"/ai-rag-lab/docs/prepare-the-data/ingest-data","docId":"prepare-the-data/ingest-data","unlisted":false}],"href":"/ai-rag-lab/docs/category/prepare-the-data"},{"type":"category","label":"Perform Semantic Search on Your Data","collapsible":true,"collapsed":true,"items":[{"type":"link","label":"\ud83d\udcd8 Semantic search in MongoDB","href":"/ai-rag-lab/docs/perform-semantic-search/concepts","docId":"perform-semantic-search/concepts","unlisted":false},{"type":"link","label":"\ud83d\udc50 Create a vector search index","href":"/ai-rag-lab/docs/perform-semantic-search/create-vector-index","docId":"perform-semantic-search/create-vector-index","unlisted":false},{"type":"link","label":"\ud83d\udc50 Perform semantic search","href":"/ai-rag-lab/docs/perform-semantic-search/vector-search","docId":"perform-semantic-search/vector-search","unlisted":false},{"type":"link","label":"\ud83e\uddb9 Combine pre-filtering with vector search","href":"/ai-rag-lab/docs/perform-semantic-search/pre-filtering","docId":"perform-semantic-search/pre-filtering","unlisted":false}],"href":"/ai-rag-lab/docs/category/perform-semantic-search-on-your-data"},{"type":"category","label":"Build the RAG Application","collapsible":true,"collapsed":true,"items":[{"type":"link","label":"\ud83d\udc50 Build the RAG application","href":"/ai-rag-lab/docs/build-rag-app/build-rag-app","docId":"build-rag-app/build-rag-app","unlisted":false},{"type":"link","label":"\ud83e\uddb9 Re-rank retrieved results","href":"/ai-rag-lab/docs/build-rag-app/add-reranking","docId":"build-rag-app/add-reranking","unlisted":false},{"type":"link","label":"\ud83e\uddb9 Stream responses from the RAG application","href":"/ai-rag-lab/docs/build-rag-app/stream-responses","docId":"build-rag-app/stream-responses","unlisted":false}],"href":"/ai-rag-lab/docs/category/build-the-rag-application"},{"type":"category","label":"Add memory to the RAG application","collapsible":true,"collapsed":true,"items":[{"type":"link","label":"\ud83d\udcd8 Tools, libraries, and concepts","href":"/ai-rag-lab/docs/add-memory/concepts","docId":"add-memory/concepts","unlisted":false},{"type":"link","label":"\ud83d\udc50 Add memory to the RAG application","href":"/ai-rag-lab/docs/add-memory/add-memory","docId":"add-memory/add-memory","unlisted":false}],"href":"/ai-rag-lab/docs/category/add-memory-to-the-rag-application"},{"type":"link","label":"\ud83c\udfaf Summary","href":"/ai-rag-lab/docs/summary","docId":"summary","unlisted":false}]},"docs":{"add-memory/add-memory":{"id":"add-memory/add-memory","title":"\ud83d\udc50 Add memory to the RAG application","description":"In many Q&A applications we want to allow the user to have a back-and-forth conversation with the LLM, meaning the application needs some sort of \\"memory\\" of past questions and answers, and some logic for incorporating those into its current thinking. In this section, you will retrieve chat message history from MongoDB and incorporate it in your RAG application.","sidebar":"tutorialSidebar"},"add-memory/concepts":{"id":"add-memory/concepts","title":"\ud83d\udcd8 Tools, libraries, and concepts","description":"Memory is important for the LLM to have multi-turn conversations with the user.","sidebar":"tutorialSidebar"},"build-rag-app/add-reranking":{"id":"build-rag-app/add-reranking","title":"\ud83e\uddb9 Re-rank retrieved results","description":"Re-rankers are specialized models that are trained to calculate the relevance between query-document pairs. Without re-ranking the order of retrieved results is governed by the embedding model, which isn\'t optimized for relevance and can lead to poor LLM recall in RAG applications.","sidebar":"tutorialSidebar"},"build-rag-app/build-rag-app":{"id":"build-rag-app/build-rag-app","title":"\ud83d\udc50 Build the RAG application","description":"Let\'s create a simple RAG application that takes in a user query, retrieves contextually relevant documents from MongoDB Atlas, and passes the query and retrieved context to the Llama 3 8B Instruct model to generate an answer to the user question.","sidebar":"tutorialSidebar"},"build-rag-app/stream-responses":{"id":"build-rag-app/stream-responses","title":"\ud83e\uddb9 Stream responses from the RAG application","description":"By default, generation results are returned once the generation is completed. Another option is to stream the results as they come, which is useful for chat use cases where the user can incrementally see results as each token is generated.","sidebar":"tutorialSidebar"},"dev-env/dev-setup":{"id":"dev-env/dev-setup","title":"\ud83d\udc50 Setup dev environment","description":"You will be working in a Jupyter Notebook throughout this lab. The easiest and recommended way to run the lab notebook is using Google Colab.","sidebar":"tutorialSidebar"},"dev-env/setup-pre-reqs":{"id":"dev-env/setup-pre-reqs","title":"\ud83d\udc50 Setup prerequisites","description":"Replace any placeholders and run the cells under the Step 1 Setup prerequisites sections in the notebook.","sidebar":"tutorialSidebar"},"fireworks-ai/create-account":{"id":"fireworks-ai/create-account","title":"\ud83d\udc50 Create an account","description":"In this lab, we will use the Llama 3 8B Instruct model hosted by Fireworks AI. Fireworks gives you $1 credit upon sign up which is plenty to experiment with industry-leading models on their platform.","sidebar":"tutorialSidebar"},"fireworks-ai/create-api-key":{"id":"fireworks-ai/create-api-key","title":"\ud83d\udc50 Create an API key","description":"To use the Fireworks API, you will need an API Key. To create a secure API key, follow the steps below.","sidebar":"tutorialSidebar"},"intro":{"id":"intro","title":"Introduction","description":"|Lab goals|Learn how to build a RAG application from scratch|","sidebar":"tutorialSidebar"},"mongodb-atlas/create-account":{"id":"mongodb-atlas/create-account","title":"\ud83d\udc50 Create your account","description":"In this lab, you will learn how to use MongoDB Atlas as a knowledge base as well as a memory provider for RAG applications.","sidebar":"tutorialSidebar"},"mongodb-atlas/create-cluster":{"id":"mongodb-atlas/create-cluster","title":"\ud83d\udc50 Deploy a database cluster","description":"Now that you have a MongoDB Atlas account, you can create your first cluster for free.","sidebar":"tutorialSidebar"},"mongodb-atlas/get-connection-string":{"id":"mongodb-atlas/get-connection-string","title":"\ud83d\udc50 Get your connection string","description":"In order to ingest data into your cluster later in the lab, you will need to get the connection string for your cluster.","sidebar":"tutorialSidebar"},"perform-semantic-search/concepts":{"id":"perform-semantic-search/concepts","title":"\ud83d\udcd8 Semantic search in MongoDB","description":"In MongoDB, you can semantically search through your data using MongoDB Atlas Vector Search.","sidebar":"tutorialSidebar"},"perform-semantic-search/create-vector-index":{"id":"perform-semantic-search/create-vector-index","title":"\ud83d\udc50 Create a vector search index","description":"To retrieve documents from MongoDB using vector search, you must configure a vector search index on the collection into which you ingested your data.","sidebar":"tutorialSidebar"},"perform-semantic-search/pre-filtering":{"id":"perform-semantic-search/pre-filtering","title":"\ud83e\uddb9 Combine pre-filtering with vector search","description":"Pre-filtering is a technique to optimize vector search by only considering documents that match certain criteria during vector search.","sidebar":"tutorialSidebar"},"perform-semantic-search/vector-search":{"id":"perform-semantic-search/vector-search","title":"\ud83d\udc50 Perform semantic search","description":"Now let\'s run some vector search queries against our data present in MongoDB.","sidebar":"tutorialSidebar"},"prepare-the-data/chunk-data":{"id":"prepare-the-data/chunk-data","title":"\ud83d\udc50 Chunk up the data","description":"Since we are working with large documents, we first need to break them up into smaller chunks before embedding and storing them in MongoDB.","sidebar":"tutorialSidebar"},"prepare-the-data/concepts":{"id":"prepare-the-data/concepts","title":"\ud83d\udcd8 Tools, libraries, and concepts","description":"datasets","sidebar":"tutorialSidebar"},"prepare-the-data/embed-data":{"id":"prepare-the-data/embed-data","title":"\ud83d\udc50 Generate embeddings","description":"To perform vector search on our data, we need to embed it (i.e. generate embedding vectors) before ingesting it into MongoDB.","sidebar":"tutorialSidebar"},"prepare-the-data/ingest-data":{"id":"prepare-the-data/ingest-data","title":"\ud83d\udc50 Ingest data into MongoDB","description":"The final step to build a MongoDB vector store for our RAG application is to ingest the embedded article chunks into MongoDB.","sidebar":"tutorialSidebar"},"prepare-the-data/load-data":{"id":"prepare-the-data/load-data","title":"\ud83d\udc50 Load the dataset","description":"First, let\'s download the dataset for our lab. We\'ll use a subset of articles from the MongoDB Developer Center as the source data for our RAG application.","sidebar":"tutorialSidebar"},"rag/components-of-rag":{"id":"rag/components-of-rag","title":"\ud83d\udcd8 Components of a RAG system","description":"RAG systems have two main components: Retrieval and Generation.","sidebar":"tutorialSidebar"},"rag/rag-usecases":{"id":"rag/rag-usecases","title":"\ud83d\udcd8 When to use RAG?","description":"RAG is best suited for the following:","sidebar":"tutorialSidebar"},"rag/what-is-rag":{"id":"rag/what-is-rag","title":"\ud83d\udcd8 What is RAG?","description":"RAG, short for Retrieval Augmented Generation, is a technique to enhance the quality of responses generated by a large language model (LLM), by augmenting its pre-trained knowledge with information retrieved from external sources. This results is more accurate responses from the LLM by grounding them in real, contextually relevant data.","sidebar":"tutorialSidebar"},"summary":{"id":"summary","title":"\ud83c\udfaf Summary","description":"Congratulations! Following this lab, you have successfully:","sidebar":"tutorialSidebar"}}}')}}]); \ No newline at end of file diff --git a/assets/js/ade674ed.52ec81a8.js b/assets/js/ade674ed.52ec81a8.js deleted file mode 100644 index 18703393..00000000 --- a/assets/js/ade674ed.52ec81a8.js +++ /dev/null @@ -1 +0,0 @@ -"use strict";(self.webpackChunkai_rag_lab=self.webpackChunkai_rag_lab||[]).push([[888],{8022:(e,t,a)=>{a.r(t),a.d(t,{assets:()=>l,contentTitle:()=>i,default:()=>u,frontMatter:()=>o,metadata:()=>c,toc:()=>p});var s=a(4848),r=a(8453),n=a(1179);const o={},i="\ud83d\udc50 Create an API key",c={id:"fireworks-ai/create-api-key",title:"\ud83d\udc50 Create an API key",description:"If you just created a new account or want to use an existing API key, skip to the last step to copy the API key.",source:"@site/docs/30-fireworks-ai/2-create-api-key.mdx",sourceDirName:"30-fireworks-ai",slug:"/fireworks-ai/create-api-key",permalink:"/ai-rag-lab/docs/fireworks-ai/create-api-key",draft:!1,unlisted:!1,editUrl:"https://github.com/mongodb-developer/ai-rag-lab/blob/main/docs/30-fireworks-ai/2-create-api-key.mdx",tags:[],version:"current",sidebarPosition:2,frontMatter:{},sidebar:"tutorialSidebar",previous:{title:"\ud83d\udc50 Create an account",permalink:"/ai-rag-lab/docs/fireworks-ai/create-account"},next:{title:"Dev Environment",permalink:"/ai-rag-lab/docs/category/dev-environment"}},l={},p=[];function d(e){const t={h1:"h1",p:"p",strong:"strong",...(0,r.R)(),...e.components};return(0,s.jsxs)(s.Fragment,{children:[(0,s.jsx)(t.h1,{id:"-create-an-api-key",children:"\ud83d\udc50 Create an API key"}),"\n",(0,s.jsx)(t.p,{children:(0,s.jsx)(t.strong,{children:"If you just created a new account or want to use an existing API key, skip to the last step to copy the API key."})}),"\n",(0,s.jsx)(t.p,{children:"If you already have a Fireworks account and want to create a new API key, follow the steps below."}),"\n",(0,s.jsxs)(t.p,{children:["Upon logging in, click the ",(0,s.jsx)(t.strong,{children:"API Keys"})," tab."]}),"\n",(0,s.jsx)(n.A,{url:"https://fireworks.ai/",src:"img/screenshots/30-fireworks-ai/2-create-api-key/1-api-key.png",alt:"Select API keys"}),"\n",(0,s.jsxs)(t.p,{children:["Click the purple ",(0,s.jsx)(t.strong,{children:"Create API Key"})," button. In the modal that appears, enter a name and click ",(0,s.jsx)(t.strong,{children:"Create Key"})," to create an API key."]}),"\n",(0,s.jsx)(n.A,{url:"https://fireworks.ai/",src:"img/screenshots/30-fireworks-ai/2-create-api-key/2-create-api-key.png",alt:"Create API key"}),"\n",(0,s.jsx)(t.p,{children:"Click the copy button next to your API key to copy it to your clipboard. Paste the API key somewhere safe."}),"\n",(0,s.jsx)(n.A,{url:"https://fireworks.ai/",src:"img/screenshots/30-fireworks-ai/2-create-api-key/3-copy-api-key.png",alt:"Copy API key"})]})}function u(e={}){const{wrapper:t}={...(0,r.R)(),...e.components};return t?(0,s.jsx)(t,{...e,children:(0,s.jsx)(d,{...e})}):d(e)}},1179:(e,t,a)=>{a.d(t,{A:()=>o});a(6540);var s=a(4848);function r(e){const t=e.url||"http://localhost:3000";return(0,s.jsxs)("div",{className:"browser container",children:[(0,s.jsxs)("div",{className:"row",children:[(0,s.jsxs)("div",{className:"column left",children:[(0,s.jsx)("span",{className:"dot",style:{background:"#ED594A"}}),(0,s.jsx)("span",{className:"dot",style:{background:"#FDD800"}}),(0,s.jsx)("span",{className:"dot",style:{background:"#5AC05A"}})]}),(0,s.jsx)("div",{className:"column middle",children:(0,s.jsx)("input",{type:"text",value:t})}),(0,s.jsx)("div",{className:"column right",children:(0,s.jsxs)("div",{style:{float:"right"},children:[(0,s.jsx)("span",{className:"bar"}),(0,s.jsx)("span",{className:"bar"}),(0,s.jsx)("span",{className:"bar"})]})})]}),(0,s.jsx)("div",{className:"content",children:e.children})]})}var n=a(8180);function o(e){return(0,s.jsx)(r,{...e,children:(0,s.jsx)("img",{src:(0,n.A)(e.src),alt:e.alt})})}},8453:(e,t,a)=>{a.d(t,{R:()=>o,x:()=>i});var s=a(6540);const r={},n=s.createContext(r);function o(e){const t=s.useContext(n);return s.useMemo((function(){return"function"==typeof e?e(t):{...t,...e}}),[t,e])}function i(e){let t;return t=e.disableParentContext?"function"==typeof e.components?e.components(r):e.components||r:o(e.components),s.createElement(n.Provider,{value:t},e.children)}}}]); \ No newline at end of file diff --git a/assets/js/ade674ed.99a0fb3b.js b/assets/js/ade674ed.99a0fb3b.js new file mode 100644 index 00000000..ca357a00 --- /dev/null +++ b/assets/js/ade674ed.99a0fb3b.js @@ -0,0 +1 @@ +"use strict";(self.webpackChunkai_rag_lab=self.webpackChunkai_rag_lab||[]).push([[888],{8022:(e,t,a)=>{a.r(t),a.d(t,{assets:()=>l,contentTitle:()=>o,default:()=>u,frontMatter:()=>i,metadata:()=>c,toc:()=>d});var r=a(4848),s=a(8453),n=a(1179);const i={},o="\ud83d\udc50 Create an API key",c={id:"fireworks-ai/create-api-key",title:"\ud83d\udc50 Create an API key",description:"To use the Fireworks API, you will need an API Key. To create a secure API key, follow the steps below.",source:"@site/docs/30-fireworks-ai/2-create-api-key.mdx",sourceDirName:"30-fireworks-ai",slug:"/fireworks-ai/create-api-key",permalink:"/ai-rag-lab/docs/fireworks-ai/create-api-key",draft:!1,unlisted:!1,editUrl:"https://github.com/mongodb-developer/ai-rag-lab/blob/main/docs/30-fireworks-ai/2-create-api-key.mdx",tags:[],version:"current",sidebarPosition:2,frontMatter:{},sidebar:"tutorialSidebar",previous:{title:"\ud83d\udc50 Create an account",permalink:"/ai-rag-lab/docs/fireworks-ai/create-account"},next:{title:"Dev Environment",permalink:"/ai-rag-lab/docs/category/dev-environment"}},l={},d=[];function p(e){const t={h1:"h1",p:"p",strong:"strong",...(0,s.R)(),...e.components};return(0,r.jsxs)(r.Fragment,{children:[(0,r.jsx)(t.h1,{id:"-create-an-api-key",children:"\ud83d\udc50 Create an API key"}),"\n",(0,r.jsx)(t.p,{children:"To use the Fireworks API, you will need an API Key. To create a secure API key, follow the steps below."}),"\n",(0,r.jsxs)(t.p,{children:["Upon logging in, click the ",(0,r.jsx)(t.strong,{children:"User"})," tab."]}),"\n",(0,r.jsx)(n.A,{url:"https://fireworks.ai/",src:"img/screenshots/30-fireworks-ai/2-create-api-key/1-api-key.png",alt:"Select API keys"}),"\n",(0,r.jsxs)(t.p,{children:["Click the purple ",(0,r.jsx)(t.strong,{children:"Create API Key"})," button. In the modal that appears, enter a name and click ",(0,r.jsx)(t.strong,{children:"Create Key"})," to create an API key."]}),"\n",(0,r.jsx)(n.A,{url:"https://fireworks.ai/",src:"img/screenshots/30-fireworks-ai/2-create-api-key/2-create-api-key.png",alt:"Create API key"}),"\n",(0,r.jsx)(t.p,{children:"When prompted, copy the API key to a safe location."})]})}function u(e={}){const{wrapper:t}={...(0,s.R)(),...e.components};return t?(0,r.jsx)(t,{...e,children:(0,r.jsx)(p,{...e})}):p(e)}},1179:(e,t,a)=>{a.d(t,{A:()=>i});a(6540);var r=a(4848);function s(e){const t=e.url||"http://localhost:3000";return(0,r.jsxs)("div",{className:"browser container",children:[(0,r.jsxs)("div",{className:"row",children:[(0,r.jsxs)("div",{className:"column left",children:[(0,r.jsx)("span",{className:"dot",style:{background:"#ED594A"}}),(0,r.jsx)("span",{className:"dot",style:{background:"#FDD800"}}),(0,r.jsx)("span",{className:"dot",style:{background:"#5AC05A"}})]}),(0,r.jsx)("div",{className:"column middle",children:(0,r.jsx)("input",{type:"text",value:t})}),(0,r.jsx)("div",{className:"column right",children:(0,r.jsxs)("div",{style:{float:"right"},children:[(0,r.jsx)("span",{className:"bar"}),(0,r.jsx)("span",{className:"bar"}),(0,r.jsx)("span",{className:"bar"})]})})]}),(0,r.jsx)("div",{className:"content",children:e.children})]})}var n=a(8180);function i(e){return(0,r.jsx)(s,{...e,children:(0,r.jsx)("img",{src:(0,n.A)(e.src),alt:e.alt})})}},8453:(e,t,a)=>{a.d(t,{R:()=>i,x:()=>o});var r=a(6540);const s={},n=r.createContext(s);function i(e){const t=r.useContext(n);return r.useMemo((function(){return"function"==typeof e?e(t):{...t,...e}}),[t,e])}function o(e){let t;return t=e.disableParentContext?"function"==typeof e.components?e.components(s):e.components||s:i(e.components),r.createElement(n.Provider,{value:t},e.children)}}}]); \ No newline at end of file diff --git a/assets/js/runtime~main.5284819a.js b/assets/js/runtime~main.c932e1c0.js similarity index 95% rename from assets/js/runtime~main.5284819a.js rename to assets/js/runtime~main.c932e1c0.js index b80deeb8..94f82538 100644 --- a/assets/js/runtime~main.5284819a.js +++ b/assets/js/runtime~main.c932e1c0.js @@ -1 +1 @@ -(()=>{"use strict";var e,a,r,t,f,c={},d={};function o(e){var a=d[e];if(void 0!==a)return a.exports;var r=d[e]={exports:{}};return c[e].call(r.exports,r,r.exports,o),r.exports}o.m=c,e=[],o.O=(a,r,t,f)=>{if(!r){var c=1/0;for(i=0;i=f)&&Object.keys(o.O).every((e=>o.O[e](r[b])))?r.splice(b--,1):(d=!1,f0&&e[i-1][2]>f;i--)e[i]=e[i-1];e[i]=[r,t,f]},o.n=e=>{var a=e&&e.__esModule?()=>e.default:()=>e;return o.d(a,{a:a}),a},r=Object.getPrototypeOf?e=>Object.getPrototypeOf(e):e=>e.__proto__,o.t=function(e,t){if(1&t&&(e=this(e)),8&t)return e;if("object"==typeof e&&e){if(4&t&&e.__esModule)return e;if(16&t&&"function"==typeof e.then)return e}var f=Object.create(null);o.r(f);var c={};a=a||[null,r({}),r([]),r(r)];for(var d=2&t&&e;"object"==typeof d&&!~a.indexOf(d);d=r(d))Object.getOwnPropertyNames(d).forEach((a=>c[a]=()=>e[a]));return c.default=()=>e,o.d(f,c),f},o.d=(e,a)=>{for(var r in a)o.o(a,r)&&!o.o(e,r)&&Object.defineProperty(e,r,{enumerable:!0,get:a[r]})},o.f={},o.e=e=>Promise.all(Object.keys(o.f).reduce(((a,r)=>(o.f[r](e,a),a)),[])),o.u=e=>"assets/js/"+({24:"0e16189c",48:"a94703ab",93:"3aaaf183",98:"a7bd4aaa",142:"d6501d9d",186:"86a88343",199:"412449fd",214:"e962eb68",254:"400dfa73",256:"72d756b8",260:"798f680c",262:"8be1a27a",264:"71a1ca8e",290:"a17e1ad5",301:"6e787a66",350:"45b31a90",401:"17896441",426:"a541a3e1",454:"47cd1b4f",458:"2a2ea0d2",459:"f23f5105",462:"3bf69056",507:"843aaef4",548:"49a3b57d",581:"935f2afb",634:"c4f5d8e4",647:"5e95c892",676:"e6ef851e",710:"d09226b2",711:"7a749954",722:"8e28e76d",723:"c8620672",730:"6bb24948",807:"350ab7ce",839:"6effaccf",850:"36d48778",888:"ade674ed",902:"fa1a64f0",903:"f8409a7e",906:"bac890e3",969:"14eb3368",970:"88870176",983:"88a0bd0a",988:"36c22dfc"}[e]||e)+"."+{24:"30561a78",48:"d13df985",93:"43320edc",98:"80c64d81",142:"bbd6be5f",186:"24b0994d",199:"40d85668",214:"a5640a76",254:"184a7b29",256:"6f853c74",260:"7474a8ee",262:"32bf80d7",264:"eb8eb148",290:"e3ab0070",301:"8776d2c8",350:"1e1e7bb2",401:"a68ad7e9",426:"b7a6b495",454:"eeed1185",458:"cbbe08f4",459:"a61891e2",462:"2d31350d",507:"55423b8b",548:"9434d500",560:"a9c1cb91",581:"8fc15c94",634:"f3a98f32",647:"ad038dcd",676:"5c9e4a8a",710:"3ce758ff",711:"5da4c1f2",722:"8cdd0315",723:"afc66b2e",730:"a8c7173d",807:"e4dd0929",839:"43550ce6",850:"5c024004",888:"52ec81a8",902:"5b2741a5",903:"f0cad3c3",904:"497d6008",906:"68591a79",969:"f8033aa7",970:"6337458e",983:"6aa81761",988:"b38987cc"}[e]+".js",o.miniCssF=e=>{},o.g=function(){if("object"==typeof globalThis)return globalThis;try{return this||new Function("return this")()}catch(e){if("object"==typeof window)return window}}(),o.o=(e,a)=>Object.prototype.hasOwnProperty.call(e,a),t={},f="ai-rag-lab:",o.l=(e,a,r,c)=>{if(t[e])t[e].push(a);else{var d,b;if(void 0!==r)for(var n=document.getElementsByTagName("script"),i=0;i{d.onerror=d.onload=null,clearTimeout(s);var f=t[e];if(delete t[e],d.parentNode&&d.parentNode.removeChild(d),f&&f.forEach((e=>e(r))),a)return a(r)},s=setTimeout(u.bind(null,void 0,{type:"timeout",target:d}),12e4);d.onerror=u.bind(null,d.onerror),d.onload=u.bind(null,d.onload),b&&document.head.appendChild(d)}},o.r=e=>{"undefined"!=typeof Symbol&&Symbol.toStringTag&&Object.defineProperty(e,Symbol.toStringTag,{value:"Module"}),Object.defineProperty(e,"__esModule",{value:!0})},o.p="/ai-rag-lab/",o.gca=function(e){return e={17896441:"401",88870176:"970","0e16189c":"24",a94703ab:"48","3aaaf183":"93",a7bd4aaa:"98",d6501d9d:"142","86a88343":"186","412449fd":"199",e962eb68:"214","400dfa73":"254","72d756b8":"256","798f680c":"260","8be1a27a":"262","71a1ca8e":"264",a17e1ad5:"290","6e787a66":"301","45b31a90":"350",a541a3e1:"426","47cd1b4f":"454","2a2ea0d2":"458",f23f5105:"459","3bf69056":"462","843aaef4":"507","49a3b57d":"548","935f2afb":"581",c4f5d8e4:"634","5e95c892":"647",e6ef851e:"676",d09226b2:"710","7a749954":"711","8e28e76d":"722",c8620672:"723","6bb24948":"730","350ab7ce":"807","6effaccf":"839","36d48778":"850",ade674ed:"888",fa1a64f0:"902",f8409a7e:"903",bac890e3:"906","14eb3368":"969","88a0bd0a":"983","36c22dfc":"988"}[e]||e,o.p+o.u(e)},(()=>{var e={354:0,869:0};o.f.j=(a,r)=>{var t=o.o(e,a)?e[a]:void 0;if(0!==t)if(t)r.push(t[2]);else if(/^(354|869)$/.test(a))e[a]=0;else{var f=new Promise(((r,f)=>t=e[a]=[r,f]));r.push(t[2]=f);var c=o.p+o.u(a),d=new Error;o.l(c,(r=>{if(o.o(e,a)&&(0!==(t=e[a])&&(e[a]=void 0),t)){var f=r&&("load"===r.type?"missing":r.type),c=r&&r.target&&r.target.src;d.message="Loading chunk "+a+" failed.\n("+f+": "+c+")",d.name="ChunkLoadError",d.type=f,d.request=c,t[1](d)}}),"chunk-"+a,a)}},o.O.j=a=>0===e[a];var a=(a,r)=>{var t,f,c=r[0],d=r[1],b=r[2],n=0;if(c.some((a=>0!==e[a]))){for(t in d)o.o(d,t)&&(o.m[t]=d[t]);if(b)var i=b(o)}for(a&&a(r);n{"use strict";var e,a,r,t,f,c={},d={};function o(e){var a=d[e];if(void 0!==a)return a.exports;var r=d[e]={exports:{}};return c[e].call(r.exports,r,r.exports,o),r.exports}o.m=c,e=[],o.O=(a,r,t,f)=>{if(!r){var c=1/0;for(i=0;i=f)&&Object.keys(o.O).every((e=>o.O[e](r[b])))?r.splice(b--,1):(d=!1,f0&&e[i-1][2]>f;i--)e[i]=e[i-1];e[i]=[r,t,f]},o.n=e=>{var a=e&&e.__esModule?()=>e.default:()=>e;return o.d(a,{a:a}),a},r=Object.getPrototypeOf?e=>Object.getPrototypeOf(e):e=>e.__proto__,o.t=function(e,t){if(1&t&&(e=this(e)),8&t)return e;if("object"==typeof e&&e){if(4&t&&e.__esModule)return e;if(16&t&&"function"==typeof e.then)return e}var f=Object.create(null);o.r(f);var c={};a=a||[null,r({}),r([]),r(r)];for(var d=2&t&&e;"object"==typeof d&&!~a.indexOf(d);d=r(d))Object.getOwnPropertyNames(d).forEach((a=>c[a]=()=>e[a]));return c.default=()=>e,o.d(f,c),f},o.d=(e,a)=>{for(var r in a)o.o(a,r)&&!o.o(e,r)&&Object.defineProperty(e,r,{enumerable:!0,get:a[r]})},o.f={},o.e=e=>Promise.all(Object.keys(o.f).reduce(((a,r)=>(o.f[r](e,a),a)),[])),o.u=e=>"assets/js/"+({24:"0e16189c",48:"a94703ab",93:"3aaaf183",98:"a7bd4aaa",142:"d6501d9d",186:"86a88343",199:"412449fd",214:"e962eb68",254:"400dfa73",256:"72d756b8",260:"798f680c",262:"8be1a27a",264:"71a1ca8e",290:"a17e1ad5",301:"6e787a66",350:"45b31a90",401:"17896441",426:"a541a3e1",454:"47cd1b4f",458:"2a2ea0d2",459:"f23f5105",462:"3bf69056",507:"843aaef4",548:"49a3b57d",581:"935f2afb",634:"c4f5d8e4",647:"5e95c892",676:"e6ef851e",710:"d09226b2",711:"7a749954",722:"8e28e76d",723:"c8620672",730:"6bb24948",807:"350ab7ce",839:"6effaccf",850:"36d48778",888:"ade674ed",902:"fa1a64f0",903:"f8409a7e",906:"bac890e3",969:"14eb3368",970:"88870176",983:"88a0bd0a",988:"36c22dfc"}[e]||e)+"."+{24:"30561a78",48:"d13df985",93:"43320edc",98:"80c64d81",142:"bbd6be5f",186:"be9144b8",199:"40d85668",214:"a5640a76",254:"184a7b29",256:"6f853c74",260:"7474a8ee",262:"a8147315",264:"eb8eb148",290:"e3ab0070",301:"8776d2c8",350:"1e1e7bb2",401:"a68ad7e9",426:"b7a6b495",454:"eeed1185",458:"cbbe08f4",459:"a61891e2",462:"2d31350d",507:"55423b8b",548:"9434d500",560:"a9c1cb91",581:"5728985f",634:"f3a98f32",647:"ad038dcd",676:"5c9e4a8a",710:"3ce758ff",711:"5da4c1f2",722:"8cdd0315",723:"afc66b2e",730:"a8c7173d",807:"e4dd0929",839:"43550ce6",850:"5c024004",888:"99a0fb3b",902:"5b2741a5",903:"f0cad3c3",904:"497d6008",906:"68591a79",969:"f8033aa7",970:"6337458e",983:"6aa81761",988:"b38987cc"}[e]+".js",o.miniCssF=e=>{},o.g=function(){if("object"==typeof globalThis)return globalThis;try{return this||new Function("return this")()}catch(e){if("object"==typeof window)return window}}(),o.o=(e,a)=>Object.prototype.hasOwnProperty.call(e,a),t={},f="ai-rag-lab:",o.l=(e,a,r,c)=>{if(t[e])t[e].push(a);else{var d,b;if(void 0!==r)for(var n=document.getElementsByTagName("script"),i=0;i{d.onerror=d.onload=null,clearTimeout(s);var f=t[e];if(delete t[e],d.parentNode&&d.parentNode.removeChild(d),f&&f.forEach((e=>e(r))),a)return a(r)},s=setTimeout(u.bind(null,void 0,{type:"timeout",target:d}),12e4);d.onerror=u.bind(null,d.onerror),d.onload=u.bind(null,d.onload),b&&document.head.appendChild(d)}},o.r=e=>{"undefined"!=typeof Symbol&&Symbol.toStringTag&&Object.defineProperty(e,Symbol.toStringTag,{value:"Module"}),Object.defineProperty(e,"__esModule",{value:!0})},o.p="/ai-rag-lab/",o.gca=function(e){return e={17896441:"401",88870176:"970","0e16189c":"24",a94703ab:"48","3aaaf183":"93",a7bd4aaa:"98",d6501d9d:"142","86a88343":"186","412449fd":"199",e962eb68:"214","400dfa73":"254","72d756b8":"256","798f680c":"260","8be1a27a":"262","71a1ca8e":"264",a17e1ad5:"290","6e787a66":"301","45b31a90":"350",a541a3e1:"426","47cd1b4f":"454","2a2ea0d2":"458",f23f5105:"459","3bf69056":"462","843aaef4":"507","49a3b57d":"548","935f2afb":"581",c4f5d8e4:"634","5e95c892":"647",e6ef851e:"676",d09226b2:"710","7a749954":"711","8e28e76d":"722",c8620672:"723","6bb24948":"730","350ab7ce":"807","6effaccf":"839","36d48778":"850",ade674ed:"888",fa1a64f0:"902",f8409a7e:"903",bac890e3:"906","14eb3368":"969","88a0bd0a":"983","36c22dfc":"988"}[e]||e,o.p+o.u(e)},(()=>{var e={354:0,869:0};o.f.j=(a,r)=>{var t=o.o(e,a)?e[a]:void 0;if(0!==t)if(t)r.push(t[2]);else if(/^(354|869)$/.test(a))e[a]=0;else{var f=new Promise(((r,f)=>t=e[a]=[r,f]));r.push(t[2]=f);var c=o.p+o.u(a),d=new Error;o.l(c,(r=>{if(o.o(e,a)&&(0!==(t=e[a])&&(e[a]=void 0),t)){var f=r&&("load"===r.type?"missing":r.type),c=r&&r.target&&r.target.src;d.message="Loading chunk "+a+" failed.\n("+f+": "+c+")",d.name="ChunkLoadError",d.type=f,d.request=c,t[1](d)}}),"chunk-"+a,a)}},o.O.j=a=>0===e[a];var a=(a,r)=>{var t,f,c=r[0],d=r[1],b=r[2],n=0;if(c.some((a=>0!==e[a]))){for(t in d)o.o(d,t)&&(o.m[t]=d[t]);if(b)var i=b(o)}for(a&&a(r);n - + diff --git a/docs/add-memory/concepts.html b/docs/add-memory/concepts.html index 9b92dd80..d91c7a4f 100644 --- a/docs/add-memory/concepts.html +++ b/docs/add-memory/concepts.html @@ -7,7 +7,7 @@ - + diff --git a/docs/build-rag-app/add-reranking.html b/docs/build-rag-app/add-reranking.html index 4b880a07..89a8c54d 100644 --- a/docs/build-rag-app/add-reranking.html +++ b/docs/build-rag-app/add-reranking.html @@ -7,7 +7,7 @@ - + diff --git a/docs/build-rag-app/build-rag-app.html b/docs/build-rag-app/build-rag-app.html index 38738d6b..b041c7cd 100644 --- a/docs/build-rag-app/build-rag-app.html +++ b/docs/build-rag-app/build-rag-app.html @@ -7,7 +7,7 @@ - + diff --git a/docs/build-rag-app/stream-responses.html b/docs/build-rag-app/stream-responses.html index 7ef5ff6e..340db31f 100644 --- a/docs/build-rag-app/stream-responses.html +++ b/docs/build-rag-app/stream-responses.html @@ -7,7 +7,7 @@ - + diff --git a/docs/category/add-memory-to-the-rag-application.html b/docs/category/add-memory-to-the-rag-application.html index ee693c1f..0de5e88d 100644 --- a/docs/category/add-memory-to-the-rag-application.html +++ b/docs/category/add-memory-to-the-rag-application.html @@ -7,7 +7,7 @@ - + diff --git a/docs/category/build-the-rag-application.html b/docs/category/build-the-rag-application.html index 2eea6cf0..f25d298e 100644 --- a/docs/category/build-the-rag-application.html +++ b/docs/category/build-the-rag-application.html @@ -7,7 +7,7 @@ - + diff --git a/docs/category/dev-environment.html b/docs/category/dev-environment.html index e4314d60..45a6d34c 100644 --- a/docs/category/dev-environment.html +++ b/docs/category/dev-environment.html @@ -7,7 +7,7 @@ - + diff --git a/docs/category/fireworks-ai.html b/docs/category/fireworks-ai.html index fc1496f8..f08989b9 100644 --- a/docs/category/fireworks-ai.html +++ b/docs/category/fireworks-ai.html @@ -7,10 +7,10 @@ - + -

Fireworks AI

Create a Fireworks AI account and API key.

+

Fireworks AI

Create a Fireworks AI account and API key.

\ No newline at end of file diff --git a/docs/category/mongodb-atlas.html b/docs/category/mongodb-atlas.html index a8aedafa..c484b085 100644 --- a/docs/category/mongodb-atlas.html +++ b/docs/category/mongodb-atlas.html @@ -7,7 +7,7 @@ - + diff --git a/docs/category/perform-semantic-search-on-your-data.html b/docs/category/perform-semantic-search-on-your-data.html index b8eb2ff6..e91b66cb 100644 --- a/docs/category/perform-semantic-search-on-your-data.html +++ b/docs/category/perform-semantic-search-on-your-data.html @@ -7,10 +7,10 @@ - + -

Perform Semantic Search on Your Data

Retrieve semantically relevant documents to the user query using vector search.

+

Perform Semantic Search on Your Data

Retrieve semantically relevant documents to the user query using vector search.

\ No newline at end of file diff --git a/docs/category/prepare-the-data.html b/docs/category/prepare-the-data.html index 90d80ba1..d282974e 100644 --- a/docs/category/prepare-the-data.html +++ b/docs/category/prepare-the-data.html @@ -7,7 +7,7 @@ - + diff --git a/docs/category/retrieval-augmented-generation.html b/docs/category/retrieval-augmented-generation.html index 765b7718..b0b54347 100644 --- a/docs/category/retrieval-augmented-generation.html +++ b/docs/category/retrieval-augmented-generation.html @@ -7,7 +7,7 @@ - + diff --git a/docs/dev-env/dev-setup.html b/docs/dev-env/dev-setup.html index 7b229963..b7dd1be5 100644 --- a/docs/dev-env/dev-setup.html +++ b/docs/dev-env/dev-setup.html @@ -7,7 +7,7 @@ - + diff --git a/docs/dev-env/setup-pre-reqs.html b/docs/dev-env/setup-pre-reqs.html index 29767475..cc0cfbe8 100644 --- a/docs/dev-env/setup-pre-reqs.html +++ b/docs/dev-env/setup-pre-reqs.html @@ -7,7 +7,7 @@ - + diff --git a/docs/fireworks-ai/create-account.html b/docs/fireworks-ai/create-account.html index b52f9a4c..75ffaf73 100644 --- a/docs/fireworks-ai/create-account.html +++ b/docs/fireworks-ai/create-account.html @@ -7,7 +7,7 @@ - + @@ -16,7 +16,7 @@

The easiest way to use the model is via the Fireworks API. But first, you will need to create a Fireworks account. If you already have an account, you can skip the following steps and move on to the next section.

Start by navigating to the Fireworks AI homepage and click the purple Get Started Free button to create an account.

Get started
-

Click Login With Google and authenticate with your Google account. This will provision a new Fireworks account and API Key for you.

+

Click Login With Google and authenticate with your Google account. This will provision a new Fireworks account for you.

Login
\ No newline at end of file diff --git a/docs/fireworks-ai/create-api-key.html b/docs/fireworks-ai/create-api-key.html index 26e9e479..60314655 100644 --- a/docs/fireworks-ai/create-api-key.html +++ b/docs/fireworks-ai/create-api-key.html @@ -3,22 +3,20 @@ -👐 Create an API key | Build RAG Applications using MongoDB +👐 Create an API key | Build RAG Applications using MongoDB - +

👐 Create an API key

-

If you just created a new account or want to use an existing API key, skip to the last step to copy the API key.

-

If you already have a Fireworks account and want to create a new API key, follow the steps below.

-

Upon logging in, click the API Keys tab.

+

To use the Fireworks API, you will need an API Key. To create a secure API key, follow the steps below.

+

Upon logging in, click the User tab.

Select API keys

Click the purple Create API Key button. In the modal that appears, enter a name and click Create Key to create an API key.

Create API key
-

Click the copy button next to your API key to copy it to your clipboard. Paste the API key somewhere safe.

-
Copy API key
+

When prompted, copy the API key to a safe location.

\ No newline at end of file diff --git a/docs/intro.html b/docs/intro.html index 57c25aaa..9416974d 100644 --- a/docs/intro.html +++ b/docs/intro.html @@ -7,7 +7,7 @@ - + diff --git a/docs/mongodb-atlas/create-account.html b/docs/mongodb-atlas/create-account.html index 7c77222b..a93833d5 100644 --- a/docs/mongodb-atlas/create-account.html +++ b/docs/mongodb-atlas/create-account.html @@ -7,7 +7,7 @@ - + diff --git a/docs/mongodb-atlas/create-cluster.html b/docs/mongodb-atlas/create-cluster.html index 5d763e68..977047b8 100644 --- a/docs/mongodb-atlas/create-cluster.html +++ b/docs/mongodb-atlas/create-cluster.html @@ -7,7 +7,7 @@ - + diff --git a/docs/mongodb-atlas/get-connection-string.html b/docs/mongodb-atlas/get-connection-string.html index c3b3cb72..9ccf7994 100644 --- a/docs/mongodb-atlas/get-connection-string.html +++ b/docs/mongodb-atlas/get-connection-string.html @@ -7,7 +7,7 @@ - + diff --git a/docs/perform-semantic-search/concepts.html b/docs/perform-semantic-search/concepts.html index 4b138a49..df2e913e 100644 --- a/docs/perform-semantic-search/concepts.html +++ b/docs/perform-semantic-search/concepts.html @@ -7,7 +7,7 @@ - + diff --git a/docs/perform-semantic-search/create-vector-index.html b/docs/perform-semantic-search/create-vector-index.html index 1d2e895f..fe75d5f7 100644 --- a/docs/perform-semantic-search/create-vector-index.html +++ b/docs/perform-semantic-search/create-vector-index.html @@ -7,7 +7,7 @@ - + diff --git a/docs/perform-semantic-search/pre-filtering.html b/docs/perform-semantic-search/pre-filtering.html index e0366f2f..767a2499 100644 --- a/docs/perform-semantic-search/pre-filtering.html +++ b/docs/perform-semantic-search/pre-filtering.html @@ -3,28 +3,35 @@ -🦹 Combine pre-filtering with vector search | Build RAG Applications using MongoDB +🦹 Combine pre-filtering with vector search | Build RAG Applications using MongoDB - +

🦹 Combine pre-filtering with vector search

-

Pre-filtering a technique to optimize vector search by only considering documents that match certain criteria during vector search.

+

Pre-filtering is a technique to optimize vector search by only considering documents that match certain criteria during vector search.

+

In this section, you will learn how to combine filters with vector search. This mainly involves:

+
    +
  • Updating the vector search index to include the appropriate filter fields
    • +
  • Updating the $vectorSearch stage in the aggregation pipeline definition to include the filters
    • +

Filter for documents where the content type is Video​

-

To do this, you will first need to modify the vector search index you created previously. The new index definition should look as follows:

+

To do this, you will first need to modify the vector search index you created previously.

+

Updated index definition

Answer
{
  "fields": [
    {
      "type": "vector",
      "path": "embedding",
      "numDimensions": 384,
      "similarity": "cosine"
    },
    {
      "type":"filter",
      "path":"metadata.contentType"
    }
  ]
}
-

Once you have updated the vector search index, fill in <CODE_BLOCK_11> and run the cells under the Filter for documents where the content type is Video section in the notebook to see how the filter impacts the vector search results.

-

The answer for this code block is as follows:

+

Once you have updated the vector search index, fill in any <CODE_BLOCK_N> placeholders and run the cells under the Filter for documents where the content type is Video section in the notebook to see how the filter impacts the vector search results.

+

The answers for code blocks in this section are as follows:

CODE_BLOCK_11

Answer
[
    {
        "$vectorSearch": {
            "index": "vector_index",
            "path": "embedding",
            "queryVector": query_embedding,
            "numCandidates": 150,
            "limit": 5,
            "filter": {"metadata.contentType": "Video"}
        }
    },
    {
        "$project": {
            "_id": 0,
            "body": 1,
            "score": {"$meta": "vectorSearchScore"}
        }
    }
]

Filter on documents which have been updated on or after 2024-05-19 and where the content type is Tutorial​

-

Again, you will need to modify the vector search index. The new index definition should look as follows:

+

Again, you will first need to modify the vector search index.

+

Updated index definition

Answer
{
  "fields": [
    {
      "type": "vector",
      "path": "embedding",
      "numDimensions": 384,
      "similarity": "cosine"
    },
    {
      "type":"filter",
      "path":"metadata.contentType"
    },
    {
      "type":"filter",
      "path":"updated"
    }
  ]
}
-

Once you have updated the vector search index, fill in <CODE_BLOCK_12> and run the cells under the Filter on documents which have been updated on or after 2024-05-19 and where the content type is Tutorial section in the notebook to see how the filter impacts the vector search results.

-

The answer for this code block is as follows:

+

Once you have updated the vector search index, fill in any <CODE_BLOCK_N> placeholders and run the cells under the Filter on documents which have been updated on or after 2024-05-19 and where the content type is Tutorial section in the notebook to see how the filter impacts the vector search results.

+

The answers for code blocks in this section are as follows:

CODE_BLOCK_12

Answer
[
    {
        "$vectorSearch": {
            "index": "vector_index",
            "path": "embedding",
            "queryVector": query_embedding,
            "numCandidates": 150,
            "limit": 5,
            "filter": {
                "metadata.contentType": "Tutorial",
                "updated": {"$gte": "2024-05-19"}
            }
        }
    },
    {
        "$project": {
            "_id": 0,
            "body": 1,
            "score": {"$meta": "vectorSearchScore"}
        }
    }
]
diff --git a/docs/perform-semantic-search/vector-search.html b/docs/perform-semantic-search/vector-search.html index be97cd03..bd9dfe75 100644 --- a/docs/perform-semantic-search/vector-search.html +++ b/docs/perform-semantic-search/vector-search.html @@ -7,7 +7,7 @@ - + diff --git a/docs/prepare-the-data/chunk-data.html b/docs/prepare-the-data/chunk-data.html index 63a4d523..aebf5a59 100644 --- a/docs/prepare-the-data/chunk-data.html +++ b/docs/prepare-the-data/chunk-data.html @@ -7,7 +7,7 @@ - + diff --git a/docs/prepare-the-data/concepts.html b/docs/prepare-the-data/concepts.html index 2f9c774b..2d4a9898 100644 --- a/docs/prepare-the-data/concepts.html +++ b/docs/prepare-the-data/concepts.html @@ -7,7 +7,7 @@ - + diff --git a/docs/prepare-the-data/embed-data.html b/docs/prepare-the-data/embed-data.html index 9b0840d2..b132c96d 100644 --- a/docs/prepare-the-data/embed-data.html +++ b/docs/prepare-the-data/embed-data.html @@ -7,7 +7,7 @@ - + diff --git a/docs/prepare-the-data/ingest-data.html b/docs/prepare-the-data/ingest-data.html index 624aef7f..be01c897 100644 --- a/docs/prepare-the-data/ingest-data.html +++ b/docs/prepare-the-data/ingest-data.html @@ -7,7 +7,7 @@ - + diff --git a/docs/prepare-the-data/load-data.html b/docs/prepare-the-data/load-data.html index 14371379..36ddc1e1 100644 --- a/docs/prepare-the-data/load-data.html +++ b/docs/prepare-the-data/load-data.html @@ -7,7 +7,7 @@ - + diff --git a/docs/rag/components-of-rag.html b/docs/rag/components-of-rag.html index 51694e11..d0e34e09 100644 --- a/docs/rag/components-of-rag.html +++ b/docs/rag/components-of-rag.html @@ -7,7 +7,7 @@ - + diff --git a/docs/rag/rag-usecases.html b/docs/rag/rag-usecases.html index 7802e564..5dc7ae30 100644 --- a/docs/rag/rag-usecases.html +++ b/docs/rag/rag-usecases.html @@ -7,7 +7,7 @@ - + diff --git a/docs/rag/what-is-rag.html b/docs/rag/what-is-rag.html index 4aea44a1..d43d7371 100644 --- a/docs/rag/what-is-rag.html +++ b/docs/rag/what-is-rag.html @@ -7,7 +7,7 @@ - + diff --git a/docs/summary.html b/docs/summary.html index 116e7a1d..261b5fec 100644 --- a/docs/summary.html +++ b/docs/summary.html @@ -7,7 +7,7 @@ - + diff --git a/helloWorld.html b/helloWorld.html index a660513d..66b7c9e4 100644 --- a/helloWorld.html +++ b/helloWorld.html @@ -7,7 +7,7 @@ - + diff --git a/img/screenshots/30-fireworks-ai/2-create-api-key/1-api-key.png b/img/screenshots/30-fireworks-ai/2-create-api-key/1-api-key.png index b4378356..f2e4d939 100644 Binary files a/img/screenshots/30-fireworks-ai/2-create-api-key/1-api-key.png and b/img/screenshots/30-fireworks-ai/2-create-api-key/1-api-key.png differ diff --git a/img/screenshots/30-fireworks-ai/2-create-api-key/2-create-api-key.png b/img/screenshots/30-fireworks-ai/2-create-api-key/2-create-api-key.png index 3043db16..3699c7a6 100644 Binary files a/img/screenshots/30-fireworks-ai/2-create-api-key/2-create-api-key.png and b/img/screenshots/30-fireworks-ai/2-create-api-key/2-create-api-key.png differ diff --git a/img/screenshots/30-fireworks-ai/2-create-api-key/3-copy-api-key.png b/img/screenshots/30-fireworks-ai/2-create-api-key/3-copy-api-key.png deleted file mode 100644 index 5b3ba347..00000000 Binary files a/img/screenshots/30-fireworks-ai/2-create-api-key/3-copy-api-key.png and /dev/null differ diff --git a/index.html b/index.html index cef4bb87..fd72ad0b 100644 --- a/index.html +++ b/index.html @@ -7,7 +7,7 @@ - + diff --git a/search-index-docs-default-current.json b/search-index-docs-default-current.json index e4a3ce1d..a54147dd 100644 --- a/search-index-docs-default-current.json +++ b/search-index-docs-default-current.json @@ -1 +1 @@ -{"documents":[{"id":2,"pageTitle":"👐 Add memory to the RAG application","sectionTitle":"👐 Add memory to the RAG application","sectionRoute":"/ai-rag-lab/docs/add-memory/add-memory","type":"docs"},{"id":1,"pageTitle":"📘 Tools, libraries, and concepts","sectionTitle":"📘 Tools, libraries, and concepts","sectionRoute":"/ai-rag-lab/docs/add-memory/concepts","type":"docs"},{"id":3,"pageTitle":"🦹 Re-rank retrieved results","sectionTitle":"🦹 Re-rank retrieved results","sectionRoute":"/ai-rag-lab/docs/build-rag-app/add-reranking","type":"docs"},{"id":4,"pageTitle":"👐 Build the RAG application","sectionTitle":"👐 Build the RAG application","sectionRoute":"/ai-rag-lab/docs/build-rag-app/build-rag-app","type":"docs"},{"id":5,"pageTitle":"🦹 Stream responses from the RAG application","sectionTitle":"🦹 Stream responses from the RAG application","sectionRoute":"/ai-rag-lab/docs/build-rag-app/stream-responses","type":"docs"},{"id":9,"pageTitle":"","sectionTitle":"📄️ 📘 Tools, libraries, and concepts","sectionRoute":"/ai-rag-lab/docs/category/add-memory-to-the-rag-application","type":"docs"},{"id":10,"pageTitle":"","sectionTitle":"📄️ 👐 Add memory to the RAG application","sectionRoute":"/ai-rag-lab/docs/category/add-memory-to-the-rag-application","type":"docs"},{"id":6,"pageTitle":"","sectionTitle":"📄️ 👐 Build the RAG application","sectionRoute":"/ai-rag-lab/docs/category/build-the-rag-application","type":"docs"},{"id":7,"pageTitle":"","sectionTitle":"📄️ 🦹 Re-rank retrieved results","sectionRoute":"/ai-rag-lab/docs/category/build-the-rag-application","type":"docs"},{"id":8,"pageTitle":"","sectionTitle":"📄️ 🦹 Stream responses from the RAG application","sectionRoute":"/ai-rag-lab/docs/category/build-the-rag-application","type":"docs"},{"id":11,"pageTitle":"","sectionTitle":"📄️ 👐 Setup dev environment","sectionRoute":"/ai-rag-lab/docs/category/dev-environment","type":"docs"},{"id":12,"pageTitle":"","sectionTitle":"📄️ 👐 Setup prerequisites","sectionRoute":"/ai-rag-lab/docs/category/dev-environment","type":"docs"},{"id":13,"pageTitle":"","sectionTitle":"📄️ 👐 Create an account","sectionRoute":"/ai-rag-lab/docs/category/fireworks-ai","type":"docs"},{"id":14,"pageTitle":"","sectionTitle":"📄️ 👐 Create an API key","sectionRoute":"/ai-rag-lab/docs/category/fireworks-ai","type":"docs"},{"id":15,"pageTitle":"","sectionTitle":"📄️ 👐 Create your account","sectionRoute":"/ai-rag-lab/docs/category/mongodb-atlas","type":"docs"},{"id":16,"pageTitle":"","sectionTitle":"📄️ 👐 Deploy a database cluster","sectionRoute":"/ai-rag-lab/docs/category/mongodb-atlas","type":"docs"},{"id":17,"pageTitle":"","sectionTitle":"📄️ 👐 Get your connection string","sectionRoute":"/ai-rag-lab/docs/category/mongodb-atlas","type":"docs"},{"id":23,"pageTitle":"","sectionTitle":"📄️ 📘 Semantic search in MongoDB","sectionRoute":"/ai-rag-lab/docs/category/perform-semantic-search-on-your-data","type":"docs"},{"id":24,"pageTitle":"","sectionTitle":"📄️ 👐 Create a vector search index","sectionRoute":"/ai-rag-lab/docs/category/perform-semantic-search-on-your-data","type":"docs"},{"id":25,"pageTitle":"","sectionTitle":"📄️ 👐 Perform semantic search","sectionRoute":"/ai-rag-lab/docs/category/perform-semantic-search-on-your-data","type":"docs"},{"id":26,"pageTitle":"","sectionTitle":"📄️ 🦹 Combine pre-filtering with vector search","sectionRoute":"/ai-rag-lab/docs/category/perform-semantic-search-on-your-data","type":"docs"},{"id":18,"pageTitle":"","sectionTitle":"📄️ 📘 Tools, libraries, and concepts","sectionRoute":"/ai-rag-lab/docs/category/prepare-the-data","type":"docs"},{"id":19,"pageTitle":"","sectionTitle":"📄️ 👐 Load the dataset","sectionRoute":"/ai-rag-lab/docs/category/prepare-the-data","type":"docs"},{"id":20,"pageTitle":"","sectionTitle":"📄️ 👐 Chunk up the data","sectionRoute":"/ai-rag-lab/docs/category/prepare-the-data","type":"docs"},{"id":21,"pageTitle":"","sectionTitle":"📄️ 👐 Generate embeddings","sectionRoute":"/ai-rag-lab/docs/category/prepare-the-data","type":"docs"},{"id":22,"pageTitle":"","sectionTitle":"📄️ 👐 Ingest data into MongoDB","sectionRoute":"/ai-rag-lab/docs/category/prepare-the-data","type":"docs"},{"id":27,"pageTitle":"","sectionTitle":"📄️ 📘 What is RAG?","sectionRoute":"/ai-rag-lab/docs/category/retrieval-augmented-generation","type":"docs"},{"id":28,"pageTitle":"","sectionTitle":"📄️ 📘 When to use RAG?","sectionRoute":"/ai-rag-lab/docs/category/retrieval-augmented-generation","type":"docs"},{"id":29,"pageTitle":"","sectionTitle":"📄️ 📘 Components of a RAG system","sectionRoute":"/ai-rag-lab/docs/category/retrieval-augmented-generation","type":"docs"},{"id":40,"pageTitle":"👐 Setup dev environment","sectionTitle":"👐 Setup dev environment","sectionRoute":"/ai-rag-lab/docs/dev-env/dev-setup","type":"docs"},{"id":41,"pageTitle":"👐 Setup dev environment","sectionTitle":"Local setup","sectionRoute":"/ai-rag-lab/docs/dev-env/dev-setup#local-setup","type":"docs"},{"id":30,"pageTitle":"👐 Setup prerequisites","sectionTitle":"👐 Setup prerequisites","sectionRoute":"/ai-rag-lab/docs/dev-env/setup-pre-reqs","type":"docs"},{"id":31,"pageTitle":"👐 Create an account","sectionTitle":"👐 Create an account","sectionRoute":"/ai-rag-lab/docs/fireworks-ai/create-account","type":"docs"},{"id":33,"pageTitle":"👐 Create an API key","sectionTitle":"👐 Create an API key","sectionRoute":"/ai-rag-lab/docs/fireworks-ai/create-api-key","type":"docs"},{"id":32,"pageTitle":"Introduction","sectionTitle":"Introduction","sectionRoute":"/ai-rag-lab/docs/intro","type":"docs"},{"id":42,"pageTitle":"👐 Create your account","sectionTitle":"👐 Create your account","sectionRoute":"/ai-rag-lab/docs/mongodb-atlas/create-account","type":"docs"},{"id":43,"pageTitle":"👐 Create your account","sectionTitle":"Sign up for MongoDB Atlas","sectionRoute":"/ai-rag-lab/docs/mongodb-atlas/create-account#sign-up-for-mongodb-atlas","type":"docs"},{"id":44,"pageTitle":"👐 Create your account","sectionTitle":"Verify your email address","sectionRoute":"/ai-rag-lab/docs/mongodb-atlas/create-account#verify-your-email-address","type":"docs"},{"id":45,"pageTitle":"👐 Create your account","sectionTitle":"Finish the onboarding","sectionRoute":"/ai-rag-lab/docs/mongodb-atlas/create-account#finish-the-onboarding","type":"docs"},{"id":34,"pageTitle":"👐 Deploy a database cluster","sectionTitle":"👐 Deploy a database cluster","sectionRoute":"/ai-rag-lab/docs/mongodb-atlas/create-cluster","type":"docs"},{"id":35,"pageTitle":"👐 Deploy a database cluster","sectionTitle":"Security quickstart","sectionRoute":"/ai-rag-lab/docs/mongodb-atlas/create-cluster#security-quickstart","type":"docs"},{"id":36,"pageTitle":"👐 Deploy a database cluster","sectionTitle":"Network access","sectionRoute":"/ai-rag-lab/docs/mongodb-atlas/create-cluster#network-access","type":"docs"},{"id":37,"pageTitle":"👐 Deploy a database cluster","sectionTitle":"Database user","sectionRoute":"/ai-rag-lab/docs/mongodb-atlas/create-cluster#database-user","type":"docs"},{"id":38,"pageTitle":"👐 Deploy a database cluster","sectionTitle":"Manual network access configuration","sectionRoute":"/ai-rag-lab/docs/mongodb-atlas/create-cluster#manual-network-access-configuration","type":"docs"},{"id":39,"pageTitle":"👐 Deploy a database cluster","sectionTitle":"That's all!","sectionRoute":"/ai-rag-lab/docs/mongodb-atlas/create-cluster#thats-all","type":"docs"},{"id":46,"pageTitle":"👐 Get your connection string","sectionTitle":"👐 Get your connection string","sectionRoute":"/ai-rag-lab/docs/mongodb-atlas/get-connection-string","type":"docs"},{"id":47,"pageTitle":"📘 Semantic search in MongoDB","sectionTitle":"📘 Semantic search in MongoDB","sectionRoute":"/ai-rag-lab/docs/perform-semantic-search/concepts","type":"docs"},{"id":48,"pageTitle":"👐 Create a vector search index","sectionTitle":"👐 Create a vector search index","sectionRoute":"/ai-rag-lab/docs/perform-semantic-search/create-vector-index","type":"docs"},{"id":57,"pageTitle":"🦹 Combine pre-filtering with vector search","sectionTitle":"🦹 Combine pre-filtering with vector search","sectionRoute":"/ai-rag-lab/docs/perform-semantic-search/pre-filtering","type":"docs"},{"id":58,"pageTitle":"🦹 Combine pre-filtering with vector search","sectionTitle":"Filter for documents where the content type is Video","sectionRoute":"/ai-rag-lab/docs/perform-semantic-search/pre-filtering#filter-for-documents-where-the-content-type-is-video","type":"docs"},{"id":59,"pageTitle":"🦹 Combine pre-filtering with vector search","sectionTitle":"Filter on documents which have been updated on or after 2024-05-19 and where the content type is Tutorial","sectionRoute":"/ai-rag-lab/docs/perform-semantic-search/pre-filtering#filter-on-documents-which-have-been-updated-on-or-after-2024-05-19-and-where-the-content-type-is-tutorial","type":"docs"},{"id":50,"pageTitle":"👐 Perform semantic search","sectionTitle":"👐 Perform semantic search","sectionRoute":"/ai-rag-lab/docs/perform-semantic-search/vector-search","type":"docs"},{"id":49,"pageTitle":"👐 Chunk up the data","sectionTitle":"👐 Chunk up the data","sectionRoute":"/ai-rag-lab/docs/prepare-the-data/chunk-data","type":"docs"},{"id":51,"pageTitle":"📘 Tools, libraries, and concepts","sectionTitle":"📘 Tools, libraries, and concepts","sectionRoute":"/ai-rag-lab/docs/prepare-the-data/concepts","type":"docs"},{"id":52,"pageTitle":"📘 Tools, libraries, and concepts","sectionTitle":"datasets","sectionRoute":"/ai-rag-lab/docs/prepare-the-data/concepts#datasets","type":"docs"},{"id":53,"pageTitle":"📘 Tools, libraries, and concepts","sectionTitle":"RecursiveCharacterTextSplitter","sectionRoute":"/ai-rag-lab/docs/prepare-the-data/concepts#recursivecharactertextsplitter","type":"docs"},{"id":54,"pageTitle":"📘 Tools, libraries, and concepts","sectionTitle":"Sentence Transformers","sectionRoute":"/ai-rag-lab/docs/prepare-the-data/concepts#sentence-transformers","type":"docs"},{"id":55,"pageTitle":"📘 Tools, libraries, and concepts","sectionTitle":"PyMongo","sectionRoute":"/ai-rag-lab/docs/prepare-the-data/concepts#pymongo","type":"docs"},{"id":56,"pageTitle":"👐 Generate embeddings","sectionTitle":"👐 Generate embeddings","sectionRoute":"/ai-rag-lab/docs/prepare-the-data/embed-data","type":"docs"},{"id":61,"pageTitle":"👐 Ingest data into MongoDB","sectionTitle":"👐 Ingest data into MongoDB","sectionRoute":"/ai-rag-lab/docs/prepare-the-data/ingest-data","type":"docs"},{"id":60,"pageTitle":"👐 Load the dataset","sectionTitle":"👐 Load the dataset","sectionRoute":"/ai-rag-lab/docs/prepare-the-data/load-data","type":"docs"},{"id":62,"pageTitle":"📘 Components of a RAG system","sectionTitle":"📘 Components of a RAG system","sectionRoute":"/ai-rag-lab/docs/rag/components-of-rag","type":"docs"},{"id":63,"pageTitle":"📘 Components of a RAG system","sectionTitle":"Retrieval","sectionRoute":"/ai-rag-lab/docs/rag/components-of-rag#retrieval","type":"docs"},{"id":64,"pageTitle":"📘 Components of a RAG system","sectionTitle":"Generation","sectionRoute":"/ai-rag-lab/docs/rag/components-of-rag#generation","type":"docs"},{"id":66,"pageTitle":"📘 When to use RAG?","sectionTitle":"📘 When to use RAG?","sectionRoute":"/ai-rag-lab/docs/rag/rag-usecases","type":"docs"},{"id":65,"pageTitle":"📘 What is RAG?","sectionTitle":"📘 What is RAG?","sectionRoute":"/ai-rag-lab/docs/rag/what-is-rag","type":"docs"},{"id":67,"pageTitle":"🎯 Summary","sectionTitle":"🎯 Summary","sectionRoute":"/ai-rag-lab/docs/summary","type":"docs"}],"index":{"version":"2.3.9","fields":["title","content","tags"],"fieldVectors":[["title/2",[0,0.165,1,1.659,2,1.504,3,0.438,4,0.772]],["content/2",[1,2.307,2,2.45,3,0.714,4,1.457,5,2.331,6,2.546,7,1.689,8,2.015,9,2.339,10,2.546,11,2.546,12,2.331,13,1.326,14,2.159,15,0.988,16,2.546,17,2.159,18,1.785,19,1.883,20,2.546,21,3.664,22,2.546,23,2.546,24,2.331,25,1.665,26,0.912,27,1.785,28,2.159,29,2.546,30,0.383,31,1.525,32,1.785,33,1.525,34,1.029,35,1.326,36,1.165,37,0.842,38,2.546,39,1.216,40,1.388,41,1.603,42,0.949,43,3.274,44,3.274,45,3.274,46,3.274,47,3.274,48,3.274,49,3.274,50,1.525,51,3.274,52,3.274,53,3.274,54,3.274,55,1.603,56,4.079,57,3.274,58,3.274,59,3.274,60,3.274]],["tags/2",[]],["title/1",[0,0.183,61,1.744,62,1.516,63,1.744]],["content/1",[2,1.828,9,2.342,12,2.931,13,2.526,19,1.405,27,2.245,28,3.642,30,0.482,64,2.714,65,2.931,66,3.202,67,1.059,68,4.117,69,5.524,70,3.603,71,1.828,72,5.399,73,5.524,74,2.714,75,2.245,76,2.417,77,4.117,78,4.117,79,2.714,80,2.245,81,1.147,82,1.918,83,4.117,84,4.117,85,2.534,86,4.117,87,3.565,88,3.565]],["tags/1",[]],["title/3",[0,0.165,26,0.943,89,2.085,90,2.085,91,1.372]],["content/3",[0,0.249,1,1.799,3,0.662,4,1.165,13,1.488,19,1.254,25,1.543,26,1.423,31,1.712,32,2.003,33,1.712,34,1.155,35,1.488,36,1.307,39,1.364,40,1.557,41,1.799,42,1.065,56,3.181,76,1.424,89,3.91,90,3.617,91,2.07,92,2.615,93,2.615,94,2.07,95,1.896,96,2.615,97,2.381,98,2.615,99,1.119,100,2.615,101,2.615,102,2.003,103,2.615,104,1.109,105,2.422,106,1.896,107,2.123,108,2.615,109,2.615,110,3.181,111,3.673,112,3.673,113,3.673,114,3.673]],["tags/3",[]],["title/4",[0,0.183,3,0.485,4,0.853,115,1.586]],["content/4",[0,0.179,3,0.761,4,1.34,9,2.491,18,2.003,19,1.744,25,1.543,26,1.423,30,0.43,31,1.712,32,2.003,33,1.712,34,1.155,35,1.488,36,1.307,37,0.945,39,1.364,40,1.557,41,1.799,42,1.065,55,1.799,76,1.981,79,2.422,81,1.023,94,1.488,97,1.712,99,0.804,115,2.166,116,1.424,117,0.654,118,2.261,119,2.261,120,2.003,121,1.065,122,2.615,123,2.123,124,2.003,125,2.123,126,2.003,127,3.673,128,3.673,129,3.673,130,3.673,131,3.181,132,3.673,133,3.181,134,3.181,135,3.181,136,2.615]],["tags/4",[]],["title/5",[0,0.165,3,0.438,4,0.772,82,1.578,137,2.085]],["content/5",[0,0.247,3,0.469,4,0.826,9,2.145,19,1.236,25,1.527,27,1.974,31,1.687,32,1.974,33,1.687,34,1.139,35,1.467,36,1.289,39,1.345,40,1.535,41,1.774,42,1.05,55,1.774,74,2.388,80,1.974,81,1.624,82,2.357,91,2.558,131,3.136,133,3.136,134,3.136,135,3.136,136,2.578,137,3.589,138,2.388,139,3.336,140,2.093,141,2.578,142,2.388,143,2.578,144,0.593,145,2.229,146,2.578,147,1.608,148,2.388,149,3.621,150,3.621,151,3.621,152,3.621,153,3.621,154,1.535,155,3.621,156,3.621,157,3.621]],["tags/5",[]],["title/9",[0,0.236,61,1.578,62,1.372,63,1.578]],["content/9",[0,0.32,1,1.938,2,2.713,3,0.696,4,1.495,5,2.818,6,3.078,7,2.042,8,2.436,9,2.28,10,3.078,11,3.078,12,3.829,13,2.179,14,2.609,15,1.195,16,3.078,17,2.609,18,2.158,19,1.351,20,3.078,21,4.184,22,3.078,23,3.078,24,2.818,25,1.195,26,1.103,27,2.158,28,2.609,29,3.078,30,0.464,61,1.844,62,1.604,63,1.844,64,2.609,65,2.818,66,3.078]],["tags/9",[]],["title/10",[0,0.221,1,1.515,2,1.373,3,0.4,4,0.705]],["content/10",[0,0.32,1,1.938,2,2.713,3,0.696,4,1.495,5,2.818,6,3.078,7,2.042,8,2.436,9,2.28,10,3.078,11,3.078,12,3.829,13,2.179,14,2.609,15,1.195,16,3.078,17,2.609,18,2.158,19,1.351,20,3.078,21,4.184,22,3.078,23,3.078,24,2.818,25,1.195,26,1.103,27,2.158,28,2.609,29,3.078,30,0.464,61,1.844,62,1.604,63,1.844,64,2.609,65,2.818,66,3.078]],["tags/10",[]],["title/6",[0,0.236,3,0.438,4,0.772,115,1.436]],["content/6",[0,0.312,3,0.74,4,1.303,9,2.189,13,1.183,18,1.591,19,0.996,26,1.592,27,1.591,30,0.342,74,1.925,76,2.002,79,1.925,80,1.591,81,1.592,82,1.36,89,3.179,90,2.666,91,2.473,92,2.078,93,2.078,94,2.092,95,1.506,96,2.078,97,2.406,98,2.078,99,0.948,100,2.078,101,2.078,102,1.591,103,2.078,104,0.881,105,1.925,106,1.506,107,1.687,108,2.078,109,2.078,115,1.237,116,1.132,117,0.519,118,1.797,119,1.797,120,1.591,121,0.846,122,2.078,123,1.687,124,1.591,125,1.687,126,1.591,137,2.666,138,1.925,139,1.925,140,1.687,141,2.078,142,1.925,143,2.078,144,0.507,145,1.797,146,2.078,147,1.296,148,1.925]],["tags/6",[]],["title/7",[0,0.221,26,0.862,89,1.904,90,1.904,91,1.253]],["content/7",[0,0.312,3,0.74,4,1.303,9,2.189,13,1.183,18,1.591,19,0.996,26,1.592,27,1.591,30,0.342,74,1.925,76,2.002,79,1.925,80,1.591,81,1.592,82,1.36,89,3.179,90,2.666,91,2.473,92,2.078,93,2.078,94,2.092,95,1.506,96,2.078,97,2.406,98,2.078,99,0.948,100,2.078,101,2.078,102,1.591,103,2.078,104,0.881,105,1.925,106,1.506,107,1.687,108,2.078,109,2.078,115,1.237,116,1.132,117,0.519,118,1.797,119,1.797,120,1.591,121,0.846,122,2.078,123,1.687,124,1.591,125,1.687,126,1.591,137,2.666,138,1.925,139,1.925,140,1.687,141,2.078,142,1.925,143,2.078,144,0.507,145,1.797,146,2.078,147,1.296,148,1.925]],["tags/7",[]],["title/8",[0,0.221,3,0.4,4,0.705,82,1.441,137,1.904]],["content/8",[0,0.312,3,0.74,4,1.303,9,2.189,13,1.183,18,1.591,19,0.996,26,1.592,27,1.591,30,0.342,74,1.925,76,2.002,79,1.925,80,1.591,81,1.592,82,1.36,89,3.179,90,2.666,91,2.473,92,2.078,93,2.078,94,2.092,95,1.506,96,2.078,97,2.406,98,2.078,99,0.948,100,2.078,101,2.078,102,1.591,103,2.078,104,0.881,105,1.925,106,1.506,107,1.687,108,2.078,109,2.078,115,1.237,116,1.132,117,0.519,118,1.797,119,1.797,120,1.591,121,0.846,122,2.078,123,1.687,124,1.591,125,1.687,126,1.591,137,2.666,138,1.925,139,1.925,140,1.687,141,2.078,142,1.925,143,2.078,144,0.507,145,1.797,146,2.078,147,1.296,148,1.925]],["tags/8",[]],["title/11",[0,0.236,158,1.748,159,2.411,160,2.085]],["content/11",[0,0.337,25,1.364,33,2.105,34,1.846,35,1.83,36,1.607,37,1.162,39,2.423,50,2.105,67,1.51,144,0.529,158,3.367,159,3.216,160,2.78,161,2.212,162,3.216,163,3.513,164,3.216,165,3.513,166,2.78,167,3.216,168,3.513,169,3.872,170,3.216]],["tags/11",[]],["title/12",[0,0.253,158,1.931,169,2.467]],["content/12",[0,0.337,25,1.364,33,2.105,34,1.846,35,1.83,36,1.607,37,1.162,39,2.423,50,2.105,67,1.51,144,0.529,158,3.367,159,3.216,160,2.78,161,2.212,162,3.216,163,3.513,164,3.216,165,3.513,166,2.78,167,3.216,168,3.513,169,3.872,170,3.216]],["tags/12",[]],["title/13",[0,0.253,117,0.666,171,1.451]],["content/13",[0,0.324,7,2.108,37,1.05,50,1.903,67,1.05,75,2.227,94,2.226,107,2.361,117,1.105,123,2.361,124,2.227,125,2.361,126,2.227,144,0.644,171,2.13,172,3.177,173,3.622,174,2.514,175,2.908,176,2.908,177,2.908,178,2.908,179,1.583,180,3.177,181,3.177,182,3.177,183,3.177,184,3.822,185,3.822,186,3.177,187,2.693,188,2.908,189,2.693]],["tags/13",[]],["title/14",[0,0.236,117,0.602,184,2.085,185,2.085]],["content/14",[0,0.324,7,2.108,37,1.05,50,1.903,67,1.05,75,2.227,94,2.226,107,2.361,117,1.105,123,2.361,124,2.227,125,2.361,126,2.227,144,0.644,171,2.13,172,3.177,173,3.622,174,2.514,175,2.908,176,2.908,177,2.908,178,2.908,179,1.583,180,3.177,181,3.177,182,3.177,183,3.177,184,3.822,185,3.822,186,3.177,187,2.693,188,2.908,189,2.693]],["tags/14",[]],["title/15",[0,0.253,117,0.666,171,1.451]],["content/15",[0,0.351,2,1.858,3,0.542,4,0.954,15,1.263,30,0.654,67,1.436,102,2.281,117,0.993,121,1.619,144,0.49,171,2.165,190,2.576,191,1.95,192,2.576,193,2.759,194,2.576,195,2.159,196,1.774,197,3.656,198,2.159,199,1.489,200,2.576,201,2.882,202,3.437,203,1.428,204,0.81,205,2.576]],["tags/15",[]],["title/16",[0,0.236,195,1.748,196,1.436,197,1.846]],["content/16",[0,0.351,2,1.858,3,0.542,4,0.954,15,1.263,30,0.654,67,1.436,102,2.281,117,0.993,121,1.619,144,0.49,171,2.165,190,2.576,191,1.95,192,2.576,193,2.759,194,2.576,195,2.159,196,1.774,197,3.656,198,2.159,199,1.489,200,2.576,201,2.882,202,3.437,203,1.428,204,0.81,205,2.576]],["tags/16",[]],["title/17",[0,0.253,201,1.931,202,2.304]],["content/17",[0,0.351,2,1.858,3,0.542,4,0.954,15,1.263,30,0.654,67,1.436,102,2.281,117,0.993,121,1.619,144,0.49,171,2.165,190,2.576,191,1.95,192,2.576,193,2.759,194,2.576,195,2.159,196,1.774,197,3.656,198,2.159,199,1.489,200,2.576,201,2.882,202,3.437,203,1.428,204,0.81,205,2.576]],["tags/17",[]],["title/23",[0,0.236,30,0.397,206,1.436,207,0.804]],["content/23",[0,0.347,26,0.955,30,0.762,34,1.077,70,1.981,71,2.161,76,1.329,99,1.066,106,1.769,116,1.329,117,0.61,121,0.994,144,0.57,198,1.769,203,1.17,204,1.095,206,2.399,207,1.76,208,2.26,209,1.979,210,1.981,211,1.273,212,2.11,213,2.11,214,2.11,215,2.063,216,2.161,217,1.769,218,2.26,219,2.11,220,2.11,221,2.26,222,1.981]],["tags/23",[]],["title/24",[0,0.221,71,1.373,117,0.55,207,0.734,209,0.862]],["content/24",[0,0.347,26,0.955,30,0.762,34,1.077,70,1.981,71,2.161,76,1.329,99,1.066,106,1.769,116,1.329,117,0.61,121,0.994,144,0.57,198,1.769,203,1.17,204,1.095,206,2.399,207,1.76,208,2.26,209,1.979,210,1.981,211,1.273,212,2.11,213,2.11,214,2.11,215,2.063,216,2.161,217,1.769,218,2.26,219,2.11,220,2.11,221,2.26,222,1.981]],["tags/24",[]],["title/25",[0,0.236,206,1.436,207,0.804,211,1.257]],["content/25",[0,0.347,26,0.955,30,0.762,34,1.077,70,1.981,71,2.161,76,1.329,99,1.066,106,1.769,116,1.329,117,0.61,121,0.994,144,0.57,198,1.769,203,1.17,204,1.095,206,2.399,207,1.76,208,2.26,209,1.979,210,1.981,211,1.273,212,2.11,213,2.11,214,2.11,215,2.063,216,2.161,217,1.769,218,2.26,219,2.11,220,2.11,221,2.26,222,1.981]],["tags/25",[]],["title/26",[0,0.207,207,0.675,209,0.793,214,1.752,215,1.206,216,1.264]],["content/26",[0,0.347,26,0.955,30,0.762,34,1.077,70,1.981,71,2.161,76,1.329,99,1.066,106,1.769,116,1.329,117,0.61,121,0.994,144,0.57,198,1.769,203,1.17,204,1.095,206,2.399,207,1.76,208,2.26,209,1.979,210,1.981,211,1.273,212,2.11,213,2.11,214,2.11,215,2.063,216,2.161,217,1.769,218,2.26,219,2.11,220,2.11,221,2.26,222,1.981]],["tags/26",[]],["title/18",[0,0.236,61,1.578,62,1.372,63,1.578]],["content/18",[0,0.353,3,0.604,4,1.064,15,1.409,30,0.776,37,0.831,61,1.506,62,1.31,63,1.506,67,0.831,81,1.3,99,0.708,104,1.811,115,1.37,116,1.253,144,0.379,154,2.322,161,1.583,179,1.809,199,1.661,203,1.869,204,1.161,207,0.767,209,1.526,211,1.2,223,2.552,224,1.668,225,1.868,226,1.99,227,1.99,228,2.408,229,1.762,230,1.762,231,1.37,232,1.506,233,1.868,234,1.868,235,2.698,236,2.544,237,1.99,238,1.868,239,1.868]],["tags/18",[]],["title/19",[0,0.253,223,1.744,224,1.931]],["content/19",[0,0.353,3,0.604,4,1.064,15,1.409,30,0.776,37,0.831,61,1.506,62,1.31,63,1.506,67,0.831,81,1.3,99,0.708,104,1.811,115,1.37,116,1.253,144,0.379,154,2.322,161,1.583,179,1.809,199,1.661,203,1.869,204,1.161,207,0.767,209,1.526,211,1.2,223,2.552,224,1.668,225,1.868,226,1.99,227,1.99,228,2.408,229,1.762,230,1.762,231,1.37,232,1.506,233,1.868,234,1.868,235,2.698,236,2.544,237,1.99,238,1.868,239,1.868]],["tags/19",[]],["title/20",[0,0.236,154,1.436,179,1.313,204,0.656]],["content/20",[0,0.353,3,0.604,4,1.064,15,1.409,30,0.776,37,0.831,61,1.506,62,1.31,63,1.506,67,0.831,81,1.3,99,0.708,104,1.811,115,1.37,116,1.253,144,0.379,154,2.322,161,1.583,179,1.809,199,1.661,203,1.869,204,1.161,207,0.767,209,1.526,211,1.2,223,2.552,224,1.668,225,1.868,226,1.99,227,1.99,228,2.408,229,1.762,230,1.762,231,1.37,232,1.506,233,1.868,234,1.868,235,2.698,236,2.544,237,1.99,238,1.868,239,1.868]],["tags/20",[]],["title/21",[0,0.253,81,1.043,104,1.13]],["content/21",[0,0.353,3,0.604,4,1.064,15,1.409,30,0.776,37,0.831,61,1.506,62,1.31,63,1.506,67,0.831,81,1.3,99,0.708,104,1.811,115,1.37,116,1.253,144,0.379,154,2.322,161,1.583,179,1.809,199,1.661,203,1.869,204,1.161,207,0.767,209,1.526,211,1.2,223,2.552,224,1.668,225,1.868,226,1.99,227,1.99,228,2.408,229,1.762,230,1.762,231,1.37,232,1.506,233,1.868,234,1.868,235,2.698,236,2.544,237,1.99,238,1.868,239,1.868]],["tags/21",[]],["title/22",[0,0.236,30,0.397,203,1.156,204,0.656]],["content/22",[0,0.353,3,0.604,4,1.064,15,1.409,30,0.776,37,0.831,61,1.506,62,1.31,63,1.506,67,0.831,81,1.3,99,0.708,104,1.811,115,1.37,116,1.253,144,0.379,154,2.322,161,1.583,179,1.809,199,1.661,203,1.869,204,1.161,207,0.767,209,1.526,211,1.2,223,2.552,224,1.668,225,1.868,226,1.99,227,1.99,228,2.408,229,1.762,230,1.762,231,1.37,232,1.506,233,1.868,234,1.868,235,2.698,236,2.544,237,1.99,238,1.868,239,1.868]],["tags/22",[]],["title/27",[0,0.273,3,0.541]],["content/27",[0,0.341,3,0.905,13,2.123,26,1.669,42,1.105,81,1.669,82,2.442,85,2.345,91,1.544,94,1.544,95,1.966,97,1.775,120,2.077,144,0.446,191,1.775,204,0.738,215,1.615,217,1.966,231,1.615,232,1.775,240,2.713,241,3.455,242,2.713,243,2.713,244,2.713,245,2.202,246,2.713,247,2.202,248,2.512,249,2.713,250,2.512,251,2.713,252,2.713,253,3.029,254,3.029,255,2.512]],["tags/27",[]],["title/28",[0,0.253,3,0.485,144,0.438]],["content/28",[0,0.341,3,0.905,13,2.123,26,1.669,42,1.105,81,1.669,82,2.442,85,2.345,91,1.544,94,1.544,95,1.966,97,1.775,120,2.077,144,0.446,191,1.775,204,0.738,215,1.615,217,1.966,231,1.615,232,1.775,240,2.713,241,3.455,242,2.713,243,2.713,244,2.713,245,2.202,246,2.713,247,2.202,248,2.512,249,2.713,250,2.512,251,2.713,252,2.713,253,3.029,254,3.029,255,2.512]],["tags/28",[]],["title/29",[0,0.236,3,0.438,253,1.957,254,1.957]],["content/29",[0,0.341,3,0.905,13,2.123,26,1.669,42,1.105,81,1.669,82,2.442,85,2.345,91,1.544,94,1.544,95,1.966,97,1.775,120,2.077,144,0.446,191,1.775,204,0.738,215,1.615,217,1.966,231,1.615,232,1.775,240,2.713,241,3.455,242,2.713,243,2.713,244,2.713,245,2.202,246,2.713,247,2.202,248,2.512,249,2.713,250,2.512,251,2.713,252,2.713,253,3.029,254,3.029,255,2.512]],["tags/29",[]],["title/40",[0,0.183,158,1.931,159,2.664,160,2.304]],["content/40",[34,1.189,39,2.59,40,1.603,67,1.535,142,2.494,144,0.443,161,1.852,162,2.693,163,2.942,164,2.693,165,2.942,166,2.328,167,4.248,168,5.003,189,3.438,222,2.186,256,2.693,257,3.276,258,1.68,259,4.248,260,3.782,261,3.782,262,2.693,263,3.782,264,3.782,265,3.782,266,4.516,267,3.276,268,2.942,269,3.276,270,3.782,271,3.276,272,3.276,273,2.693,274,3.782,275,3.782,276,3.782,277,2.942,278,2.942,279,3.276]],["tags/40",[]],["title/41",[158,2.445,280,4.103]],["content/41",[3,0.812,7,1.843,30,0.587,34,1.123,37,0.918,39,2.543,42,1.453,67,1.613,117,0.635,160,2.198,162,3.567,174,3.562,179,1.384,231,1.514,257,3.093,259,2.542,280,3.093,281,2.778,282,5.787,283,3.571,284,3.571,285,3.571,286,3.571,287,3.571,288,3.571,289,3.571,290,3.571,291,5.01,292,3.571,293,3.571,294,3.567,295,3.093,296,3.571,297,3.571,298,3.571,299,3.897,300,3.571,301,3.571,302,3.571,303,2.542,304,3.571,305,2.542,306,3.571]],["tags/41",[]],["title/30",[0,0.204,158,2.158,169,2.757]],["content/30",[25,1.638,33,2.529,34,1.706,35,2.199,36,1.931,37,1.695,39,2.015,50,2.529,62,2.199,158,2.801,169,3.578,170,3.864,299,4.222,307,5.427]],["tags/30",[]],["title/31",[0,0.204,117,0.744,171,1.621]],["content/31",[15,1.056,25,1.056,37,0.899,42,1.014,50,1.63,67,0.899,75,1.907,94,2.319,107,2.022,117,0.878,123,2.022,124,1.907,125,2.022,126,1.907,144,0.578,164,2.49,166,2.153,167,3.515,171,2.542,172,2.721,173,4.486,174,3.039,175,2.49,176,2.49,177,2.49,178,2.49,179,1.356,180,2.721,181,2.721,182,2.721,183,2.721,184,3.039,185,2.153,187,2.306,199,1.245,200,2.153,256,2.49,258,2.193,308,3.498,309,2.49,310,2.721,311,2.022,312,3.84,313,3.498,314,3.029,315,2.022,316,3.498,317,3.498,318,3.029]],["tags/31",[]],["title/33",[0,0.183,117,0.666,184,2.304,185,2.304]],["content/33",[7,2.637,17,2.422,37,1.314,42,1.065,75,2.786,117,1.188,144,0.43,171,1.981,173,2.422,177,2.615,184,4.451,185,4.52,186,2.857,187,2.422,188,2.615,189,3.874,258,2.821,281,2.857,303,2.615,305,2.615,309,2.615,311,2.123,314,3.181,315,2.954,319,3.181,320,3.181,321,3.673,322,3.673,323,3.181,324,3.181,325,3.181]],["tags/33",[]],["title/32",[326,5.464]],["content/32",[0,0.285,1,1.498,2,1.358,3,0.806,4,1.022,14,2.956,30,0.358,37,0.787,42,1.3,55,2.599,67,1.365,72,2.649,76,1.186,99,0.982,105,2.017,115,1.9,121,1.3,140,1.768,144,0.525,161,1.498,173,2.017,174,1.883,190,3.267,206,1.297,207,1.064,209,0.852,211,1.136,222,1.768,247,1.768,253,1.768,254,2.591,256,2.177,271,2.649,278,2.379,279,2.649,309,2.177,327,3.058,328,3.058,329,2.649,330,3.058,331,3.058,332,3.058,333,2.649,334,3.058,335,2.177,336,3.058,337,4.483,338,2.379,339,3.058,340,3.058,341,3.058,342,3.058,343,3.058,344,3.058,345,3.058,346,4.483,347,5.307,348,3.058,349,3.058,350,3.058,351,2.649,352,3.058]],["tags/32",[]],["title/42",[0,0.204,117,0.744,171,1.621]],["content/42",[2,2.138,3,0.623,4,1.098,15,1.453,25,1.453,30,0.717,37,1.238,42,1.396,67,1.238,117,0.857,121,1.774,144,0.717,171,2.372,187,3.174,190,2.963,191,2.243,192,2.963,193,3.174,194,2.963,309,3.428,310,3.745,311,2.783,312,3.745]],["tags/42",[]],["title/43",[30,0.438,121,1.085,178,2.664,179,1.451]],["content/43",[30,0.672,67,1.122,88,3.778,117,1.141,121,1.665,140,2.522,144,0.672,171,2.487,176,3.106,200,2.685,258,1.937,262,3.106,273,3.106,281,3.393,312,3.393,315,2.522,353,3.778,354,4.363,355,3.393,356,4.363,357,4.363,358,4.465,359,2.685,360,3.778,361,4.363,362,5.741,363,3.393,364,2.876,365,4.363]],["tags/43",[]],["title/44",[363,3.253,364,2.757,366,3.622]],["content/44",[30,0.586,85,3.079,258,2.222,351,4.333,363,5.748,364,4.133,366,5.429,367,6.268,368,5.003,369,5.003,370,3.891,371,5.003,372,5.003,373,5.003,374,5.003,375,5.003]],["tags/44",[]],["title/45",[376,4.103,377,4.103]],["content/45",[30,0.671,31,2.671,121,1.662,258,2.545,358,4.458,376,4.964,377,4.964,378,4.964,379,5.731,380,5.731]],["tags/45",[]],["title/34",[0,0.183,195,1.931,196,1.586,197,2.04]],["content/34",[0,0.146,7,1.541,30,0.35,37,0.768,64,1.969,67,1.133,80,2.402,117,1.028,121,0.866,144,0.35,158,1.541,171,1.158,179,1.158,194,2.712,195,1.541,197,3.359,198,1.541,199,1.063,200,3.222,204,0.578,205,1.839,223,2.053,236,1.629,239,1.727,258,1.957,272,3.816,273,2.127,278,2.323,305,3.137,311,1.727,315,2.547,319,2.587,335,3.137,378,2.587,381,2.587,382,4.406,383,2.987,384,4.406,385,4.406,386,1.727,387,5.234,388,2.587,389,2.987,390,2.987,391,5.234,392,2.987,393,2.987,394,2.987,395,4.406,396,2.987,397,3.451,398,2.323,399,2.587,400,2.987,401,2.987,402,2.323,403,2.987,404,2.987,405,2.987,406,2.987,407,2.987,408,2.323,409,2.987,410,2.323]],["tags/34",[]],["title/35",[397,3.124,410,3.685]],["content/35",[9,2.142,15,1.525,30,0.592,117,0.899,121,1.465,138,3.331,140,2.92,147,2.244,195,3.255,196,2.142,210,2.92,318,4.375,397,3.331,398,3.93,410,3.93,411,5.052,412,4.375,413,3.331,414,3.11,415,5.052,416,4.375]],["tags/35",[]],["title/36",[413,3.124,414,2.916]],["content/36",[1,2.781,8,2.64,14,2.828,67,1.103,144,0.502,147,1.905,160,3.494,196,2.407,199,1.527,201,2.214,215,1.818,250,2.828,258,1.905,295,3.715,364,4.465,370,3.337,413,2.828,414,2.64,417,3.715,418,2.828,419,4.289,420,5.865,421,3.715,422,3.715,423,4.289,424,4.289,425,4.289,426,4.289,427,4.289,428,4.289,429,4.289]],["tags/36",[]],["title/37",[9,2.008,196,2.008]],["content/37",[7,2.747,9,2.761,15,1.607,117,1.213,118,2.399,121,1.543,144,0.623,145,2.399,171,2.063,196,2.569,201,2.011,205,2.399,219,2.399,247,2.253,258,1.731,262,2.775,266,3.375,269,3.375,273,2.775,311,2.253,329,3.375,388,3.375,397,2.57,430,6.061,431,5.641,432,3.897,433,3.897,434,3.897,435,5.322,436,3.897,437,3.897,438,3.375]],["tags/37",[]],["title/38",[210,2.163,399,3.241,413,2.467,414,2.304]],["content/38",[1,2.979,8,2.936,25,1.44,36,1.697,147,2.118,258,2.701,303,3.396,315,3.515,353,4.131,364,4.01,397,3.145,413,3.145,414,3.744,416,4.131,417,4.131,420,5.267,421,4.131,439,4.131,440,4.769,441,4.769,442,4.769,443,4.769]],["tags/38",[]],["title/39",[277,4.25]],["content/39",[25,1.621,36,1.911,75,2.928,117,0.955,147,2.385,193,3.541,195,2.771,196,2.776,197,3.571,277,4.177,303,3.823,444,5.37,445,5.37,446,5.37]],["tags/39",[]],["title/46",[0,0.204,201,2.158,202,2.574]],["content/46",[15,1.035,17,2.26,25,1.035,64,2.26,67,0.881,102,1.869,117,0.866,121,0.994,144,0.401,147,1.522,166,2.996,170,2.44,189,3.209,196,1.453,197,3.547,201,3.588,202,4.005,203,1.17,204,0.942,205,2.11,256,2.44,258,2.161,262,2.44,311,1.981,315,1.981,320,2.968,323,2.968,324,2.968,325,2.968,335,2.44,381,2.968,398,2.666,402,3.786,431,4.215,439,2.968,447,2.968,448,3.427,449,3.427,450,4.867,451,3.427,452,3.427,453,3.427,454,3.465,455,3.427,456,3.427,457,3.427,458,3.427]],["tags/46",[]],["title/47",[0,0.183,30,0.438,206,1.586,207,0.888]],["content/47",[0,0.355,5,1.461,8,1.263,15,0.996,30,0.555,38,1.596,42,1.373,50,0.956,55,1.615,71,2.303,76,1.279,91,0.832,99,0.722,104,1.429,110,4.492,117,0.365,119,1.263,121,0.595,139,2.174,144,0.24,147,0.911,199,0.73,204,0.638,206,1.398,207,1.555,208,1.353,209,1.825,211,0.762,215,1.398,216,2.303,220,1.263,358,1.596,359,2.914,386,1.906,408,1.596,418,3.42,422,1.777,454,1.461,459,3.216,460,2.943,461,3.42,462,2.348,463,2.052,464,2.052,465,1.461,466,2.052,467,3.298,468,3.581,469,1.596,470,1.777,471,2.052,472,2.052,473,2.052,474,2.052,475,1.777,476,2.052,477,2.052,478,1.777,479,4.134,480,2.052,481,2.052,482,2.348,483,1.461,484,2.052,485,1.461,486,2.052,487,2.052,488,1.461,489,1.461,490,2.348,491,2.348,492,1.461,493,1.461,494,2.348,495,1.461,496,1.461]],["tags/47",[]],["title/48",[0,0.165,71,1.504,117,0.602,207,0.804,209,0.943]],["content/48",[0,0.319,1,1.525,26,0.868,30,0.365,36,1.617,42,0.903,67,0.801,70,2.626,71,3,81,0.868,94,1.262,99,0.682,104,1.371,117,0.954,121,1.555,144,0.532,191,1.451,195,1.607,196,1.926,203,1.063,204,0.603,207,1.488,209,1.642,210,1.8,258,2.017,259,2.217,268,2.422,305,2.217,315,1.8,335,2.217,359,1.917,360,2.697,386,1.8,402,3.533,418,2.053,447,2.697,460,3.234,461,2.053,462,2.217,465,2.217,469,2.422,470,2.697,483,2.217,497,3.114,498,3.114,499,3.114,500,4.543,501,4.543,502,3.114,503,3.533,504,2.697,505,3.114]],["tags/48",[]],["title/57",[0,0.151,207,0.734,209,0.862,214,1.904,215,1.311,216,1.373]],["content/57",[99,1.201,106,2.831,207,1.575,209,1.848,215,2.325,216,2.436,217,2.831,218,3.617,219,3.377,220,3.377,221,3.617,222,3.171]],["tags/57",[]],["title/58",[55,1.659,99,0.742,216,1.504,386,1.957,506,2.634]],["content/58",[0,0.368,15,0.902,19,1.786,25,0.902,31,1.392,34,0.939,35,1.21,36,1.063,39,1.109,40,1.266,41,1.463,42,1.278,50,1.392,55,1.463,71,2.566,75,1.629,80,1.629,91,1.21,99,0.654,104,1.33,117,0.531,147,1.326,199,1.063,207,1.242,209,1.61,216,2.325,359,1.839,386,2.547,418,1.969,454,2.127,460,2.127,461,2.905,462,2.127,465,2.127,482,2.127,483,2.127,485,2.127,488,2.127,489,2.127,490,2.127,491,2.127,492,2.127,493,2.127,494,2.127,495,2.127,496,2.127,503,2.323,506,3.427,507,2.587,508,2.987,509,2.587,510,2.587,511,2.323,512,4.406,513,2.323,514,2.323,515,2.127,516,2.587,517,2.127]],["tags/58",[]],["title/59",[55,1.202,99,0.537,216,1.09,386,1.418,511,1.908,518,2.125,519,2.125,520,2.125,521,1.908]],["content/59",[0,0.372,15,0.838,19,1.711,25,0.838,31,1.294,34,0.873,35,1.125,36,0.988,39,1.031,40,1.177,41,1.36,42,1.21,50,1.294,55,1.36,71,2.475,75,1.514,80,1.514,91,1.125,99,0.608,104,1.26,147,1.233,207,1.19,209,1.553,216,2.226,359,1.709,386,2.412,418,1.83,454,1.977,460,1.977,461,2.751,462,1.977,465,1.977,482,1.977,483,1.977,485,1.977,488,1.977,489,1.977,490,1.977,491,1.977,492,1.977,493,1.977,494,1.977,495,1.977,496,1.977,503,2.159,504,2.404,507,2.404,509,3.613,510,2.404,511,3.899,513,2.159,514,2.159,515,1.977,516,2.404,517,1.977,518,3.613,519,3.613,520,3.613,521,3.245,522,2.404,523,2.776,524,4.172]],["tags/59",[]],["title/50",[0,0.183,206,1.586,207,0.888,211,1.39]],["content/50",[0,0.353,19,1.669,25,1.476,30,0.404,31,1.608,32,1.881,33,1.608,34,1.786,35,1.398,36,1.228,37,0.887,39,1.281,40,1.463,41,1.69,42,1.001,50,1.608,71,1.532,76,1.896,104,1.042,116,1.338,198,1.781,204,1.099,206,1.463,207,1.348,209,1.362,211,1.281,212,3.01,213,2.124,461,2.275,482,2.457,485,2.457,488,2.457,489,2.457,490,2.457,491,2.457,492,2.457,493,2.457,494,2.457,495,2.457,496,2.457,514,2.684,515,2.457,517,2.457,525,3.45,526,3.45,527,3.45,528,3.45,529,3.45,530,3.45,531,3.45]],["tags/50",[]],["title/49",[0,0.183,154,1.586,179,1.451,204,0.724]],["content/49",[0,0.198,15,1.223,19,1.383,25,1.65,30,0.475,31,1.888,32,2.209,33,1.888,34,1.274,35,1.642,36,1.442,37,1.042,39,1.504,40,1.718,41,1.985,42,1.175,99,0.887,104,1.223,154,2.621,161,1.985,179,2.397,199,1.442,204,0.784,224,2.091,228,2.091,232,1.888,233,2.342,234,2.342,235,2.342,236,2.209,517,2.885,532,4.052,533,4.052,534,4.052,535,4.052,536,4.052,537,4.052,538,4.052,539,4.052,540,4.052,541,4.052,542,4.052]],["tags/49",[]],["title/51",[0,0.183,61,1.744,62,1.516,63,1.744]],["content/51",[]],["tags/51",[]],["title/52",[223,2.546]],["content/52",[30,0.671,62,2.322,144,0.671,223,2.671,225,3.313,229,3.125,230,3.125,521,4.458,543,5.731,544,5.731]],["tags/52",[]],["title/53",[545,5.464]],["content/53",[99,1.164,148,3.504,154,2.253,199,1.891,468,4.603,546,5.315,547,4.603,548,5.315,549,5.315,550,4.603,551,6.507,552,5.315,553,5.315,554,4.603,555,5.315,556,5.315]],["tags/53",[]],["title/54",[557,4.738,558,4.738]],["content/54",[62,2.349,94,2.349,95,2.991,104,1.75,144,0.679,231,2.457,259,4.127,294,4.127,414,3.568]],["tags/54",[]],["title/55",[559,5.464]],["content/55",[30,0.843,70,3.24,99,1.227,144,0.657,196,2.376,201,2.893,294,3.991,560,5.606,561,5.606,562,5.606]],["tags/55",[]],["title/56",[0,0.204,81,1.165,104,1.262]],["content/56",[0,0.253,15,1.133,19,1.281,25,1.566,30,0.44,31,1.749,32,2.047,33,1.749,34,1.18,35,2.102,36,1.336,37,1.334,39,1.394,40,1.591,41,1.839,42,1.089,81,1.656,99,0.822,104,1.936,119,2.311,154,1.591,179,1.456,203,1.281,204,0.727,207,0.891,209,1.445,211,1.394,228,1.937,235,2.17,237,3.193,238,2.17,310,2.92,311,2.17,333,3.251,370,2.92,515,3.693,554,3.251,563,3.754,564,3.754,565,3.754,566,3.754,567,3.754,568,3.251,569,3.754,570,3.754]],["tags/56",[]],["title/61",[0,0.183,30,0.438,203,1.277,204,0.724]],["content/61",[3,0.56,4,0.986,19,1.476,25,1.723,30,0.796,31,2.016,32,2.358,33,2.016,34,1.36,35,1.753,36,1.539,37,1.468,39,1.606,40,1.834,41,2.119,42,1.254,99,0.947,104,1.723,115,1.834,154,1.834,203,2.181,204,0.837,209,1.205,228,2.232,236,2.358,239,2.5,571,4.326,572,4.326,573,4.326,574,4.326,575,4.326]],["tags/61",[]],["title/60",[0,0.204,223,1.948,224,2.158]],["content/60",[3,0.585,4,1.03,25,1.364,30,0.529,34,1.42,35,1.83,36,1.607,37,1.162,39,1.677,55,2.212,67,1.162,97,2.105,116,1.751,124,2.463,144,0.529,199,1.607,204,0.874,223,2.736,224,3.03,225,2.611,226,2.78,227,2.78,228,3.03,229,2.463,230,2.463,231,1.915,294,3.216,475,3.912,550,3.912,576,4.517,577,3.912]],["tags/60",[]],["title/62",[0,0.183,3,0.485,253,2.163,254,2.163]],["content/62",[3,0.768,26,1.652,81,1.652,85,3.651,253,3.428,254,3.428,255,3.91]],["tags/62",[]],["title/63",[26,1.522]],["content/63",[26,1.682,37,0.995,76,1.5,97,2.467,99,0.847,104,1.599,154,2.245,166,2.381,191,2.467,192,3.716,204,0.749,206,1.64,207,0.918,209,1.475,232,1.802,233,2.236,234,2.236,245,3.49,255,2.55,359,2.381,408,3.009,412,3.35,469,3.009,506,3.009,547,3.35,578,3.868,579,4.119,580,3.868,581,3.868,582,3.868,583,3.868,584,4.586,585,3.868,586,3.868,587,3.35,588,3.868,589,3.868,590,3.868,591,3.868,592,3.35]],["tags/63",[]],["title/64",[81,1.522]],["content/64",[9,2.325,13,2.223,19,1.872,76,2.127,81,1.848,126,2.991,136,3.905,245,3.171,248,3.617,355,4.267,579,4.267,593,5.485,594,5.485]],["tags/64",[]],["title/66",[0,0.204,3,0.541,144,0.49]],["content/66",[3,0.704,13,1.875,18,3.123,19,1.735,24,1.405,28,1.301,37,0.507,38,1.535,40,0.836,42,0.572,65,1.405,87,1.709,99,0.432,118,1.215,136,1.405,144,0.595,145,1.967,174,1.215,175,1.405,188,1.405,191,2.156,192,1.215,194,1.215,199,0.702,204,0.779,213,2.478,231,0.836,238,1.14,245,3.311,247,1.14,251,1.405,252,2.275,267,1.709,268,1.535,299,2.485,338,2.485,355,4.232,438,2.767,459,1.535,478,1.709,513,1.535,522,1.709,568,1.709,577,1.709,579,3.132,584,1.709,587,1.709,595,5.084,596,3.195,597,3.195,598,1.973,599,4.026,600,3.195,601,4.026,602,1.973,603,3.195,604,1.973,605,1.973,606,1.973,607,1.973,608,1.973,609,1.973,610,1.973,611,3.195,612,1.973,613,1.973,614,3.195,615,1.973,616,1.973,617,1.973,618,1.973,619,3.195,620,3.195,621,3.195,622,3.195,623,1.973,624,1.973,625,1.973,626,1.973,627,1.973,628,1.973,629,3.195,630,3.195,631,1.973,632,1.973,633,1.973,634,1.973,635,1.973,636,1.973,637,1.973,638,1.973,639,1.973,640,1.973,641,1.973,642,1.973,643,1.973,644,1.973,645,1.973,646,1.973,647,1.973,648,3.195,649,1.973,650,1.973,651,3.195,652,1.973,653,1.973,654,1.973,655,1.973,656,1.973,657,1.973,658,1.973]],["tags/66",[]],["title/65",[0,0.231,3,0.613]],["content/65",[3,0.595,13,2.407,26,1.655,81,1.655,82,2.768,91,1.863,94,1.863,95,2.373,97,2.142,120,2.507,191,2.142,204,0.89,215,1.949,217,2.373,231,1.949,232,2.142,240,3.274,241,3.917,242,3.274,243,3.274,244,3.274,245,2.658,246,3.274,247,2.658,248,3.032,249,3.274,250,3.032]],["tags/65",[]],["title/67",[0,0.231,659,4.738]],["content/67",[2,1.889,3,0.874,4,1.287,26,1.185,30,0.661,40,1.803,42,1.234,67,1.094,81,1.185,144,0.498,190,3.9,204,0.823,206,1.803,207,1.01,211,1.579,212,2.618,229,2.319,230,2.319,241,2.805,338,3.309,459,3.309,592,3.684,660,4.254,661,4.254,662,4.254,663,4.254,664,4.254,665,4.254,666,4.254,667,5.646,668,4.254,669,4.254,670,4.254]],["tags/67",[]]],"invertedIndex":[["",{"_index":0,"title":{"1":{},"2":{},"3":{},"4":{},"5":{},"6":{},"7":{},"8":{},"9":{},"10":{},"11":{},"12":{},"13":{},"14":{},"15":{},"16":{},"17":{},"18":{},"19":{},"20":{},"21":{},"22":{},"23":{},"24":{},"25":{},"26":{},"27":{},"28":{},"29":{},"30":{},"31":{},"33":{},"34":{},"40":{},"42":{},"46":{},"47":{},"48":{},"49":{},"50":{},"51":{},"56":{},"57":{},"60":{},"61":{},"62":{},"65":{},"66":{},"67":{}},"content":{"3":{},"4":{},"5":{},"6":{},"7":{},"8":{},"9":{},"10":{},"11":{},"12":{},"13":{},"14":{},"15":{},"16":{},"17":{},"18":{},"19":{},"20":{},"21":{},"22":{},"23":{},"24":{},"25":{},"26":{},"27":{},"28":{},"29":{},"32":{},"34":{},"47":{},"48":{},"49":{},"50":{},"56":{},"58":{},"59":{}},"tags":{}}],["0",{"_index":493,"title":{},"content":{"47":{},"50":{},"58":{},"59":{}},"tags":{}}],["0.0.0.0/0",{"_index":421,"title":{},"content":{"36":{},"38":{}},"tags":{}}],["0.022372592",{"_index":487,"title":{},"content":{"47":{}},"tags":{}}],["0.02421053",{"_index":486,"title":{},"content":{"47":{}},"tags":{}}],["05",{"_index":519,"title":{"59":{}},"content":{"59":{}},"tags":{}}],["1",{"_index":50,"title":{},"content":{"2":{},"11":{},"12":{},"13":{},"14":{},"30":{},"31":{},"47":{},"50":{},"58":{},"59":{}},"tags":{}}],["10",{"_index":38,"title":{},"content":{"2":{},"47":{},"66":{}},"tags":{}}],["1234",{"_index":654,"title":{},"content":{"66":{}},"tags":{}}],["150",{"_index":489,"title":{},"content":{"47":{},"50":{},"58":{},"59":{}},"tags":{}}],["1536",{"_index":463,"title":{},"content":{"47":{}},"tags":{}}],["19",{"_index":520,"title":{"59":{}},"content":{"59":{}},"tags":{}}],["2",{"_index":307,"title":{},"content":{"30":{}},"tags":{}}],["2024",{"_index":518,"title":{"59":{}},"content":{"59":{}},"tags":{}}],["3",{"_index":124,"title":{},"content":{"4":{},"6":{},"7":{},"8":{},"13":{},"14":{},"31":{},"60":{}},"tags":{}}],["384",{"_index":503,"title":{},"content":{"48":{},"58":{},"59":{}},"tags":{}}],["4",{"_index":532,"title":{},"content":{"49":{}},"tags":{}}],["5",{"_index":515,"title":{},"content":{"50":{},"56":{},"58":{},"59":{}},"tags":{}}],["6",{"_index":571,"title":{},"content":{"61":{}},"tags":{}}],["8",{"_index":525,"title":{},"content":{"50":{}},"tags":{}}],["8b",{"_index":125,"title":{},"content":{"4":{},"6":{},"7":{},"8":{},"13":{},"14":{},"31":{}},"tags":{}}],["9",{"_index":127,"title":{},"content":{"4":{}},"tags":{}}],["90",{"_index":332,"title":{},"content":{"32":{}},"tags":{}}],["_id",{"_index":492,"title":{},"content":{"47":{},"50":{},"58":{},"59":{}},"tags":{}}],["a.k.a",{"_index":592,"title":{},"content":{"63":{},"67":{}},"tags":{}}],["abmd",{"_index":484,"title":{},"content":{"47":{}},"tags":{}}],["access",{"_index":414,"title":{"36":{},"38":{}},"content":{"35":{},"36":{},"38":{},"54":{}},"tags":{}}],["account",{"_index":171,"title":{"13":{},"15":{},"31":{},"42":{}},"content":{"13":{},"14":{},"15":{},"16":{},"17":{},"31":{},"33":{},"34":{},"37":{},"42":{},"43":{}},"tags":{}}],["accur",{"_index":248,"title":{},"content":{"27":{},"28":{},"29":{},"64":{},"65":{}},"tags":{}}],["achiev",{"_index":617,"title":{},"content":{"66":{}},"tags":{}}],["activ",{"_index":293,"title":{},"content":{"41":{}},"tags":{}}],["ad",{"_index":663,"title":{},"content":{"67":{}},"tags":{}}],["add",{"_index":1,"title":{"2":{},"10":{}},"content":{"2":{},"3":{},"9":{},"10":{},"32":{},"36":{},"38":{},"48":{}},"tags":{}}],["addition",{"_index":631,"title":{},"content":{"66":{}},"tags":{}}],["address",{"_index":364,"title":{"44":{}},"content":{"36":{},"38":{},"43":{},"44":{}},"tags":{}}],["adult",{"_index":627,"title":{},"content":{"66":{}},"tags":{}}],["advanc",{"_index":349,"title":{},"content":{"32":{}},"tags":{}}],["again",{"_index":522,"title":{},"content":{"59":{},"66":{}},"tags":{}}],["against",{"_index":212,"title":{},"content":{"23":{},"24":{},"25":{},"26":{},"50":{},"67":{}},"tags":{}}],["agent",{"_index":614,"title":{},"content":{"66":{}},"tags":{}}],["aggreg",{"_index":478,"title":{},"content":{"47":{},"66":{}},"tags":{}}],["ai",{"_index":174,"title":{},"content":{"13":{},"14":{},"31":{},"32":{},"41":{},"66":{}},"tags":{}}],["allow",{"_index":8,"title":{},"content":{"2":{},"9":{},"10":{},"36":{},"38":{},"47":{}},"tags":{}}],["allowlist",{"_index":423,"title":{},"content":{"36":{}},"tags":{}}],["along",{"_index":342,"title":{},"content":{"32":{}},"tags":{}}],["alreadi",{"_index":309,"title":{},"content":{"31":{},"32":{},"33":{},"42":{}},"tags":{}}],["alway",{"_index":480,"title":{},"content":{"47":{}},"tags":{}}],["anoth",{"_index":141,"title":{},"content":{"5":{},"6":{},"7":{},"8":{}},"tags":{}}],["answer",{"_index":19,"title":{},"content":{"1":{},"2":{},"3":{},"4":{},"5":{},"6":{},"7":{},"8":{},"9":{},"10":{},"49":{},"50":{},"56":{},"58":{},"59":{},"61":{},"64":{},"66":{}},"tags":{}}],["answercollection.aggregate(pipelin",{"_index":531,"title":{},"content":{"50":{}},"tags":{}}],["answercollection.insert_many(embedded_doc",{"_index":575,"title":{},"content":{"61":{}},"tags":{}}],["answercreate_prompt(user_queri",{"_index":131,"title":{},"content":{"4":{},"5":{}},"tags":{}}],["answerdoc[\"embed",{"_index":566,"title":{},"content":{"56":{}},"tags":{}}],["answerembedding_model.encode(text",{"_index":564,"title":{},"content":{"56":{}},"tags":{}}],["answerfor",{"_index":153,"title":{},"content":{"5":{}},"tags":{}}],["answerfw_client.chat.completions.cr",{"_index":133,"title":{},"content":{"4":{},"5":{}},"tags":{}}],["answerget_chunks(doc",{"_index":542,"title":{},"content":{"49":{}},"tags":{}}],["answerget_embedding(user_queri",{"_index":527,"title":{},"content":{"50":{}},"tags":{}}],["answerhistory_collection.create_index(\"session_id",{"_index":44,"title":{},"content":{"2":{}},"tags":{}}],["answerhistory_collection.find({\"session_id",{"_index":48,"title":{},"content":{"2":{}},"tags":{}}],["answerhistory_collection.insert_one(messag",{"_index":46,"title":{},"content":{"2":{}},"tags":{}}],["answermongodb_client[db_name][collection_nam",{"_index":573,"title":{},"content":{"61":{}},"tags":{}}],["answerrecursivecharactertextsplitter.from_tiktoken_encod",{"_index":534,"title":{},"content":{"49":{}},"tags":{}}],["answerrerank_model.rank",{"_index":112,"title":{},"content":{"3":{}},"tags":{}}],["answerretrieve_session_history(session_id",{"_index":52,"title":{},"content":{"2":{}},"tags":{}}],["answerstore_chat_message(session_id",{"_index":58,"title":{},"content":{"2":{}},"tags":{}}],["answertext_splitter.split_text(text",{"_index":540,"title":{},"content":{"49":{}},"tags":{}}],["answervector_search(user_queri",{"_index":129,"title":{},"content":{"4":{}},"tags":{}}],["answer{\"rol",{"_index":54,"title":{},"content":{"2":{}},"tags":{}}],["anywher",{"_index":417,"title":{},"content":{"36":{},"38":{}},"tags":{}}],["api",{"_index":184,"title":{"14":{},"33":{}},"content":{"13":{},"14":{},"31":{},"33":{}},"tags":{}}],["appear",{"_index":321,"title":{},"content":{"33":{}},"tags":{}}],["applic",{"_index":4,"title":{"2":{},"4":{},"5":{},"6":{},"8":{},"10":{}},"content":{"2":{},"3":{},"4":{},"5":{},"6":{},"7":{},"8":{},"9":{},"10":{},"15":{},"16":{},"17":{},"18":{},"19":{},"20":{},"21":{},"22":{},"32":{},"42":{},"60":{},"61":{},"67":{}},"tags":{}}],["array",{"_index":591,"title":{},"content":{"63":{}},"tags":{}}],["articl",{"_index":228,"title":{},"content":{"18":{},"19":{},"20":{},"21":{},"22":{},"49":{},"56":{},"60":{},"61":{}},"tags":{}}],["ask",{"_index":368,"title":{},"content":{"44":{}},"tags":{}}],["assign",{"_index":392,"title":{},"content":{"34":{}},"tags":{}}],["assist",{"_index":60,"title":{},"content":{"2":{}},"tags":{}}],["atla",{"_index":121,"title":{"43":{}},"content":{"4":{},"6":{},"7":{},"8":{},"15":{},"16":{},"17":{},"23":{},"24":{},"25":{},"26":{},"32":{},"34":{},"35":{},"37":{},"42":{},"43":{},"45":{},"46":{},"47":{},"48":{}},"tags":{}}],["atlas_vector_search_index_nam",{"_index":529,"title":{},"content":{"50":{}},"tags":{}}],["audio",{"_index":589,"title":{},"content":{"63":{}},"tags":{}}],["augment",{"_index":241,"title":{},"content":{"27":{},"28":{},"29":{},"65":{},"67":{}},"tags":{}}],["authent",{"_index":317,"title":{},"content":{"31":{}},"tags":{}}],["autom",{"_index":396,"title":{},"content":{"34":{}},"tags":{}}],["automat",{"_index":432,"title":{},"content":{"37":{}},"tags":{}}],["avail",{"_index":601,"title":{},"content":{"66":{}},"tags":{}}],["averag",{"_index":623,"title":{},"content":{"66":{}},"tags":{}}],["back",{"_index":10,"title":{},"content":{"2":{},"9":{},"10":{}},"tags":{}}],["badg",{"_index":260,"title":{},"content":{"40":{}},"tags":{}}],["bar",{"_index":334,"title":{},"content":{"32":{}},"tags":{}}],["base",{"_index":192,"title":{},"content":{"15":{},"16":{},"17":{},"42":{},"63":{},"66":{}},"tags":{}}],["basic",{"_index":605,"title":{},"content":{"66":{}},"tags":{}}],["be",{"_index":415,"title":{},"content":{"35":{}},"tags":{}}],["befor",{"_index":235,"title":{},"content":{"18":{},"19":{},"20":{},"21":{},"22":{},"49":{},"56":{}},"tags":{}}],["below",{"_index":281,"title":{},"content":{"33":{},"41":{},"43":{}},"tags":{}}],["best",{"_index":251,"title":{},"content":{"27":{},"28":{},"29":{},"66":{}},"tags":{}}],["between",{"_index":98,"title":{},"content":{"3":{},"6":{},"7":{},"8":{}},"tags":{}}],["block",{"_index":41,"title":{},"content":{"2":{},"3":{},"4":{},"5":{},"49":{},"50":{},"56":{},"58":{},"59":{},"61":{}},"tags":{}}],["bodi",{"_index":517,"title":{},"content":{"49":{},"50":{},"58":{},"59":{}},"tags":{}}],["box",{"_index":391,"title":{},"content":{"34":{}},"tags":{}}],["break",{"_index":233,"title":{},"content":{"18":{},"19":{},"20":{},"21":{},"22":{},"49":{},"63":{}},"tags":{}}],["browser",{"_index":302,"title":{},"content":{"41":{}},"tags":{}}],["build",{"_index":115,"title":{"4":{},"6":{}},"content":{"4":{},"6":{},"7":{},"8":{},"18":{},"19":{},"20":{},"21":{},"22":{},"32":{},"61":{}},"tags":{}}],["built",{"_index":662,"title":{},"content":{"67":{}},"tags":{}}],["button",{"_index":315,"title":{},"content":{"31":{},"33":{},"34":{},"38":{},"43":{},"46":{},"48":{}},"tags":{}}],["calcul",{"_index":96,"title":{},"content":{"3":{},"6":{},"7":{},"8":{}},"tags":{}}],["calori",{"_index":625,"title":{},"content":{"66":{}},"tags":{}}],["captcha",{"_index":409,"title":{},"content":{"34":{}},"tags":{}}],["card",{"_index":356,"title":{},"content":{"43":{}},"tags":{}}],["case",{"_index":145,"title":{},"content":{"5":{},"6":{},"7":{},"8":{},"37":{},"66":{}},"tags":{}}],["caution",{"_index":370,"title":{},"content":{"36":{},"44":{},"56":{}},"tags":{}}],["cd",{"_index":291,"title":{},"content":{"41":{}},"tags":{}}],["cell",{"_index":35,"title":{},"content":{"2":{},"3":{},"4":{},"5":{},"11":{},"12":{},"30":{},"49":{},"50":{},"56":{},"58":{},"59":{},"60":{},"61":{}},"tags":{}}],["center",{"_index":230,"title":{},"content":{"18":{},"19":{},"20":{},"21":{},"22":{},"52":{},"60":{},"67":{}},"tags":{}}],["certain",{"_index":220,"title":{},"content":{"23":{},"24":{},"25":{},"26":{},"47":{},"57":{}},"tags":{}}],["chang",{"_index":268,"title":{},"content":{"40":{},"48":{},"66":{}},"tags":{}}],["charact",{"_index":551,"title":{},"content":{"53":{}},"tags":{}}],["chat",{"_index":27,"title":{},"content":{"1":{},"2":{},"5":{},"6":{},"7":{},"8":{},"9":{},"10":{}},"tags":{}}],["check",{"_index":351,"title":{},"content":{"32":{},"44":{}},"tags":{}}],["choos",{"_index":272,"title":{},"content":{"34":{},"40":{}},"tags":{}}],["chunk",{"_index":154,"title":{"20":{},"49":{}},"content":{"5":{},"18":{},"19":{},"20":{},"21":{},"22":{},"49":{},"53":{},"56":{},"61":{},"63":{}},"tags":{}}],["chunk.choices[0].delta.cont",{"_index":155,"title":{},"content":{"5":{}},"tags":{}}],["chunk_overlap=30",{"_index":538,"title":{},"content":{"49":{}},"tags":{}}],["chunk_size=200",{"_index":537,"title":{},"content":{"49":{}},"tags":{}}],["click",{"_index":258,"title":{},"content":{"31":{},"33":{},"34":{},"36":{},"37":{},"38":{},"40":{},"43":{},"44":{},"45":{},"46":{},"48":{}},"tags":{}}],["clipboard",{"_index":323,"title":{},"content":{"33":{},"46":{}},"tags":{}}],["clone",{"_index":282,"title":{},"content":{"41":{}},"tags":{}}],["close",{"_index":440,"title":{},"content":{"38":{}},"tags":{}}],["closest",{"_index":404,"title":{},"content":{"34":{}},"tags":{}}],["cloud",{"_index":384,"title":{},"content":{"34":{}},"tags":{}}],["cluster",{"_index":197,"title":{"16":{},"34":{}},"content":{"15":{},"16":{},"17":{},"34":{},"39":{},"46":{}},"tags":{}}],["code",{"_index":40,"title":{},"content":{"2":{},"3":{},"4":{},"5":{},"40":{},"49":{},"50":{},"56":{},"58":{},"59":{},"61":{},"66":{},"67":{}},"tags":{}}],["code_block_1",{"_index":533,"title":{},"content":{"49":{}},"tags":{}}],["code_block_10",{"_index":530,"title":{},"content":{"50":{}},"tags":{}}],["code_block_11",{"_index":512,"title":{},"content":{"58":{}},"tags":{}}],["code_block_12",{"_index":524,"title":{},"content":{"59":{}},"tags":{}}],["code_block_13",{"_index":128,"title":{},"content":{"4":{}},"tags":{}}],["code_block_14",{"_index":130,"title":{},"content":{"4":{}},"tags":{}}],["code_block_15",{"_index":132,"title":{},"content":{"4":{}},"tags":{}}],["code_block_16",{"_index":111,"title":{},"content":{"3":{}},"tags":{}}],["code_block_17",{"_index":149,"title":{},"content":{"5":{}},"tags":{}}],["code_block_18",{"_index":150,"title":{},"content":{"5":{}},"tags":{}}],["code_block_19",{"_index":152,"title":{},"content":{"5":{}},"tags":{}}],["code_block_2",{"_index":539,"title":{},"content":{"49":{}},"tags":{}}],["code_block_20",{"_index":43,"title":{},"content":{"2":{}},"tags":{}}],["code_block_21",{"_index":45,"title":{},"content":{"2":{}},"tags":{}}],["code_block_22",{"_index":47,"title":{},"content":{"2":{}},"tags":{}}],["code_block_23",{"_index":51,"title":{},"content":{"2":{}},"tags":{}}],["code_block_24",{"_index":53,"title":{},"content":{"2":{}},"tags":{}}],["code_block_25",{"_index":57,"title":{},"content":{"2":{}},"tags":{}}],["code_block_3",{"_index":541,"title":{},"content":{"49":{}},"tags":{}}],["code_block_4",{"_index":563,"title":{},"content":{"56":{}},"tags":{}}],["code_block_5",{"_index":565,"title":{},"content":{"56":{}},"tags":{}}],["code_block_6",{"_index":572,"title":{},"content":{"61":{}},"tags":{}}],["code_block_7",{"_index":574,"title":{},"content":{"61":{}},"tags":{}}],["code_block_8",{"_index":526,"title":{},"content":{"50":{}},"tags":{}}],["code_block_9",{"_index":528,"title":{},"content":{"50":{}},"tags":{}}],["code_block_n",{"_index":32,"title":{},"content":{"2":{},"3":{},"4":{},"5":{},"49":{},"50":{},"56":{},"61":{}},"tags":{}}],["colab",{"_index":168,"title":{},"content":{"11":{},"12":{},"40":{}},"tags":{}}],["collect",{"_index":70,"title":{},"content":{"1":{},"23":{},"24":{},"25":{},"26":{},"48":{},"55":{}},"tags":{}}],["combin",{"_index":214,"title":{"26":{},"57":{}},"content":{"23":{},"24":{},"25":{},"26":{}},"tags":{}}],["come",{"_index":143,"title":{},"content":{"5":{},"6":{},"7":{},"8":{}},"tags":{}}],["command",{"_index":285,"title":{},"content":{"41":{}},"tags":{}}],["commun",{"_index":669,"title":{},"content":{"67":{}},"tags":{}}],["compani",{"_index":642,"title":{},"content":{"66":{}},"tags":{}}],["company'",{"_index":644,"title":{},"content":{"66":{}},"tags":{}}],["compass",{"_index":450,"title":{},"content":{"46":{}},"tags":{}}],["complet",{"_index":140,"title":{},"content":{"5":{},"6":{},"7":{},"8":{},"32":{},"35":{},"43":{}},"tags":{}}],["complex",{"_index":609,"title":{},"content":{"66":{}},"tags":{}}],["compon",{"_index":253,"title":{"29":{},"62":{}},"content":{"27":{},"28":{},"29":{},"32":{},"62":{}},"tags":{}}],["comput",{"_index":650,"title":{},"content":{"66":{}},"tags":{}}],["concept",{"_index":63,"title":{"1":{},"9":{},"18":{},"51":{}},"content":{"9":{},"10":{},"18":{},"19":{},"20":{},"21":{},"22":{}},"tags":{}}],["configur",{"_index":210,"title":{"38":{}},"content":{"23":{},"24":{},"25":{},"26":{},"35":{},"48":{}},"tags":{}}],["confirm",{"_index":443,"title":{},"content":{"38":{}},"tags":{}}],["congratul",{"_index":660,"title":{},"content":{"67":{}},"tags":{}}],["connect",{"_index":201,"title":{"17":{},"46":{}},"content":{"15":{},"16":{},"17":{},"36":{},"37":{},"46":{},"55":{}},"tags":{}}],["consid",{"_index":218,"title":{},"content":{"23":{},"24":{},"25":{},"26":{},"57":{}},"tags":{}}],["consist",{"_index":577,"title":{},"content":{"60":{},"66":{}},"tags":{}}],["construct",{"_index":580,"title":{},"content":{"63":{}},"tags":{}}],["contain",{"_index":594,"title":{},"content":{"64":{}},"tags":{}}],["content",{"_index":55,"title":{"58":{},"59":{}},"content":{"2":{},"4":{},"5":{},"32":{},"47":{},"58":{},"59":{},"60":{}},"tags":{}}],["context",{"_index":122,"title":{},"content":{"4":{},"6":{},"7":{},"8":{}},"tags":{}}],["contextu",{"_index":120,"title":{},"content":{"4":{},"6":{},"7":{},"8":{},"27":{},"28":{},"29":{},"65":{}},"tags":{}}],["continu",{"_index":380,"title":{},"content":{"45":{}},"tags":{}}],["convers",{"_index":12,"title":{},"content":{"1":{},"2":{},"9":{},"10":{}},"tags":{}}],["convert",{"_index":586,"title":{},"content":{"63":{}},"tags":{}}],["copi",{"_index":189,"title":{},"content":{"13":{},"14":{},"33":{},"40":{},"46":{}},"tags":{}}],["corner",{"_index":499,"title":{},"content":{"48":{}},"tags":{}}],["cosin",{"_index":465,"title":{},"content":{"47":{},"48":{},"58":{},"59":{}},"tags":{}}],["cover",{"_index":346,"title":{},"content":{"32":{}},"tags":{}}],["craft",{"_index":593,"title":{},"content":{"64":{}},"tags":{}}],["creat",{"_index":117,"title":{"13":{},"14":{},"15":{},"24":{},"31":{},"33":{},"42":{},"48":{}},"content":{"4":{},"6":{},"7":{},"8":{},"13":{},"14":{},"15":{},"16":{},"17":{},"23":{},"24":{},"25":{},"26":{},"31":{},"33":{},"34":{},"35":{},"37":{},"39":{},"41":{},"42":{},"43":{},"46":{},"47":{},"48":{},"58":{}},"tags":{}}],["creation",{"_index":383,"title":{},"content":{"34":{}},"tags":{}}],["credenti",{"_index":433,"title":{},"content":{"37":{}},"tags":{}}],["credit",{"_index":176,"title":{},"content":{"13":{},"14":{},"31":{},"43":{}},"tags":{}}],["criteria",{"_index":221,"title":{},"content":{"23":{},"24":{},"25":{},"26":{},"57":{}},"tags":{}}],["current",{"_index":23,"title":{},"content":{"2":{},"9":{},"10":{}},"tags":{}}],["daili",{"_index":624,"title":{},"content":{"66":{}},"tags":{}}],["danger",{"_index":424,"title":{},"content":{"36":{}},"tags":{}}],["data",{"_index":204,"title":{"20":{},"22":{},"49":{},"61":{}},"content":{"15":{},"16":{},"17":{},"18":{},"19":{},"20":{},"21":{},"22":{},"23":{},"24":{},"25":{},"26":{},"27":{},"28":{},"29":{},"34":{},"46":{},"47":{},"48":{},"49":{},"50":{},"56":{},"60":{},"61":{},"63":{},"65":{},"66":{},"67":{}},"tags":{}}],["databas",{"_index":196,"title":{"16":{},"34":{},"37":{}},"content":{"15":{},"16":{},"17":{},"35":{},"36":{},"37":{},"39":{},"46":{},"48":{},"55":{}},"tags":{}}],["dataset",{"_index":223,"title":{"19":{},"52":{},"60":{}},"content":{"18":{},"19":{},"20":{},"21":{},"22":{},"34":{},"52":{},"60":{}},"tags":{}}],["decad",{"_index":628,"title":{},"content":{"66":{}},"tags":{}}],["deduct",{"_index":610,"title":{},"content":{"66":{}},"tags":{}}],["default",{"_index":138,"title":{},"content":{"5":{},"6":{},"7":{},"8":{},"35":{}},"tags":{}}],["definit",{"_index":460,"title":{},"content":{"47":{},"48":{},"58":{},"59":{}},"tags":{}}],["delet",{"_index":561,"title":{},"content":{"55":{}},"tags":{}}],["deploy",{"_index":195,"title":{"16":{},"34":{}},"content":{"15":{},"16":{},"17":{},"34":{},"35":{},"39":{},"48":{}},"tags":{}}],["descript",{"_index":339,"title":{},"content":{"32":{}},"tags":{}}],["determin",{"_index":472,"title":{},"content":{"47":{}},"tags":{}}],["dev",{"_index":159,"title":{"11":{},"40":{}},"content":{"11":{},"12":{}},"tags":{}}],["develop",{"_index":229,"title":{},"content":{"18":{},"19":{},"20":{},"21":{},"22":{},"52":{},"60":{},"67":{}},"tags":{}}],["developer/ai",{"_index":289,"title":{},"content":{"41":{}},"tags":{}}],["dialog",{"_index":416,"title":{},"content":{"35":{},"38":{}},"tags":{}}],["differ",{"_index":604,"title":{},"content":{"66":{}},"tags":{}}],["dimens",{"_index":470,"title":{},"content":{"47":{},"48":{}},"tags":{}}],["directori",{"_index":292,"title":{},"content":{"41":{}},"tags":{}}],["display",{"_index":448,"title":{},"content":{"46":{}},"tags":{}}],["do",{"_index":361,"title":{},"content":{"43":{}},"tags":{}}],["document",{"_index":99,"title":{"58":{},"59":{}},"content":{"3":{},"4":{},"6":{},"7":{},"8":{},"18":{},"19":{},"20":{},"21":{},"22":{},"23":{},"24":{},"25":{},"26":{},"32":{},"47":{},"48":{},"49":{},"53":{},"55":{},"56":{},"57":{},"58":{},"59":{},"61":{},"63":{},"66":{}},"tags":{}}],["don't",{"_index":439,"title":{},"content":{"38":{},"46":{}},"tags":{}}],["done",{"_index":405,"title":{},"content":{"34":{}},"tags":{}}],["don’t",{"_index":598,"title":{},"content":{"66":{}},"tags":{}}],["dotproduct",{"_index":466,"title":{},"content":{"47":{}},"tags":{}}],["down",{"_index":412,"title":{},"content":{"35":{},"63":{}},"tags":{}}],["download",{"_index":225,"title":{},"content":{"18":{},"19":{},"20":{},"21":{},"22":{},"52":{},"60":{}},"tags":{}}],["driver",{"_index":560,"title":{},"content":{"55":{}},"tags":{}}],["dure",{"_index":222,"title":{},"content":{"23":{},"24":{},"25":{},"26":{},"32":{},"40":{},"57":{}},"tags":{}}],["each",{"_index":74,"title":{},"content":{"1":{},"5":{},"6":{},"7":{},"8":{}},"tags":{}}],["easi",{"_index":453,"title":{},"content":{"46":{}},"tags":{}}],["easiest",{"_index":164,"title":{},"content":{"11":{},"12":{},"31":{},"40":{}},"tags":{}}],["easili",{"_index":643,"title":{},"content":{"66":{}},"tags":{}}],["editor",{"_index":501,"title":{},"content":{"48":{}},"tags":{}}],["effici",{"_index":581,"title":{},"content":{"63":{}},"tags":{}}],["email",{"_index":363,"title":{"44":{}},"content":{"43":{},"44":{}},"tags":{}}],["emb",{"_index":237,"title":{},"content":{"18":{},"19":{},"20":{},"21":{},"22":{},"56":{}},"tags":{}}],["embed",{"_index":104,"title":{"21":{},"56":{}},"content":{"3":{},"6":{},"7":{},"8":{},"18":{},"19":{},"20":{},"21":{},"22":{},"47":{},"48":{},"49":{},"50":{},"54":{},"56":{},"58":{},"59":{},"61":{},"63":{}},"tags":{}}],["encoding_name=\"cl100k_bas",{"_index":535,"title":{},"content":{"49":{}},"tags":{}}],["end",{"_index":157,"title":{},"content":{"5":{}},"tags":{}}],["enhanc",{"_index":242,"title":{},"content":{"27":{},"28":{},"29":{},"65":{}},"tags":{}}],["enter",{"_index":322,"title":{},"content":{"33":{}},"tags":{}}],["entir",{"_index":426,"title":{},"content":{"36":{}},"tags":{}}],["entri",{"_index":86,"title":{},"content":{"1":{}},"tags":{}}],["environ",{"_index":160,"title":{"11":{},"40":{}},"content":{"11":{},"12":{},"36":{},"41":{}},"tags":{}}],["error",{"_index":651,"title":{},"content":{"66":{}},"tags":{}}],["etc",{"_index":590,"title":{},"content":{"63":{}},"tags":{}}],["euclidean",{"_index":464,"title":{},"content":{"47":{}},"tags":{}}],["event",{"_index":362,"title":{},"content":{"43":{}},"tags":{}}],["everyth",{"_index":444,"title":{},"content":{"39":{}},"tags":{}}],["exampl",{"_index":459,"title":{},"content":{"47":{},"66":{},"67":{}},"tags":{}}],["execut",{"_index":284,"title":{},"content":{"41":{}},"tags":{}}],["exist",{"_index":186,"title":{},"content":{"13":{},"14":{},"33":{}},"tags":{}}],["expect",{"_index":607,"title":{},"content":{"66":{}},"tags":{}}],["experi",{"_index":181,"title":{},"content":{"13":{},"14":{},"31":{}},"tags":{}}],["expos",{"_index":425,"title":{},"content":{"36":{}},"tags":{}}],["extern",{"_index":246,"title":{},"content":{"27":{},"28":{},"29":{},"65":{}},"tags":{}}],["face",{"_index":544,"title":{},"content":{"52":{}},"tags":{}}],["fail",{"_index":653,"title":{},"content":{"66":{}},"tags":{}}],["favorit",{"_index":403,"title":{},"content":{"34":{}},"tags":{}}],["fetch",{"_index":77,"title":{},"content":{"1":{}},"tags":{}}],["field",{"_index":418,"title":{},"content":{"36":{},"47":{},"48":{},"58":{},"59":{}},"tags":{}}],["file",{"_index":275,"title":{},"content":{"40":{}},"tags":{}}],["fill",{"_index":31,"title":{},"content":{"2":{},"3":{},"4":{},"5":{},"45":{},"49":{},"50":{},"56":{},"58":{},"59":{},"61":{}},"tags":{}}],["filter",{"_index":216,"title":{"26":{},"57":{},"58":{},"59":{}},"content":{"23":{},"24":{},"25":{},"26":{},"47":{},"57":{},"58":{},"59":{}},"tags":{}}],["final",{"_index":239,"title":{},"content":{"18":{},"19":{},"20":{},"21":{},"22":{},"34":{},"61":{}},"tags":{}}],["find",{"_index":665,"title":{},"content":{"67":{}},"tags":{}}],["finish",{"_index":376,"title":{"45":{}},"content":{"45":{}},"tags":{}}],["firework",{"_index":173,"title":{},"content":{"13":{},"14":{},"31":{},"32":{},"33":{}},"tags":{}}],["first",{"_index":199,"title":{},"content":{"15":{},"16":{},"17":{},"18":{},"19":{},"20":{},"21":{},"22":{},"31":{},"34":{},"36":{},"47":{},"49":{},"53":{},"58":{},"60":{},"66":{}},"tags":{}}],["folder",{"_index":375,"title":{},"content":{"44":{}},"tags":{}}],["follow",{"_index":42,"title":{},"content":{"2":{},"3":{},"4":{},"5":{},"27":{},"28":{},"29":{},"31":{},"32":{},"33":{},"41":{},"42":{},"47":{},"48":{},"49":{},"50":{},"56":{},"58":{},"59":{},"61":{},"66":{},"67":{}},"tags":{}}],["forget",{"_index":458,"title":{},"content":{"46":{}},"tags":{}}],["form",{"_index":358,"title":{},"content":{"43":{},"45":{},"47":{}},"tags":{}}],["forth",{"_index":11,"title":{},"content":{"2":{},"9":{},"10":{}},"tags":{}}],["forum",{"_index":670,"title":{},"content":{"67":{}},"tags":{}}],["free",{"_index":200,"title":{},"content":{"15":{},"16":{},"17":{},"31":{},"34":{},"43":{}},"tags":{}}],["further",{"_index":481,"title":{},"content":{"47":{}},"tags":{}}],["futur",{"_index":270,"title":{},"content":{"40":{}},"tags":{}}],["genai",{"_index":667,"title":{},"content":{"67":{}},"tags":{}}],["gener",{"_index":81,"title":{"21":{},"56":{},"64":{}},"content":{"1":{},"4":{},"5":{},"6":{},"7":{},"8":{},"18":{},"19":{},"20":{},"21":{},"22":{},"27":{},"28":{},"29":{},"48":{},"56":{},"62":{},"64":{},"65":{},"67":{}},"tags":{}}],["get_embedding(doc[\"bodi",{"_index":567,"title":{},"content":{"56":{}},"tags":{}}],["git",{"_index":287,"title":{},"content":{"41":{}},"tags":{}}],["github",{"_index":257,"title":{},"content":{"40":{},"41":{}},"tags":{}}],["give",{"_index":175,"title":{},"content":{"13":{},"14":{},"31":{},"66":{}},"tags":{}}],["go",{"_index":353,"title":{},"content":{"38":{},"43":{}},"tags":{}}],["goal",{"_index":327,"title":{},"content":{"32":{}},"tags":{}}],["goe",{"_index":445,"title":{},"content":{"39":{}},"tags":{}}],["good",{"_index":637,"title":{},"content":{"66":{}},"tags":{}}],["googl",{"_index":167,"title":{},"content":{"11":{},"12":{},"31":{},"40":{}},"tags":{}}],["govern",{"_index":103,"title":{},"content":{"3":{},"6":{},"7":{},"8":{}},"tags":{}}],["graphic",{"_index":632,"title":{},"content":{"66":{}},"tags":{}}],["green",{"_index":382,"title":{},"content":{"34":{}},"tags":{}}],["greet",{"_index":357,"title":{},"content":{"43":{}},"tags":{}}],["ground",{"_index":249,"title":{},"content":{"27":{},"28":{},"29":{},"65":{}},"tags":{}}],["gte",{"_index":504,"title":{},"content":{"48":{},"59":{}},"tags":{}}],["hand",{"_index":347,"title":{},"content":{"32":{}},"tags":{}}],["hardest",{"_index":406,"title":{},"content":{"34":{}},"tags":{}}],["have",{"_index":87,"title":{},"content":{"1":{},"66":{}},"tags":{}}],["haven't",{"_index":371,"title":{},"content":{"44":{}},"tags":{}}],["help",{"_index":666,"title":{},"content":{"67":{}},"tags":{}}],["henc",{"_index":621,"title":{},"content":{"66":{}},"tags":{}}],["here",{"_index":338,"title":{},"content":{"32":{},"66":{},"67":{}},"tags":{}}],["hi",{"_index":645,"title":{},"content":{"66":{}},"tags":{}}],["histori",{"_index":29,"title":{},"content":{"2":{},"9":{},"10":{}},"tags":{}}],["homepag",{"_index":313,"title":{},"content":{"31":{}},"tags":{}}],["host",{"_index":172,"title":{},"content":{"13":{},"14":{},"31":{}},"tags":{}}],["https://github.com/mongodb",{"_index":288,"title":{},"content":{"41":{}},"tags":{}}],["hug",{"_index":543,"title":{},"content":{"52":{}},"tags":{}}],["i'm",{"_index":646,"title":{},"content":{"66":{}},"tags":{}}],["i.",{"_index":238,"title":{},"content":{"18":{},"19":{},"20":{},"21":{},"22":{},"56":{},"66":{}},"tags":{}}],["icon",{"_index":337,"title":{},"content":{"32":{}},"tags":{}}],["id",{"_index":73,"title":{},"content":{"1":{}},"tags":{}}],["imag",{"_index":588,"title":{},"content":{"63":{}},"tags":{}}],["impact",{"_index":513,"title":{},"content":{"58":{},"59":{},"66":{}},"tags":{}}],["import",{"_index":64,"title":{},"content":{"1":{},"9":{},"10":{},"34":{},"46":{}},"tags":{}}],["includ",{"_index":422,"title":{},"content":{"36":{},"47":{}},"tags":{}}],["incorpor",{"_index":21,"title":{},"content":{"2":{},"9":{},"10":{}},"tags":{}}],["increment",{"_index":146,"title":{},"content":{"5":{},"6":{},"7":{},"8":{}},"tags":{}}],["index",{"_index":71,"title":{"24":{},"48":{}},"content":{"1":{},"23":{},"24":{},"25":{},"26":{},"47":{},"48":{},"50":{},"58":{},"59":{}},"tags":{}}],["industri",{"_index":182,"title":{},"content":{"13":{},"14":{},"31":{}},"tags":{}}],["info",{"_index":360,"title":{},"content":{"43":{},"48":{}},"tags":{}}],["inform",{"_index":245,"title":{},"content":{"27":{},"28":{},"29":{},"63":{},"64":{},"65":{},"66":{}},"tags":{}}],["ingest",{"_index":203,"title":{"22":{},"61":{}},"content":{"15":{},"16":{},"17":{},"18":{},"19":{},"20":{},"21":{},"22":{},"23":{},"24":{},"25":{},"26":{},"46":{},"48":{},"56":{},"61":{}},"tags":{}}],["input",{"_index":390,"title":{},"content":{"34":{}},"tags":{}}],["insert",{"_index":562,"title":{},"content":{"55":{}},"tags":{}}],["instal",{"_index":299,"title":{},"content":{"30":{},"41":{},"66":{}},"tags":{}}],["instruct",{"_index":126,"title":{},"content":{"4":{},"6":{},"7":{},"8":{},"13":{},"14":{},"31":{},"64":{}},"tags":{}}],["instructor",{"_index":343,"title":{},"content":{"32":{}},"tags":{}}],["intak",{"_index":626,"title":{},"content":{"66":{}},"tags":{}}],["interest",{"_index":350,"title":{},"content":{"32":{}},"tags":{}}],["internet",{"_index":602,"title":{},"content":{"66":{}},"tags":{}}],["introduct",{"_index":326,"title":{"32":{}},"content":{},"tags":{}}],["involv",{"_index":579,"title":{},"content":{"63":{},"64":{},"66":{}},"tags":{}}],["ip",{"_index":420,"title":{},"content":{"36":{},"38":{}},"tags":{}}],["isn't",{"_index":105,"title":{},"content":{"3":{},"6":{},"7":{},"8":{},"32":{}},"tags":{}}],["issu",{"_index":656,"title":{},"content":{"66":{}},"tags":{}}],["it'",{"_index":452,"title":{},"content":{"46":{}},"tags":{}}],["json",{"_index":500,"title":{},"content":{"48":{}},"tags":{}}],["jupyt",{"_index":162,"title":{},"content":{"11":{},"12":{},"40":{},"41":{}},"tags":{}}],["keep",{"_index":267,"title":{},"content":{"40":{},"66":{}},"tags":{}}],["key",{"_index":185,"title":{"14":{},"33":{}},"content":{"13":{},"14":{},"31":{},"33":{}},"tags":{}}],["kill/interrupt",{"_index":569,"title":{},"content":{"56":{}},"tags":{}}],["knowledg",{"_index":191,"title":{},"content":{"15":{},"16":{},"17":{},"27":{},"28":{},"29":{},"42":{},"48":{},"63":{},"65":{},"66":{}},"tags":{}}],["lab",{"_index":67,"title":{},"content":{"1":{},"11":{},"12":{},"13":{},"14":{},"15":{},"16":{},"17":{},"18":{},"19":{},"20":{},"21":{},"22":{},"31":{},"32":{},"34":{},"36":{},"40":{},"41":{},"42":{},"43":{},"46":{},"48":{},"60":{},"67":{}},"tags":{}}],["lab/bin/activ",{"_index":298,"title":{},"content":{"41":{}},"tags":{}}],["langchain",{"_index":546,"title":{},"content":{"53":{}},"tags":{}}],["languag",{"_index":244,"title":{},"content":{"27":{},"28":{},"29":{},"65":{}},"tags":{}}],["larg",{"_index":232,"title":{},"content":{"18":{},"19":{},"20":{},"21":{},"22":{},"27":{},"28":{},"29":{},"49":{},"63":{},"65":{}},"tags":{}}],["last",{"_index":188,"title":{},"content":{"13":{},"14":{},"33":{},"66":{}},"tags":{}}],["later",{"_index":205,"title":{},"content":{"15":{},"16":{},"17":{},"34":{},"37":{},"46":{}},"tags":{}}],["launch",{"_index":300,"title":{},"content":{"41":{}},"tags":{}}],["lead",{"_index":107,"title":{},"content":{"3":{},"6":{},"7":{},"8":{},"13":{},"14":{},"31":{}},"tags":{}}],["learn",{"_index":190,"title":{},"content":{"15":{},"16":{},"17":{},"32":{},"42":{},"67":{}},"tags":{}}],["lectur",{"_index":340,"title":{},"content":{"32":{}},"tags":{}}],["led",{"_index":344,"title":{},"content":{"32":{}},"tags":{}}],["left",{"_index":441,"title":{},"content":{"38":{}},"tags":{}}],["let'",{"_index":116,"title":{},"content":{"4":{},"6":{},"7":{},"8":{},"18":{},"19":{},"20":{},"21":{},"22":{},"23":{},"24":{},"25":{},"26":{},"50":{},"60":{}},"tags":{}}],["librari",{"_index":62,"title":{"1":{},"9":{},"18":{},"51":{}},"content":{"9":{},"10":{},"18":{},"19":{},"20":{},"21":{},"22":{},"30":{},"52":{},"54":{}},"tags":{}}],["limit",{"_index":490,"title":{},"content":{"47":{},"50":{},"58":{},"59":{}},"tags":{}}],["link",{"_index":369,"title":{},"content":{"44":{}},"tags":{}}],["list",{"_index":550,"title":{},"content":{"53":{},"60":{}},"tags":{}}],["llama",{"_index":123,"title":{},"content":{"4":{},"6":{},"7":{},"8":{},"13":{},"14":{},"31":{}},"tags":{}}],["llm",{"_index":13,"title":{},"content":{"1":{},"2":{},"3":{},"6":{},"7":{},"8":{},"9":{},"10":{},"27":{},"28":{},"29":{},"64":{},"65":{},"66":{}},"tags":{}}],["llm'",{"_index":84,"title":{},"content":{"1":{}},"tags":{}}],["load",{"_index":224,"title":{"19":{},"60":{}},"content":{"18":{},"19":{},"20":{},"21":{},"22":{},"49":{},"60":{}},"tags":{}}],["local",{"_index":280,"title":{"41":{}},"content":{"41":{}},"tags":{}}],["lock",{"_index":411,"title":{},"content":{"35":{}},"tags":{}}],["log",{"_index":319,"title":{},"content":{"33":{},"34":{}},"tags":{}}],["logic",{"_index":20,"title":{},"content":{"2":{},"9":{},"10":{}},"tags":{}}],["login",{"_index":316,"title":{},"content":{"31":{}},"tags":{}}],["long",{"_index":568,"title":{},"content":{"56":{},"66":{}},"tags":{}}],["look",{"_index":454,"title":{},"content":{"46":{},"47":{},"58":{},"59":{}},"tags":{}}],["lower",{"_index":497,"title":{},"content":{"48":{}},"tags":{}}],["m",{"_index":296,"title":{},"content":{"41":{}},"tags":{}}],["m0",{"_index":389,"title":{},"content":{"34":{}},"tags":{}}],["main",{"_index":255,"title":{},"content":{"27":{},"28":{},"29":{},"62":{},"63":{}},"tags":{}}],["mainli",{"_index":578,"title":{},"content":{"63":{}},"tags":{}}],["make",{"_index":266,"title":{},"content":{"37":{},"40":{}},"tags":{}}],["mani",{"_index":5,"title":{},"content":{"2":{},"9":{},"10":{},"47":{}},"tags":{}}],["manual",{"_index":399,"title":{"38":{}},"content":{"34":{}},"tags":{}}],["match",{"_index":219,"title":{},"content":{"23":{},"24":{},"25":{},"26":{},"37":{},"57":{}},"tags":{}}],["materi",{"_index":341,"title":{},"content":{"32":{}},"tags":{}}],["meal",{"_index":641,"title":{},"content":{"66":{}},"tags":{}}],["mean",{"_index":14,"title":{},"content":{"2":{},"9":{},"10":{},"32":{},"36":{}},"tags":{}}],["memori",{"_index":2,"title":{"2":{},"10":{}},"content":{"1":{},"2":{},"9":{},"10":{},"15":{},"16":{},"17":{},"32":{},"42":{},"67":{}},"tags":{}}],["menu",{"_index":276,"title":{},"content":{"40":{}},"tags":{}}],["merg",{"_index":553,"title":{},"content":{"53":{}},"tags":{}}],["messag",{"_index":28,"title":{},"content":{"1":{},"2":{},"9":{},"10":{},"66":{}},"tags":{}}],["messages=[{\"rol",{"_index":135,"title":{},"content":{"4":{},"5":{}},"tags":{}}],["meta",{"_index":495,"title":{},"content":{"47":{},"50":{},"58":{},"59":{}},"tags":{}}],["metadata",{"_index":475,"title":{},"content":{"47":{},"60":{}},"tags":{}}],["metadata.contenttyp",{"_index":516,"title":{},"content":{"58":{},"59":{}},"tags":{}}],["metric",{"_index":471,"title":{},"content":{"47":{}},"tags":{}}],["min",{"_index":333,"title":{},"content":{"32":{},"56":{}},"tags":{}}],["minut",{"_index":373,"title":{},"content":{"44":{}},"tags":{}}],["modal",{"_index":320,"title":{},"content":{"33":{},"46":{}},"tags":{}}],["mode",{"_index":264,"title":{},"content":{"40":{}},"tags":{}}],["model",{"_index":94,"title":{},"content":{"3":{},"4":{},"6":{},"7":{},"8":{},"13":{},"14":{},"27":{},"28":{},"29":{},"31":{},"48":{},"54":{},"65":{}},"tags":{}}],["model=model",{"_index":134,"title":{},"content":{"4":{},"5":{}},"tags":{}}],["modifi",{"_index":507,"title":{},"content":{"58":{},"59":{}},"tags":{}}],["mongo",{"_index":330,"title":{},"content":{"32":{}},"tags":{}}],["mongodb",{"_index":30,"title":{"22":{},"23":{},"43":{},"47":{},"61":{}},"content":{"1":{},"2":{},"4":{},"6":{},"7":{},"8":{},"9":{},"10":{},"15":{},"16":{},"17":{},"18":{},"19":{},"20":{},"21":{},"22":{},"23":{},"24":{},"25":{},"26":{},"32":{},"34":{},"35":{},"41":{},"42":{},"43":{},"44":{},"45":{},"47":{},"48":{},"49":{},"50":{},"52":{},"55":{},"56":{},"60":{},"61":{},"67":{}},"tags":{}}],["mongodb+srv://:@:@