79 |
80 |
81 |
82 |
83 |
84 |
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/README.md:
--------------------------------------------------------------------------------
1 | # Dora
2 |
3 | Local drive, AI assisted deep search.
4 |
5 | **For a cloud managed version with agentic capabilities, please see [Dora](https://dorafiles.com)**
6 |
7 | 
8 |
9 |
10 | ## About
11 | Dora is a local search tool that allows you to search files on your local drive using natural language.
12 |
13 | ## Installation
14 |
15 | ### Pull Repo
16 | ```bash
17 | git clone https://github.com/space0blaster/dora.git
18 | cd dora
19 | ```
20 |
21 | ### With Docker
22 | I have provided a `compose.yaml` file so you have everything you need (services) to run Dora.
23 | The `compose.yaml` file includes Ollama and ChromaDB, that's all you need for Dora search.
24 |
25 | There is a start script called `start.sh`. This script is contains all the steps you need to run the `compose.yaml` and the electron app.
26 | The `start.sh` will do the following:
27 | 1. Spin up images with the `compose.yaml` file.
28 | 2. Pull the default models `nomic-embed-text` for embeddings and `artifish/llama3.2-uncensored` for chat search.
29 | 3. Install the Electron app dependencies.
30 | 4. Run the Electron app.
31 |
32 | **Important**: If you already have Ollama and/or ChromaDB running, please spin them down first. If not, the ports will have conflicts and it will not work. If you'd rather use your existing Ollama and/or ChromaDB services, see the Without Docker section below.
33 |
34 | To run the `start.sh` script:
35 | ```bash
36 | sh start.sh
37 | ```
38 |
39 |
40 | ### Without Docker
41 | Assuming you already have Ollama and ChromaDB installed and running, you can simply just run the below commands to run the electron app by itself.
42 | Please note, if you already have Ollama, be sure to pull `nomic-embed-text` and `artifish/llama3.2-uncensored` as they are used. If you'd like, you can run your own choice of embedding and chat models. Configure your config/settings modal with your models.
43 | Dora defaults to the default ports for both Ollama and ChromaDB, `11434` and `8000` respectively, and will point to `localhost` as a base host for both.
44 |
45 | To run the electron app:
46 | ```bash
47 | npm install
48 | npm start
49 | ```
50 |
51 | ---
52 |
53 | ### Initialization
54 | When the program runs initially, it will pop-up the Settings modal. Below are the fields:
55 |
56 | 
57 |
58 | 1. `Target Directory`: This is the base directory which will be the starting point for the crawler/indexing function. Default is your base user directory See note no. 1.
59 | 2. `Ollama Host`: The host where Ollama is located. Default is `localhost`.
60 | 3. `Ollama Port`: The port for Ollama. Default is `11434` which is the default Ollama port.
61 | 4. `Chroma Host`: The host where ChromaDB is located. Default is `8000` which is the default ChromaDB port.
62 | 5. `Embed Model`: The model used specifically to create embeddings. Default is `nomic-embed-text` and it will be automatically pulled if you use `start.sh` to install and Dora.
63 | 6. `Chat Model`: The model used for chat search. Default is `antifish/llama3.2-uncensored` and it will be pulled automatically if you use `start.sh` to install and run Dora.
64 |
65 | Click the Save button and you're ready to go.
66 |
67 | ### Changing Target Directory
68 | To change your `Target Directory`, which is where the program starts to crawl recursively, simple click on the gear icon on top right corner and enter whatever directory you want.
69 | This will reset the crawler and embed function.
70 | Use absolute paths.
71 |
72 | ---
73 |
74 | ### Packaging The App
75 | You can package the app for yourself as an application so you have an executable. Please note, if you do this, you'll still have to run the Docker images for the services for the executable to work.
76 |
77 | To package the app:
78 | ```bash
79 | npm run make
80 | ```
81 |
82 | This will output your executable to a new sub folder in the `dora` directory located in `dora/out` and then the folder specific to your system architecture.
83 |
84 | ---
85 |
86 | If you want an executable that is cloud-based using the latest SOTA models, please see [Dora](https://dorafiles.com).
87 |
88 | ## Notes
89 | 1. If you have a lot of files here, I recommend pointing it to something less dense so you can try Dora out first without the crawler running for a long time; you can change this later.
90 |
91 | * Allow the model to warm up on the first chat request. Especially if you're running this on a relatively weak machine.
92 | * Dora will create an application folder call `.dora` in your base user directory where it will store the above-mentioned configs, chat log and the indexed files.
93 | * I am using [artifish/llama3.2-uncensored](https://ollama.com/artifish/llama3.2-uncensored) because asking some models for private files freaks them out.
94 | * You can try and use other uncensored models, I picked this one because it's relatively small and does well locally.
95 | * You can also change your embedding model, the default `nomic-embed-text` does the job fine though. You can just use the embedding models that come with ChromaDB, just make sure you specify each time you embed and query.
96 |
97 | ## License
98 | Apache 2.0
99 |
100 |
--------------------------------------------------------------------------------
/src/scripts/files.js:
--------------------------------------------------------------------------------
1 | let indexedFiles=0;
2 | let embeddedMetadata=0;
3 |
4 | class DoraFiles {
5 | constructor() {
6 | this.indexPath=appDataDir+'/index.json';
7 | }
8 | showFiles(dir) {
9 | E.get('pathIndicator').innerHTML='';
10 | E.get('filesGrid').innerHTML='';
11 | let pathIndicator=E.get('pathIndicator');
12 | //
13 | let base=E.span(pathIndicator,'pathIndicatorFolder','');
14 | base.innerHTML='';
15 | base.onclick=()=>{
16 | this.showFiles(config.targetDirectory);
17 | };
18 | E.span(pathIndicator,'','').innerHTML=' / ';
19 | for(let i=1;i{
23 | let buildPath='';
24 | for(let j=1;j<=i;j++) {
25 | buildPath=buildPath+'/'+dir.split('/')[j];
26 | }
27 | this.showFiles(buildPath);
28 | };
29 | E.span(pathIndicator,'','').innerHTML=' / ';
30 | }
31 | //
32 | let filesGrid=E.get('filesGrid');
33 | fs.readdir(dir, async (err, files) => {
34 | if (files) {
35 | files.forEach((file) => {
36 | let isDir=DoraFiles.isDirectory(path.join(dir,file));
37 | let f=E.div(filesGrid, 'gridItem', '');
38 | if(file.split('.')[file.split('.').length - 1] === 'png') E.img(f, 'gridItemThumb', '', dir + '/' + file);
39 | else if(isDir) E.div(f, 'gridItemIcon', '').innerHTML = '';
40 | else E.div(f, 'gridItemIcon', '').innerHTML = '';
41 | E.div(f, 'gridItemName', '').innerHTML = T.s(file, 20);
42 | f.onclick=()=>{};
43 | f.addEventListener("dblclick", (e) => {
44 | e.preventDefault();
45 | if(isDir) this.showFiles(dir+'/'+file);
46 | else shell.openPath(dir+'/'+file);
47 | });
48 | });
49 | if(fs.existsSync(this.indexPath)) {
50 | if(JSON.parse(fs.readFileSync(this.indexPath)).targetDirectory===config.targetDirectory) {
51 | indexedFiles=JSON.parse(fs.readFileSync(this.indexPath)).files.length;
52 | const collection=await chroma.getCollection({name:md5(config.targetDirectory)});
53 | embeddedMetadata=await collection.count();
54 | E.get('indexed').innerHTML='Target Directory: '+config.targetDirectory+' Files Indexed: '+H.numberNotation(indexedFiles, {notation:'short'})+' Metadata Embedded: '+H.numberNotation(embeddedMetadata,{notation:'short'});
55 | }
56 | else this.indexDirectory();
57 | }
58 | else {
59 | this.indexDirectory();
60 | }
61 | }
62 | });
63 | }
64 | indexDirectory() {
65 | let indexed={
66 | targetDirectory:config.targetDirectory,
67 | model:config.embedModel,
68 | files:[]
69 | };
70 | function walk(dir) {
71 | let items=fs.readdirSync(dir);
72 | if(items && items.length>0) {
73 | items.forEach((item)=>{
74 | if(config.ignored.indexOf(item)===-1) {
75 | let isDir=DoraFiles.isDirectory(path.join(dir,item));
76 | if(isDir) walk(path.join(dir,item));
77 | else {
78 | let filePath=path.join(dir,item);
79 | indexed.files.push({name:item,isDirectory:isDir,path:filePath,embedded:false});
80 | indexedFiles++;
81 | E.get('indexed').innerHTML='Target Directory: '+config.targetDirectory+' Files Indexed: '+indexedFiles;
82 | }
83 | }
84 | });
85 | }
86 | }
87 | walk(config.targetDirectory);
88 | E.get('indexed').innerHTML='Target Directory: '+config.targetDirectory+' Files Indexed: '+H.numberNotation(indexedFiles,{notation:'short'});
89 | fs.writeFile(this.indexPath,JSON.stringify(indexed),()=>{
90 | this.embedToChroma(indexed.files).then(vector=>{
91 | E.get('indexed').innerHTML='Target Directory: '+config.targetDirectory+' Files Indexed: '+H.numberNotation(indexedFiles,{notation:'short'})+' Indexes Embedded: '+H.numberNotation(embeddedMetadata,{notation:'short'});
92 | });
93 | });
94 | };
95 | static isDirectory(filePath) {
96 | try {
97 | const stats=fs.statSync(filePath);
98 | return (stats.mode & fs.constants.S_IFDIR)===fs.constants.S_IFDIR;
99 | } catch (error) {
100 | return false;
101 | }
102 | }
103 | async embedToChroma(data) {
104 | //
105 | let ids=[];
106 | let vectors=[];
107 | let documents=[];
108 | for(let i=0;iFiles Indexed: '+H.numberNotation(indexedFiles,{notation:'short'})+' Metadata Embedded: '+embeddedMetadata+'/'+indexedFiles+' ('+(embeddedMetadata/indexedFiles*100).toFixed(2)+'%)';
116 | E.get('progressInner').style.width=Math.floor((embeddedMetadata/indexedFiles)*100)+'%';
117 | }
118 | const collection=await chroma.getOrCreateCollection({name: md5(config.targetDirectory)});
119 | await collection.add({ids:ids,embeddings:vectors,documents:documents});
120 | return true;
121 | }
122 | }
123 |
124 |
125 | let files=new DoraFiles();
126 | files.showFiles(config.targetDirectory);
127 |
128 |
129 | E.get('settings').onclick=()=>{
130 | ipcRenderer.send('open-settings',{});
131 | };
132 |
--------------------------------------------------------------------------------
/src/scripts/chat.js:
--------------------------------------------------------------------------------
1 | class DoraChat {
2 | constructor() {
3 | this.path=appDataDir+'/chat.json';
4 | this.systemPrompt="Your name is Dora, a local file search assistant. Respond in JSON format with results in an array called 'files' and your accompanying text response in a key called 'text'. Be brief.";
5 | }
6 | async startModel() {
7 | ollama.ps().then(async running=>{
8 | if(running.models.findIndex(x=>x.name===config.chatModel)===-1) {
9 | await ollama.create({model:config.chatModel,from:config.chatModel,system:this.systemPrompt});
10 | console.log('start new model');
11 | }
12 | else {
13 | await ollama.show({model:config.chatModel}).then(async model=>{
14 | if(model.system!==this.systemPrompt) {
15 | await ollama.create({model:config.chatModel,from:config.chatModel,system:this.systemPrompt});
16 | console.log('running model system prompt does not match, starting a new one');
17 | }
18 | else console.log('no need to start model, already running');
19 | });
20 | }
21 | });
22 | };
23 | history(chatHistory,chatTable) {
24 | fs.readFile(this.path, 'utf-8', (err, data) => {
25 | if(err){
26 | alert("An error reading history :" + err.message);
27 | return;
28 | }
29 | chatHistory=JSON.parse(data);
30 | for(let i=0;i';
41 | for(let i=0;i';
44 | f.onclick=()=>{
45 | shell.openPath(structuredReply.files[i][Object.keys(structuredReply.files[i])[1]]);
46 | };
47 | }
48 | r.scrollIntoView();
49 | }
50 | }
51 | //
52 | });
53 | };
54 | async query(chatHistory,prompt,promptEmbeddings,r) {
55 | const collection=await chroma.getCollection({name:md5(config.targetDirectory)});
56 | let nResults=10;
57 | if(await collection.count()<10) nResults=await collection.count();
58 | const queryData=await collection.query({
59 | queryEmbeddings:promptEmbeddings.embeddings,
60 | nResults:nResults
61 | });
62 | ollama.chat({model:config.chatModel,messages:[{role:"user",content:"Using this data: " + queryData['documents'][0] + ". Respond to this prompt: " + prompt}]}).then(reply=>{
63 | console.log(reply.message.content);
64 | try {
65 | let structuredReply=JSON.parse(reply.message.content);
66 | r.innerHTML='';
67 | r.innerHTML='
COULD NOT PARSE. Note: chat model could not follow stuctured output in this instance, so here is the raw output instead:
'+reply.message.content+'
';
83 | }
84 | });
85 |
86 | //
87 | };
88 | chat() {
89 | let chatHistory=[];
90 | E.get('response').innerHTML='';
91 | let chatTable=E.table(E.get('response'),'','chatTable','center','100%');
92 | //
93 | if(!fs.existsSync(this.path)){
94 | fs.writeFile(this.path+'/chat.json','[]',(err)=>{
95 | if(err) alert('Could not create file'+err);
96 | });
97 | }
98 | //
99 | this.history(chatHistory,chatTable);
100 |
101 | let input=document.getElementById('input');
102 | input.onkeydown=(e)=>{
103 | if(e.keyCode===13) {
104 | let q=E.div(E.tableC(E.tableR(chatTable),''),'inputText','');
105 | q.innerHTML=input.value;
106 | q.scrollIntoView();
107 | chatHistory.push({role:'user',content:input.value});
108 | let inputVal=input.value;
109 | input.value='';
110 | let r=E.div(E.tableC(E.tableR(chatTable),''),'responseBlock','');
111 | E.img(r,'responseLoad','','images/loading.gif').scrollIntoView();
112 | async function embedPrompt(){
113 | return await ollama.embed({model:config.embedModel,input:inputVal});
114 | }
115 | embedPrompt().then(promptEmbeddings=>{
116 | this.query(chatHistory,inputVal,promptEmbeddings,r);
117 | fs.writeFile(this.path, JSON.stringify(chatHistory),(err)=>{
118 | if(err) alert('Error saving session');
119 | });
120 | });
121 | }
122 | };
123 | //
124 | let clear=document.getElementById('clear');
125 | clear.onclick=()=>{
126 | fs.writeFile(this.path,'[]',(err)=>{
127 | if(err) alert('Could not create file'+err);
128 | this.chat();
129 | });
130 | };
131 | };
132 | }
133 | //
134 | const chat=new DoraChat();
135 | chat.startModel().then(()=>{
136 | chat.chat();
137 | });
138 |
--------------------------------------------------------------------------------
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/src/scripts/e.js:
--------------------------------------------------------------------------------
1 | class E {
2 | static get(id) {
3 | return document.getElementById(id);
4 | };
5 | static fetch(type,value) {
6 | let e;
7 | switch(type) {
8 | case 'className':
9 | e=document.getElementsByClassName(value);
10 | break;
11 | case 'tagName':
12 | e=document.getElementsByTagName(value);
13 | break;
14 | }
15 | return e;
16 | }
17 | static fetch2(parent,type,value) {
18 | let e;
19 | switch(type) {
20 | case 'className':
21 | e=parent.getElementsByClassName(value);
22 | break;
23 | case 'tagName':
24 | e=parent.getElementsByTagName(value);
25 | break;
26 | }
27 | return e;
28 | }
29 | static bool(e) {
30 | let val;
31 | if(e.checked===true) val=1;
32 | if(e.checked===false) val=0;
33 | return val;
34 | };
35 | static script(parent,src) {
36 | let e=document.createElement('div');
37 | parent.appendChild(e);
38 | e.src=src;
39 | return e;
40 | };
41 |
42 | static div(parent,className,id) {
43 | let e=document.createElement('div');
44 | parent.appendChild(e);
45 | e.className=className;
46 | e.id=id;
47 | return e;
48 | };
49 | static span(parent,className,id) {
50 | let e=document.createElement('span');
51 | parent.appendChild(e);
52 | e.className=className;
53 | e.id=id;
54 | return e;
55 | };
56 | static form(parent,method) {
57 | let e=document.createElement('form');
58 | parent.appendChild(e);
59 | e.method=method;
60 | return e;
61 | };
62 | static a(parent,className,id,href,target) {
63 | let e=document.createElement('a');
64 | parent.appendChild(e);
65 | e.className=className;
66 | e.id=id;
67 | e.href=href;
68 | if(target) e.target=target;
69 | return e;
70 | };
71 | static table(parent,className,id,align,width) {
72 | let e=document.createElement('table');
73 | parent.appendChild(e);
74 | e.className=className;
75 | e.id=id;
76 | e.align=align;
77 | e.width=width;
78 | return e;
79 | };
80 | static tableR(table) {
81 | return table.insertRow(table.rows.length);
82 | };
83 | static tableC(tr,width) {
84 | let e=tr.insertCell(tr.cells.length);
85 | e.width=width;
86 | return e;
87 | };
88 | static tableC2(tr,width,style) {
89 | let e=tr.insertCell(tr.cells.length);
90 | e.width=width;
91 | e.style.background=style.background;
92 | return e;
93 | };
94 | static tableH(tr,width) {
95 | let e=document.createElement('th');
96 | tr.appendChild(e);
97 | e.width=width;
98 | return e;
99 | };
100 | static tableH2(tr,colspan) {
101 | let e=document.createElement('th');
102 | tr.appendChild(e);
103 | e.colSpan=colspan;
104 | return e;
105 | };
106 | static tableHV(tr,rowspan) {
107 | let e=document.createElement('th');
108 | tr.appendChild(e);
109 | e.rowSpan=rowspan;
110 | return e;
111 | };
112 | static img(parent,className,id,src) {
113 | let e=document.createElement('img');
114 | parent.appendChild(e);
115 | e.className=className;
116 | e.id=id;
117 | e.src=src;
118 | return e;
119 | };
120 | static video(parent,className,id,src,ext) {
121 | let e=document.createElement('video');
122 | parent.appendChild(e);
123 | e.className=className;
124 | e.id=id;
125 | //e.innerHTML="";
126 | e.setAttribute("width", "1000");
127 | e.setAttribute("height", "450");
128 | e.setAttribute("controls","controls");
129 | let s=document.createElement('source');
130 | s.src=src;
131 | s.type='video/'+ext;
132 | e.appendChild(s);
133 | return e;
134 | };
135 | static audio(parent,className,id,src,ext) {
136 | let e=document.createElement('audio');
137 | parent.appendChild(e);
138 | e.className=className;
139 | e.id=id;
140 | e.setAttribute("controls","controls");
141 | let s=document.createElement('source');
142 | s.src=src;
143 | s.type='audio/'+ext;
144 | e.appendChild(s);
145 | //e.innerHTML="";
146 | return e;
147 | };
148 | static canvas(parent,className,id,width,height) {
149 | let e=document.createElement('canvas');
150 | parent.appendChild(e);
151 | e.className=className;
152 | e.id=id;
153 | e.width=width;
154 | e.height=height;
155 | e.style.width=width;
156 | e.style.height=height;
157 | return e;
158 | };
159 |
160 | static input(parent,type,className,id,placeholder) {
161 | let e=document.createElement('input');
162 | parent.appendChild(e);
163 | e.type=type;
164 | e.className=className;
165 | e.id=id;
166 | e.placeholder=placeholder;
167 | return e;
168 | };
169 | static textarea(parent,className,id,placeholder) {
170 | let e=document.createElement('textarea');
171 | parent.appendChild(e);
172 | e.className=className;
173 | e.id=id;
174 | e.placeholder=placeholder;
175 | return e;
176 | };
177 | static button(parent,className,id,text) {
178 | let e=document.createElement('button');
179 | parent.appendChild(e);
180 | e.className=className;
181 | e.id=id;
182 | e.innerHTML=text;
183 | return e;
184 | };
185 | static select(parent,className,id,options) {
186 | let e=document.createElement('select');
187 | parent.appendChild(e);
188 | e.className=className;
189 | e.id=id;
190 | if(options.length>0) {
191 | for(let i=0;ilimit) return text.substr(0,limit)+" ...";
449 | else return text;
450 | };
451 |
452 | // check empty
453 | static e(text) {
454 | if(text===null || text==='' || !text) return true;
455 | else return false;
456 | }
457 |
458 | static e404(url) {
459 | let http = new XMLHttpRequest();
460 | http.open('HEAD', url, false);
461 | http.send();
462 | if(http.status===404) return true;
463 | else return false;
464 | };
465 |
466 | static yn(val) {
467 | if(parseInt(val)===1) return 'YES';
468 | else return 'NO';
469 | };
470 |
471 | static nullOrNot(val) {
472 | if(val) return 'YES';
473 | else return 'NO';
474 | };
475 |
476 | static finishTime(startTime,hours) {
477 | let today=new Date(startTime).getTime()/1000;
478 | let nextDate=today+(hours*3600);
479 | let finishTime=new Date(nextDate*1000);
480 | return finishTime.toLocaleString('en-US',{hour:'numeric',minute:'numeric',hour12:true});
481 | };
482 |
483 | static isPrimary(isPrimary) {
484 | if(isPrimary===1) return 'Primary';
485 | else return 'Backup';
486 | };
487 | static active(active) {
488 | if(active===1) return 'Active';
489 | else return 'Inactive';
490 | };
491 | static required(required) {
492 | if(required===1) return 'Required';
493 | else return 'Optional';
494 | };
495 | static tagColor(hexColor) {
496 | const hex = hexColor.replace('#', '');
497 | const c_r = parseInt(hex.substr(0, 2), 16);
498 | const c_g = parseInt(hex.substr(2, 2), 16);
499 | const c_b = parseInt(hex.substr(4, 2), 16);
500 | const brightness = ((c_r * 299) + (c_g * 587) + (c_b * 114)) / 1000;
501 | //return brightness > 155;
502 | if((brightness < 155)) return '#FFFFFF';
503 | else return '#222222';
504 | };
505 | static isMe(userId) {
506 | if(userId===currentUser.id) return ' Me';
507 | else return '';
508 | };
509 | static isOwner(isOwner) {
510 | if(parseInt(isOwner)===1) return ' Owner';
511 | else return '';
512 | };
513 |
514 | static isAdmin(isAdmin) {
515 | if(parseInt(isAdmin)===1) return ' Admin';
516 | else return '';
517 | };
518 | static isCurrent(isCurrent) {
519 | if(parseInt(isCurrent)===1) return ' This Session';
520 | else return '';
521 | };
522 | static isDefault(isDefault) {
523 | if(parseInt(isDefault)===1) return ' Default';
524 | else return '';
525 | };
526 | static sourceMethod(method) {
527 | if(method) return ''+method.toUpperCase()+' ';
528 | else return '';
529 | };
530 | static isObjectEmpty(obj) {
531 | for(const prop in obj) {
532 | if(Object.hasOwn(obj,prop)) {
533 | return false;
534 | }
535 | }
536 | return true;
537 | }
538 | static hasParam(obj,param) {
539 | if(obj) {
540 | if(obj[param]) return obj[param];
541 | }
542 | return 'n/a';
543 | }
544 | }
545 | class I {
546 | static search(box,searchTerm) {
547 | let boxes=box.getElementsByClassName('gridItem');
548 | for(let i=0;i<=boxes.length;i++) {
549 | if(boxes[i].innerHTML.toUpperCase().indexOf(searchTerm.toUpperCase())>-1) {
550 | boxes[i].style.display='unset';
551 | }
552 | else {
553 | boxes[i].style.display='none';
554 | }
555 | }
556 | };
557 | }
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