diff --git a/.editorconfig b/.editorconfig new file mode 100644 index 00000000..37dfa3ca --- /dev/null +++ b/.editorconfig @@ -0,0 +1,14 @@ +# editorconfig.org +root = true + +[*] +charset = utf-8 +indent_size = 2 +indent_style = space +insert_final_newline = true +max_line_length = 120 +quote_type = double +trim_trailing_whitespace = true + +[*.md] +trim_trailing_whitespace = false diff --git a/.eslintignore b/.eslintignore new file mode 100644 index 00000000..76add878 --- /dev/null +++ b/.eslintignore @@ -0,0 +1,2 @@ +node_modules +dist \ No newline at end of file diff --git a/.eslintrc.json b/.eslintrc.json new file mode 100644 index 00000000..4c535795 --- /dev/null +++ b/.eslintrc.json @@ -0,0 +1,32 @@ +{ + "root": true, + "extends": [ + "eslint:recommended", + "plugin:@typescript-eslint/recommended", + "plugin:prettier/recommended", + "plugin:unicorn/recommended" + ], + "parser": "@typescript-eslint/parser", + "plugins": [ + "@typescript-eslint", + "prettier", + "unicorn" + ], + "rules": { + "unicorn/filename-case": [ + "error", + { + "cases": { + "camelCase": true, + "pascalCase": true + } + } + ], + "unicorn/prevent-abbreviations": "warn", + "unicorn/no-null": "off", + "@typescript-eslint/no-unused-vars": "off" + }, + "overrides": [ + + ] +} \ No newline at end of file diff --git a/.github/FUNDING.yml b/.github/FUNDING.yml deleted file mode 100644 index faa9fa9f..00000000 --- a/.github/FUNDING.yml +++ /dev/null @@ -1 +0,0 @@ -patreon: itzcrazykns diff --git a/.github/ISSUE_TEMPLATE/bug_report.md b/.github/ISSUE_TEMPLATE/bug_report.md deleted file mode 100644 index 1de11777..00000000 --- a/.github/ISSUE_TEMPLATE/bug_report.md +++ /dev/null @@ -1,27 +0,0 @@ ---- -name: Bug report -about: Create an issue to help us fix bugs -title: '' -labels: bug -assignees: '' ---- - -**Describe the bug** -A clear and concise description of what the bug is. - -**To Reproduce** -Steps to reproduce the behavior: - -1. Go to '...' -2. Click on '....' -3. Scroll down to '....' -4. See error - -**Expected behavior** -A clear and concise description of what you expected to happen. - -**Screenshots** -If applicable, add screenshots to help explain your problem. - -**Additional context** -Add any other context about the problem here. diff --git a/.github/ISSUE_TEMPLATE/custom.md b/.github/ISSUE_TEMPLATE/custom.md deleted file mode 100644 index 96a47352..00000000 --- a/.github/ISSUE_TEMPLATE/custom.md +++ /dev/null @@ -1,7 +0,0 @@ ---- -name: Custom issue template -about: Describe this issue template's purpose here. -title: '' -labels: '' -assignees: '' ---- diff --git a/.github/ISSUE_TEMPLATE/feature_request.md b/.github/ISSUE_TEMPLATE/feature_request.md deleted file mode 100644 index 5f0a04ce..00000000 --- a/.github/ISSUE_TEMPLATE/feature_request.md +++ /dev/null @@ -1,19 +0,0 @@ ---- -name: Feature request -about: Suggest an idea for this project -title: '' -labels: enhancement -assignees: '' ---- - -**Is your feature request related to a problem? Please describe.** -A clear and concise description of what the problem is. Ex. I'm always frustrated when [...] - -**Describe the solution you'd like** -A clear and concise description of what you want to happen. - -**Describe alternatives you've considered** -A clear and concise description of any alternative solutions or features you've considered. - -**Additional context** -Add any other context or screenshots about the feature request here. diff --git a/.github/workflows/pr-gated.yml b/.github/workflows/pr-gated.yml new file mode 100644 index 00000000..0aed1286 --- /dev/null +++ b/.github/workflows/pr-gated.yml @@ -0,0 +1,39 @@ +name: PR-gated + +on: + pull_request: + branches: [main] + types: [opened, synchronize, reopened, ready_for_review] + + workflow_dispatch: + +jobs: + build: + if: github.event.pull_request.draft == false + name: Test on node ${{ matrix.node_version }} and ${{ matrix.os }} + runs-on: ${{ matrix.os }} + strategy: + matrix: + node_version: + - 20.x + - 22.4.x + os: [ubuntu-latest, windows-latest, macOS-latest] + + steps: + - uses: actions/checkout@v3 + - name: Use Node.js ${{ matrix.node_version }} + uses: actions/setup-node@v3 + with: + node-version: ${{ matrix.node_version }} + - name: yarn install + run: yarn --frozen-lockfile + - name: lint + run: yarn lint + - name: build + run: yarn build + - name: yarn install:ui + run: yarn --frozen-lockfine + working-directory: ./ui + - name: build:ui + run: yarn build + working-directory: ./ui diff --git a/.gitignore b/.gitignore index a3dd5cc6..a1381023 100644 --- a/.gitignore +++ b/.gitignore @@ -8,11 +8,6 @@ yarn-error.log /out/ /dist/ -# IDE/Editor specific -.vscode/ -.idea/ -*.iml - # Environment variables .env .env.local diff --git a/.prettierrc b/.prettierrc new file mode 100644 index 00000000..3a181a15 --- /dev/null +++ b/.prettierrc @@ -0,0 +1,5 @@ +{ + "endOfLine": "auto", + "trailingComma": "all", + "arrowParens": "avoid" +} diff --git a/.vscode/extensions.json b/.vscode/extensions.json new file mode 100644 index 00000000..364113b5 --- /dev/null +++ b/.vscode/extensions.json @@ -0,0 +1,14 @@ +{ + "recommendations": [ + "dbaeumer.vscode-eslint", + "streetsidesoftware.code-spell-checker", + "github.codespaces", + "github.copilot", + "github.copilot-chat", + "github.vscode-pull-request-github", + "eamodio.gitlens", + "vincaslt.highlight-matching-tag", + "orta.vscode-jest", + "esbenp.prettier-vscode" + ] +} diff --git a/.vscode/settings.json b/.vscode/settings.json new file mode 100644 index 00000000..376e78f8 --- /dev/null +++ b/.vscode/settings.json @@ -0,0 +1,250 @@ +{ + "files.exclude": { + "**/.git": true, + "**/.svn": true, + "**/.hg": true, + "**/CVS": true, + "**/.DS_Store": true, + "**/.vs": true, + "**/.cache": true + }, + "files.watcherExclude": { + "**/.git": true, + "**/.svn": true, + "**/.hg": true, + "**/CVS": true, + "**/.DS_Store": true, + "**/.vs": true, + "**/.cache": true, + "**/node_modules": true, + "**/node_modules/**": true, + "**/node_modules/*/**": true, + "**/dist": true, + "**/dist/**": true, + "**/dist/*/**": true + }, + "search.exclude": { + "**/.cache": true, + "**/build": true, + "**/dist": true, + "**/coverage": true, + "**/yarn.lock": true, + "**/en-us.*.json": true, + "**/*.lcl": true + }, + "editor.codeActionsOnSave": { + "source.fixAll.eslint": "explicit", + "source.fixAll.stylelint": "explicit" + }, + "[json]": { + "editor.defaultFormatter": "esbenp.prettier-vscode" + }, + "[javascript]": { + "editor.defaultFormatter": "esbenp.prettier-vscode" + }, + "[javascriptreact]": { + "editor.defaultFormatter": "esbenp.prettier-vscode" + }, + "[typescript]": { + "editor.defaultFormatter": "esbenp.prettier-vscode" + }, + "[typescriptreact]": { + "editor.defaultFormatter": "esbenp.prettier-vscode" + }, + "typescript.tsdk": "node_modules/typescript/lib", + "typescript.tsserver.maxTsServerMemory": 4096, + "eslint.workingDirectories": [ + { + "mode": "auto" + } + ], + "eslint.execArgv": ["--max_old_space_size=8192"], + "eslint.codeActionsOnSave.mode": "problems", + "css.validate": false, + "less.validate": false, + "scss.validate": false, + "files.associations": { + "*.js.mustache": "javascript", + "*.json.mustache": "json" + }, + "cSpell.words": [ + "abortcontroller", + "aistudio", + "Algos", + "amlcompute", + "aoai", + "appinsights", + "automl", + "aznb", + "azureml", + "bigint", + "browserslist", + "buildresult", + "buildscripts", + "callout", + "clsx", + "cobertura", + "Conda", + "continuationtoken", + "cudatoolkit", + "Customizer", + "customneuralvoice", + "customspeech", + "cyclomatic", + "Databricks", + "dataprep", + "Dataset", + "Datasets", + "Datastore", + "Datastores", + "dataview", + "dcid", + "debounced", + "Detailskey", + "devtools", + "Dismissable", + "Dont", + "Dropdown", + "eastus", + "Edat", + "endregion", + "Ensembling", + "esnext", + "etag", + "experimentrun", + "explainability", + "fairlearn", + "fbprophet", + "featurization", + "fileexplorer", + "Finetune", + "finetuned", + "Finetuning", + "fluentui", + "formik", + "Ftaas", + "generageresult", + "generatebuildresult", + "gettingstarted", + "Groundedness", + "Handleable", + "hyperdrive", + "Hyperparameters", + "inferencing", + "Interop", + "ipynb", + "IUJS", + "jqueryui", + "jsnext", + "jszip", + "junit", + "Jupyter", + "kubernetes", + "kuende", + "lcov", + "leaderboard", + "lerna", + "lintfix", + "livestamp", + "locstrings", + "machinelearningservices", + "managedenv", + "mcmf", + "metastore", + "metricsmetadata", + "mfeclient", + "mlchartlib", + "mllifecycle", + "mlworkspace", + "mockdate", + "modelmanagement", + "Mooncake", + "msal", + "nameof", + "npmrc", + "numpy", + "odata", + "onnx", + "onwarn", + "openai", + "packagejson", + "papaparse", + "parcoords", + "paygo", + "plotly", + "polyfill", + "Prefetcher", + "projectcontent", + "Projectless", + "Promptflow", + "pytorch", + "quickprofile", + "Rbac", + "realtimespeechtotext", + "recents", + "Resizable", + "resjson", + "resourcegraph", + "resourcegroups", + "rollup", + "roosterjs", + "RTSTT", + "runhistory", + "salte", + "scipy", + "scriptrun", + "scrollable", + "semibold", + "serializable", + "serializer", + "Serializers", + "setuptools", + "Signup", + "skiptoken", + "sklearn", + "SKUs", + "sourcemap", + "spacy", + "storyshots", + "storysource", + "studiocoreservices", + "stylelint", + "stylelintrc", + "submodule", + "Subsampling", + "svgr", + "tablist", + "taskkill", + "Templatized", + "testid", + "theming", + "ticktext", + "tickvals", + "timeframe", + "timeseries", + "Timespan", + "treeshake", + "tslib", + "uifabric", + "Unauth", + "uniquefy", + "unmock", + "unmount", + "Unversioned", + "viewmodel", + "vsts", + "webdriverio", + "webendpoint", + "websockets", + "workspaces", + "wsid", + "xgboost", + "xlarge", + "xmlhttprequest", + "xsmall", + "YYYYMMDD" + ], + "cSpell.ignoreWords": ["editor", "format", "on", "save"], + "editor.tabSize": 2, + "jest.jestCommandLine": "yarn jest --passWithNoTests", +} diff --git a/README.md b/README.md index 9e7f7d89..5ae2e6c2 100644 --- a/README.md +++ b/README.md @@ -88,9 +88,9 @@ There are mainly 2 ways of installing Perplexica - With Docker, Without Docker. 1. Install SearXNG and allow `JSON` format in the SearXNG settings. 2. Clone the repository and rename the `sample.config.toml` file to `config.toml` in the root directory. Ensure you complete all required fields in this file. 3. Rename the `.env.example` file to `.env` in the `ui` folder and fill in all necessary fields. -4. After populating the configuration and environment files, run `npm i` in both the `ui` folder and the root directory. -5. Install the dependencies and then execute `npm run build` in both the `ui` folder and the root directory. -6. Finally, start both the frontend and the backend by running `npm run start` in both the `ui` folder and the root directory. +4. After populating the configuration and environment files, run `yarn install` in both the `ui` folder and the root directory. +5. Install the dependencies and then execute `yarn build` in both the `ui` folder and the root directory. +6. Finally, start both the frontend and the backend by running `yarn start` in both the `ui` folder and the root directory. **Note**: Using Docker is recommended as it simplifies the setup process, especially for managing environment variables and dependencies. diff --git a/drizzle.config.ts b/drizzle.config.ts index 9ac3ec50..802a5fda 100644 --- a/drizzle.config.ts +++ b/drizzle.config.ts @@ -1,10 +1,10 @@ -import { defineConfig } from 'drizzle-kit'; +import { defineConfig } from "drizzle-kit"; export default defineConfig({ - dialect: 'sqlite', - schema: './src/db/schema.ts', - out: './drizzle', + dialect: "sqlite", + schema: "./src/db/schema.ts", + out: "./drizzle", dbCredentials: { - url: './data/db.sqlite', + url: "./data/db.sqlite", }, }); diff --git a/package.json b/package.json index 4f2bb32b..76c311a0 100644 --- a/package.json +++ b/package.json @@ -8,15 +8,22 @@ "build": "tsc", "dev": "nodemon src/app.ts", "db:push": "drizzle-kit push sqlite", - "format": "prettier . --check", - "format:write": "prettier . --write" + "lint": "eslint ." }, "devDependencies": { "@types/better-sqlite3": "^7.6.10", "@types/cors": "^2.8.17", "@types/express": "^4.17.21", "@types/readable-stream": "^4.0.11", + "@typescript-eslint/eslint-plugin": "^7.15.0", + "@typescript-eslint/parser": "^7.15.0", "drizzle-kit": "^0.22.7", + "eslint": "^8.57.0", + "eslint-config-prettier": "^9.1.0", + "eslint-plugin-prettier": "^5.1.3", + "eslint-plugin-react": "^7.34.3", + "eslint-plugin-react-hooks": "^4.6.2", + "eslint-plugin-unicorn": "^54.0.0", "nodemon": "^3.1.0", "prettier": "^3.2.5", "ts-node": "^10.9.2", diff --git a/src/agents/academicSearchAgent.ts b/src/agents/academicSearchAgent.ts index 5c11307a..e8544ab5 100644 --- a/src/agents/academicSearchAgent.ts +++ b/src/agents/academicSearchAgent.ts @@ -1,24 +1,16 @@ -import { BaseMessage } from '@langchain/core/messages'; -import { - PromptTemplate, - ChatPromptTemplate, - MessagesPlaceholder, -} from '@langchain/core/prompts'; -import { - RunnableSequence, - RunnableMap, - RunnableLambda, -} from '@langchain/core/runnables'; -import { StringOutputParser } from '@langchain/core/output_parsers'; -import { Document } from '@langchain/core/documents'; -import { searchSearxng } from '../lib/searxng'; -import type { StreamEvent } from '@langchain/core/tracers/log_stream'; -import type { BaseChatModel } from '@langchain/core/language_models/chat_models'; -import type { Embeddings } from '@langchain/core/embeddings'; -import formatChatHistoryAsString from '../utils/formatHistory'; -import eventEmitter from 'events'; -import computeSimilarity from '../utils/computeSimilarity'; -import logger from '../utils/logger'; +import { BaseMessage } from "@langchain/core/messages"; +import { PromptTemplate, ChatPromptTemplate, MessagesPlaceholder } from "@langchain/core/prompts"; +import { RunnableSequence, RunnableMap, RunnableLambda } from "@langchain/core/runnables"; +import { StringOutputParser } from "@langchain/core/output_parsers"; +import { Document } from "@langchain/core/documents"; +import { searchSearxng } from "../lib/searxng"; +import type { StreamEvent } from "@langchain/core/tracers/log_stream"; +import type { BaseChatModel } from "@langchain/core/language_models/chat_models"; +import type { Embeddings } from "@langchain/core/embeddings"; +import formatChatHistoryAsString from "../utils/formatHistory"; +import eventEmitter from "node:events"; +import computeSimilarity from "../utils/computeSimilarity"; +import logger from "../utils/logger"; const basicAcademicSearchRetrieverPrompt = ` You will be given a conversation below and a follow up question. You need to rephrase the follow-up question if needed so it is a standalone question that can be used by the LLM to search the web for information. @@ -63,36 +55,18 @@ const basicAcademicSearchResponsePrompt = ` Anything between the \`context\` is retrieved from a search engine and is not a part of the conversation with the user. Today's date is ${new Date().toISOString()} `; -const strParser = new StringOutputParser(); +const stringParser = new StringOutputParser(); -const handleStream = async ( - stream: AsyncGenerator, - emitter: eventEmitter, -) => { +const handleStream = async (stream: AsyncGenerator, emitter: eventEmitter) => { for await (const event of stream) { - if ( - event.event === 'on_chain_end' && - event.name === 'FinalSourceRetriever' - ) { - emitter.emit( - 'data', - JSON.stringify({ type: 'sources', data: event.data.output }), - ); + if (event.event === "on_chain_end" && event.name === "FinalSourceRetriever") { + emitter.emit("data", JSON.stringify({ type: "sources", data: event.data.output })); } - if ( - event.event === 'on_chain_stream' && - event.name === 'FinalResponseGenerator' - ) { - emitter.emit( - 'data', - JSON.stringify({ type: 'response', data: event.data.chunk }), - ); + if (event.event === "on_chain_stream" && event.name === "FinalResponseGenerator") { + emitter.emit("data", JSON.stringify({ type: "response", data: event.data.chunk })); } - if ( - event.event === 'on_chain_end' && - event.name === 'FinalResponseGenerator' - ) { - emitter.emit('end'); + if (event.event === "on_chain_end" && event.name === "FinalResponseGenerator") { + emitter.emit("end"); } } }; @@ -106,24 +80,19 @@ const createBasicAcademicSearchRetrieverChain = (llm: BaseChatModel) => { return RunnableSequence.from([ PromptTemplate.fromTemplate(basicAcademicSearchRetrieverPrompt), llm, - strParser, + stringParser, RunnableLambda.from(async (input: string) => { - if (input === 'not_needed') { - return { query: '', docs: [] }; + if (input === "not_needed") { + return { query: "", docs: [] }; } const res = await searchSearxng(input, { - language: 'en', - engines: [ - 'arxiv', - 'google scholar', - 'internetarchivescholar', - 'pubmed', - ], + language: "en", + engines: ["arxiv", "google scholar", "internetarchivescholar", "pubmed"], }); const documents = res.results.map( - (result) => + result => new Document({ pageContent: result.content, metadata: { @@ -139,44 +108,30 @@ const createBasicAcademicSearchRetrieverChain = (llm: BaseChatModel) => { ]); }; -const createBasicAcademicSearchAnsweringChain = ( - llm: BaseChatModel, - embeddings: Embeddings, -) => { - const basicAcademicSearchRetrieverChain = - createBasicAcademicSearchRetrieverChain(llm); - - const processDocs = async (docs: Document[]) => { - return docs - .map((_, index) => `${index + 1}. ${docs[index].pageContent}`) - .join('\n'); - }; +const processDocs = async (docs: Document[]) => { + return docs.map((_, index) => `${index + 1}. ${docs[index].pageContent}`).join("\n"); +}; - const rerankDocs = async ({ - query, - docs, - }: { - query: string; - docs: Document[]; - }) => { +const createBasicAcademicSearchAnsweringChain = (llm: BaseChatModel, embeddings: Embeddings) => { + const basicAcademicSearchRetrieverChain = createBasicAcademicSearchRetrieverChain(llm); + + const rerankDocs = async ({ query, docs }: { query: string; docs: Document[] }) => { if (docs.length === 0) { return docs; } - const docsWithContent = docs.filter( - (doc) => doc.pageContent && doc.pageContent.length > 0, - ); + const docsWithContent = docs.filter(document => document.pageContent && document.pageContent.length > 0); - const [docEmbeddings, queryEmbedding] = await Promise.all([ - embeddings.embedDocuments(docsWithContent.map((doc) => doc.pageContent)), + const [documentEmbeddings, queryEmbedding] = await Promise.all([ + embeddings.embedDocuments(docsWithContent.map(document => document.pageContent)), embeddings.embedQuery(query), ]); - const similarity = docEmbeddings.map((docEmbedding, i) => { - const sim = computeSimilarity(queryEmbedding, docEmbedding); + const similarity = documentEmbeddings.map((documentEmbedding, index) => { + const sim = computeSimilarity(queryEmbedding, documentEmbedding); return { - index: i, + index: index, similarity: sim, }; }); @@ -184,7 +139,7 @@ const createBasicAcademicSearchAnsweringChain = ( const sortedDocs = similarity .sort((a, b) => b.similarity - a.similarity) .slice(0, 15) - .map((sim) => docsWithContent[sim.index]); + .map(sim => docsWithContent[sim.index]); return sortedDocs; }; @@ -194,41 +149,35 @@ const createBasicAcademicSearchAnsweringChain = ( query: (input: BasicChainInput) => input.query, chat_history: (input: BasicChainInput) => input.chat_history, context: RunnableSequence.from([ - (input) => ({ + input => ({ query: input.query, chat_history: formatChatHistoryAsString(input.chat_history), }), basicAcademicSearchRetrieverChain .pipe(rerankDocs) .withConfig({ - runName: 'FinalSourceRetriever', + runName: "FinalSourceRetriever", }) .pipe(processDocs), ]), }), ChatPromptTemplate.fromMessages([ - ['system', basicAcademicSearchResponsePrompt], - new MessagesPlaceholder('chat_history'), - ['user', '{query}'], + ["system", basicAcademicSearchResponsePrompt], + new MessagesPlaceholder("chat_history"), + ["user", "{query}"], ]), llm, - strParser, + stringParser, ]).withConfig({ - runName: 'FinalResponseGenerator', + runName: "FinalResponseGenerator", }); }; -const basicAcademicSearch = ( - query: string, - history: BaseMessage[], - llm: BaseChatModel, - embeddings: Embeddings, -) => { +const basicAcademicSearch = (query: string, history: BaseMessage[], llm: BaseChatModel, embeddings: Embeddings) => { const emitter = new eventEmitter(); try { - const basicAcademicSearchAnsweringChain = - createBasicAcademicSearchAnsweringChain(llm, embeddings); + const basicAcademicSearchAnsweringChain = createBasicAcademicSearchAnsweringChain(llm, embeddings); const stream = basicAcademicSearchAnsweringChain.streamEvents( { @@ -236,28 +185,20 @@ const basicAcademicSearch = ( query: query, }, { - version: 'v1', + version: "v1", }, ); handleStream(stream, emitter); - } catch (err) { - emitter.emit( - 'error', - JSON.stringify({ data: 'An error has occurred please try again later' }), - ); - logger.error(`Error in academic search: ${err}`); + } catch (error) { + emitter.emit("error", JSON.stringify({ data: "An error has occurred please try again later" })); + logger.error(`Error in academic search: ${error}`); } return emitter; }; -const handleAcademicSearch = ( - message: string, - history: BaseMessage[], - llm: BaseChatModel, - embeddings: Embeddings, -) => { +const handleAcademicSearch = (message: string, history: BaseMessage[], llm: BaseChatModel, embeddings: Embeddings) => { const emitter = basicAcademicSearch(message, history, llm, embeddings); return emitter; }; diff --git a/src/agents/imageSearchAgent.ts b/src/agents/imageSearchAgent.ts index 167019ff..196f26e5 100644 --- a/src/agents/imageSearchAgent.ts +++ b/src/agents/imageSearchAgent.ts @@ -1,14 +1,10 @@ -import { - RunnableSequence, - RunnableMap, - RunnableLambda, -} from '@langchain/core/runnables'; -import { PromptTemplate } from '@langchain/core/prompts'; -import formatChatHistoryAsString from '../utils/formatHistory'; -import { BaseMessage } from '@langchain/core/messages'; -import { StringOutputParser } from '@langchain/core/output_parsers'; -import { searchSearxng } from '../lib/searxng'; -import type { BaseChatModel } from '@langchain/core/language_models/chat_models'; +import { RunnableSequence, RunnableMap, RunnableLambda } from "@langchain/core/runnables"; +import { PromptTemplate } from "@langchain/core/prompts"; +import formatChatHistoryAsString from "../utils/formatHistory"; +import { BaseMessage } from "@langchain/core/messages"; +import { StringOutputParser } from "@langchain/core/output_parsers"; +import { searchSearxng } from "../lib/searxng"; +import type { BaseChatModel } from "@langchain/core/language_models/chat_models"; const imageSearchChainPrompt = ` You will be given a conversation below and a follow up question. You need to rephrase the follow-up question so it is a standalone question that can be used by the LLM to search the web for images. @@ -36,7 +32,7 @@ type ImageSearchChainInput = { query: string; }; -const strParser = new StringOutputParser(); +const stringParser = new StringOutputParser(); const createImageSearchChain = (llm: BaseChatModel) => { return RunnableSequence.from([ @@ -50,15 +46,15 @@ const createImageSearchChain = (llm: BaseChatModel) => { }), PromptTemplate.fromTemplate(imageSearchChainPrompt), llm, - strParser, + stringParser, RunnableLambda.from(async (input: string) => { const res = await searchSearxng(input, { - engines: ['bing images', 'google images'], + engines: ["bing images", "google images"], }); const images = []; - res.results.forEach((result) => { + for (const result of res.results) { if (result.img_src && result.url && result.title) { images.push({ img_src: result.img_src, @@ -66,17 +62,14 @@ const createImageSearchChain = (llm: BaseChatModel) => { title: result.title, }); } - }); + } return images.slice(0, 10); }), ]); }; -const handleImageSearch = ( - input: ImageSearchChainInput, - llm: BaseChatModel, -) => { +const handleImageSearch = (input: ImageSearchChainInput, llm: BaseChatModel) => { const imageSearchChain = createImageSearchChain(llm); return imageSearchChain.invoke(input); }; diff --git a/src/agents/redditSearchAgent.ts b/src/agents/redditSearchAgent.ts index 34e9ec2b..15c654bc 100644 --- a/src/agents/redditSearchAgent.ts +++ b/src/agents/redditSearchAgent.ts @@ -1,24 +1,16 @@ -import { BaseMessage } from '@langchain/core/messages'; -import { - PromptTemplate, - ChatPromptTemplate, - MessagesPlaceholder, -} from '@langchain/core/prompts'; -import { - RunnableSequence, - RunnableMap, - RunnableLambda, -} from '@langchain/core/runnables'; -import { StringOutputParser } from '@langchain/core/output_parsers'; -import { Document } from '@langchain/core/documents'; -import { searchSearxng } from '../lib/searxng'; -import type { StreamEvent } from '@langchain/core/tracers/log_stream'; -import type { BaseChatModel } from '@langchain/core/language_models/chat_models'; -import type { Embeddings } from '@langchain/core/embeddings'; -import formatChatHistoryAsString from '../utils/formatHistory'; -import eventEmitter from 'events'; -import computeSimilarity from '../utils/computeSimilarity'; -import logger from '../utils/logger'; +import { BaseMessage } from "@langchain/core/messages"; +import { PromptTemplate, ChatPromptTemplate, MessagesPlaceholder } from "@langchain/core/prompts"; +import { RunnableSequence, RunnableMap, RunnableLambda } from "@langchain/core/runnables"; +import { StringOutputParser } from "@langchain/core/output_parsers"; +import { Document } from "@langchain/core/documents"; +import { searchSearxng } from "../lib/searxng"; +import type { StreamEvent } from "@langchain/core/tracers/log_stream"; +import type { BaseChatModel } from "@langchain/core/language_models/chat_models"; +import type { Embeddings } from "@langchain/core/embeddings"; +import formatChatHistoryAsString from "../utils/formatHistory"; +import eventEmitter from "node:events"; +import computeSimilarity from "../utils/computeSimilarity"; +import logger from "../utils/logger"; const basicRedditSearchRetrieverPrompt = ` You will be given a conversation below and a follow up question. You need to rephrase the follow-up question if needed so it is a standalone question that can be used by the LLM to search the web for information. @@ -63,36 +55,18 @@ const basicRedditSearchResponsePrompt = ` Anything between the \`context\` is retrieved from Reddit and is not a part of the conversation with the user. Today's date is ${new Date().toISOString()} `; -const strParser = new StringOutputParser(); +const stringParser = new StringOutputParser(); -const handleStream = async ( - stream: AsyncGenerator, - emitter: eventEmitter, -) => { +const handleStream = async (stream: AsyncGenerator, emitter: eventEmitter) => { for await (const event of stream) { - if ( - event.event === 'on_chain_end' && - event.name === 'FinalSourceRetriever' - ) { - emitter.emit( - 'data', - JSON.stringify({ type: 'sources', data: event.data.output }), - ); + if (event.event === "on_chain_end" && event.name === "FinalSourceRetriever") { + emitter.emit("data", JSON.stringify({ type: "sources", data: event.data.output })); } - if ( - event.event === 'on_chain_stream' && - event.name === 'FinalResponseGenerator' - ) { - emitter.emit( - 'data', - JSON.stringify({ type: 'response', data: event.data.chunk }), - ); + if (event.event === "on_chain_stream" && event.name === "FinalResponseGenerator") { + emitter.emit("data", JSON.stringify({ type: "response", data: event.data.chunk })); } - if ( - event.event === 'on_chain_end' && - event.name === 'FinalResponseGenerator' - ) { - emitter.emit('end'); + if (event.event === "on_chain_end" && event.name === "FinalResponseGenerator") { + emitter.emit("end"); } } }; @@ -106,21 +80,21 @@ const createBasicRedditSearchRetrieverChain = (llm: BaseChatModel) => { return RunnableSequence.from([ PromptTemplate.fromTemplate(basicRedditSearchRetrieverPrompt), llm, - strParser, + stringParser, RunnableLambda.from(async (input: string) => { - if (input === 'not_needed') { - return { query: '', docs: [] }; + if (input === "not_needed") { + return { query: "", docs: [] }; } const res = await searchSearxng(input, { - language: 'en', - engines: ['reddit'], + language: "en", + engines: ["reddit"], }); const documents = res.results.map( - (result) => + result => new Document({ - pageContent: result.content ? result.content : result.title, + pageContent: result.content ?? result.title, metadata: { title: result.title, url: result.url, @@ -134,44 +108,30 @@ const createBasicRedditSearchRetrieverChain = (llm: BaseChatModel) => { ]); }; -const createBasicRedditSearchAnsweringChain = ( - llm: BaseChatModel, - embeddings: Embeddings, -) => { - const basicRedditSearchRetrieverChain = - createBasicRedditSearchRetrieverChain(llm); - - const processDocs = async (docs: Document[]) => { - return docs - .map((_, index) => `${index + 1}. ${docs[index].pageContent}`) - .join('\n'); - }; +const processDocs = async (docs: Document[]) => { + return docs.map((_, index) => `${index + 1}. ${docs[index].pageContent}`).join("\n"); +}; - const rerankDocs = async ({ - query, - docs, - }: { - query: string; - docs: Document[]; - }) => { +const createBasicRedditSearchAnsweringChain = (llm: BaseChatModel, embeddings: Embeddings) => { + const basicRedditSearchRetrieverChain = createBasicRedditSearchRetrieverChain(llm); + + const rerankDocs = async ({ query, docs }: { query: string; docs: Document[] }) => { if (docs.length === 0) { return docs; } - const docsWithContent = docs.filter( - (doc) => doc.pageContent && doc.pageContent.length > 0, - ); + const docsWithContent = docs.filter(document => document.pageContent && document.pageContent.length > 0); - const [docEmbeddings, queryEmbedding] = await Promise.all([ - embeddings.embedDocuments(docsWithContent.map((doc) => doc.pageContent)), + const [documentEmbeddings, queryEmbedding] = await Promise.all([ + embeddings.embedDocuments(docsWithContent.map(document => document.pageContent)), embeddings.embedQuery(query), ]); - const similarity = docEmbeddings.map((docEmbedding, i) => { - const sim = computeSimilarity(queryEmbedding, docEmbedding); + const similarity = documentEmbeddings.map((documentEmbedding, index) => { + const sim = computeSimilarity(queryEmbedding, documentEmbedding); return { - index: i, + index: index, similarity: sim, }; }); @@ -179,8 +139,8 @@ const createBasicRedditSearchAnsweringChain = ( const sortedDocs = similarity .sort((a, b) => b.similarity - a.similarity) .slice(0, 15) - .filter((sim) => sim.similarity > 0.3) - .map((sim) => docsWithContent[sim.index]); + .filter(sim => sim.similarity > 0.3) + .map(sim => docsWithContent[sim.index]); return sortedDocs; }; @@ -190,69 +150,55 @@ const createBasicRedditSearchAnsweringChain = ( query: (input: BasicChainInput) => input.query, chat_history: (input: BasicChainInput) => input.chat_history, context: RunnableSequence.from([ - (input) => ({ + input => ({ query: input.query, chat_history: formatChatHistoryAsString(input.chat_history), }), basicRedditSearchRetrieverChain .pipe(rerankDocs) .withConfig({ - runName: 'FinalSourceRetriever', + runName: "FinalSourceRetriever", }) .pipe(processDocs), ]), }), ChatPromptTemplate.fromMessages([ - ['system', basicRedditSearchResponsePrompt], - new MessagesPlaceholder('chat_history'), - ['user', '{query}'], + ["system", basicRedditSearchResponsePrompt], + new MessagesPlaceholder("chat_history"), + ["user", "{query}"], ]), llm, - strParser, + stringParser, ]).withConfig({ - runName: 'FinalResponseGenerator', + runName: "FinalResponseGenerator", }); }; -const basicRedditSearch = ( - query: string, - history: BaseMessage[], - llm: BaseChatModel, - embeddings: Embeddings, -) => { +const basicRedditSearch = (query: string, history: BaseMessage[], llm: BaseChatModel, embeddings: Embeddings) => { const emitter = new eventEmitter(); try { - const basicRedditSearchAnsweringChain = - createBasicRedditSearchAnsweringChain(llm, embeddings); + const basicRedditSearchAnsweringChain = createBasicRedditSearchAnsweringChain(llm, embeddings); const stream = basicRedditSearchAnsweringChain.streamEvents( { chat_history: history, query: query, }, { - version: 'v1', + version: "v1", }, ); handleStream(stream, emitter); - } catch (err) { - emitter.emit( - 'error', - JSON.stringify({ data: 'An error has occurred please try again later' }), - ); - logger.error(`Error in RedditSearch: ${err}`); + } catch (error) { + emitter.emit("error", JSON.stringify({ data: "An error has occurred please try again later" })); + logger.error(`Error in RedditSearch: ${error}`); } return emitter; }; -const handleRedditSearch = ( - message: string, - history: BaseMessage[], - llm: BaseChatModel, - embeddings: Embeddings, -) => { +const handleRedditSearch = (message: string, history: BaseMessage[], llm: BaseChatModel, embeddings: Embeddings) => { const emitter = basicRedditSearch(message, history, llm, embeddings); return emitter; }; diff --git a/src/agents/suggestionGeneratorAgent.ts b/src/agents/suggestionGeneratorAgent.ts index 0efdfa9b..7e29f111 100644 --- a/src/agents/suggestionGeneratorAgent.ts +++ b/src/agents/suggestionGeneratorAgent.ts @@ -1,10 +1,10 @@ -import { RunnableSequence, RunnableMap } from '@langchain/core/runnables'; -import ListLineOutputParser from '../lib/outputParsers/listLineOutputParser'; -import { PromptTemplate } from '@langchain/core/prompts'; -import formatChatHistoryAsString from '../utils/formatHistory'; -import { BaseMessage } from '@langchain/core/messages'; -import { BaseChatModel } from '@langchain/core/language_models/chat_models'; -import { ChatOpenAI } from '@langchain/openai'; +import { RunnableSequence, RunnableMap } from "@langchain/core/runnables"; +import ListLineOutputParser from "../lib/outputParsers/listLineOutputParser"; +import { PromptTemplate } from "@langchain/core/prompts"; +import formatChatHistoryAsString from "../utils/formatHistory"; +import { BaseMessage } from "@langchain/core/messages"; +import { BaseChatModel } from "@langchain/core/language_models/chat_models"; +import { ChatOpenAI } from "@langchain/openai"; const suggestionGeneratorPrompt = ` You are an AI suggestion generator for an AI powered search engine. You will be given a conversation below. You need to generate 4-5 suggestions based on the conversation. The suggestion should be relevant to the conversation that can be used by the user to ask the chat model for more information. @@ -28,14 +28,13 @@ type SuggestionGeneratorInput = { }; const outputParser = new ListLineOutputParser({ - key: 'suggestions', + key: "suggestions", }); const createSuggestionGeneratorChain = (llm: BaseChatModel) => { return RunnableSequence.from([ RunnableMap.from({ - chat_history: (input: SuggestionGeneratorInput) => - formatChatHistoryAsString(input.chat_history), + chat_history: (input: SuggestionGeneratorInput) => formatChatHistoryAsString(input.chat_history), }), PromptTemplate.fromTemplate(suggestionGeneratorPrompt), llm, @@ -43,10 +42,7 @@ const createSuggestionGeneratorChain = (llm: BaseChatModel) => { ]); }; -const generateSuggestions = ( - input: SuggestionGeneratorInput, - llm: BaseChatModel, -) => { +const generateSuggestions = (input: SuggestionGeneratorInput, llm: BaseChatModel) => { (llm as ChatOpenAI).temperature = 0; const suggestionGeneratorChain = createSuggestionGeneratorChain(llm); return suggestionGeneratorChain.invoke(input); diff --git a/src/agents/videoSearchAgent.ts b/src/agents/videoSearchAgent.ts index cdd1ac06..ced2a807 100644 --- a/src/agents/videoSearchAgent.ts +++ b/src/agents/videoSearchAgent.ts @@ -1,14 +1,10 @@ -import { - RunnableSequence, - RunnableMap, - RunnableLambda, -} from '@langchain/core/runnables'; -import { PromptTemplate } from '@langchain/core/prompts'; -import formatChatHistoryAsString from '../utils/formatHistory'; -import { BaseMessage } from '@langchain/core/messages'; -import { StringOutputParser } from '@langchain/core/output_parsers'; -import { searchSearxng } from '../lib/searxng'; -import type { BaseChatModel } from '@langchain/core/language_models/chat_models'; +import { RunnableSequence, RunnableMap, RunnableLambda } from "@langchain/core/runnables"; +import { PromptTemplate } from "@langchain/core/prompts"; +import formatChatHistoryAsString from "../utils/formatHistory"; +import { BaseMessage } from "@langchain/core/messages"; +import { StringOutputParser } from "@langchain/core/output_parsers"; +import { searchSearxng } from "../lib/searxng"; +import type { BaseChatModel } from "@langchain/core/language_models/chat_models"; const VideoSearchChainPrompt = ` You will be given a conversation below and a follow up question. You need to rephrase the follow-up question so it is a standalone question that can be used by the LLM to search Youtube for videos. @@ -36,7 +32,7 @@ type VideoSearchChainInput = { query: string; }; -const strParser = new StringOutputParser(); +const stringParser = new StringOutputParser(); const createVideoSearchChain = (llm: BaseChatModel) => { return RunnableSequence.from([ @@ -50,21 +46,16 @@ const createVideoSearchChain = (llm: BaseChatModel) => { }), PromptTemplate.fromTemplate(VideoSearchChainPrompt), llm, - strParser, + stringParser, RunnableLambda.from(async (input: string) => { const res = await searchSearxng(input, { - engines: ['youtube'], + engines: ["youtube"], }); const videos = []; - res.results.forEach((result) => { - if ( - result.thumbnail && - result.url && - result.title && - result.iframe_src - ) { + for (const result of res.results) { + if (result.thumbnail && result.url && result.title && result.iframe_src) { videos.push({ img_src: result.thumbnail, url: result.url, @@ -72,17 +63,14 @@ const createVideoSearchChain = (llm: BaseChatModel) => { iframe_src: result.iframe_src, }); } - }); + } return videos.slice(0, 10); }), ]); }; -const handleVideoSearch = ( - input: VideoSearchChainInput, - llm: BaseChatModel, -) => { +const handleVideoSearch = (input: VideoSearchChainInput, llm: BaseChatModel) => { const VideoSearchChain = createVideoSearchChain(llm); return VideoSearchChain.invoke(input); }; diff --git a/src/agents/webSearchAgent.ts b/src/agents/webSearchAgent.ts index 1364742b..3e3eb9c5 100644 --- a/src/agents/webSearchAgent.ts +++ b/src/agents/webSearchAgent.ts @@ -1,24 +1,16 @@ -import { BaseMessage } from '@langchain/core/messages'; -import { - PromptTemplate, - ChatPromptTemplate, - MessagesPlaceholder, -} from '@langchain/core/prompts'; -import { - RunnableSequence, - RunnableMap, - RunnableLambda, -} from '@langchain/core/runnables'; -import { StringOutputParser } from '@langchain/core/output_parsers'; -import { Document } from '@langchain/core/documents'; -import { searchSearxng } from '../lib/searxng'; -import type { StreamEvent } from '@langchain/core/tracers/log_stream'; -import type { BaseChatModel } from '@langchain/core/language_models/chat_models'; -import type { Embeddings } from '@langchain/core/embeddings'; -import formatChatHistoryAsString from '../utils/formatHistory'; -import eventEmitter from 'events'; -import computeSimilarity from '../utils/computeSimilarity'; -import logger from '../utils/logger'; +import { BaseMessage } from "@langchain/core/messages"; +import { PromptTemplate, ChatPromptTemplate, MessagesPlaceholder } from "@langchain/core/prompts"; +import { RunnableSequence, RunnableMap, RunnableLambda } from "@langchain/core/runnables"; +import { StringOutputParser } from "@langchain/core/output_parsers"; +import { Document } from "@langchain/core/documents"; +import { searchSearxng } from "../lib/searxng"; +import type { StreamEvent } from "@langchain/core/tracers/log_stream"; +import type { BaseChatModel } from "@langchain/core/language_models/chat_models"; +import type { Embeddings } from "@langchain/core/embeddings"; +import formatChatHistoryAsString from "../utils/formatHistory"; +import eventEmitter from "node:events"; +import computeSimilarity from "../utils/computeSimilarity"; +import logger from "../utils/logger"; const basicSearchRetrieverPrompt = ` You will be given a conversation below and a follow up question. You need to rephrase the follow-up question if needed so it is a standalone question that can be used by the LLM to search the web for information. @@ -63,36 +55,18 @@ const basicWebSearchResponsePrompt = ` Anything between the \`context\` is retrieved from a search engine and is not a part of the conversation with the user. Today's date is ${new Date().toISOString()} `; -const strParser = new StringOutputParser(); +const stringParser = new StringOutputParser(); -const handleStream = async ( - stream: AsyncGenerator, - emitter: eventEmitter, -) => { +const handleStream = async (stream: AsyncGenerator, emitter: eventEmitter) => { for await (const event of stream) { - if ( - event.event === 'on_chain_end' && - event.name === 'FinalSourceRetriever' - ) { - emitter.emit( - 'data', - JSON.stringify({ type: 'sources', data: event.data.output }), - ); + if (event.event === "on_chain_end" && event.name === "FinalSourceRetriever") { + emitter.emit("data", JSON.stringify({ type: "sources", data: event.data.output })); } - if ( - event.event === 'on_chain_stream' && - event.name === 'FinalResponseGenerator' - ) { - emitter.emit( - 'data', - JSON.stringify({ type: 'response', data: event.data.chunk }), - ); + if (event.event === "on_chain_stream" && event.name === "FinalResponseGenerator") { + emitter.emit("data", JSON.stringify({ type: "response", data: event.data.chunk })); } - if ( - event.event === 'on_chain_end' && - event.name === 'FinalResponseGenerator' - ) { - emitter.emit('end'); + if (event.event === "on_chain_end" && event.name === "FinalResponseGenerator") { + emitter.emit("end"); } } }; @@ -106,18 +80,18 @@ const createBasicWebSearchRetrieverChain = (llm: BaseChatModel) => { return RunnableSequence.from([ PromptTemplate.fromTemplate(basicSearchRetrieverPrompt), llm, - strParser, + stringParser, RunnableLambda.from(async (input: string) => { - if (input === 'not_needed') { - return { query: '', docs: [] }; + if (input === "not_needed") { + return { query: "", docs: [] }; } const res = await searchSearxng(input, { - language: 'en', + language: "en", }); const documents = res.results.map( - (result) => + result => new Document({ pageContent: result.content, metadata: { @@ -133,52 +107,39 @@ const createBasicWebSearchRetrieverChain = (llm: BaseChatModel) => { ]); }; -const createBasicWebSearchAnsweringChain = ( - llm: BaseChatModel, - embeddings: Embeddings, -) => { - const basicWebSearchRetrieverChain = createBasicWebSearchRetrieverChain(llm); +const processDocs = async (docs: Document[]) => { + return docs.map((_, index) => `${index + 1}. ${docs[index].pageContent}`).join("\n"); +}; - const processDocs = async (docs: Document[]) => { - return docs - .map((_, index) => `${index + 1}. ${docs[index].pageContent}`) - .join('\n'); - }; +const createBasicWebSearchAnsweringChain = (llm: BaseChatModel, embeddings: Embeddings) => { + const basicWebSearchRetrieverChain = createBasicWebSearchRetrieverChain(llm); - const rerankDocs = async ({ - query, - docs, - }: { - query: string; - docs: Document[]; - }) => { + const rerankDocs = async ({ query, docs }: { query: string; docs: Document[] }) => { if (docs.length === 0) { return docs; } - const docsWithContent = docs.filter( - (doc) => doc.pageContent && doc.pageContent.length > 0, - ); + const docsWithContent = docs.filter(document => document.pageContent && document.pageContent.length > 0); - const [docEmbeddings, queryEmbedding] = await Promise.all([ - embeddings.embedDocuments(docsWithContent.map((doc) => doc.pageContent)), + const [documentEmbeddings, queryEmbedding] = await Promise.all([ + embeddings.embedDocuments(docsWithContent.map(document => document.pageContent)), embeddings.embedQuery(query), ]); - const similarity = docEmbeddings.map((docEmbedding, i) => { - const sim = computeSimilarity(queryEmbedding, docEmbedding); + const similarity = documentEmbeddings.map((documentEmbedding, index) => { + const sim = computeSimilarity(queryEmbedding, documentEmbedding); return { - index: i, + index: index, similarity: sim, }; }); const sortedDocs = similarity .sort((a, b) => b.similarity - a.similarity) - .filter((sim) => sim.similarity > 0.5) + .filter(sim => sim.similarity > 0.5) .slice(0, 15) - .map((sim) => docsWithContent[sim.index]); + .map(sim => docsWithContent[sim.index]); return sortedDocs; }; @@ -188,43 +149,35 @@ const createBasicWebSearchAnsweringChain = ( query: (input: BasicChainInput) => input.query, chat_history: (input: BasicChainInput) => input.chat_history, context: RunnableSequence.from([ - (input) => ({ + input => ({ query: input.query, chat_history: formatChatHistoryAsString(input.chat_history), }), basicWebSearchRetrieverChain .pipe(rerankDocs) .withConfig({ - runName: 'FinalSourceRetriever', + runName: "FinalSourceRetriever", }) .pipe(processDocs), ]), }), ChatPromptTemplate.fromMessages([ - ['system', basicWebSearchResponsePrompt], - new MessagesPlaceholder('chat_history'), - ['user', '{query}'], + ["system", basicWebSearchResponsePrompt], + new MessagesPlaceholder("chat_history"), + ["user", "{query}"], ]), llm, - strParser, + stringParser, ]).withConfig({ - runName: 'FinalResponseGenerator', + runName: "FinalResponseGenerator", }); }; -const basicWebSearch = ( - query: string, - history: BaseMessage[], - llm: BaseChatModel, - embeddings: Embeddings, -) => { +const basicWebSearch = (query: string, history: BaseMessage[], llm: BaseChatModel, embeddings: Embeddings) => { const emitter = new eventEmitter(); try { - const basicWebSearchAnsweringChain = createBasicWebSearchAnsweringChain( - llm, - embeddings, - ); + const basicWebSearchAnsweringChain = createBasicWebSearchAnsweringChain(llm, embeddings); const stream = basicWebSearchAnsweringChain.streamEvents( { @@ -232,28 +185,20 @@ const basicWebSearch = ( query: query, }, { - version: 'v1', + version: "v1", }, ); handleStream(stream, emitter); - } catch (err) { - emitter.emit( - 'error', - JSON.stringify({ data: 'An error has occurred please try again later' }), - ); - logger.error(`Error in websearch: ${err}`); + } catch (error) { + emitter.emit("error", JSON.stringify({ data: "An error has occurred please try again later" })); + logger.error(`Error in websearch: ${error}`); } return emitter; }; -const handleWebSearch = ( - message: string, - history: BaseMessage[], - llm: BaseChatModel, - embeddings: Embeddings, -) => { +const handleWebSearch = (message: string, history: BaseMessage[], llm: BaseChatModel, embeddings: Embeddings) => { const emitter = basicWebSearch(message, history, llm, embeddings); return emitter; }; diff --git a/src/agents/wolframAlphaSearchAgent.ts b/src/agents/wolframAlphaSearchAgent.ts index f810a1e0..a0330840 100644 --- a/src/agents/wolframAlphaSearchAgent.ts +++ b/src/agents/wolframAlphaSearchAgent.ts @@ -1,23 +1,15 @@ -import { BaseMessage } from '@langchain/core/messages'; -import { - PromptTemplate, - ChatPromptTemplate, - MessagesPlaceholder, -} from '@langchain/core/prompts'; -import { - RunnableSequence, - RunnableMap, - RunnableLambda, -} from '@langchain/core/runnables'; -import { StringOutputParser } from '@langchain/core/output_parsers'; -import { Document } from '@langchain/core/documents'; -import { searchSearxng } from '../lib/searxng'; -import type { StreamEvent } from '@langchain/core/tracers/log_stream'; -import type { BaseChatModel } from '@langchain/core/language_models/chat_models'; -import type { Embeddings } from '@langchain/core/embeddings'; -import formatChatHistoryAsString from '../utils/formatHistory'; -import eventEmitter from 'events'; -import logger from '../utils/logger'; +import { BaseMessage } from "@langchain/core/messages"; +import { PromptTemplate, ChatPromptTemplate, MessagesPlaceholder } from "@langchain/core/prompts"; +import { RunnableSequence, RunnableMap, RunnableLambda } from "@langchain/core/runnables"; +import { StringOutputParser } from "@langchain/core/output_parsers"; +import { Document } from "@langchain/core/documents"; +import { searchSearxng } from "../lib/searxng"; +import type { StreamEvent } from "@langchain/core/tracers/log_stream"; +import type { BaseChatModel } from "@langchain/core/language_models/chat_models"; +import type { Embeddings } from "@langchain/core/embeddings"; +import formatChatHistoryAsString from "../utils/formatHistory"; +import eventEmitter from "node:events"; +import logger from "../utils/logger"; const basicWolframAlphaSearchRetrieverPrompt = ` You will be given a conversation below and a follow up question. You need to rephrase the follow-up question if needed so it is a standalone question that can be used by the LLM to search the web for information. @@ -62,36 +54,18 @@ const basicWolframAlphaSearchResponsePrompt = ` Anything between the \`context\` is retrieved from Wolfram Alpha and is not a part of the conversation with the user. Today's date is ${new Date().toISOString()} `; -const strParser = new StringOutputParser(); +const stringParser = new StringOutputParser(); -const handleStream = async ( - stream: AsyncGenerator, - emitter: eventEmitter, -) => { +const handleStream = async (stream: AsyncGenerator, emitter: eventEmitter) => { for await (const event of stream) { - if ( - event.event === 'on_chain_end' && - event.name === 'FinalSourceRetriever' - ) { - emitter.emit( - 'data', - JSON.stringify({ type: 'sources', data: event.data.output }), - ); + if (event.event === "on_chain_end" && event.name === "FinalSourceRetriever") { + emitter.emit("data", JSON.stringify({ type: "sources", data: event.data.output })); } - if ( - event.event === 'on_chain_stream' && - event.name === 'FinalResponseGenerator' - ) { - emitter.emit( - 'data', - JSON.stringify({ type: 'response', data: event.data.chunk }), - ); + if (event.event === "on_chain_stream" && event.name === "FinalResponseGenerator") { + emitter.emit("data", JSON.stringify({ type: "response", data: event.data.chunk })); } - if ( - event.event === 'on_chain_end' && - event.name === 'FinalResponseGenerator' - ) { - emitter.emit('end'); + if (event.event === "on_chain_end" && event.name === "FinalResponseGenerator") { + emitter.emit("end"); } } }; @@ -105,19 +79,19 @@ const createBasicWolframAlphaSearchRetrieverChain = (llm: BaseChatModel) => { return RunnableSequence.from([ PromptTemplate.fromTemplate(basicWolframAlphaSearchRetrieverPrompt), llm, - strParser, + stringParser, RunnableLambda.from(async (input: string) => { - if (input === 'not_needed') { - return { query: '', docs: [] }; + if (input === "not_needed") { + return { query: "", docs: [] }; } const res = await searchSearxng(input, { - language: 'en', - engines: ['wolframalpha'], + language: "en", + engines: ["wolframalpha"], }); const documents = res.results.map( - (result) => + result => new Document({ pageContent: result.content, metadata: { @@ -133,74 +107,63 @@ const createBasicWolframAlphaSearchRetrieverChain = (llm: BaseChatModel) => { ]); }; -const createBasicWolframAlphaSearchAnsweringChain = (llm: BaseChatModel) => { - const basicWolframAlphaSearchRetrieverChain = - createBasicWolframAlphaSearchRetrieverChain(llm); +const processDocs = (docs: Document[]) => { + return docs.map((_, index) => `${index + 1}. ${docs[index].pageContent}`).join("\n"); +}; - const processDocs = (docs: Document[]) => { - return docs - .map((_, index) => `${index + 1}. ${docs[index].pageContent}`) - .join('\n'); - }; +const createBasicWolframAlphaSearchAnsweringChain = (llm: BaseChatModel) => { + const basicWolframAlphaSearchRetrieverChain = createBasicWolframAlphaSearchRetrieverChain(llm); return RunnableSequence.from([ RunnableMap.from({ query: (input: BasicChainInput) => input.query, chat_history: (input: BasicChainInput) => input.chat_history, context: RunnableSequence.from([ - (input) => ({ + input => ({ query: input.query, chat_history: formatChatHistoryAsString(input.chat_history), }), basicWolframAlphaSearchRetrieverChain - .pipe(({ query, docs }) => { + .pipe(({ docs }) => { return docs; }) .withConfig({ - runName: 'FinalSourceRetriever', + runName: "FinalSourceRetriever", }) .pipe(processDocs), ]), }), ChatPromptTemplate.fromMessages([ - ['system', basicWolframAlphaSearchResponsePrompt], - new MessagesPlaceholder('chat_history'), - ['user', '{query}'], + ["system", basicWolframAlphaSearchResponsePrompt], + new MessagesPlaceholder("chat_history"), + ["user", "{query}"], ]), llm, - strParser, + stringParser, ]).withConfig({ - runName: 'FinalResponseGenerator', + runName: "FinalResponseGenerator", }); }; -const basicWolframAlphaSearch = ( - query: string, - history: BaseMessage[], - llm: BaseChatModel, -) => { +const basicWolframAlphaSearch = (query: string, history: BaseMessage[], llm: BaseChatModel) => { const emitter = new eventEmitter(); try { - const basicWolframAlphaSearchAnsweringChain = - createBasicWolframAlphaSearchAnsweringChain(llm); + const basicWolframAlphaSearchAnsweringChain = createBasicWolframAlphaSearchAnsweringChain(llm); const stream = basicWolframAlphaSearchAnsweringChain.streamEvents( { chat_history: history, query: query, }, { - version: 'v1', + version: "v1", }, ); handleStream(stream, emitter); - } catch (err) { - emitter.emit( - 'error', - JSON.stringify({ data: 'An error has occurred please try again later' }), - ); - logger.error(`Error in WolframAlphaSearch: ${err}`); + } catch (error) { + emitter.emit("error", JSON.stringify({ data: "An error has occurred please try again later" })); + logger.error(`Error in WolframAlphaSearch: ${error}`); } return emitter; @@ -210,7 +173,8 @@ const handleWolframAlphaSearch = ( message: string, history: BaseMessage[], llm: BaseChatModel, - embeddings: Embeddings, + // eslint-disable-next-line @typescript-eslint/no-unused-vars + _embeddings: Embeddings, ) => { const emitter = basicWolframAlphaSearch(message, history, llm); return emitter; diff --git a/src/agents/writingAssistant.ts b/src/agents/writingAssistant.ts index 7c2cb498..7493abe2 100644 --- a/src/agents/writingAssistant.ts +++ b/src/agents/writingAssistant.ts @@ -1,42 +1,27 @@ -import { BaseMessage } from '@langchain/core/messages'; -import { - ChatPromptTemplate, - MessagesPlaceholder, -} from '@langchain/core/prompts'; -import { RunnableSequence } from '@langchain/core/runnables'; -import { StringOutputParser } from '@langchain/core/output_parsers'; -import type { StreamEvent } from '@langchain/core/tracers/log_stream'; -import eventEmitter from 'events'; -import type { BaseChatModel } from '@langchain/core/language_models/chat_models'; -import type { Embeddings } from '@langchain/core/embeddings'; -import logger from '../utils/logger'; +import { BaseMessage } from "@langchain/core/messages"; +import { ChatPromptTemplate, MessagesPlaceholder } from "@langchain/core/prompts"; +import { RunnableSequence } from "@langchain/core/runnables"; +import { StringOutputParser } from "@langchain/core/output_parsers"; +import type { StreamEvent } from "@langchain/core/tracers/log_stream"; +import eventEmitter from "node:events"; +import type { BaseChatModel } from "@langchain/core/language_models/chat_models"; +import type { Embeddings } from "@langchain/core/embeddings"; +import logger from "../utils/logger"; const writingAssistantPrompt = ` You are Perplexica, an AI model who is expert at searching the web and answering user's queries. You are currently set on focus mode 'Writing Assistant', this means you will be helping the user write a response to a given query. Since you are a writing assistant, you would not perform web searches. If you think you lack information to answer the query, you can ask the user for more information or suggest them to switch to a different focus mode. `; -const strParser = new StringOutputParser(); +const stringParser = new StringOutputParser(); -const handleStream = async ( - stream: AsyncGenerator, - emitter: eventEmitter, -) => { +const handleStream = async (stream: AsyncGenerator, emitter: eventEmitter) => { for await (const event of stream) { - if ( - event.event === 'on_chain_stream' && - event.name === 'FinalResponseGenerator' - ) { - emitter.emit( - 'data', - JSON.stringify({ type: 'response', data: event.data.chunk }), - ); + if (event.event === "on_chain_stream" && event.name === "FinalResponseGenerator") { + emitter.emit("data", JSON.stringify({ type: "response", data: event.data.chunk })); } - if ( - event.event === 'on_chain_end' && - event.name === 'FinalResponseGenerator' - ) { - emitter.emit('end'); + if (event.event === "on_chain_end" && event.name === "FinalResponseGenerator") { + emitter.emit("end"); } } }; @@ -44,14 +29,14 @@ const handleStream = async ( const createWritingAssistantChain = (llm: BaseChatModel) => { return RunnableSequence.from([ ChatPromptTemplate.fromMessages([ - ['system', writingAssistantPrompt], - new MessagesPlaceholder('chat_history'), - ['user', '{query}'], + ["system", writingAssistantPrompt], + new MessagesPlaceholder("chat_history"), + ["user", "{query}"], ]), llm, - strParser, + stringParser, ]).withConfig({ - runName: 'FinalResponseGenerator', + runName: "FinalResponseGenerator", }); }; @@ -59,7 +44,8 @@ const handleWritingAssistant = ( query: string, history: BaseMessage[], llm: BaseChatModel, - embeddings: Embeddings, + // eslint-disable-next-line @typescript-eslint/no-unused-vars + _embeddings: Embeddings, ) => { const emitter = new eventEmitter(); @@ -71,17 +57,14 @@ const handleWritingAssistant = ( query: query, }, { - version: 'v1', + version: "v1", }, ); handleStream(stream, emitter); - } catch (err) { - emitter.emit( - 'error', - JSON.stringify({ data: 'An error has occurred please try again later' }), - ); - logger.error(`Error in writing assistant: ${err}`); + } catch (error) { + emitter.emit("error", JSON.stringify({ data: "An error has occurred please try again later" })); + logger.error(`Error in writing assistant: ${error}`); } return emitter; diff --git a/src/agents/youtubeSearchAgent.ts b/src/agents/youtubeSearchAgent.ts index 4e82cc78..c235a325 100644 --- a/src/agents/youtubeSearchAgent.ts +++ b/src/agents/youtubeSearchAgent.ts @@ -1,24 +1,16 @@ -import { BaseMessage } from '@langchain/core/messages'; -import { - PromptTemplate, - ChatPromptTemplate, - MessagesPlaceholder, -} from '@langchain/core/prompts'; -import { - RunnableSequence, - RunnableMap, - RunnableLambda, -} from '@langchain/core/runnables'; -import { StringOutputParser } from '@langchain/core/output_parsers'; -import { Document } from '@langchain/core/documents'; -import { searchSearxng } from '../lib/searxng'; -import type { StreamEvent } from '@langchain/core/tracers/log_stream'; -import type { BaseChatModel } from '@langchain/core/language_models/chat_models'; -import type { Embeddings } from '@langchain/core/embeddings'; -import formatChatHistoryAsString from '../utils/formatHistory'; -import eventEmitter from 'events'; -import computeSimilarity from '../utils/computeSimilarity'; -import logger from '../utils/logger'; +import { BaseMessage } from "@langchain/core/messages"; +import { PromptTemplate, ChatPromptTemplate, MessagesPlaceholder } from "@langchain/core/prompts"; +import { RunnableSequence, RunnableMap, RunnableLambda } from "@langchain/core/runnables"; +import { StringOutputParser } from "@langchain/core/output_parsers"; +import { Document } from "@langchain/core/documents"; +import { searchSearxng } from "../lib/searxng"; +import type { StreamEvent } from "@langchain/core/tracers/log_stream"; +import type { BaseChatModel } from "@langchain/core/language_models/chat_models"; +import type { Embeddings } from "@langchain/core/embeddings"; +import formatChatHistoryAsString from "../utils/formatHistory"; +import eventEmitter from "node:events"; +import computeSimilarity from "../utils/computeSimilarity"; +import logger from "../utils/logger"; const basicYoutubeSearchRetrieverPrompt = ` You will be given a conversation below and a follow up question. You need to rephrase the follow-up question if needed so it is a standalone question that can be used by the LLM to search the web for information. @@ -63,36 +55,18 @@ const basicYoutubeSearchResponsePrompt = ` Anything between the \`context\` is retrieved from Youtube and is not a part of the conversation with the user. Today's date is ${new Date().toISOString()} `; -const strParser = new StringOutputParser(); +const stringParser = new StringOutputParser(); -const handleStream = async ( - stream: AsyncGenerator, - emitter: eventEmitter, -) => { +const handleStream = async (stream: AsyncGenerator, emitter: eventEmitter) => { for await (const event of stream) { - if ( - event.event === 'on_chain_end' && - event.name === 'FinalSourceRetriever' - ) { - emitter.emit( - 'data', - JSON.stringify({ type: 'sources', data: event.data.output }), - ); + if (event.event === "on_chain_end" && event.name === "FinalSourceRetriever") { + emitter.emit("data", JSON.stringify({ type: "sources", data: event.data.output })); } - if ( - event.event === 'on_chain_stream' && - event.name === 'FinalResponseGenerator' - ) { - emitter.emit( - 'data', - JSON.stringify({ type: 'response', data: event.data.chunk }), - ); + if (event.event === "on_chain_stream" && event.name === "FinalResponseGenerator") { + emitter.emit("data", JSON.stringify({ type: "response", data: event.data.chunk })); } - if ( - event.event === 'on_chain_end' && - event.name === 'FinalResponseGenerator' - ) { - emitter.emit('end'); + if (event.event === "on_chain_end" && event.name === "FinalResponseGenerator") { + emitter.emit("end"); } } }; @@ -106,21 +80,21 @@ const createBasicYoutubeSearchRetrieverChain = (llm: BaseChatModel) => { return RunnableSequence.from([ PromptTemplate.fromTemplate(basicYoutubeSearchRetrieverPrompt), llm, - strParser, + stringParser, RunnableLambda.from(async (input: string) => { - if (input === 'not_needed') { - return { query: '', docs: [] }; + if (input === "not_needed") { + return { query: "", docs: [] }; } const res = await searchSearxng(input, { - language: 'en', - engines: ['youtube'], + language: "en", + engines: ["youtube"], }); const documents = res.results.map( - (result) => + result => new Document({ - pageContent: result.content ? result.content : result.title, + pageContent: result.content ?? result.title, metadata: { title: result.title, url: result.url, @@ -134,44 +108,30 @@ const createBasicYoutubeSearchRetrieverChain = (llm: BaseChatModel) => { ]); }; -const createBasicYoutubeSearchAnsweringChain = ( - llm: BaseChatModel, - embeddings: Embeddings, -) => { - const basicYoutubeSearchRetrieverChain = - createBasicYoutubeSearchRetrieverChain(llm); - - const processDocs = async (docs: Document[]) => { - return docs - .map((_, index) => `${index + 1}. ${docs[index].pageContent}`) - .join('\n'); - }; +const processDocs = async (docs: Document[]) => { + return docs.map((_, index) => `${index + 1}. ${docs[index].pageContent}`).join("\n"); +}; - const rerankDocs = async ({ - query, - docs, - }: { - query: string; - docs: Document[]; - }) => { +const createBasicYoutubeSearchAnsweringChain = (llm: BaseChatModel, embeddings: Embeddings) => { + const basicYoutubeSearchRetrieverChain = createBasicYoutubeSearchRetrieverChain(llm); + + const rerankDocs = async ({ query, docs }: { query: string; docs: Document[] }) => { if (docs.length === 0) { return docs; } - const docsWithContent = docs.filter( - (doc) => doc.pageContent && doc.pageContent.length > 0, - ); + const docsWithContent = docs.filter(document => document.pageContent && document.pageContent.length > 0); - const [docEmbeddings, queryEmbedding] = await Promise.all([ - embeddings.embedDocuments(docsWithContent.map((doc) => doc.pageContent)), + const [documentEmbeddings, queryEmbedding] = await Promise.all([ + embeddings.embedDocuments(docsWithContent.map(document => document.pageContent)), embeddings.embedQuery(query), ]); - const similarity = docEmbeddings.map((docEmbedding, i) => { - const sim = computeSimilarity(queryEmbedding, docEmbedding); + const similarity = documentEmbeddings.map((documentEmbedding, index) => { + const sim = computeSimilarity(queryEmbedding, documentEmbedding); return { - index: i, + index: index, similarity: sim, }; }); @@ -179,8 +139,8 @@ const createBasicYoutubeSearchAnsweringChain = ( const sortedDocs = similarity .sort((a, b) => b.similarity - a.similarity) .slice(0, 15) - .filter((sim) => sim.similarity > 0.3) - .map((sim) => docsWithContent[sim.index]); + .filter(sim => sim.similarity > 0.3) + .map(sim => docsWithContent[sim.index]); return sortedDocs; }; @@ -190,41 +150,35 @@ const createBasicYoutubeSearchAnsweringChain = ( query: (input: BasicChainInput) => input.query, chat_history: (input: BasicChainInput) => input.chat_history, context: RunnableSequence.from([ - (input) => ({ + input => ({ query: input.query, chat_history: formatChatHistoryAsString(input.chat_history), }), basicYoutubeSearchRetrieverChain .pipe(rerankDocs) .withConfig({ - runName: 'FinalSourceRetriever', + runName: "FinalSourceRetriever", }) .pipe(processDocs), ]), }), ChatPromptTemplate.fromMessages([ - ['system', basicYoutubeSearchResponsePrompt], - new MessagesPlaceholder('chat_history'), - ['user', '{query}'], + ["system", basicYoutubeSearchResponsePrompt], + new MessagesPlaceholder("chat_history"), + ["user", "{query}"], ]), llm, - strParser, + stringParser, ]).withConfig({ - runName: 'FinalResponseGenerator', + runName: "FinalResponseGenerator", }); }; -const basicYoutubeSearch = ( - query: string, - history: BaseMessage[], - llm: BaseChatModel, - embeddings: Embeddings, -) => { +const basicYoutubeSearch = (query: string, history: BaseMessage[], llm: BaseChatModel, embeddings: Embeddings) => { const emitter = new eventEmitter(); try { - const basicYoutubeSearchAnsweringChain = - createBasicYoutubeSearchAnsweringChain(llm, embeddings); + const basicYoutubeSearchAnsweringChain = createBasicYoutubeSearchAnsweringChain(llm, embeddings); const stream = basicYoutubeSearchAnsweringChain.streamEvents( { @@ -232,28 +186,20 @@ const basicYoutubeSearch = ( query: query, }, { - version: 'v1', + version: "v1", }, ); handleStream(stream, emitter); - } catch (err) { - emitter.emit( - 'error', - JSON.stringify({ data: 'An error has occurred please try again later' }), - ); - logger.error(`Error in youtube search: ${err}`); + } catch (error) { + emitter.emit("error", JSON.stringify({ data: "An error has occurred please try again later" })); + logger.error(`Error in youtube search: ${error}`); } return emitter; }; -const handleYoutubeSearch = ( - message: string, - history: BaseMessage[], - llm: BaseChatModel, - embeddings: Embeddings, -) => { +const handleYoutubeSearch = (message: string, history: BaseMessage[], llm: BaseChatModel, embeddings: Embeddings) => { const emitter = basicYoutubeSearch(message, history, llm, embeddings); return emitter; }; diff --git a/src/app.ts b/src/app.ts index b8c23716..7032e9eb 100644 --- a/src/app.ts +++ b/src/app.ts @@ -1,10 +1,10 @@ -import { startWebSocketServer } from './websocket'; -import express from 'express'; -import cors from 'cors'; -import http from 'http'; -import routes from './routes'; -import { getPort } from './config'; -import logger from './utils/logger'; +import { startWebSocketServer } from "./websocket"; +import express from "express"; +import cors from "cors"; +import http from "node:http"; +import routes from "./routes"; +import { getPort } from "./config"; +import logger from "./utils/logger"; const port = getPort(); @@ -12,15 +12,15 @@ const app = express(); const server = http.createServer(app); const corsOptions = { - origin: '*', + origin: "*", }; app.use(cors(corsOptions)); app.use(express.json()); -app.use('/api', routes); -app.get('/api', (_, res) => { - res.status(200).json({ status: 'ok' }); +app.use("/api", routes); +app.get("/api", (_, res) => { + res.status(200).json({ status: "ok" }); }); server.listen(port, () => { diff --git a/src/config.ts b/src/config.ts index 7c0c7f14..50a456e2 100644 --- a/src/config.ts +++ b/src/config.ts @@ -1,8 +1,9 @@ -import fs from 'fs'; -import path from 'path'; -import toml from '@iarna/toml'; +/* eslint-disable unicorn/prefer-module */ +import fs from "node:fs"; +import path from "node:path"; +import toml from "@iarna/toml"; -const configFileName = 'config.toml'; +const configFileName = "config.toml"; interface Config { GENERAL: { @@ -24,14 +25,11 @@ type RecursivePartial = { }; const loadConfig = () => - toml.parse( - fs.readFileSync(path.join(__dirname, `../${configFileName}`), 'utf-8'), - ) as any as Config; + toml.parse(fs.readFileSync(path.join(__dirname, `../${configFileName}`), "utf8")) as unknown as Config; export const getPort = () => loadConfig().GENERAL.PORT; -export const getSimilarityMeasure = () => - loadConfig().GENERAL.SIMILARITY_MEASURE; +export const getSimilarityMeasure = () => loadConfig().GENERAL.SIMILARITY_MEASURE; export const getOpenaiApiKey = () => loadConfig().API_KEYS.OPENAI; @@ -47,23 +45,16 @@ export const updateConfig = (config: RecursivePartial) => { for (const key in currentConfig) { if (!config[key]) config[key] = {}; - if (typeof currentConfig[key] === 'object' && currentConfig[key] !== null) { + if (typeof currentConfig[key] === "object" && currentConfig[key] !== null) { for (const nestedKey in currentConfig[key]) { - if ( - !config[key][nestedKey] && - currentConfig[key][nestedKey] && - config[key][nestedKey] !== '' - ) { + if (!config[key][nestedKey] && currentConfig[key][nestedKey] && config[key][nestedKey] !== "") { config[key][nestedKey] = currentConfig[key][nestedKey]; } } - } else if (currentConfig[key] && config[key] !== '') { + } else if (currentConfig[key] && config[key] !== "") { config[key] = currentConfig[key]; } } - fs.writeFileSync( - path.join(__dirname, `../${configFileName}`), - toml.stringify(config), - ); + fs.writeFileSync(path.join(__dirname, `../${configFileName}`), toml.stringify(config)); }; diff --git a/src/db/index.ts b/src/db/index.ts index b431b47f..75980ed5 100644 --- a/src/db/index.ts +++ b/src/db/index.ts @@ -1,10 +1,10 @@ -import { drizzle } from 'drizzle-orm/better-sqlite3'; -import Database from 'better-sqlite3'; -import * as schema from './schema'; +import { drizzle } from "drizzle-orm/better-sqlite3"; +import Database from "better-sqlite3"; +import * as schema from "./schema"; -const sqlite = new Database('data/db.sqlite'); -const db = drizzle(sqlite, { +const sqlite = new Database("data/db.sqlite"); +const database = drizzle(sqlite, { schema: schema, }); -export default db; +export default database; diff --git a/src/db/schema.ts b/src/db/schema.ts index 9eefa558..fae4f9e4 100644 --- a/src/db/schema.ts +++ b/src/db/schema.ts @@ -1,19 +1,19 @@ -import { text, integer, sqliteTable } from 'drizzle-orm/sqlite-core'; +import { text, integer, sqliteTable } from "drizzle-orm/sqlite-core"; -export const messages = sqliteTable('messages', { - id: integer('id').primaryKey(), - content: text('content').notNull(), - chatId: text('chatId').notNull(), - messageId: text('messageId').notNull(), - role: text('type', { enum: ['assistant', 'user'] }), - metadata: text('metadata', { - mode: 'json', +export const messages = sqliteTable("messages", { + id: integer("id").primaryKey(), + content: text("content").notNull(), + chatId: text("chatId").notNull(), + messageId: text("messageId").notNull(), + role: text("type", { enum: ["assistant", "user"] }), + metadata: text("metadata", { + mode: "json", }), }); -export const chats = sqliteTable('chats', { - id: text('id').primaryKey(), - title: text('title').notNull(), - createdAt: text('createdAt').notNull(), - focusMode: text('focusMode').notNull(), +export const chats = sqliteTable("chats", { + id: text("id").primaryKey(), + title: text("title").notNull(), + createdAt: text("createdAt").notNull(), + focusMode: text("focusMode").notNull(), }); diff --git a/src/lib/huggingfaceTransformer.ts b/src/lib/huggingfaceTransformer.ts index 7a959ca3..3807ac32 100644 --- a/src/lib/huggingfaceTransformer.ts +++ b/src/lib/huggingfaceTransformer.ts @@ -1,8 +1,7 @@ -import { Embeddings, type EmbeddingsParams } from '@langchain/core/embeddings'; -import { chunkArray } from '@langchain/core/utils/chunk_array'; +import { Embeddings, type EmbeddingsParams } from "@langchain/core/embeddings"; +import { chunkArray } from "@langchain/core/utils/chunk_array"; -export interface HuggingFaceTransformersEmbeddingsParams - extends EmbeddingsParams { +export interface HuggingFaceTransformersEmbeddingsParameters extends EmbeddingsParams { modelName: string; model: string; @@ -16,11 +15,11 @@ export interface HuggingFaceTransformersEmbeddingsParams export class HuggingFaceTransformersEmbeddings extends Embeddings - implements HuggingFaceTransformersEmbeddingsParams + implements HuggingFaceTransformersEmbeddingsParameters { - modelName = 'Xenova/all-MiniLM-L6-v2'; + modelName = "Xenova/all-MiniLM-L6-v2"; - model = 'Xenova/all-MiniLM-L6-v2'; + model = "Xenova/all-MiniLM-L6-v2"; batchSize = 512; @@ -28,9 +27,10 @@ export class HuggingFaceTransformersEmbeddings timeout?: number; + // eslint-disable-next-line @typescript-eslint/no-explicit-any private pipelinePromise: Promise; - constructor(fields?: Partial) { + constructor(fields?: Partial) { super(fields ?? {}); this.modelName = fields?.model ?? fields?.modelName ?? this.model; @@ -40,19 +40,15 @@ export class HuggingFaceTransformersEmbeddings } async embedDocuments(texts: string[]): Promise { - const batches = chunkArray( - this.stripNewLines ? texts.map((t) => t.replace(/\n/g, ' ')) : texts, - this.batchSize, - ); + const batches = chunkArray(this.stripNewLines ? texts.map(t => t.replaceAll("\n", " ")) : texts, this.batchSize); - const batchRequests = batches.map((batch) => this.runEmbedding(batch)); + const batchRequests = batches.map(batch => this.runEmbedding(batch)); const batchResponses = await Promise.all(batchRequests); const embeddings: number[][] = []; - for (let i = 0; i < batchResponses.length; i += 1) { - const batchResponse = batchResponses[i]; - for (let j = 0; j < batchResponse.length; j += 1) { - embeddings.push(batchResponse[j]); + for (const batchResponse of batchResponses) { + for (const element of batchResponse) { + embeddings.push(element); } } @@ -60,22 +56,17 @@ export class HuggingFaceTransformersEmbeddings } async embedQuery(text: string): Promise { - const data = await this.runEmbedding([ - this.stripNewLines ? text.replace(/\n/g, ' ') : text, - ]); + const data = await this.runEmbedding([this.stripNewLines ? text.replaceAll("\n", " ") : text]); return data[0]; } private async runEmbedding(texts: string[]) { - const { pipeline } = await import('@xenova/transformers'); + const { pipeline } = await import("@xenova/transformers"); - const pipe = await (this.pipelinePromise ??= pipeline( - 'feature-extraction', - this.model, - )); + const pipe = await (this.pipelinePromise ??= pipeline("feature-extraction", this.model)); return this.caller.call(async () => { - const output = await pipe(texts, { pooling: 'mean', normalize: true }); + const output = await pipe(texts, { pooling: "mean", normalize: true }); return output.tolist(); }); } diff --git a/src/lib/outputParsers/listLineOutputParser.ts b/src/lib/outputParsers/listLineOutputParser.ts index 57a9bbc8..966ebfa9 100644 --- a/src/lib/outputParsers/listLineOutputParser.ts +++ b/src/lib/outputParsers/listLineOutputParser.ts @@ -1,42 +1,41 @@ -import { BaseOutputParser } from '@langchain/core/output_parsers'; +import { BaseOutputParser } from "@langchain/core/output_parsers"; -interface LineListOutputParserArgs { +interface LineListOutputParserArguments { key?: string; } class LineListOutputParser extends BaseOutputParser { - private key = 'questions'; + private key = "questions"; - constructor(args?: LineListOutputParserArgs) { + constructor(arguments_?: LineListOutputParserArguments) { super(); - this.key = args.key ?? this.key; + this.key = arguments_.key ?? this.key; } static lc_name() { - return 'LineListOutputParser'; + return "LineListOutputParser"; } - lc_namespace = ['langchain', 'output_parsers', 'line_list_output_parser']; + lc_namespace = ["langchain", "output_parsers", "line_list_output_parser"]; async parse(text: string): Promise { const regex = /^(\s*(-|\*|\d+\.\s|\d+\)\s|\u2022)\s*)+/; const startKeyIndex = text.indexOf(`<${this.key}>`); const endKeyIndex = text.indexOf(``); - const questionsStartIndex = - startKeyIndex === -1 ? 0 : startKeyIndex + `<${this.key}>`.length; + const questionsStartIndex = startKeyIndex === -1 ? 0 : startKeyIndex + `<${this.key}>`.length; const questionsEndIndex = endKeyIndex === -1 ? text.length : endKeyIndex; const lines = text .slice(questionsStartIndex, questionsEndIndex) .trim() - .split('\n') - .filter((line) => line.trim() !== '') - .map((line) => line.replace(regex, '')); + .split("\n") + .filter(line => line.trim() !== "") + .map(line => line.replace(regex, "")); return lines; } getFormatInstructions(): string { - throw new Error('Not implemented.'); + throw new Error("Not implemented."); } } diff --git a/src/lib/providers.ts b/src/lib/providers.ts index 32231936..7a7c5063 100644 --- a/src/lib/providers.ts +++ b/src/lib/providers.ts @@ -1,13 +1,9 @@ -import { ChatOpenAI, OpenAIEmbeddings } from '@langchain/openai'; -import { ChatOllama } from '@langchain/community/chat_models/ollama'; -import { OllamaEmbeddings } from '@langchain/community/embeddings/ollama'; -import { HuggingFaceTransformersEmbeddings } from './huggingfaceTransformer'; -import { - getGroqApiKey, - getOllamaApiEndpoint, - getOpenaiApiKey, -} from '../config'; -import logger from '../utils/logger'; +import { ChatOpenAI, OpenAIEmbeddings } from "@langchain/openai"; +import { ChatOllama } from "@langchain/community/chat_models/ollama"; +import { OllamaEmbeddings } from "@langchain/community/embeddings/ollama"; +import { HuggingFaceTransformersEmbeddings } from "./huggingfaceTransformer"; +import { getGroqApiKey, getOllamaApiEndpoint, getOpenaiApiKey } from "../config"; +import logger from "../utils/logger"; export const getAvailableChatModelProviders = async () => { const openAIApiKey = getOpenaiApiKey(); @@ -18,79 +14,79 @@ export const getAvailableChatModelProviders = async () => { if (openAIApiKey) { try { - models['openai'] = { - 'GPT-3.5 turbo': new ChatOpenAI({ + models["openai"] = { + "GPT-3.5 turbo": new ChatOpenAI({ openAIApiKey, - modelName: 'gpt-3.5-turbo', + modelName: "gpt-3.5-turbo", temperature: 0.7, }), - 'GPT-4': new ChatOpenAI({ + "GPT-4": new ChatOpenAI({ openAIApiKey, - modelName: 'gpt-4', + modelName: "gpt-4", temperature: 0.7, }), - 'GPT-4 turbo': new ChatOpenAI({ + "GPT-4 turbo": new ChatOpenAI({ openAIApiKey, - modelName: 'gpt-4-turbo', + modelName: "gpt-4-turbo", temperature: 0.7, }), - 'GPT-4 omni': new ChatOpenAI({ + "GPT-4 omni": new ChatOpenAI({ openAIApiKey, - modelName: 'gpt-4o', + modelName: "gpt-4o", temperature: 0.7, }), }; - } catch (err) { - logger.error(`Error loading OpenAI models: ${err}`); + } catch (error) { + logger.error(`Error loading OpenAI models: ${error}`); } } if (groqApiKey) { try { - models['groq'] = { - 'LLaMA3 8b': new ChatOpenAI( + models["groq"] = { + "LLaMA3 8b": new ChatOpenAI( { openAIApiKey: groqApiKey, - modelName: 'llama3-8b-8192', + modelName: "llama3-8b-8192", temperature: 0.7, }, { - baseURL: 'https://api.groq.com/openai/v1', + baseURL: "https://api.groq.com/openai/v1", }, ), - 'LLaMA3 70b': new ChatOpenAI( + "LLaMA3 70b": new ChatOpenAI( { openAIApiKey: groqApiKey, - modelName: 'llama3-70b-8192', + modelName: "llama3-70b-8192", temperature: 0.7, }, { - baseURL: 'https://api.groq.com/openai/v1', + baseURL: "https://api.groq.com/openai/v1", }, ), - 'Mixtral 8x7b': new ChatOpenAI( + "Mixtral 8x7b": new ChatOpenAI( { openAIApiKey: groqApiKey, - modelName: 'mixtral-8x7b-32768', + modelName: "mixtral-8x7b-32768", temperature: 0.7, }, { - baseURL: 'https://api.groq.com/openai/v1', + baseURL: "https://api.groq.com/openai/v1", }, ), - 'Gemma 7b': new ChatOpenAI( + "Gemma 7b": new ChatOpenAI( { openAIApiKey: groqApiKey, - modelName: 'gemma-7b-it', + modelName: "gemma-7b-it", temperature: 0.7, }, { - baseURL: 'https://api.groq.com/openai/v1', + baseURL: "https://api.groq.com/openai/v1", }, ), }; - } catch (err) { - logger.error(`Error loading Groq models: ${err}`); + } catch (error) { + logger.error(`Error loading Groq models: ${error}`); } } @@ -98,26 +94,28 @@ export const getAvailableChatModelProviders = async () => { try { const response = await fetch(`${ollamaEndpoint}/api/tags`, { headers: { - 'Content-Type': 'application/json', + "Content-Type": "application/json", }, }); + // eslint-disable-next-line @typescript-eslint/no-explicit-any const { models: ollamaModels } = (await response.json()) as any; - models['ollama'] = ollamaModels.reduce((acc, model) => { - acc[model.model] = new ChatOllama({ + // eslint-disable-next-line unicorn/no-array-reduce + models["ollama"] = ollamaModels.reduce((accumulator, model) => { + accumulator[model.model] = new ChatOllama({ baseUrl: ollamaEndpoint, model: model.model, temperature: 0.7, }); - return acc; + return accumulator; }, {}); - } catch (err) { - logger.error(`Error loading Ollama models: ${err}`); + } catch (error) { + logger.error(`Error loading Ollama models: ${error}`); } } - models['custom_openai'] = {}; + models["custom_openai"] = {}; return models; }; @@ -130,18 +128,18 @@ export const getAvailableEmbeddingModelProviders = async () => { if (openAIApiKey) { try { - models['openai'] = { - 'Text embedding 3 small': new OpenAIEmbeddings({ + models["openai"] = { + "Text embedding 3 small": new OpenAIEmbeddings({ openAIApiKey, - modelName: 'text-embedding-3-small', + modelName: "text-embedding-3-small", }), - 'Text embedding 3 large': new OpenAIEmbeddings({ + "Text embedding 3 large": new OpenAIEmbeddings({ openAIApiKey, - modelName: 'text-embedding-3-large', + modelName: "text-embedding-3-large", }), }; - } catch (err) { - logger.error(`Error loading OpenAI embeddings: ${err}`); + } catch (error) { + logger.error(`Error loading OpenAI embeddings: ${error}`); } } @@ -149,38 +147,40 @@ export const getAvailableEmbeddingModelProviders = async () => { try { const response = await fetch(`${ollamaEndpoint}/api/tags`, { headers: { - 'Content-Type': 'application/json', + "Content-Type": "application/json", }, }); + // eslint-disable-next-line @typescript-eslint/no-explicit-any const { models: ollamaModels } = (await response.json()) as any; - models['ollama'] = ollamaModels.reduce((acc, model) => { - acc[model.model] = new OllamaEmbeddings({ + // eslint-disable-next-line unicorn/no-array-reduce + models["ollama"] = ollamaModels.reduce((accumulator, model) => { + accumulator[model.model] = new OllamaEmbeddings({ baseUrl: ollamaEndpoint, model: model.model, }); - return acc; + return accumulator; }, {}); - } catch (err) { - logger.error(`Error loading Ollama embeddings: ${err}`); + } catch (error) { + logger.error(`Error loading Ollama embeddings: ${error}`); } } try { - models['local'] = { - 'BGE Small': new HuggingFaceTransformersEmbeddings({ - modelName: 'Xenova/bge-small-en-v1.5', + models["local"] = { + "BGE Small": new HuggingFaceTransformersEmbeddings({ + modelName: "Xenova/bge-small-en-v1.5", }), - 'GTE Small': new HuggingFaceTransformersEmbeddings({ - modelName: 'Xenova/gte-small', + "GTE Small": new HuggingFaceTransformersEmbeddings({ + modelName: "Xenova/gte-small", }), - 'Bert Multilingual': new HuggingFaceTransformersEmbeddings({ - modelName: 'Xenova/bert-base-multilingual-uncased', + "Bert Multilingual": new HuggingFaceTransformersEmbeddings({ + modelName: "Xenova/bert-base-multilingual-uncased", }), }; - } catch (err) { - logger.error(`Error loading local embeddings: ${err}`); + } catch (error) { + logger.error(`Error loading local embeddings: ${error}`); } return models; diff --git a/src/lib/searxng.ts b/src/lib/searxng.ts index da62457b..67beae20 100644 --- a/src/lib/searxng.ts +++ b/src/lib/searxng.ts @@ -1,5 +1,5 @@ -import axios from 'axios'; -import { getSearxngApiEndpoint } from '../config'; +import axios from "axios"; +import { getSearxngApiEndpoint } from "../config"; interface SearxngSearchOptions { categories?: string[]; @@ -19,23 +19,20 @@ interface SearxngSearchResult { iframe_src?: string; } -export const searchSearxng = async ( - query: string, - opts?: SearxngSearchOptions, -) => { +export const searchSearxng = async (query: string, options?: SearxngSearchOptions) => { const searxngURL = getSearxngApiEndpoint(); const url = new URL(`${searxngURL}/search?format=json`); - url.searchParams.append('q', query); + url.searchParams.append("q", query); - if (opts) { - Object.keys(opts).forEach((key) => { - if (Array.isArray(opts[key])) { - url.searchParams.append(key, opts[key].join(',')); - return; + if (options) { + for (const key of Object.keys(options)) { + if (Array.isArray(options[key])) { + url.searchParams.append(key, options[key].join(",")); + continue; } - url.searchParams.append(key, opts[key]); - }); + url.searchParams.append(key, options[key]); + } } const res = await axios.get(url.toString()); diff --git a/src/routes/chats.ts b/src/routes/chats.ts index afa74f97..62eb0ccd 100644 --- a/src/routes/chats.ts +++ b/src/routes/chats.ts @@ -1,65 +1,62 @@ -import express from 'express'; -import logger from '../utils/logger'; -import db from '../db/index'; -import { eq } from 'drizzle-orm'; -import { chats, messages } from '../db/schema'; +import express from "express"; +import logger from "../utils/logger"; +import database from "../db/index"; +import { eq } from "drizzle-orm"; +import { chats, messages } from "../db/schema"; const router = express.Router(); -router.get('/', async (_, res) => { +router.get("/", async (_, res) => { try { - let chats = await db.query.chats.findMany(); + let chats = await database.query.chats.findMany(); chats = chats.reverse(); return res.status(200).json({ chats: chats }); - } catch (err) { - res.status(500).json({ message: 'An error has occurred.' }); - logger.error(`Error in getting chats: ${err.message}`); + } catch (error) { + res.status(500).json({ message: "An error has occurred." }); + logger.error(`Error in getting chats: ${error.message}`); } }); -router.get('/:id', async (req, res) => { +router.get("/:id", async (request, res) => { try { - const chatExists = await db.query.chats.findFirst({ - where: eq(chats.id, req.params.id), + const chatExists = await database.query.chats.findFirst({ + where: eq(chats.id, request.params.id), }); if (!chatExists) { - return res.status(404).json({ message: 'Chat not found' }); + return res.status(404).json({ message: "Chat not found" }); } - const chatMessages = await db.query.messages.findMany({ - where: eq(messages.chatId, req.params.id), + const chatMessages = await database.query.messages.findMany({ + where: eq(messages.chatId, request.params.id), }); return res.status(200).json({ chat: chatExists, messages: chatMessages }); - } catch (err) { - res.status(500).json({ message: 'An error has occurred.' }); - logger.error(`Error in getting chat: ${err.message}`); + } catch (error) { + res.status(500).json({ message: "An error has occurred." }); + logger.error(`Error in getting chat: ${error.message}`); } }); -router.delete(`/:id`, async (req, res) => { +router.delete(`/:id`, async (request, res) => { try { - const chatExists = await db.query.chats.findFirst({ - where: eq(chats.id, req.params.id), + const chatExists = await database.query.chats.findFirst({ + where: eq(chats.id, request.params.id), }); if (!chatExists) { - return res.status(404).json({ message: 'Chat not found' }); + return res.status(404).json({ message: "Chat not found" }); } - await db.delete(chats).where(eq(chats.id, req.params.id)).execute(); - await db - .delete(messages) - .where(eq(messages.chatId, req.params.id)) - .execute(); + await database.delete(chats).where(eq(chats.id, request.params.id)).execute(); + await database.delete(messages).where(eq(messages.chatId, request.params.id)).execute(); - return res.status(200).json({ message: 'Chat deleted successfully' }); - } catch (err) { - res.status(500).json({ message: 'An error has occurred.' }); - logger.error(`Error in deleting chat: ${err.message}`); + return res.status(200).json({ message: "Chat deleted successfully" }); + } catch (error) { + res.status(500).json({ message: "An error has occurred." }); + logger.error(`Error in deleting chat: ${error.message}`); } }); diff --git a/src/routes/config.ts b/src/routes/config.ts index bf13b639..bf727ea6 100644 --- a/src/routes/config.ts +++ b/src/routes/config.ts @@ -1,18 +1,10 @@ -import express from 'express'; -import { - getAvailableChatModelProviders, - getAvailableEmbeddingModelProviders, -} from '../lib/providers'; -import { - getGroqApiKey, - getOllamaApiEndpoint, - getOpenaiApiKey, - updateConfig, -} from '../config'; +import express from "express"; +import { getAvailableChatModelProviders, getAvailableEmbeddingModelProviders } from "../lib/providers"; +import { getGroqApiKey, getOllamaApiEndpoint, getOpenaiApiKey, updateConfig } from "../config"; const router = express.Router(); -router.get('/', async (_, res) => { +router.get("/", async (_, res) => { const config = {}; const [chatModelProviders, embeddingModelProviders] = await Promise.all([ @@ -20,30 +12,26 @@ router.get('/', async (_, res) => { getAvailableEmbeddingModelProviders(), ]); - config['chatModelProviders'] = {}; - config['embeddingModelProviders'] = {}; + config["chatModelProviders"] = {}; + config["embeddingModelProviders"] = {}; for (const provider in chatModelProviders) { - config['chatModelProviders'][provider] = Object.keys( - chatModelProviders[provider], - ); + config["chatModelProviders"][provider] = Object.keys(chatModelProviders[provider]); } for (const provider in embeddingModelProviders) { - config['embeddingModelProviders'][provider] = Object.keys( - embeddingModelProviders[provider], - ); + config["embeddingModelProviders"][provider] = Object.keys(embeddingModelProviders[provider]); } - config['openaiApiKey'] = getOpenaiApiKey(); - config['ollamaApiUrl'] = getOllamaApiEndpoint(); - config['groqApiKey'] = getGroqApiKey(); + config["openaiApiKey"] = getOpenaiApiKey(); + config["ollamaApiUrl"] = getOllamaApiEndpoint(); + config["groqApiKey"] = getGroqApiKey(); res.status(200).json(config); }); -router.post('/', async (req, res) => { - const config = req.body; +router.post("/", async (request, res) => { + const config = request.body; const updatedConfig = { API_KEYS: { @@ -57,7 +45,7 @@ router.post('/', async (req, res) => { updateConfig(updatedConfig); - res.status(200).json({ message: 'Config updated' }); + res.status(200).json({ message: "Config updated" }); }); export default router; diff --git a/src/routes/images.ts b/src/routes/images.ts index 6bd43d3c..ce3db108 100644 --- a/src/routes/images.ts +++ b/src/routes/images.ts @@ -1,21 +1,22 @@ -import express from 'express'; -import handleImageSearch from '../agents/imageSearchAgent'; -import { BaseChatModel } from '@langchain/core/language_models/chat_models'; -import { getAvailableChatModelProviders } from '../lib/providers'; -import { HumanMessage, AIMessage } from '@langchain/core/messages'; -import logger from '../utils/logger'; +import express from "express"; +import handleImageSearch from "../agents/imageSearchAgent"; +import { BaseChatModel } from "@langchain/core/language_models/chat_models"; +import { getAvailableChatModelProviders } from "../lib/providers"; +import { HumanMessage, AIMessage } from "@langchain/core/messages"; +import logger from "../utils/logger"; const router = express.Router(); -router.post('/', async (req, res) => { +router.post("/", async (request, res) => { try { - let { query, chat_history, chat_model_provider, chat_model } = req.body; - - chat_history = chat_history.map((msg: any) => { - if (msg.role === 'user') { - return new HumanMessage(msg.content); - } else if (msg.role === 'assistant') { - return new AIMessage(msg.content); + const { query, chat_history: raw_chat_history, chat_model_provider, chat_model } = request.body; + + // eslint-disable-next-line @typescript-eslint/no-explicit-any + const chat_history = raw_chat_history.map((message: any) => { + if (message.role === "user") { + return new HumanMessage(message.content); + } else if (message.role === "assistant") { + return new AIMessage(message.content); } }); @@ -30,16 +31,16 @@ router.post('/', async (req, res) => { } if (!llm) { - res.status(500).json({ message: 'Invalid LLM model selected' }); + res.status(500).json({ message: "Invalid LLM model selected" }); return; } const images = await handleImageSearch({ query, chat_history }, llm); res.status(200).json({ images }); - } catch (err) { - res.status(500).json({ message: 'An error has occurred.' }); - logger.error(`Error in image search: ${err.message}`); + } catch (error) { + res.status(500).json({ message: "An error has occurred." }); + logger.error(`Error in image search: ${error.message}`); } }); diff --git a/src/routes/index.ts b/src/routes/index.ts index af928abe..79283f64 100644 --- a/src/routes/index.ts +++ b/src/routes/index.ts @@ -1,18 +1,18 @@ -import express from 'express'; -import imagesRouter from './images'; -import videosRouter from './videos'; -import configRouter from './config'; -import modelsRouter from './models'; -import suggestionsRouter from './suggestions'; -import chatsRouter from './chats'; +import express from "express"; +import imagesRouter from "./images"; +import videosRouter from "./videos"; +import configRouter from "./config"; +import modelsRouter from "./models"; +import suggestionsRouter from "./suggestions"; +import chatsRouter from "./chats"; const router = express.Router(); -router.use('/images', imagesRouter); -router.use('/videos', videosRouter); -router.use('/config', configRouter); -router.use('/models', modelsRouter); -router.use('/suggestions', suggestionsRouter); -router.use('/chats', chatsRouter); +router.use("/images", imagesRouter); +router.use("/videos", videosRouter); +router.use("/config", configRouter); +router.use("/models", modelsRouter); +router.use("/suggestions", suggestionsRouter); +router.use("/chats", chatsRouter); export default router; diff --git a/src/routes/models.ts b/src/routes/models.ts index 36df25a5..38ae7ffa 100644 --- a/src/routes/models.ts +++ b/src/routes/models.ts @@ -1,13 +1,10 @@ -import express from 'express'; -import logger from '../utils/logger'; -import { - getAvailableChatModelProviders, - getAvailableEmbeddingModelProviders, -} from '../lib/providers'; +import express from "express"; +import logger from "../utils/logger"; +import { getAvailableChatModelProviders, getAvailableEmbeddingModelProviders } from "../lib/providers"; const router = express.Router(); -router.get('/', async (req, res) => { +router.get("/", async (_request, res) => { try { const [chatModelProviders, embeddingModelProviders] = await Promise.all([ getAvailableChatModelProviders(), @@ -15,9 +12,9 @@ router.get('/', async (req, res) => { ]); res.status(200).json({ chatModelProviders, embeddingModelProviders }); - } catch (err) { - res.status(500).json({ message: 'An error has occurred.' }); - logger.error(err.message); + } catch (error) { + res.status(500).json({ message: "An error has occurred." }); + logger.error(error.message); } }); diff --git a/src/routes/suggestions.ts b/src/routes/suggestions.ts index b15ff5f8..046e75b4 100644 --- a/src/routes/suggestions.ts +++ b/src/routes/suggestions.ts @@ -1,21 +1,22 @@ -import express from 'express'; -import generateSuggestions from '../agents/suggestionGeneratorAgent'; -import { BaseChatModel } from '@langchain/core/language_models/chat_models'; -import { getAvailableChatModelProviders } from '../lib/providers'; -import { HumanMessage, AIMessage } from '@langchain/core/messages'; -import logger from '../utils/logger'; +import express from "express"; +import generateSuggestions from "../agents/suggestionGeneratorAgent"; +import { BaseChatModel } from "@langchain/core/language_models/chat_models"; +import { getAvailableChatModelProviders } from "../lib/providers"; +import { HumanMessage, AIMessage } from "@langchain/core/messages"; +import logger from "../utils/logger"; const router = express.Router(); -router.post('/', async (req, res) => { +router.post("/", async (request, res) => { try { - let { chat_history, chat_model, chat_model_provider } = req.body; - - chat_history = chat_history.map((msg: any) => { - if (msg.role === 'user') { - return new HumanMessage(msg.content); - } else if (msg.role === 'assistant') { - return new AIMessage(msg.content); + const { chat_history: raw_chat_history, chat_model, chat_model_provider } = request.body; + + // eslint-disable-next-line @typescript-eslint/no-explicit-any + const chat_history = raw_chat_history.map((message: any) => { + if (message.role === "user") { + return new HumanMessage(message.content); + } else if (message.role === "assistant") { + return new AIMessage(message.content); } }); @@ -30,16 +31,16 @@ router.post('/', async (req, res) => { } if (!llm) { - res.status(500).json({ message: 'Invalid LLM model selected' }); + res.status(500).json({ message: "Invalid LLM model selected" }); return; } const suggestions = await generateSuggestions({ chat_history }, llm); res.status(200).json({ suggestions: suggestions }); - } catch (err) { - res.status(500).json({ message: 'An error has occurred.' }); - logger.error(`Error in generating suggestions: ${err.message}`); + } catch (error) { + res.status(500).json({ message: "An error has occurred." }); + logger.error(`Error in generating suggestions: ${error.message}`); } }); diff --git a/src/routes/videos.ts b/src/routes/videos.ts index 0ffdb2c6..2a97a87a 100644 --- a/src/routes/videos.ts +++ b/src/routes/videos.ts @@ -1,21 +1,22 @@ -import express from 'express'; -import { BaseChatModel } from '@langchain/core/language_models/chat_models'; -import { getAvailableChatModelProviders } from '../lib/providers'; -import { HumanMessage, AIMessage } from '@langchain/core/messages'; -import logger from '../utils/logger'; -import handleVideoSearch from '../agents/videoSearchAgent'; +import express from "express"; +import { BaseChatModel } from "@langchain/core/language_models/chat_models"; +import { getAvailableChatModelProviders } from "../lib/providers"; +import { HumanMessage, AIMessage } from "@langchain/core/messages"; +import logger from "../utils/logger"; +import handleVideoSearch from "../agents/videoSearchAgent"; const router = express.Router(); -router.post('/', async (req, res) => { +router.post("/", async (request, res) => { try { - let { query, chat_history, chat_model_provider, chat_model } = req.body; - - chat_history = chat_history.map((msg: any) => { - if (msg.role === 'user') { - return new HumanMessage(msg.content); - } else if (msg.role === 'assistant') { - return new AIMessage(msg.content); + const { query, chat_history: raw_chat_history, chat_model_provider, chat_model } = request.body; + + // eslint-disable-next-line @typescript-eslint/no-explicit-any + const chat_history = raw_chat_history.map((message: any) => { + if (message.role === "user") { + return new HumanMessage(message.content); + } else if (message.role === "assistant") { + return new AIMessage(message.content); } }); @@ -30,16 +31,16 @@ router.post('/', async (req, res) => { } if (!llm) { - res.status(500).json({ message: 'Invalid LLM model selected' }); + res.status(500).json({ message: "Invalid LLM model selected" }); return; } const videos = await handleVideoSearch({ chat_history, query }, llm); res.status(200).json({ videos }); - } catch (err) { - res.status(500).json({ message: 'An error has occurred.' }); - logger.error(`Error in video search: ${err.message}`); + } catch (error) { + res.status(500).json({ message: "An error has occurred." }); + logger.error(`Error in video search: ${error.message}`); } }); diff --git a/src/utils/computeSimilarity.ts b/src/utils/computeSimilarity.ts index 6e36b759..ac088374 100644 --- a/src/utils/computeSimilarity.ts +++ b/src/utils/computeSimilarity.ts @@ -1,17 +1,17 @@ -import dot from 'compute-dot'; -import cosineSimilarity from 'compute-cosine-similarity'; -import { getSimilarityMeasure } from '../config'; +import dot from "compute-dot"; +import cosineSimilarity from "compute-cosine-similarity"; +import { getSimilarityMeasure } from "../config"; const computeSimilarity = (x: number[], y: number[]): number => { const similarityMeasure = getSimilarityMeasure(); - if (similarityMeasure === 'cosine') { + if (similarityMeasure === "cosine") { return cosineSimilarity(x, y); - } else if (similarityMeasure === 'dot') { + } else if (similarityMeasure === "dot") { return dot(x, y); } - throw new Error('Invalid similarity measure'); + throw new Error("Invalid similarity measure"); }; export default computeSimilarity; diff --git a/src/utils/formatHistory.ts b/src/utils/formatHistory.ts index 6d0d309c..ab783cbe 100644 --- a/src/utils/formatHistory.ts +++ b/src/utils/formatHistory.ts @@ -1,9 +1,7 @@ -import { BaseMessage } from '@langchain/core/messages'; +import { BaseMessage } from "@langchain/core/messages"; const formatChatHistoryAsString = (history: BaseMessage[]) => { - return history - .map((message) => `${message._getType()}: ${message.content}`) - .join('\n'); + return history.map(message => `${message._getType()}: ${message.content}`).join("\n"); }; export default formatChatHistoryAsString; diff --git a/src/utils/logger.ts b/src/utils/logger.ts index 1c81eb9d..8cbf0d78 100644 --- a/src/utils/logger.ts +++ b/src/utils/logger.ts @@ -1,20 +1,14 @@ -import winston from 'winston'; +import winston from "winston"; const logger = winston.createLogger({ - level: 'info', + level: "info", transports: [ new winston.transports.Console({ - format: winston.format.combine( - winston.format.colorize(), - winston.format.simple(), - ), + format: winston.format.combine(winston.format.colorize(), winston.format.simple()), }), new winston.transports.File({ - filename: 'app.log', - format: winston.format.combine( - winston.format.timestamp(), - winston.format.json(), - ), + filename: "app.log", + format: winston.format.combine(winston.format.timestamp(), winston.format.json()), }), ], }); diff --git a/src/websocket/connectionManager.ts b/src/websocket/connectionManager.ts index 5cb075b6..3cb10b9e 100644 --- a/src/websocket/connectionManager.ts +++ b/src/websocket/connectionManager.ts @@ -1,41 +1,28 @@ -import { WebSocket } from 'ws'; -import { handleMessage } from './messageHandler'; -import { - getAvailableEmbeddingModelProviders, - getAvailableChatModelProviders, -} from '../lib/providers'; -import { BaseChatModel } from '@langchain/core/language_models/chat_models'; -import type { Embeddings } from '@langchain/core/embeddings'; -import type { IncomingMessage } from 'http'; -import logger from '../utils/logger'; -import { ChatOpenAI } from '@langchain/openai'; +import { WebSocket } from "ws"; +import { handleMessage } from "./messageHandler"; +import { getAvailableEmbeddingModelProviders, getAvailableChatModelProviders } from "../lib/providers"; +import { BaseChatModel } from "@langchain/core/language_models/chat_models"; +import type { Embeddings } from "@langchain/core/embeddings"; +import type { IncomingMessage } from "node:http"; +import logger from "../utils/logger"; +import { ChatOpenAI } from "@langchain/openai"; -export const handleConnection = async ( - ws: WebSocket, - request: IncomingMessage, -) => { +export const handleConnection = async (ws: WebSocket, request: IncomingMessage) => { try { - const searchParams = new URL(request.url, `http://${request.headers.host}`) - .searchParams; + const searchParameters = new URL(request.url, `http://${request.headers.host}`).searchParams; const [chatModelProviders, embeddingModelProviders] = await Promise.all([ getAvailableChatModelProviders(), getAvailableEmbeddingModelProviders(), ]); - const chatModelProvider = - searchParams.get('chatModelProvider') || - Object.keys(chatModelProviders)[0]; - const chatModel = - searchParams.get('chatModel') || - Object.keys(chatModelProviders[chatModelProvider])[0]; + const chatModelProvider = searchParameters.get("chatModelProvider") || Object.keys(chatModelProviders)[0]; + const chatModel = searchParameters.get("chatModel") || Object.keys(chatModelProviders[chatModelProvider])[0]; const embeddingModelProvider = - searchParams.get('embeddingModelProvider') || - Object.keys(embeddingModelProviders)[0]; + searchParameters.get("embeddingModelProvider") || Object.keys(embeddingModelProviders)[0]; const embeddingModel = - searchParams.get('embeddingModel') || - Object.keys(embeddingModelProviders[embeddingModelProvider])[0]; + searchParameters.get("embeddingModel") || Object.keys(embeddingModelProviders[embeddingModelProvider])[0]; let llm: BaseChatModel | undefined; let embeddings: Embeddings | undefined; @@ -43,18 +30,16 @@ export const handleConnection = async ( if ( chatModelProviders[chatModelProvider] && chatModelProviders[chatModelProvider][chatModel] && - chatModelProvider != 'custom_openai' + chatModelProvider != "custom_openai" ) { - llm = chatModelProviders[chatModelProvider][chatModel] as - | BaseChatModel - | undefined; - } else if (chatModelProvider == 'custom_openai') { + llm = chatModelProviders[chatModelProvider][chatModel] as BaseChatModel | undefined; + } else if (chatModelProvider == "custom_openai") { llm = new ChatOpenAI({ modelName: chatModel, - openAIApiKey: searchParams.get('openAIApiKey'), + openAIApiKey: searchParameters.get("openAIApiKey"), temperature: 0.7, configuration: { - baseURL: searchParams.get('openAIBaseURL'), + baseURL: searchParameters.get("openAIBaseURL"), }, }); } @@ -63,38 +48,32 @@ export const handleConnection = async ( embeddingModelProviders[embeddingModelProvider] && embeddingModelProviders[embeddingModelProvider][embeddingModel] ) { - embeddings = embeddingModelProviders[embeddingModelProvider][ - embeddingModel - ] as Embeddings | undefined; + embeddings = embeddingModelProviders[embeddingModelProvider][embeddingModel] as Embeddings | undefined; } if (!llm || !embeddings) { ws.send( JSON.stringify({ - type: 'error', - data: 'Invalid LLM or embeddings model selected, please refresh the page and try again.', - key: 'INVALID_MODEL_SELECTED', + type: "error", + data: "Invalid LLM or embeddings model selected, please refresh the page and try again.", + key: "INVALID_MODEL_SELECTED", }), ); ws.close(); } - ws.on( - 'message', - async (message) => - await handleMessage(message.toString(), ws, llm, embeddings), - ); + ws.on("message", async message => await handleMessage(message.toString(), ws, llm, embeddings)); - ws.on('close', () => logger.debug('Connection closed')); - } catch (err) { + ws.on("close", () => logger.debug("Connection closed")); + } catch (error) { ws.send( JSON.stringify({ - type: 'error', - data: 'Internal server error.', - key: 'INTERNAL_SERVER_ERROR', + type: "error", + data: "Internal server error.", + key: "INTERNAL_SERVER_ERROR", }), ); ws.close(); - logger.error(err); + logger.error(error); } }; diff --git a/src/websocket/index.ts b/src/websocket/index.ts index 1b9ae770..be32a6ea 100644 --- a/src/websocket/index.ts +++ b/src/websocket/index.ts @@ -1,8 +1,6 @@ -import { initServer } from './websocketServer'; -import http from 'http'; +import { initServer } from "./websocketServer"; +import http from "node:http"; -export const startWebSocketServer = ( - server: http.Server, -) => { +export const startWebSocketServer = (server: http.Server) => { initServer(server); }; diff --git a/src/websocket/messageHandler.ts b/src/websocket/messageHandler.ts index 0afda9f4..6f30762b 100644 --- a/src/websocket/messageHandler.ts +++ b/src/websocket/messageHandler.ts @@ -1,18 +1,18 @@ -import { EventEmitter, WebSocket } from 'ws'; -import { BaseMessage, AIMessage, HumanMessage } from '@langchain/core/messages'; -import handleWebSearch from '../agents/webSearchAgent'; -import handleAcademicSearch from '../agents/academicSearchAgent'; -import handleWritingAssistant from '../agents/writingAssistant'; -import handleWolframAlphaSearch from '../agents/wolframAlphaSearchAgent'; -import handleYoutubeSearch from '../agents/youtubeSearchAgent'; -import handleRedditSearch from '../agents/redditSearchAgent'; -import type { BaseChatModel } from '@langchain/core/language_models/chat_models'; -import type { Embeddings } from '@langchain/core/embeddings'; -import logger from '../utils/logger'; -import db from '../db'; -import { chats, messages } from '../db/schema'; -import { eq } from 'drizzle-orm'; -import crypto from 'crypto'; +import { EventEmitter, WebSocket } from "ws"; +import { BaseMessage, AIMessage, HumanMessage } from "@langchain/core/messages"; +import handleWebSearch from "../agents/webSearchAgent"; +import handleAcademicSearch from "../agents/academicSearchAgent"; +import handleWritingAssistant from "../agents/writingAssistant"; +import handleWolframAlphaSearch from "../agents/wolframAlphaSearchAgent"; +import handleYoutubeSearch from "../agents/youtubeSearchAgent"; +import handleRedditSearch from "../agents/redditSearchAgent"; +import type { BaseChatModel } from "@langchain/core/language_models/chat_models"; +import type { Embeddings } from "@langchain/core/embeddings"; +import logger from "../utils/logger"; +import database from "../db"; +import { chats, messages } from "../db/schema"; +import { eq } from "drizzle-orm"; +import crypto from "node:crypto"; type Message = { messageId: string; @@ -37,30 +37,25 @@ const searchHandlers = { redditSearch: handleRedditSearch, }; -const handleEmitterEvents = ( - emitter: EventEmitter, - ws: WebSocket, - messageId: string, - chatId: string, -) => { - let recievedMessage = ''; +const handleEmitterEvents = (emitter: EventEmitter, ws: WebSocket, messageId: string, chatId: string) => { + let recievedMessage = ""; let sources = []; - emitter.on('data', (data) => { + emitter.on("data", data => { const parsedData = JSON.parse(data); - if (parsedData.type === 'response') { + if (parsedData.type === "response") { ws.send( JSON.stringify({ - type: 'message', + type: "message", data: parsedData.data, messageId: messageId, }), ); recievedMessage += parsedData.data; - } else if (parsedData.type === 'sources') { + } else if (parsedData.type === "sources") { ws.send( JSON.stringify({ - type: 'sources', + type: "sources", data: parsedData.data, messageId: messageId, }), @@ -68,15 +63,16 @@ const handleEmitterEvents = ( sources = parsedData.data; } }); - emitter.on('end', () => { - ws.send(JSON.stringify({ type: 'messageEnd', messageId: messageId })); + emitter.on("end", () => { + ws.send(JSON.stringify({ type: "messageEnd", messageId: messageId })); - db.insert(messages) + database + .insert(messages) .values({ content: recievedMessage, chatId: chatId, messageId: messageId, - role: 'assistant', + role: "assistant", metadata: JSON.stringify({ createdAt: new Date(), ...(sources && sources.length > 0 && { sources }), @@ -84,70 +80,58 @@ const handleEmitterEvents = ( }) .execute(); }); - emitter.on('error', (data) => { + emitter.on("error", data => { const parsedData = JSON.parse(data); ws.send( JSON.stringify({ - type: 'error', + type: "error", data: parsedData.data, - key: 'CHAIN_ERROR', + key: "CHAIN_ERROR", }), ); }); }; -export const handleMessage = async ( - message: string, - ws: WebSocket, - llm: BaseChatModel, - embeddings: Embeddings, -) => { +export const handleMessage = async (message: string, ws: WebSocket, llm: BaseChatModel, embeddings: Embeddings) => { try { const parsedWSMessage = JSON.parse(message) as WSMessage; const parsedMessage = parsedWSMessage.message; - const id = crypto.randomBytes(7).toString('hex'); + const id = crypto.randomBytes(7).toString("hex"); if (!parsedMessage.content) return ws.send( JSON.stringify({ - type: 'error', - data: 'Invalid message format', - key: 'INVALID_FORMAT', + type: "error", + data: "Invalid message format", + key: "INVALID_FORMAT", }), ); - const history: BaseMessage[] = parsedWSMessage.history.map((msg) => { - if (msg[0] === 'human') { - return new HumanMessage({ - content: msg[1], - }); - } else { - return new AIMessage({ - content: msg[1], - }); - } + const history: BaseMessage[] = parsedWSMessage.history.map(message_ => { + return message_[0] === "human" + ? new HumanMessage({ + content: message_[1], + }) + : new AIMessage({ + content: message_[1], + }); }); - if (parsedWSMessage.type === 'message') { + if (parsedWSMessage.type === "message") { const handler = searchHandlers[parsedWSMessage.focusMode]; if (handler) { - const emitter = handler( - parsedMessage.content, - history, - llm, - embeddings, - ); + const emitter = handler(parsedMessage.content, history, llm, embeddings); handleEmitterEvents(emitter, ws, id, parsedMessage.chatId); - const chat = await db.query.chats.findFirst({ + const chat = await database.query.chats.findFirst({ where: eq(chats.id, parsedMessage.chatId), }); if (!chat) { - await db + await database .insert(chats) .values({ id: parsedMessage.chatId, @@ -158,13 +142,13 @@ export const handleMessage = async ( .execute(); } - await db + await database .insert(messages) .values({ content: parsedMessage.content, chatId: parsedMessage.chatId, messageId: id, - role: 'user', + role: "user", metadata: JSON.stringify({ createdAt: new Date(), }), @@ -173,21 +157,21 @@ export const handleMessage = async ( } else { ws.send( JSON.stringify({ - type: 'error', - data: 'Invalid focus mode', - key: 'INVALID_FOCUS_MODE', + type: "error", + data: "Invalid focus mode", + key: "INVALID_FOCUS_MODE", }), ); } } - } catch (err) { + } catch (error) { ws.send( JSON.stringify({ - type: 'error', - data: 'Invalid message format', - key: 'INVALID_FORMAT', + type: "error", + data: "Invalid message format", + key: "INVALID_FORMAT", }), ); - logger.error(`Failed to handle message: ${err}`); + logger.error(`Failed to handle message: ${error}`); } }; diff --git a/src/websocket/websocketServer.ts b/src/websocket/websocketServer.ts index 3ab0b519..e6a3d795 100644 --- a/src/websocket/websocketServer.ts +++ b/src/websocket/websocketServer.ts @@ -1,16 +1,14 @@ -import { WebSocketServer } from 'ws'; -import { handleConnection } from './connectionManager'; -import http from 'http'; -import { getPort } from '../config'; -import logger from '../utils/logger'; +import { WebSocketServer } from "ws"; +import { handleConnection } from "./connectionManager"; +import http from "node:http"; +import { getPort } from "../config"; +import logger from "../utils/logger"; -export const initServer = ( - server: http.Server, -) => { +export const initServer = (server: http.Server) => { const port = getPort(); const wss = new WebSocketServer({ server }); - wss.on('connection', handleConnection); + wss.on("connection", handleConnection); logger.info(`WebSocket server started on port ${port}`); }; diff --git a/tsconfig.json b/tsconfig.json index 48e6042f..7821a4b8 100644 --- a/tsconfig.json +++ b/tsconfig.json @@ -11,7 +11,9 @@ "emitDecoratorMetadata": true, "allowSyntheticDefaultImports": true, "skipLibCheck": true, - "skipDefaultLibCheck": true + "skipDefaultLibCheck": true, + "noUnusedLocals": true, + "noUnusedParameters": true }, "include": ["src"], "exclude": ["node_modules", "**/*.spec.ts"] diff --git a/ui/.env.example b/ui/.env.example index 57a3ed98..4032dc36 100644 --- a/ui/.env.example +++ b/ui/.env.example @@ -1,2 +1,2 @@ -NEXT_PUBLIC_WS_URL=ws://localhost:3001 -NEXT_PUBLIC_API_URL=http://localhost:3001/api \ No newline at end of file +NEXT_PUBLIC_WS_URL=ws://localhost:3000 +NEXT_PUBLIC_API_URL=http://localhost:3000/api \ No newline at end of file diff --git a/ui/.eslintignore b/ui/.eslintignore new file mode 100644 index 00000000..03dd0ead --- /dev/null +++ b/ui/.eslintignore @@ -0,0 +1,3 @@ +node_modules +dist +next-env.d.ts diff --git a/ui/.eslintrc.json b/ui/.eslintrc.json index bffb357a..48199572 100644 --- a/ui/.eslintrc.json +++ b/ui/.eslintrc.json @@ -1,3 +1,23 @@ { - "extends": "next/core-web-vitals" + "extends": ["../.eslintrc.json"], + "overrides": [ + { + "files": ["*.ts", "*.tsx"], + "plugins": ["react", "react-hooks"], + "extends": ["plugin:react/recommended", "plugin:react-hooks/recommended", "plugin:react/jsx-runtime"] + }, + { + "files": [ + "postcss.config.js", + "tailwind.config.js", + "tailwind.config.ts" + ], + "rules": { + "unicorn/prefer-module": "off" + }, + "env": { + "node": true + } + } + ] } diff --git a/ui/.prettierrc b/ui/.prettierrc new file mode 100644 index 00000000..3a181a15 --- /dev/null +++ b/ui/.prettierrc @@ -0,0 +1,5 @@ +{ + "endOfLine": "auto", + "trailingComma": "all", + "arrowParens": "avoid" +} diff --git a/ui/.prettierrc.js b/ui/.prettierrc.js deleted file mode 100644 index 8ca480f1..00000000 --- a/ui/.prettierrc.js +++ /dev/null @@ -1,11 +0,0 @@ -/** @type {import("prettier").Config} */ - -const config = { - printWidth: 80, - trailingComma: 'all', - endOfLine: 'auto', - singleQuote: true, - tabWidth: 2, -}; - -module.exports = config; diff --git a/ui/app/api/news/[id]/route.ts b/ui/app/api/news/[id]/route.ts new file mode 100644 index 00000000..e6295e23 --- /dev/null +++ b/ui/app/api/news/[id]/route.ts @@ -0,0 +1,22 @@ +import { NextResponse } from "next/server"; +import fs from "node:fs/promises"; +import path from "node:path"; +import { VALIDATED_ENV } from "../../../../lib/constants"; + +export async function GET(request: Request, { params }: { params: { id: string } }) { + try { + console.log(`Fetching news data for id: ${params.id}`); + console.log(`API URL: ${VALIDATED_ENV.API_URL}`); // Log the API URL + + const dataDirectory = path.join(process.cwd(), "public", "data"); + const filePath = path.join(dataDirectory, `${params.id}.json`); + const fileContents = await fs.readFile(filePath, "utf8"); + const newsData = JSON.parse(fileContents); + + return NextResponse.json(newsData); + } catch (error) { + console.error("Error reading news data:", error); + console.log(`WS URL: ${VALIDATED_ENV.WS_URL}`); // Log the WebSocket URL, just as an example + return NextResponse.json({ error: "News not found" }, { status: 404 }); + } +} diff --git a/ui/app/api/news/route.ts b/ui/app/api/news/route.ts new file mode 100644 index 00000000..40cedbcb --- /dev/null +++ b/ui/app/api/news/route.ts @@ -0,0 +1,16 @@ +import { NextResponse } from "next/server"; +import fs from "node:fs/promises"; +import path from "node:path"; + +export async function GET() { + try { + const dataDirectory = path.join(process.cwd(), "public", "data"); + const filePath = path.join(dataDirectory, "index.json"); + const fileContents = await fs.readFile(filePath, "utf8"); + const data = JSON.parse(fileContents); + return NextResponse.json(data); + } catch (error) { + console.error("Error reading news data:", error); + return NextResponse.json({ error: "Failed to load news data" }, { status: 500 }); + } +} diff --git a/ui/app/c/[chatId]/page.tsx b/ui/app/c/[chatId]/page.tsx index dc3c92a0..4c8ab95f 100644 --- a/ui/app/c/[chatId]/page.tsx +++ b/ui/app/c/[chatId]/page.tsx @@ -1,4 +1,4 @@ -import ChatWindow from '@/components/ChatWindow'; +import ChatWindow from "@/components/ChatWindow"; const Page = ({ params }: { params: { chatId: string } }) => { return ; diff --git a/ui/app/globals.css b/ui/app/globals.css index f75dacad..5aa0fd8c 100644 --- a/ui/app/globals.css +++ b/ui/app/globals.css @@ -10,4 +10,12 @@ .overflow-hidden-scrollable::-webkit-scrollbar { display: none; } + .line-clamp-3-5 { + display: -webkit-box; + -webkit-line-clamp: 4; + -webkit-box-orient: vertical; + overflow: hidden; + } + } + diff --git a/ui/app/layout.tsx b/ui/app/layout.tsx index 2edbf942..27c27c47 100644 --- a/ui/app/layout.tsx +++ b/ui/app/layout.tsx @@ -1,22 +1,21 @@ -import type { Metadata } from 'next'; -import { Montserrat } from 'next/font/google'; -import './globals.css'; -import { cn } from '@/lib/utils'; -import Sidebar from '@/components/Sidebar'; -import { Toaster } from 'sonner'; -import ThemeProvider from '@/components/theme/Provider'; +import type { Metadata } from "next"; +import { Montserrat } from "next/font/google"; +import "./globals.css"; +import { cn } from "@/lib/utils"; +import Sidebar from "@/components/Sidebar"; +import { Toaster } from "sonner"; +import ThemeProvider from "@/components/theme/Provider"; const montserrat = Montserrat({ - weight: ['300', '400', '500', '700'], - subsets: ['latin'], - display: 'swap', - fallback: ['Arial', 'sans-serif'], + weight: ["300", "400", "500", "700"], + subsets: ["latin"], + display: "swap", + fallback: ["Arial", "sans-serif"], }); export const metadata: Metadata = { - title: 'Perplexica - Chat with the internet', - description: - 'Perplexica is an AI powered chatbot that is connected to the internet.', + title: "Perplexica - Chat with the internet", + description: "Perplexica is an AI powered chatbot that is connected to the internet.", }; export default function RootLayout({ @@ -26,7 +25,7 @@ export default function RootLayout({ }>) { return ( - + {children} diff --git a/ui/app/library/layout.tsx b/ui/app/library/layout.tsx index 00d4a3bc..f7db5db8 100644 --- a/ui/app/library/layout.tsx +++ b/ui/app/library/layout.tsx @@ -1,8 +1,8 @@ -import { Metadata } from 'next'; -import React from 'react'; +import { Metadata } from "next"; +import React from "react"; export const metadata: Metadata = { - title: 'Library - Perplexica', + title: "Library - Perplexica", }; const Layout = ({ children }: { children: React.ReactNode }) => { diff --git a/ui/app/library/page.tsx b/ui/app/library/page.tsx index 8294fc1b..b0398594 100644 --- a/ui/app/library/page.tsx +++ b/ui/app/library/page.tsx @@ -1,10 +1,10 @@ -'use client'; +"use client"; -import DeleteChat from '@/components/DeleteChat'; -import { formatTimeDifference } from '@/lib/utils'; -import { BookOpenText, ClockIcon, Delete, ScanEye } from 'lucide-react'; -import Link from 'next/link'; -import { useEffect, useState } from 'react'; +import DeleteChat from "@/components/DeleteChat"; +import { formatTimeDifference } from "@/lib/utils"; +import { BookOpenText, ClockIcon } from "lucide-react"; +import Link from "next/link"; +import { useEffect, useState } from "react"; export interface Chat { id: string; @@ -22,9 +22,9 @@ const Page = () => { setLoading(true); const res = await fetch(`${process.env.NEXT_PUBLIC_API_URL}/chats`, { - method: 'GET', + method: "GET", headers: { - 'Content-Type': 'application/json', + "Content-Type": "application/json", }, }); @@ -61,24 +61,20 @@ const Page = () => {
-

- Library -

+

Library

{chats.length === 0 && (
-

- No chats found. -

+

No chats found.

)} {chats.length > 0 && (
- {chats.map((chat, i) => ( + {chats.map((chat, index) => (
{
-

- {formatTimeDifference(new Date(), chat.createdAt)} Ago -

+

{formatTimeDifference(new Date(), chat.createdAt)} Ago

- +
))} diff --git a/ui/app/news/[id]/layout.tsx b/ui/app/news/[id]/layout.tsx new file mode 100644 index 00000000..5dd540fa --- /dev/null +++ b/ui/app/news/[id]/layout.tsx @@ -0,0 +1,15 @@ +import { Metadata } from "next"; +import React from "react"; +import { ENV, assertEnvVariables as assertEnvironmentVariables } from "../../../lib/constants"; + +export const metadata: Metadata = { + title: "News - Perplexica", +}; + +assertEnvironmentVariables(ENV); + +const Layout = ({ children }: { children: React.ReactNode }) => { + return
{children}
; +}; + +export default Layout; diff --git a/ui/app/news/[id]/page.tsx b/ui/app/news/[id]/page.tsx new file mode 100644 index 00000000..4a0f76f8 --- /dev/null +++ b/ui/app/news/[id]/page.tsx @@ -0,0 +1,20 @@ +import NewsDetail from "../../../components/NewsDetailPage/NewsDetail"; +import { VALIDATED_ENV } from "../../../lib/constants"; + +async function getNewsData(id: string) { + const res = await fetch(`${VALIDATED_ENV.API_URL}/news/${id}`, { next: { revalidate: 60 } }); + if (!res.ok) { + throw new Error("Failed to fetch news"); + } + return res.json(); +} + +export default async function NewsPage({ params }: { params: { id: string } }) { + const newsData = await getNewsData(params.id); + + if (!newsData) { + return
News not found or failed to load
; + } + + return ; +} diff --git a/ui/app/news/layout.tsx b/ui/app/news/layout.tsx new file mode 100644 index 00000000..d773b444 --- /dev/null +++ b/ui/app/news/layout.tsx @@ -0,0 +1,5 @@ +import React from "react"; + +export default function NewsLayout({ children }: { children: React.ReactNode }) { + return
{children}
; +} diff --git a/ui/app/news/page.tsx b/ui/app/news/page.tsx new file mode 100644 index 00000000..357c4666 --- /dev/null +++ b/ui/app/news/page.tsx @@ -0,0 +1,5 @@ +import NewsPage from "@/components/NewsPage"; + +export default function Page() { + return ; +} diff --git a/ui/app/page.tsx b/ui/app/page.tsx index e18aca9d..b1397748 100644 --- a/ui/app/page.tsx +++ b/ui/app/page.tsx @@ -1,10 +1,10 @@ -import ChatWindow from '@/components/ChatWindow'; -import { Metadata } from 'next'; -import { Suspense } from 'react'; +import ChatWindow from "@/components/ChatWindow"; +import { Metadata } from "next"; +import { Suspense } from "react"; export const metadata: Metadata = { - title: 'Chat - Perplexica', - description: 'Chat with the internet, chat with Perplexica.', + title: "Chat - Perplexica", + description: "Chat with the internet, chat with Perplexica.", }; const Home = () => { diff --git a/ui/components/Chat.tsx b/ui/components/Chat.tsx index 8c0fb804..c1b5dd87 100644 --- a/ui/components/Chat.tsx +++ b/ui/components/Chat.tsx @@ -1,10 +1,10 @@ -'use client'; +"use client"; -import { Fragment, useEffect, useRef, useState } from 'react'; -import MessageInput from './MessageInput'; -import { Message } from './ChatWindow'; -import MessageBox from './MessageBox'; -import MessageBoxLoading from './MessageBoxLoading'; +import { Fragment, useEffect, useRef, useState } from "react"; +import MessageInput from "./MessageInput"; +import { Message } from "./ChatWindow"; +import MessageBox from "./MessageBox"; +import MessageBoxLoading from "./MessageBoxLoading"; const Chat = ({ loading, @@ -20,52 +20,52 @@ const Chat = ({ rewrite: (messageId: string) => void; }) => { const [dividerWidth, setDividerWidth] = useState(0); - const dividerRef = useRef(null); + const dividerReference = useRef(null); const messageEnd = useRef(null); useEffect(() => { const updateDividerWidth = () => { - if (dividerRef.current) { - setDividerWidth(dividerRef.current.scrollWidth); + if (dividerReference.current) { + setDividerWidth(dividerReference.current.scrollWidth); } }; updateDividerWidth(); - window.addEventListener('resize', updateDividerWidth); + window.addEventListener("resize", updateDividerWidth); return () => { - window.removeEventListener('resize', updateDividerWidth); + window.removeEventListener("resize", updateDividerWidth); }; }); useEffect(() => { - messageEnd.current?.scrollIntoView({ behavior: 'smooth' }); + messageEnd.current?.scrollIntoView({ behavior: "smooth" }); if (messages.length === 1) { - document.title = `${messages[0].content.substring(0, 30)} - Perplexica`; + document.title = `${messages[0].content.slice(0, 30)} - Perplexica`; } }, [messages]); return (
- {messages.map((msg, i) => { - const isLast = i === messages.length - 1; + {messages.map((message, index) => { + const isLast = index === messages.length - 1; return ( - + - {!isLast && msg.role === 'assistant' && ( + {!isLast && message.role === "assistant" && (
)} @@ -74,10 +74,7 @@ const Chat = ({ {loading && !messageAppeared && }
{dividerWidth > 0 && ( -
+
)} diff --git a/ui/components/ChatWindow.tsx b/ui/components/ChatWindow.tsx index 675df49d..b95f530a 100644 --- a/ui/components/ChatWindow.tsx +++ b/ui/components/ChatWindow.tsx @@ -1,111 +1,81 @@ -'use client'; - -import { useEffect, useRef, useState } from 'react'; -import { Document } from '@langchain/core/documents'; -import Navbar from './Navbar'; -import Chat from './Chat'; -import EmptyChat from './EmptyChat'; -import crypto from 'crypto'; -import { toast } from 'sonner'; -import { useSearchParams } from 'next/navigation'; -import { getSuggestions } from '@/lib/actions'; -import Error from 'next/error'; +/* eslint-disable @typescript-eslint/no-explicit-any */ +"use client"; + +import { useEffect, useRef, useState } from "react"; +import { Document } from "@langchain/core/documents"; +import Navbar from "./Navbar"; +import Chat from "./Chat"; +import EmptyChat from "./EmptyChat"; +import crypto from "node:crypto"; +import { toast } from "sonner"; +import { useSearchParams } from "next/navigation"; +import { getSuggestions } from "@/lib/actions"; +import Error from "next/error"; export type Message = { messageId: string; chatId: string; createdAt: Date; content: string; - role: 'user' | 'assistant'; + role: "user" | "assistant"; suggestions?: string[]; sources?: Document[]; }; -const useSocket = ( - url: string, - setIsWSReady: (ready: boolean) => void, - setError: (error: boolean) => void, -) => { +const useSocket = (url: string, setIsWSReady: (ready: boolean) => void, setError: (error: boolean) => void) => { const [ws, setWs] = useState(null); useEffect(() => { if (!ws) { const connectWs = async () => { - let chatModel = localStorage.getItem('chatModel'); - let chatModelProvider = localStorage.getItem('chatModelProvider'); - let embeddingModel = localStorage.getItem('embeddingModel'); - let embeddingModelProvider = localStorage.getItem( - 'embeddingModelProvider', - ); - - if ( - !chatModel || - !chatModelProvider || - !embeddingModel || - !embeddingModelProvider - ) { - const providers = await fetch( - `${process.env.NEXT_PUBLIC_API_URL}/models`, - { - headers: { - 'Content-Type': 'application/json', - }, + let chatModel = localStorage.getItem("chatModel"); + let chatModelProvider = localStorage.getItem("chatModelProvider"); + let embeddingModel = localStorage.getItem("embeddingModel"); + let embeddingModelProvider = localStorage.getItem("embeddingModelProvider"); + + if (!chatModel || !chatModelProvider || !embeddingModel || !embeddingModelProvider) { + const providers = await fetch(`${process.env.NEXT_PUBLIC_API_URL}/models`, { + headers: { + "Content-Type": "application/json", }, - ).then(async (res) => await res.json()); + }).then(async res => await res.json()); const chatModelProviders = providers.chatModelProviders; const embeddingModelProviders = providers.embeddingModelProviders; - if ( - !chatModelProviders || - Object.keys(chatModelProviders).length === 0 - ) - return toast.error('No chat models available'); + if (!chatModelProviders || Object.keys(chatModelProviders).length === 0) + return toast.error("No chat models available"); - if ( - !embeddingModelProviders || - Object.keys(embeddingModelProviders).length === 0 - ) - return toast.error('No embedding models available'); + if (!embeddingModelProviders || Object.keys(embeddingModelProviders).length === 0) + return toast.error("No embedding models available"); chatModelProvider = Object.keys(chatModelProviders)[0]; chatModel = Object.keys(chatModelProviders[chatModelProvider])[0]; embeddingModelProvider = Object.keys(embeddingModelProviders)[0]; - embeddingModel = Object.keys( - embeddingModelProviders[embeddingModelProvider], - )[0]; - - localStorage.setItem('chatModel', chatModel!); - localStorage.setItem('chatModelProvider', chatModelProvider); - localStorage.setItem('embeddingModel', embeddingModel!); - localStorage.setItem( - 'embeddingModelProvider', - embeddingModelProvider, - ); + embeddingModel = Object.keys(embeddingModelProviders[embeddingModelProvider])[0]; + + localStorage.setItem("chatModel", chatModel!); + localStorage.setItem("chatModelProvider", chatModelProvider); + localStorage.setItem("embeddingModel", embeddingModel!); + localStorage.setItem("embeddingModelProvider", embeddingModelProvider); } const wsURL = new URL(url); - const searchParams = new URLSearchParams({}); + const searchParameters = new URLSearchParams({}); - searchParams.append('chatModel', chatModel!); - searchParams.append('chatModelProvider', chatModelProvider); + searchParameters.append("chatModel", chatModel!); + searchParameters.append("chatModelProvider", chatModelProvider); - if (chatModelProvider === 'custom_openai') { - searchParams.append( - 'openAIApiKey', - localStorage.getItem('openAIApiKey')!, - ); - searchParams.append( - 'openAIBaseURL', - localStorage.getItem('openAIBaseURL')!, - ); + if (chatModelProvider === "custom_openai") { + searchParameters.append("openAIApiKey", localStorage.getItem("openAIApiKey")!); + searchParameters.append("openAIBaseURL", localStorage.getItem("openAIBaseURL")!); } - searchParams.append('embeddingModel', embeddingModel!); - searchParams.append('embeddingModelProvider', embeddingModelProvider); + searchParameters.append("embeddingModel", embeddingModel!); + searchParameters.append("embeddingModelProvider", embeddingModelProvider); - wsURL.search = searchParams.toString(); + wsURL.search = searchParameters.toString(); const ws = new WebSocket(wsURL.toString()); @@ -113,30 +83,29 @@ const useSocket = ( if (ws.readyState !== 1) { ws.close(); setError(true); - toast.error( - 'Failed to connect to the server. Please try again later.', - ); + toast.error("Failed to connect to the server. Please try again later."); } - }, 10000); + }, 10_000); - ws.onopen = () => { - console.log('[DEBUG] open'); + ws.addEventListener("open", () => { + console.log("[DEBUG] open"); clearTimeout(timeoutId); setError(false); setIsWSReady(true); - }; + }); + // eslint-disable-next-line unicorn/prefer-add-event-listener ws.onerror = () => { clearTimeout(timeoutId); setError(true); - toast.error('WebSocket connection error.'); + toast.error("WebSocket connection error."); }; - ws.onclose = () => { + ws.addEventListener("close", () => { clearTimeout(timeoutId); setError(true); - console.log('[DEBUG] closed'); - }; + console.log("[DEBUG] closed"); + }); setWs(ws); }; @@ -146,7 +115,7 @@ const useSocket = ( return () => { ws?.close(); - console.log('[DEBUG] closed'); + console.log("[DEBUG] closed"); }; }, [ws, url, setIsWSReady, setError]); @@ -161,15 +130,12 @@ const loadMessages = async ( setFocusMode: (mode: string) => void, setNotFound: (notFound: boolean) => void, ) => { - const res = await fetch( - `${process.env.NEXT_PUBLIC_API_URL}/chats/${chatId}`, - { - method: 'GET', - headers: { - 'Content-Type': 'application/json', - }, + const res = await fetch(`${process.env.NEXT_PUBLIC_API_URL}/chats/${chatId}`, { + method: "GET", + headers: { + "Content-Type": "application/json", }, - ); + }); if (res.status === 404) { setNotFound(true); @@ -179,20 +145,20 @@ const loadMessages = async ( const data = await res.json(); - const messages = data.messages.map((msg: any) => { + const messages = data.messages.map((message: any) => { return { - ...msg, - ...JSON.parse(msg.metadata), + ...message, + ...JSON.parse(message.metadata), }; }) as Message[]; setMessages(messages); - const history = messages.map((msg) => { - return [msg.role, msg.content]; + const history = messages.map(message => { + return [message.role, message.content]; }) as [string, string][]; - console.log('[DEBUG] messages loaded'); + console.log("[DEBUG] messages loaded"); document.title = messages[0].content; @@ -202,8 +168,8 @@ const loadMessages = async ( }; const ChatWindow = ({ id }: { id?: string }) => { - const searchParams = useSearchParams(); - const initialMessage = searchParams.get('q'); + const searchParameters = useSearchParams(); + const initialMessage = searchParameters.get("q"); const [chatId, setChatId] = useState(id); const [newChatCreated, setNewChatCreated] = useState(false); @@ -212,11 +178,7 @@ const ChatWindow = ({ id }: { id?: string }) => { const [isReady, setIsReady] = useState(false); const [isWSReady, setIsWSReady] = useState(false); - const ws = useSocket( - process.env.NEXT_PUBLIC_WS_URL!, - setIsWSReady, - setHasError, - ); + const ws = useSocket(process.env.NEXT_PUBLIC_WS_URL!, setIsWSReady, setHasError); const [loading, setLoading] = useState(false); const [messageAppeared, setMessageAppeared] = useState(false); @@ -224,39 +186,27 @@ const ChatWindow = ({ id }: { id?: string }) => { const [chatHistory, setChatHistory] = useState<[string, string][]>([]); const [messages, setMessages] = useState([]); - const [focusMode, setFocusMode] = useState('webSearch'); + const [focusMode, setFocusMode] = useState("webSearch"); const [isMessagesLoaded, setIsMessagesLoaded] = useState(false); const [notFound, setNotFound] = useState(false); useEffect(() => { - if ( - chatId && - !newChatCreated && - !isMessagesLoaded && - messages.length === 0 - ) { - loadMessages( - chatId, - setMessages, - setIsMessagesLoaded, - setChatHistory, - setFocusMode, - setNotFound, - ); + if (chatId && !newChatCreated && !isMessagesLoaded && messages.length === 0) { + loadMessages(chatId, setMessages, setIsMessagesLoaded, setChatHistory, setFocusMode, setNotFound); } else if (!chatId) { setNewChatCreated(true); setIsMessagesLoaded(true); - setChatId(crypto.randomBytes(20).toString('hex')); + setChatId(crypto.randomBytes(20).toString("hex")); } // eslint-disable-next-line react-hooks/exhaustive-deps }, []); - const messagesRef = useRef([]); + const messagesReference = useRef([]); useEffect(() => { - messagesRef.current = messages; + messagesReference.current = messages; }, [messages]); useEffect(() => { @@ -270,31 +220,31 @@ const ChatWindow = ({ id }: { id?: string }) => { setLoading(true); setMessageAppeared(false); - let sources: Document[] | undefined = undefined; - let recievedMessage = ''; + let sources: Document[] | undefined; + let recievedMessage = ""; let added = false; - const messageId = crypto.randomBytes(7).toString('hex'); + const messageId = crypto.randomBytes(7).toString("hex"); ws?.send( JSON.stringify({ - type: 'message', + type: "message", message: { chatId: chatId!, content: message, }, focusMode: focusMode, - history: [...chatHistory, ['human', message]], + history: [...chatHistory, ["human", message]], }), ); - setMessages((prevMessages) => [ - ...prevMessages, + setMessages(previousMessages => [ + ...previousMessages, { content: message, messageId: messageId, chatId: chatId!, - role: 'user', + role: "user", createdAt: new Date(), }, ]); @@ -302,22 +252,22 @@ const ChatWindow = ({ id }: { id?: string }) => { const messageHandler = async (e: MessageEvent) => { const data = JSON.parse(e.data); - if (data.type === 'error') { + if (data.type === "error") { toast.error(data.data); setLoading(false); return; } - if (data.type === 'sources') { + if (data.type === "sources") { sources = data.data; if (!added) { - setMessages((prevMessages) => [ - ...prevMessages, + setMessages(previousMessages => [ + ...previousMessages, { - content: '', + content: "", messageId: data.messageId, chatId: chatId!, - role: 'assistant', + role: "assistant", sources: sources, createdAt: new Date(), }, @@ -327,15 +277,15 @@ const ChatWindow = ({ id }: { id?: string }) => { setMessageAppeared(true); } - if (data.type === 'message') { + if (data.type === "message") { if (!added) { - setMessages((prevMessages) => [ - ...prevMessages, + setMessages(previousMessages => [ + ...previousMessages, { content: data.data, messageId: data.messageId, chatId: chatId!, - role: 'assistant', + role: "assistant", sources: sources, createdAt: new Date(), }, @@ -343,8 +293,8 @@ const ChatWindow = ({ id }: { id?: string }) => { added = true; } - setMessages((prev) => - prev.map((message) => { + setMessages(previous => + previous.map(message => { if (message.messageId === data.messageId) { return { ...message, content: message.content + data.data }; } @@ -357,52 +307,51 @@ const ChatWindow = ({ id }: { id?: string }) => { setMessageAppeared(true); } - if (data.type === 'messageEnd') { - setChatHistory((prevHistory) => [ - ...prevHistory, - ['human', message], - ['assistant', recievedMessage], - ]); + if (data.type === "messageEnd") { + setChatHistory(previousHistory => [...previousHistory, ["human", message], ["assistant", recievedMessage]]); - ws?.removeEventListener('message', messageHandler); + ws?.removeEventListener("message", messageHandler); setLoading(false); - const lastMsg = messagesRef.current[messagesRef.current.length - 1]; + const lastMessage = messagesReference.current.at(-1); if ( - lastMsg.role === 'assistant' && - lastMsg.sources && - lastMsg.sources.length > 0 && - !lastMsg.suggestions + lastMessage && + lastMessage.role === "assistant" && + lastMessage.sources && + lastMessage.sources.length > 0 && + !lastMessage.suggestions ) { - const suggestions = await getSuggestions(messagesRef.current); - setMessages((prev) => - prev.map((msg) => { - if (msg.messageId === lastMsg.messageId) { - return { ...msg, suggestions: suggestions }; + const suggestions = await getSuggestions(messagesReference.current); + setMessages(previous => + previous.map(message_ => { + if (message_.messageId === lastMessage.messageId) { + return { ...message_, suggestions: suggestions }; } - return msg; + return message_; }), ); } } }; - ws?.addEventListener('message', messageHandler); + ws?.addEventListener("message", messageHandler); }; const rewrite = (messageId: string) => { - const index = messages.findIndex((msg) => msg.messageId === messageId); + const index = messages.findIndex(message_ => message_.messageId === messageId); if (index === -1) return; const message = messages[index - 1]; - setMessages((prev) => { - return [...prev.slice(0, messages.length > 2 ? index - 1 : 0)]; + setMessages(previous => { + // eslint-disable-next-line unicorn/no-useless-spread + return [...previous.slice(0, messages.length > 2 ? index - 1 : 0)]; }); - setChatHistory((prev) => { - return [...prev.slice(0, messages.length > 2 ? index - 1 : 0)]; + setChatHistory(previous => { + // eslint-disable-next-line unicorn/no-useless-spread + return [...previous.slice(0, messages.length > 2 ? index - 1 : 0)]; }); sendMessage(message.content); @@ -442,11 +391,7 @@ const ChatWindow = ({ id }: { id?: string }) => { /> ) : ( - + )}
) diff --git a/ui/components/DeleteChat.tsx b/ui/components/DeleteChat.tsx index 165f86e3..a379d02a 100644 --- a/ui/components/DeleteChat.tsx +++ b/ui/components/DeleteChat.tsx @@ -1,8 +1,8 @@ -import { Delete, Trash } from 'lucide-react'; -import { Dialog, Transition } from '@headlessui/react'; -import { Fragment, useState } from 'react'; -import { toast } from 'sonner'; -import { Chat } from '@/app/library/page'; +import { Delete, Trash } from "lucide-react"; +import { Dialog, Transition } from "@headlessui/react"; +import { Fragment, useState } from "react"; +import { toast } from "sonner"; +import { Chat } from "@/app/library/page"; const DeleteChat = ({ chatId, @@ -19,25 +19,23 @@ const DeleteChat = ({ const handleDelete = async () => { setLoading(true); try { - const res = await fetch( - `${process.env.NEXT_PUBLIC_API_URL}/chats/${chatId}`, - { - method: 'DELETE', - headers: { - 'Content-Type': 'application/json', - }, + const res = await fetch(`${process.env.NEXT_PUBLIC_API_URL}/chats/${chatId}`, { + method: "DELETE", + headers: { + "Content-Type": "application/json", }, - ); + }); if (res.status != 200) { - throw new Error('Failed to delete chat'); + throw new Error("Failed to delete chat"); } - const newChats = chats.filter((chat) => chat.id !== chatId); + const newChats = chats.filter(chat => chat.id !== chatId); setChats(newChats); - } catch (err: any) { - toast.error(err.message); + // eslint-disable-next-line @typescript-eslint/no-explicit-any + } catch (error: any) { + toast.error(error.message); } finally { setConfirmationDialogOpen(false); setLoading(false); diff --git a/ui/components/EmptyChat.tsx b/ui/components/EmptyChat.tsx index ea3642b6..eac3f2c9 100644 --- a/ui/components/EmptyChat.tsx +++ b/ui/components/EmptyChat.tsx @@ -1,4 +1,4 @@ -import EmptyChatMessageInput from './EmptyChatMessageInput'; +import EmptyChatMessageInput from "./EmptyChatMessageInput"; const EmptyChat = ({ sendMessage, @@ -12,14 +12,8 @@ const EmptyChat = ({ return (
-

- Research begins here. -

- +

Research begins here.

+
); diff --git a/ui/components/EmptyChatMessageInput.tsx b/ui/components/EmptyChatMessageInput.tsx index 0ff9b2e3..052638c6 100644 --- a/ui/components/EmptyChatMessageInput.tsx +++ b/ui/components/EmptyChatMessageInput.tsx @@ -1,8 +1,8 @@ -import { ArrowRight } from 'lucide-react'; -import { useEffect, useRef, useState } from 'react'; -import TextareaAutosize from 'react-textarea-autosize'; -import CopilotToggle from './MessageInputActions/Copilot'; -import Focus from './MessageInputActions/Focus'; +import { ArrowRight } from "lucide-react"; +import { useEffect, useRef, useState } from "react"; +import TextareaAutosize from "react-textarea-autosize"; +import CopilotToggle from "./MessageInputActions/Copilot"; +import Focus from "./MessageInputActions/Focus"; const EmptyChatMessageInput = ({ sendMessage, @@ -14,46 +14,46 @@ const EmptyChatMessageInput = ({ setFocusMode: (mode: string) => void; }) => { const [copilotEnabled, setCopilotEnabled] = useState(false); - const [message, setMessage] = useState(''); + const [message, setMessage] = useState(""); - const inputRef = useRef(null); + const inputReference = useRef(null); const handleKeyDown = (e: KeyboardEvent) => { - if (e.key === '/') { + if (e.key === "/") { e.preventDefault(); - inputRef.current?.focus(); + inputReference.current?.focus(); } }; useEffect(() => { - document.addEventListener('keydown', handleKeyDown); + document.addEventListener("keydown", handleKeyDown); return () => { - document.removeEventListener('keydown', handleKeyDown); + document.removeEventListener("keydown", handleKeyDown); }; }, []); return (
{ + onSubmit={e => { e.preventDefault(); sendMessage(message); - setMessage(''); + setMessage(""); }} - onKeyDown={(e) => { - if (e.key === 'Enter' && !e.shiftKey) { + onKeyDown={e => { + if (e.key === "Enter" && !e.shiftKey) { e.preventDefault(); sendMessage(message); - setMessage(''); + setMessage(""); } }} className="w-full" >
setMessage(e.target.value)} + onChange={e => setMessage(e.target.value)} minRows={2} className="bg-transparent placeholder:text-black/50 dark:placeholder:text-white/50 text-sm text-black dark:text-white resize-none focus:outline-none w-full max-h-24 lg:max-h-36 xl:max-h-48" placeholder="Ask anything..." @@ -64,10 +64,7 @@ const EmptyChatMessageInput = ({ {/* */}
- +
@@ -145,7 +117,7 @@ const MessageBox = ({ {isLast && message.suggestions && message.suggestions.length > 0 && - message.role === 'assistant' && + message.role === "assistant" && !loading && ( <>
@@ -155,11 +127,8 @@ const MessageBox = ({

Related

- {message.suggestions.map((suggestion, i) => ( -
+ {message.suggestions.map((suggestion, index) => ( +
{ @@ -167,13 +136,8 @@ const MessageBox = ({ }} className="cursor-pointer flex flex-row justify-between font-medium space-x-2 items-center" > -

- {suggestion} -

- +

{suggestion}

+
))} @@ -184,14 +148,8 @@ const MessageBox = ({
- - + +
)} diff --git a/ui/components/MessageInput.tsx b/ui/components/MessageInput.tsx index 2229cdf3..75bc2932 100644 --- a/ui/components/MessageInput.tsx +++ b/ui/components/MessageInput.tsx @@ -1,84 +1,75 @@ -import { cn } from '@/lib/utils'; -import { ArrowUp } from 'lucide-react'; -import { useEffect, useRef, useState } from 'react'; -import TextareaAutosize from 'react-textarea-autosize'; -import Attach from './MessageInputActions/Attach'; -import CopilotToggle from './MessageInputActions/Copilot'; +import { cn } from "@/lib/utils"; +import { ArrowUp } from "lucide-react"; +import { useEffect, useRef, useState } from "react"; +import TextareaAutosize from "react-textarea-autosize"; +import Attach from "./MessageInputActions/Attach"; +import CopilotToggle from "./MessageInputActions/Copilot"; -const MessageInput = ({ - sendMessage, - loading, -}: { - sendMessage: (message: string) => void; - loading: boolean; -}) => { +const MessageInput = ({ sendMessage, loading }: { sendMessage: (message: string) => void; loading: boolean }) => { const [copilotEnabled, setCopilotEnabled] = useState(false); - const [message, setMessage] = useState(''); + const [message, setMessage] = useState(""); const [textareaRows, setTextareaRows] = useState(1); - const [mode, setMode] = useState<'multi' | 'single'>('single'); + const [mode, setMode] = useState<"multi" | "single">("single"); useEffect(() => { - if (textareaRows >= 2 && message && mode === 'single') { - setMode('multi'); - } else if (!message && mode === 'multi') { - setMode('single'); + if (textareaRows >= 2 && message && mode === "single") { + setMode("multi"); + } else if (!message && mode === "multi") { + setMode("single"); } }, [textareaRows, mode, message]); - const inputRef = useRef(null); + const inputReference = useRef(null); const handleKeyDown = (e: KeyboardEvent) => { - if (e.key === '/') { + if (e.key === "/") { e.preventDefault(); - inputRef.current?.focus(); + inputReference.current?.focus(); } }; useEffect(() => { - document.addEventListener('keydown', handleKeyDown); + document.addEventListener("keydown", handleKeyDown); return () => { - document.removeEventListener('keydown', handleKeyDown); + document.removeEventListener("keydown", handleKeyDown); }; }, []); return ( { + onSubmit={e => { if (loading) return; e.preventDefault(); sendMessage(message); - setMessage(''); + setMessage(""); }} - onKeyDown={(e) => { - if (e.key === 'Enter' && !e.shiftKey && !loading) { + onKeyDown={e => { + if (e.key === "Enter" && !e.shiftKey && !loading) { e.preventDefault(); sendMessage(message); - setMessage(''); + setMessage(""); } }} className={cn( - 'bg-light-secondary dark:bg-dark-secondary p-4 flex items-center overflow-hidden border border-light-200 dark:border-dark-200', - mode === 'multi' ? 'flex-col rounded-lg' : 'flex-row rounded-full', + "bg-light-secondary dark:bg-dark-secondary p-4 flex items-center overflow-hidden border border-light-200 dark:border-dark-200", + mode === "multi" ? "flex-col rounded-lg" : "flex-row rounded-full", )} > - {mode === 'single' && } + {mode === "single" && } setMessage(e.target.value)} - onHeightChange={(height, props) => { - setTextareaRows(Math.ceil(height / props.rowHeight)); + onChange={e => setMessage(e.target.value)} + onHeightChange={(height, properties) => { + setTextareaRows(Math.ceil(height / properties.rowHeight)); }} className="transition bg-transparent dark:placeholder:text-white/50 placeholder:text-sm text-sm dark:text-white resize-none focus:outline-none w-full px-2 max-h-24 lg:max-h-36 xl:max-h-48 flex-grow flex-shrink" placeholder="Ask a follow-up" /> - {mode === 'single' && ( + {mode === "single" && (
- +
)} - {mode === 'multi' && ( + {mode === "multi" && (
- + )} @@ -84,16 +82,15 @@ const MessageSources = ({ sources }: { sources: Document[] }) => { leaveTo="opacity-0 scale-95" > - - Sources - + Sources
- {i + 1} + {index + 1}
diff --git a/ui/components/Navbar.tsx b/ui/components/Navbar.tsx index 020dfb4f..be89b7bc 100644 --- a/ui/components/Navbar.tsx +++ b/ui/components/Navbar.tsx @@ -1,23 +1,18 @@ -import { Clock, Edit, Share, Trash } from 'lucide-react'; -import { Message } from './ChatWindow'; -import { useEffect, useState } from 'react'; -import { formatTimeDifference } from '@/lib/utils'; +import { Clock, Edit, Share, Trash } from "lucide-react"; +import { Message } from "./ChatWindow"; +import { useEffect, useState } from "react"; +import { formatTimeDifference } from "@/lib/utils"; const Navbar = ({ messages }: { messages: Message[] }) => { - const [title, setTitle] = useState(''); - const [timeAgo, setTimeAgo] = useState(''); + const [title, setTitle] = useState(""); + const [timeAgo, setTimeAgo] = useState(""); useEffect(() => { if (messages.length > 0) { const newTitle = - messages[0].content.length > 20 - ? `${messages[0].content.substring(0, 20).trim()}...` - : messages[0].content; + messages[0].content.length > 20 ? `${messages[0].content.slice(0, 20).trim()}...` : messages[0].content; setTitle(newTitle); - const newTimeAgo = formatTimeDifference( - new Date(), - messages[0].createdAt, - ); + const newTimeAgo = formatTimeDifference(new Date(), messages[0].createdAt); setTimeAgo(newTimeAgo); } }, [messages]); @@ -25,10 +20,7 @@ const Navbar = ({ messages }: { messages: Message[] }) => { useEffect(() => { const intervalId = setInterval(() => { if (messages.length > 0) { - const newTimeAgo = formatTimeDifference( - new Date(), - messages[0].createdAt, - ); + const newTimeAgo = formatTimeDifference(new Date(), messages[0].createdAt); setTimeAgo(newTimeAgo); } }, 1000); @@ -39,10 +31,7 @@ const Navbar = ({ messages }: { messages: Message[] }) => { return (
- +

{timeAgo} ago

@@ -50,14 +39,8 @@ const Navbar = ({ messages }: { messages: Message[] }) => {

{title}

- - + +
); diff --git a/ui/components/NewsDetailPage/ContextItem.tsx b/ui/components/NewsDetailPage/ContextItem.tsx new file mode 100644 index 00000000..a3b6beb7 --- /dev/null +++ b/ui/components/NewsDetailPage/ContextItem.tsx @@ -0,0 +1,86 @@ +import React, { useState, useEffect } from "react"; +import Image from "next/image"; +import { ReactMarkdown } from "@/components/Markdown"; +import PreviewNewsDetail from "./PreviewNewsDetail"; + +interface ContextItemProperties { + item: { + name: string; + url: string; + description: string; + provider: { + name: string; + image?: { + thumbnail: { + contentUrl: string; + }; + }; + }[]; + datePublished: string; + image?: { + contentUrl: string; + thumbnail: { contentUrl: string; width: number; height: number }; + }; + article?: string; + score?: number; + }; +} + +const ProviderInfo: React.FC<{ name: string; date: string }> = ({ name, date }) => ( +
+
+ {name} + {date} +
+
+); + +const ContextItem: React.FC = ({ item }) => { + const [isPreviewVisible, setIsPreviewVisible] = useState(false); + + const togglePreview = () => { + setIsPreviewVisible(!isPreviewVisible); + }; + + return ( + <> +
+
+ {item.image ? ( + {item.name} + ) : ( + {"placeholder"} + )} +
+
+
+

{item.name}

+
+
+ +
+ +
+
+ + {isPreviewVisible && } + + ); +}; + +export default ContextItem; diff --git a/ui/components/NewsDetailPage/ExpandableItems.tsx b/ui/components/NewsDetailPage/ExpandableItems.tsx new file mode 100644 index 00000000..783d26c3 --- /dev/null +++ b/ui/components/NewsDetailPage/ExpandableItems.tsx @@ -0,0 +1,62 @@ +"use client"; +import React, { useState } from "react"; +import ContextItem from "./ContextItem"; + +interface ContextItemType { + name: string; + url: string; + description: string; + provider: { + name: string; + image?: { + thumbnail: { + contentUrl: string; + }; + }; + }[]; + datePublished: string; + image?: { + contentUrl: string; + thumbnail: { + contentUrl: string; + width: number; + height: number; + }; + }; + article?: string; + score?: number; +} + +interface ExpandableItemsProperties { + context: ContextItemType[]; +} + +const ExpandableItems: React.FC = ({ context }) => { + const [expanded, setExpanded] = useState(false); + + const handleShowMore = () => { + setExpanded(!expanded); + }; + + return ( +
+ +
+ +
+ {expanded && + context.slice(1).map((item, index) => ( +
+ +
+ ))} +
+ ); +}; + +export default ExpandableItems; diff --git a/ui/components/NewsDetailPage/NewsDetail.tsx b/ui/components/NewsDetailPage/NewsDetail.tsx new file mode 100644 index 00000000..be6173eb --- /dev/null +++ b/ui/components/NewsDetailPage/NewsDetail.tsx @@ -0,0 +1,58 @@ +import React from "react"; +import ContextItem from "./ContextItem"; +import ExpandableItems from "./ExpandableItems"; +interface ContextItemType { + name: string; + url: string; + description: string; + provider: { + name: string; + image?: { + thumbnail: { + contentUrl: string; + }; + }; + }[]; + datePublished: string; + image?: { + contentUrl: string; + thumbnail: { + contentUrl: string; + width: number; + height: number; + }; + }; + article?: string; + score?: number; +} + +interface NewsDetailProperties { + news: { + title: string; + sections: { + title: string; + content: string; + context: ContextItemType[]; + }[]; + }; +} + +const NewsDetail: React.FC = ({ news }) => { + return ( +
+

{news.title}

+ {news.sections.map((section, index) => ( +
+

{section.title}

+

{section.content}

+
+

Related Context:

+ +
+
+ ))} +
+ ); +}; + +export default NewsDetail; diff --git a/ui/components/NewsDetailPage/PreviewNewsDetail.tsx b/ui/components/NewsDetailPage/PreviewNewsDetail.tsx new file mode 100644 index 00000000..c51fd43f --- /dev/null +++ b/ui/components/NewsDetailPage/PreviewNewsDetail.tsx @@ -0,0 +1,53 @@ +import React from "react"; +import Image from "next/image"; +import { ReactMarkdown } from "@/components/Markdown"; + +interface ContextItemProperties { + item: { + name: string; + url: string; + description: string; + provider: { + name: string; + image?: { + thumbnail: { + contentUrl: string; + }; + }; + }[]; + datePublished: string; + image?: { + contentUrl: string; + thumbnail: { contentUrl: string; width: number; height: number }; + }; + article?: string; + score?: number; + }; + togglePreview: () => void; // Add togglePreview prop +} + +const PreviewNewsDetail: React.FC = ({ item, togglePreview = () => {} }) => { + return ( +
+
+
+

{item.name}

+ +
+ + + Visit + +
+
+ ); +}; + +export default PreviewNewsDetail; diff --git a/ui/components/NewsPage.tsx b/ui/components/NewsPage.tsx new file mode 100644 index 00000000..50a72158 --- /dev/null +++ b/ui/components/NewsPage.tsx @@ -0,0 +1,99 @@ +"use client"; + +import { useEffect, useState } from "react"; +import { Newspaper } from "lucide-react"; +import Link from "next/link"; + +interface NewsItem { + id: string; + title: string; + summary: string; + image: string; +} + +const NewsPage = () => { + const [news, setNews] = useState([]); + const [loading, setLoading] = useState(true); + const [error, setError] = useState(null); + + useEffect(() => { + const fetchNews = async () => { + try { + console.log("Fetching news..."); + const response = await fetch("/api/news"); + console.log("Response status:", response.status); + if (!response.ok) { + throw new Error(`HTTP error! status: ${response.status}`); + } + const data = await response.json(); + console.log("Fetched data:", data); + setNews(data); + } catch (error) { + console.error("Error fetching news:", error); + setError(`Failed to load news. Error: ${error instanceof Error ? error.message : String(error)}`); + } finally { + setLoading(false); + } + }; + + fetchNews(); + }, []); + + const renderContent = () => { + if (loading) { + return ( +
+

Loading news...

+
+ ); + } + + if (error) { + return ( +
+

Failed to load news.

+

{error}

+
+ ); + } + + if (news.length === 0) { + return

No news available.

; + } + return ( +
+ {news.map(item => ( +
+ {/* Large and Small Responsive Screen Layout */} + + {item.title} +
+

{item.title}

+

+ {item.summary} +

+
+ +
+ ))} +
+ ); + }; + + return ( +
+
+
+ +

News

+
+
+ {renderContent()} +
+ ); +}; + +export default NewsPage; diff --git a/ui/components/SearchImages.tsx b/ui/components/SearchImages.tsx index b53b8b0b..404c5880 100644 --- a/ui/components/SearchImages.tsx +++ b/ui/components/SearchImages.tsx @@ -1,9 +1,8 @@ -/* eslint-disable @next/next/no-img-element */ -import { ImagesIcon, PlusIcon } from 'lucide-react'; -import { useState } from 'react'; -import Lightbox from 'yet-another-react-lightbox'; -import 'yet-another-react-lightbox/styles.css'; -import { Message } from './ChatWindow'; +import { ImagesIcon, PlusIcon } from "lucide-react"; +import { useState } from "react"; +import Lightbox from "yet-another-react-lightbox"; +import "yet-another-react-lightbox/styles.css"; +import { Message } from "./ChatWindow"; type Image = { url: string; @@ -11,16 +10,11 @@ type Image = { title: string; }; -const SearchImages = ({ - query, - chat_history, -}: { - query: string; - chat_history: Message[]; -}) => { +const SearchImages = ({ query, chat_history }: { query: string; chat_history: Message[] }) => { const [images, setImages] = useState(null); const [loading, setLoading] = useState(false); const [open, setOpen] = useState(false); + // eslint-disable-next-line @typescript-eslint/no-explicit-any const [slides, setSlides] = useState([]); return ( @@ -30,24 +24,21 @@ const SearchImages = ({ onClick={async () => { setLoading(true); - const chatModelProvider = localStorage.getItem('chatModelProvider'); - const chatModel = localStorage.getItem('chatModel'); + const chatModelProvider = localStorage.getItem("chatModelProvider"); + const chatModel = localStorage.getItem("chatModel"); - const res = await fetch( - `${process.env.NEXT_PUBLIC_API_URL}/images`, - { - method: 'POST', - headers: { - 'Content-Type': 'application/json', - }, - body: JSON.stringify({ - query: query, - chat_history: chat_history, - chat_model_provider: chatModelProvider, - chat_model: chatModel, - }), + const res = await fetch(`${process.env.NEXT_PUBLIC_API_URL}/images`, { + method: "POST", + headers: { + "Content-Type": "application/json", }, - ); + body: JSON.stringify({ + query: query, + chat_history: chat_history, + chat_model_provider: chatModelProvider, + chat_model: chatModel, + }), + }); const data = await res.json(); @@ -73,9 +64,9 @@ const SearchImages = ({ )} {loading && (
- {[...Array(4)].map((_, i) => ( + {Array.from({ length: 4 }).map((_, index) => (
))} @@ -85,33 +76,25 @@ const SearchImages = ({ <>
{images.length > 4 - ? images.slice(0, 3).map((image, i) => ( + ? images.slice(0, 3).map((image, index) => ( { setOpen(true); - setSlides([ - slides[i], - ...slides.slice(0, i), - ...slides.slice(i + 1), - ]); + setSlides([slides[index], ...slides.slice(0, index), ...slides.slice(index + 1)]); }} - key={i} + key={index} src={image.img_src} alt={image.title} className="h-full w-full aspect-video object-cover rounded-lg transition duration-200 active:scale-95 hover:scale-[1.02] cursor-zoom-in" /> )) - : images.map((image, i) => ( + : images.map((image, index) => ( { setOpen(true); - setSlides([ - slides[i], - ...slides.slice(0, i), - ...slides.slice(i + 1), - ]); + setSlides([slides[index], ...slides.slice(0, index), ...slides.slice(index + 1)]); }} - key={i} + key={index} src={image.img_src} alt={image.title} className="h-full w-full aspect-video object-cover rounded-lg transition duration-200 active:scale-95 hover:scale-[1.02] cursor-zoom-in" @@ -123,18 +106,16 @@ const SearchImages = ({ className="bg-light-100 hover:bg-light-200 dark:bg-dark-100 dark:hover:bg-dark-200 transition duration-200 active:scale-95 hover:scale-[1.02] h-auto w-full rounded-lg flex flex-col justify-between text-white p-2" >
- {images.slice(3, 6).map((image, i) => ( + {images.slice(3, 6).map((image, index) => ( {image.title} ))}
-

- View {images.length - 3} more -

+

View {images.length - 3} more

)}
diff --git a/ui/components/SearchVideos.tsx b/ui/components/SearchVideos.tsx index 26463228..81e821d9 100644 --- a/ui/components/SearchVideos.tsx +++ b/ui/components/SearchVideos.tsx @@ -1,9 +1,8 @@ -/* eslint-disable @next/next/no-img-element */ -import { PlayCircle, PlayIcon, PlusIcon, VideoIcon } from 'lucide-react'; -import { useState } from 'react'; -import Lightbox, { GenericSlide, VideoSlide } from 'yet-another-react-lightbox'; -import 'yet-another-react-lightbox/styles.css'; -import { Message } from './ChatWindow'; +import { PlayCircle, PlayIcon, PlusIcon, VideoIcon } from "lucide-react"; +import { useState } from "react"; +import Lightbox, { GenericSlide, VideoSlide } from "yet-another-react-lightbox"; +import "yet-another-react-lightbox/styles.css"; +import { Message } from "./ChatWindow"; type Video = { url: string; @@ -12,25 +11,19 @@ type Video = { iframe_src: string; }; -declare module 'yet-another-react-lightbox' { +declare module "yet-another-react-lightbox" { export interface VideoSlide extends GenericSlide { - type: 'video-slide'; + type: "video-slide"; src: string; iframe_src: string; } interface SlideTypes { - 'video-slide': VideoSlide; + "video-slide": VideoSlide; } } -const Searchvideos = ({ - query, - chat_history, -}: { - query: string; - chat_history: Message[]; -}) => { +const Searchvideos = ({ query, chat_history }: { query: string; chat_history: Message[] }) => { const [videos, setVideos] = useState(null); const [loading, setLoading] = useState(false); const [open, setOpen] = useState(false); @@ -43,24 +36,21 @@ const Searchvideos = ({ onClick={async () => { setLoading(true); - const chatModelProvider = localStorage.getItem('chatModelProvider'); - const chatModel = localStorage.getItem('chatModel'); + const chatModelProvider = localStorage.getItem("chatModelProvider"); + const chatModel = localStorage.getItem("chatModel"); - const res = await fetch( - `${process.env.NEXT_PUBLIC_API_URL}/videos`, - { - method: 'POST', - headers: { - 'Content-Type': 'application/json', - }, - body: JSON.stringify({ - query: query, - chat_history: chat_history, - chat_model_provider: chatModelProvider, - chat_model: chatModel, - }), + const res = await fetch(`${process.env.NEXT_PUBLIC_API_URL}/videos`, { + method: "POST", + headers: { + "Content-Type": "application/json", }, - ); + body: JSON.stringify({ + query: query, + chat_history: chat_history, + chat_model_provider: chatModelProvider, + chat_model: chatModel, + }), + }); const data = await res.json(); @@ -69,7 +59,7 @@ const Searchvideos = ({ setSlides( videos.map((video: Video) => { return { - type: 'video-slide', + type: "video-slide", iframe_src: video.iframe_src, src: video.img_src, }; @@ -88,9 +78,9 @@ const Searchvideos = ({ )} {loading && (
- {[...Array(4)].map((_, i) => ( + {Array.from({ length: 4 }).map((_, index) => (
))} @@ -100,18 +90,14 @@ const Searchvideos = ({ <>
{videos.length > 4 - ? videos.slice(0, 3).map((video, i) => ( + ? videos.slice(0, 3).map((video, index) => (
{ setOpen(true); - setSlides([ - slides[i], - ...slides.slice(0, i), - ...slides.slice(i + 1), - ]); + setSlides([slides[index], ...slides.slice(0, index), ...slides.slice(index + 1)]); }} className="relative transition duration-200 active:scale-95 hover:scale-[1.02] cursor-pointer" - key={i} + key={index} >
)) - : videos.map((video, i) => ( + : videos.map((video, index) => (
{ setOpen(true); - setSlides([ - slides[i], - ...slides.slice(0, i), - ...slides.slice(i + 1), - ]); + setSlides([slides[index], ...slides.slice(0, index), ...slides.slice(index + 1)]); }} className="relative transition duration-200 active:scale-95 hover:scale-[1.02] cursor-pointer" - key={i} + key={index} >
- {videos.slice(3, 6).map((video, i) => ( + {videos.slice(3, 6).map((video, index) => ( {video.title} ))}
-

- View {videos.length - 3} more -

+

View {videos.length - 3} more

)}
@@ -175,7 +155,7 @@ const Searchvideos = ({ slides={slides} render={{ slide: ({ slide }) => - slide.type === 'video-slide' ? ( + slide.type === "video-slide" ? (