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from '@builderbot/bot'\nimport { MemoryDB as Database } from '@builderbot/bot'\nimport { TelegramProvider as Provider } from \"@builderbot-plugins/telegram\"\n\nimport z from \"zod\"\nimport { createAIFlow } from \"./src/index\"\n\nimport { OramaClient } from '@oramacloud/client' \nimport { Product } from \"./src/types\"\n\nconst client = new OramaClient({ \n endpoint: 'https://cloud.orama.run/v1/indexes/my-shopify-irxv20', \n api_key: 'YOUR-ORAMA-API-KEY' \n }) \n\nconst aiflow = createAIFlow\n .setKeyword(EVENTS.WELCOME)\n .setAIModel({ modelName: 'openai' })\n .pipe(({ addAnswer }) => {\n return addAnswer('Hola!, dejame buscar entre el stock...')\n })\n .setCatchLayer(z.object({ \n intention: z.enum(['SALES']).describe(`La intención del cliente:\n SALES: Si el cliente pregunta, quiere informacion o esta interesado en uno o mas productos\n \n `)\n }), async (ctx, { endFlow }) => {\n console.log(ctx?.schema)\n if (ctx?.schema) {\n const { intention } = ctx.schema\n \n if (intention !== 'SALES') {\n return endFlow('Lo siento, Intenta preguntando sobre un producto')\n }\n }\n })\n .setTransformLayer(\n z.object({\n product_name: z.string().describe('El producto que busca el cliente'),\n }),\n async (ctx) => {\n console.log({ details: ctx?.context })\n }\n )\n .setStore({\n searchFn: async (term) => {\n if (typeof term === 'object') {\n term = Object.values(term).join(' ')\n }else if (Array.isArray(term)) {\n term = term.join(' ')\n }\n\n const { hits } = await client.search({ term, limit: 7 }) as any\n const products = hits.map(hit => hit.document) as Product[]\n\n const mapProducts = products.map(({ \n title,\n variants,\n priceRange,\n options,\n description, \n featuredImage, }) => ({\n product_description: description,\n product_image: featuredImage.url,\n product_name: title,\n // product_variants: variants\n // .map(({ price, selectedOptions }) => ({ price, options: selectedOptions })),\n product_price: priceRange.min,\n // product_options: options,\n }))\n\n return mapProducts\n }\n })\n .createRunnable({\n answerSchema: z.object({\n answer: z\n .string()\n .describe('Agrega una respuesta breve y clara sobre el producto.'),\n metadata: z.array(z.object({\n product_image: z.string()\n .describe('La url de la imagen del producto'),\n product_name: z\n .string()\n .describe(\"Nombre exacto del producto (SIN ALTERAR) que pregunta el cliente debe venir del contexto.\"),\n product_price: z\n .string()\n .describe(\n \"precio exacto del producto (SIN ALTERAR) que pregunta el cliente debe venir del contexto.\"\n ),\n product_description: z\n .string()\n .describe(\n \"Dale un breve pitch de venta a la descripcion del producto indica beneficios y caracteristicas (SIN ALTERAR) que pregunta el cliente debe venir del contexto.\"\n )\n }))\n .nullable().default([])\n .describe('Dado los siguientes productos, estructura los que tengan relación con la busqueda')\n }).describe('El formato de respuesta debe ser el siguiente')\n }, {\n onFailure: (err) => {\n console.log({ err })\n }\n })\n .pipe(({ addAction }) => {\n return addAction(async (_, { state, endFlow }) => {\n const answer = state.get('answer')\n console.log('answer', answer)\n if (!answer?.metadata?.length) {\n return endFlow('Lo siento, Intenta preguntando sobre otro producto')\n }\n\n await state.update({ purchase: answer.metadata })\n })\n .addAction(async (_, { state, flowDynamic }) => {\n const purchase = state.get('purchase')\n\n const template = purchase.map((p: any, i: number) => `${i+1}. ${p.product_name}\\nPrecio: $${p.product_price} c/u`).join('\\n\\n')\n\n await flowDynamic(`Estos son algunos de nuestros productos: \\n\\n ${template}`, { delay: 700 })\n flowDynamic(`Indicame cual deseas ver, ${Array.from({ length: purchase.length}, (_, i) => i + 1).join(' o ')}`)\n })\n .addAction({ capture: true }, async (ctx, { state, flowDynamic }) => {\n const purchase = state.get('purchase') as Array\n\n const product = purchase.at(Number(ctx.body) -1)\n await state.update({ product })\n flowDynamic([\n {\n body: `${product.product_name} - $${product.product_price} c/u\\n\\n${product.product_description}`,\n media: product.product_image\n }\n ])\n })\n .addAnswer('¿Deseas comprar el producto (SI / NO)?')\n })\n .setCatchLayer(z.object({\n intention: z.enum(['SI', 'NO']).describe('Repuesta del ususario')\n }), async (ctx, { endFlow, state, flowDynamic }) => {\n const product = state.get('product') as any\n if (ctx?.schema?.intention !== 'SI') {\n return endFlow('Estare acá por si deseas preguntar sobre otro producto')\n }\n\n const sc = [\n { \n name: product?.product_name,\n price: product?.product_price\n }\n ] \n if (state.getMyState()?.sc?.length) {\n await state.update({\n sc: [\n ...state.getMyState()?.sc,\n // @ts-ignore\n { \n name: product?.product_name,\n price: product?.product_price\n }\n ]\n })\n } else {\n // @ts-ignore\n await state.update({ \n sc\n })\n }\n\n const products = sc.map((p) => `${product.product_name.trim()} $${product.product_price} c/u\\n`).join('\\n')\n const total = sc.map(p => Number(product.product_price)).reduce((a, b) => Math.abs(a + b))\n const template = `Tu compra es:\\n${products}\\nTotal: $${total} dolares.`\n\n await flowDynamic(template)\n\n return endFlow()\n },true)\n .createFlow()\n\nconst main = async () => {\n \n const PORT = process.env.PORT ?? 3008\n const adapterFlow = createFlow([aiflow])\n\n const adapterProvider = createProvider(Provider)\n adapterProvider.on('message', (ctx) => console.log('new message', ctx.body))\n const adapterDB = new Database()\n\n const { httpServer, handleCtx } = await createBot({\n flow: adapterFlow,\n provider: adapterProvider,\n database: adapterDB,\n })\n httpServer(+PORT)\n\n\n adapterProvider.server.post(\n '/v1/loyalty',\n handleCtx(async (bot, req, res) => {\n const { number, name } = req.body\n await bot?.dispatch('L0Y4LTY', { from: number, name })\n return res.end('trigger')\n })\n )\n \n}\n\nmain()\n\n```","readmeFilename":"README.md","gitHead":"39fbdc2204362534dbdb5e8fbbbffeeb79136cf4","_nodeVersion":"20.10.0","_npmVersion":"10.2.3","dist":{"integrity":"sha512-6OJpv6lsvkprdjpG0hltiA03gxk8sUOz46NWMl5EjxqrSB6pdUfnoj1VP9r++diUK9RcFHwFDxTe3H41wKCzHg==","shasum":"0fc190806589aef40f8808348ef03c4c1c06b4f0","tarball":"https://registry.npmjs.org/@elimeleth/builderbot-langchain/-/builderbot-langchain-1.2.0-alpha.0.tgz","fileCount":59,"unpackedSize":78758,"signatures":[{"keyid":"SHA256:jl3bwswu80PjjokCgh0o2w5c2U4LhQAE57gj9cz1kzA","sig":"MEQCIHenjSMztx3+X6rj6un/e3K/wZbPjZ1E7oPok/C0WbKiAiAO185YQSvZ8G0QZgZPzA8/BvKA6AzpzdZVyM0pQuZsUw=="}]},"_npmUser":{"name":"elimeleth","email":"juancapuanolopez@gmail.com"},"directories":{},"maintainers":[{"name":"elimeleth","email":"juancapuanolopez@gmail.com"}],"_npmOperationalInternal":{"host":"s3://npm-registry-packages","tmp":"tmp/builderbot-langchain_1.2.0-alpha.0_1713217714262_0.45330338605032217"},"_hasShrinkwrap":false},"1.3.1-alpha.1":{"name":"@elimeleth/builderbot-langchain","version":"1.3.1-alpha.1","description":"Interface 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pack"},"dependencies":{"@builderbot-plugins/fast-embedding":"1.0.0-alpha.0","@builderbot/bot":"1.1.0","@langchain/cloudflare":"^0.0.4","@langchain/community":"^0.0.47","@langchain/core":"^0.1.57","@langchain/google-genai":"^0.0.11","@langchain/openai":"^0.0.28","@oramacloud/client":"^1.0.14","axios":"^1.6.8","d3-dsv":"2","dotenv":"^16.4.5","hnswlib-node":"^3.0.0","langchain":"^0.1.33","pdf-parse":"^1.1.1","tslib":"^2.6.2","zod":"^3.22.4"},"devDependencies":{"@builderbot-plugins/telegram":"2.0.11-alpha.0","@jest/globals":"29.7.0","@rollup/plugin-commonjs":"25.0.7","@rollup/plugin-node-resolve":"15.2.3","@types/node":"^20.12.5","@typescript-eslint/eslint-plugin":"^6.21.0","@typescript-eslint/parser":"^6.21.0","rimraf":"5.0.5","rollup-plugin-typescript2":"0.36.0","tsm":"^2.3.0","typescript":"^5.4.4"},"_id":"@elimeleth/builderbot-langchain@1.3.1-alpha.1","readme":"\nThis is a mockup with a shopify store client and Orama retriever\n\n```ts\nimport \"dotenv/config\"\nimport { createBot, createProvider, createFlow, EVENTS } from '@builderbot/bot'\nimport { MemoryDB as Database } from '@builderbot/bot'\nimport { TelegramProvider as Provider } from \"@builderbot-plugins/telegram\"\n\nimport z from \"zod\"\nimport { createAIFlow } from \"./src/index\"\n\nimport { OramaClient } from '@oramacloud/client' \nimport { Product } from \"./src/types\"\n\nconst client = new OramaClient({ \n endpoint: 'https://cloud.orama.run/v1/indexes/my-shopify-irxv20', \n api_key: 'YOUR-ORAMA-API-KEY' \n }) \n\nconst aiflow = createAIFlow\n .setKeyword(EVENTS.WELCOME)\n .pipe(({ addAnswer }) => {\n return addAnswer('Hola!, dejame buscar entre el stock...')\n })\n .setStructuredLayer(z.object({ \n intention: z.enum(['SALES']).describe(`La intención del cliente:\n SALES: Si el cliente pregunta, quiere informacion o esta interesado en uno o mas productos\n \n `)\n }), async (ctx, { endFlow }) => {\n console.log(ctx?.schema)\n if (ctx?.schema) {\n const { intention } = ctx.schema\n \n if (intention !== 'SALES') {\n return endFlow('Lo siento, Intenta preguntando sobre un producto')\n }\n }\n })\n .setContextLayer(\n z.object({\n product_name: z.string().describe('El producto que busca el cliente'),\n }),\n async (ctx) => {\n console.log({ details: ctx?.context })\n }\n )\n .setStore({\n searchFn: async (term) => {\n console.log({ term })\n\n const { hits } = await client.search({ term, limit: 7 }) as any\n const products = hits.map(hit => hit.document) as Product[]\n\n const mapProducts = products.map(({ \n title,\n variants,\n priceRange,\n options,\n description, \n featuredImage, }) => ({\n product_description: description,\n product_image: featuredImage.url,\n product_name: title,\n // product_variants: variants\n // .map(({ price, selectedOptions }) => ({ price, options: selectedOptions })),\n product_price: priceRange.min,\n // product_options: options,\n }))\n\n return mapProducts\n }\n })\n .createRunnable({\n answerSchema: z.object({\n answer: z\n .string()\n .describe('Agrega una respuesta breve y clara sobre el producto.'),\n metadata: z.array(z.object({\n product_image: z.string()\n .describe('La url de la imagen del producto'),\n product_name: z\n .string()\n .describe(\"Nombre exacto del producto (SIN ALTERAR) que pregunta el cliente debe venir del contexto.\"),\n product_price: z\n .string()\n .describe(\n \"precio exacto del producto (SIN ALTERAR) que pregunta el cliente debe venir del contexto.\"\n ),\n product_description: z\n .string()\n .describe(\n \"Dale un breve pitch de venta a la descripcion del producto indica beneficios y caracteristicas (SIN ALTERAR) que pregunta el cliente debe venir del contexto.\"\n )\n }))\n .nullable().default([])\n .describe('Dado los siguientes productos, estructura los que tengan relación con la busqueda')\n }).describe('El formato de respuesta debe ser el siguiente')\n }, {\n onFailure: (err) => {\n console.log({ err })\n }\n })\n .pipe(({ addAction }) => {\n return addAction(async (_, { state, endFlow }) => {\n const answer = state.get('answer')\n console.log('answer', answer)\n if (!answer?.metadata?.length) {\n return endFlow('Lo siento, Intenta preguntando sobre otro producto')\n }\n\n await state.update({ purchase: answer.metadata })\n })\n .addAction(async (_, { state, flowDynamic }) => {\n const purchase = state.get('purchase')\n\n const template = purchase.map((p: any, i: number) => `${i+1}. ${p.product_name}\\nPrecio: $${p.product_price} c/u`).join('\\n\\n')\n\n await flowDynamic(`Estos son algunos de nuestros productos: \\n\\n ${template}`, { delay: 700 })\n flowDynamic(`Indicame cual deseas ver, ${Array.from({ length: purchase.length}, (_, i) => i + 1).join(' o ')}`)\n })\n .addAction({ capture: true }, async (ctx, { state, flowDynamic }) => {\n const purchase = state.get('purchase') as Array\n\n const product = purchase.at(Number(ctx.body) -1)\n await state.update({ product })\n flowDynamic([\n {\n body: `${product.product_name} - $${product.product_price} c/u\\n\\n${product.product_description}`,\n media: product.product_image\n }\n ])\n })\n .addAnswer('¿Deseas comprar el producto (SI / NO)?')\n })\n .setStructuredLayer(z.object({\n intention: z.enum(['SI', 'NO']).describe('Repuesta del ususario')\n }), async (ctx, { endFlow, state, flowDynamic }) => {\n const product = state.get('product') as any\n if (ctx?.schema?.intention !== 'SI') {\n return endFlow('Estare acá por si deseas preguntar sobre otro producto')\n }\n\n const sc = [\n { \n name: product?.product_name,\n price: product?.product_price\n }\n ] \n if (state.getMyState()?.sc?.length) {\n await state.update({\n sc: [\n ...state.getMyState()?.sc,\n // @ts-ignore\n { \n name: product?.product_name,\n price: product?.product_price\n }\n ]\n })\n } else {\n // @ts-ignore\n await state.update({ \n sc\n })\n }\n\n const products = sc.map((p) => `${product.product_name.trim()} $${product.product_price} c/u\\n`).join('\\n')\n const total = sc.map(p => Number(product.product_price)).reduce((a, b) => Math.abs(a + b))\n const template = `Tu compra es:\\n${products}\\nTotal: $${total} dolares.`\n\n await flowDynamic(template)\n\n return endFlow()\n }, { capture: true })\n .createFlow()\n\nconst main = async () => {\n \n const PORT = process.env.PORT ?? 3008\n const adapterFlow = createFlow([aiflow])\n\n const adapterProvider = createProvider(Provider)\n adapterProvider.on('message', (ctx) => console.log('new message', ctx.body))\n const adapterDB = new Database()\n\n const { httpServer, handleCtx } = await createBot({\n flow: adapterFlow,\n provider: adapterProvider,\n database: adapterDB,\n })\n httpServer(+PORT)\n\n\n adapterProvider.server.post(\n '/v1/loyalty',\n handleCtx(async (bot, req, res) => {\n const { number, name } = req.body\n await bot?.dispatch('L0Y4LTY', { from: number, name })\n return res.end('trigger')\n })\n )\n \n}\n\nmain()\n\n```","readmeFilename":"README.md","gitHead":"e79dd31a2306e981cea5834d381b4238e9797bc4","_nodeVersion":"20.10.0","_npmVersion":"10.2.3","dist":{"integrity":"sha512-kKlC+QyEnL6bEorx/9aYBpM16SVjwFvG+W+t9wPJkjqjAqY0XIJRbevonEeR87bl/vfCUn+J8hbUsUNbruZVXQ==","shasum":"3709ef1bece2391a51a676ea13e7713865c6fbf7","tarball":"https://registry.npmjs.org/@elimeleth/builderbot-langchain/-/builderbot-langchain-1.3.1-alpha.1.tgz","fileCount":62,"unpackedSize":82085,"signatures":[{"keyid":"SHA256:jl3bwswu80PjjokCgh0o2w5c2U4LhQAE57gj9cz1kzA","sig":"MEUCIQC/itWiUhC3sgZ8edF4jxGRHIJkzukJS6EW9YILESpQVgIgXZv/VQzFU1KKOdZC6JPD5LNpeAZ2v+U3urtv7isVlEA="}]},"_npmUser":{"name":"elimeleth","email":"juancapuanolopez@gmail.com"},"directories":{},"maintainers":[{"name":"elimeleth","email":"juancapuanolopez@gmail.com"}],"_npmOperationalInternal":{"host":"s3://npm-registry-packages","tmp":"tmp/builderbot-langchain_1.3.1-alpha.1_1713282091599_0.2271380928863378"},"_hasShrinkwrap":false},"1.3.2-alpha.1":{"name":"@elimeleth/builderbot-langchain","version":"1.3.2-alpha.1","description":"Interface para crear chatbot con Builderbot & LangChain","main":"dist/index.cjs","types":"dist/index.d.ts","type":"module","keywords":["chatbot","builderbot","langchain","whatsapp","telegram"],"author":{"name":"Elimeleth Capuano","email":"elimeleth.contacto@gmail.com"},"scripts":{"test":"jest","build":"rimraf dist && npx rollup --config","dev":"tsm src/index.ts","start":"pnpm run build && node dist/index.cjs","local:build":"pnpm run build && npm pack"},"dependencies":{"@builderbot-plugins/fast-embedding":"1.0.0-alpha.0","@builderbot/bot":"1.1.0","@langchain/cloudflare":"^0.0.4","@langchain/community":"^0.0.47","@langchain/core":"^0.1.57","@langchain/google-genai":"^0.0.11","@langchain/openai":"^0.0.28","@oramacloud/client":"^1.0.14","axios":"^1.6.8","d3-dsv":"2","dotenv":"^16.4.5","hnswlib-node":"^3.0.0","langchain":"^0.1.33","pdf-parse":"^1.1.1","tslib":"^2.6.2","zod":"^3.22.4"},"devDependencies":{"@builderbot-plugins/telegram":"2.0.11-alpha.0","@jest/globals":"29.7.0","@rollup/plugin-commonjs":"25.0.7","@rollup/plugin-node-resolve":"15.2.3","@types/node":"^20.12.5","@typescript-eslint/eslint-plugin":"^6.21.0","@typescript-eslint/parser":"^6.21.0","rimraf":"5.0.5","rollup-plugin-typescript2":"0.36.0","tsm":"^2.3.0","typescript":"^5.4.4"},"_id":"@elimeleth/builderbot-langchain@1.3.2-alpha.1","readme":"\nThis is a mockup with a shopify store client and Orama retriever\n\n```ts\nimport \"dotenv/config\"\nimport { createBot, createProvider, createFlow, EVENTS } from '@builderbot/bot'\nimport { MemoryDB as Database } from '@builderbot/bot'\nimport { TelegramProvider as Provider } from \"@builderbot-plugins/telegram\"\n\nimport z from \"zod\"\nimport { createAIFlow } from \"./src/index\"\n\nimport { OramaClient } from '@oramacloud/client' \nimport { Product } from \"./src/types\"\n\nconst client = new OramaClient({ \n endpoint: 'https://cloud.orama.run/v1/indexes/my-shopify-irxv20', \n api_key: 'YOUR-ORAMA-API-KEY' \n }) \n\nconst aiflow = createAIFlow\n .setKeyword(EVENTS.WELCOME)\n .pipe(({ addAnswer }) => {\n return addAnswer('Hola!, dejame buscar entre el stock...')\n })\n .setStructuredLayer(z.object({ \n intention: z.enum(['SALES']).describe(`La intención del cliente:\n SALES: Si el cliente pregunta, quiere informacion o esta interesado en uno o mas productos\n \n `)\n }), async (ctx, { endFlow }) => {\n console.log(ctx?.schema)\n if (ctx?.schema) {\n const { intention } = ctx.schema\n \n if (intention !== 'SALES') {\n return endFlow('Lo siento, Intenta preguntando sobre un producto')\n }\n }\n })\n .setContextLayer(\n z.object({\n product_name: z.string().describe('El producto que busca el cliente'),\n }),\n async (ctx) => {\n console.log({ details: ctx?.context })\n }\n )\n .setStore({\n searchFn: async (term) => {\n console.log({ term })\n\n const { hits } = await client.search({ term, limit: 7 }) as any\n const products = hits.map(hit => hit.document) as Product[]\n\n const mapProducts = products.map(({ \n title,\n variants,\n priceRange,\n options,\n description, \n featuredImage, }) => ({\n product_description: description,\n product_image: featuredImage.url,\n product_name: title,\n // product_variants: variants\n // .map(({ price, selectedOptions }) => ({ price, options: selectedOptions })),\n product_price: priceRange.min,\n // product_options: options,\n }))\n\n return mapProducts\n }\n })\n .createRunnable({\n answerSchema: z.object({\n answer: z\n .string()\n .describe('Agrega una respuesta breve y clara sobre el producto.'),\n metadata: z.array(z.object({\n product_image: z.string()\n .describe('La url de la imagen del producto'),\n product_name: z\n .string()\n .describe(\"Nombre exacto del producto (SIN ALTERAR) que pregunta el cliente debe venir del contexto.\"),\n product_price: z\n .string()\n .describe(\n \"precio exacto del producto (SIN ALTERAR) que pregunta el cliente debe venir del contexto.\"\n ),\n product_description: z\n .string()\n .describe(\n \"Dale un breve pitch de venta a la descripcion del producto indica beneficios y caracteristicas (SIN ALTERAR) que pregunta el cliente debe venir del contexto.\"\n )\n }))\n .nullable().default([])\n .describe('Dado los siguientes productos, estructura los que tengan relación con la busqueda')\n }).describe('El formato de respuesta debe ser el siguiente')\n }, {\n onFailure: (err) => {\n console.log({ err })\n }\n })\n .pipe(({ addAction }) => {\n return addAction(async (_, { state, endFlow }) => {\n const answer = state.get('answer')\n console.log('answer', answer)\n if (!answer?.metadata?.length) {\n return endFlow('Lo siento, Intenta preguntando sobre otro producto')\n }\n\n await state.update({ purchase: answer.metadata })\n })\n .addAction(async (_, { state, flowDynamic }) => {\n const purchase = state.get('purchase')\n\n const template = purchase.map((p: any, i: number) => `${i+1}. ${p.product_name}\\nPrecio: $${p.product_price} c/u`).join('\\n\\n')\n\n await flowDynamic(`Estos son algunos de nuestros productos: \\n\\n ${template}`, { delay: 700 })\n flowDynamic(`Indicame cual deseas ver, ${Array.from({ length: purchase.length}, (_, i) => i + 1).join(' o ')}`)\n })\n .addAction({ capture: true }, async (ctx, { state, flowDynamic }) => {\n const purchase = state.get('purchase') as Array\n\n const product = purchase.at(Number(ctx.body) -1)\n await state.update({ product })\n flowDynamic([\n {\n body: `${product.product_name} - $${product.product_price} c/u\\n\\n${product.product_description}`,\n media: product.product_image\n }\n ])\n })\n .addAnswer('¿Deseas comprar el producto (SI / NO)?')\n })\n .setStructuredLayer(z.object({\n intention: z.enum(['SI', 'NO']).describe('Repuesta del ususario')\n }), async (ctx, { endFlow, state, flowDynamic }) => {\n const product = state.get('product') as any\n if (ctx?.schema?.intention !== 'SI') {\n return endFlow('Estare acá por si deseas preguntar sobre otro producto')\n }\n\n const sc = [\n { \n name: product?.product_name,\n price: product?.product_price\n }\n ] \n if (state.getMyState()?.sc?.length) {\n await state.update({\n sc: [\n ...state.getMyState()?.sc,\n // @ts-ignore\n { \n name: product?.product_name,\n price: product?.product_price\n }\n ]\n })\n } else {\n // @ts-ignore\n await state.update({ \n sc\n })\n }\n\n const products = sc.map((p) => `${product.product_name.trim()} $${product.product_price} c/u\\n`).join('\\n')\n const total = sc.map(p => Number(product.product_price)).reduce((a, b) => Math.abs(a + b))\n const template = `Tu compra es:\\n${products}\\nTotal: $${total} dolares.`\n\n await flowDynamic(template)\n\n return endFlow()\n }, { capture: true })\n .createFlow()\n\nconst main = async () => {\n \n const PORT = process.env.PORT ?? 3008\n const adapterFlow = createFlow([aiflow])\n\n const adapterProvider = createProvider(Provider)\n adapterProvider.on('message', (ctx) => console.log('new message', ctx.body))\n const adapterDB = new Database()\n\n const { httpServer, handleCtx } = await createBot({\n flow: adapterFlow,\n provider: adapterProvider,\n database: adapterDB,\n })\n httpServer(+PORT)\n\n\n adapterProvider.server.post(\n '/v1/loyalty',\n handleCtx(async (bot, req, res) => {\n const { number, name } = req.body\n await bot?.dispatch('L0Y4LTY', { from: number, name })\n return res.end('trigger')\n })\n )\n \n}\n\nmain()\n\n```","readmeFilename":"README.md","gitHead":"ea2725a908ffa0f87efd92bbe06de838efc63b0f","_nodeVersion":"20.10.0","_npmVersion":"10.2.3","dist":{"integrity":"sha512-k6yCpaMwHLbwa+Y+LiMGNv2oVQw8Kv4+f9pe+O12BnQ8brRf5uRiJdlXekbAjzENBD238eCDCIiKKoPnH1pP0g==","shasum":"0d67e37cbecf20755e2f610680d476f67a9c10b2","tarball":"https://registry.npmjs.org/@elimeleth/builderbot-langchain/-/builderbot-langchain-1.3.2-alpha.1.tgz","fileCount":62,"unpackedSize":82320,"signatures":[{"keyid":"SHA256:jl3bwswu80PjjokCgh0o2w5c2U4LhQAE57gj9cz1kzA","sig":"MEQCIG3ZDYWeH7UJBTI0bIHpm5YRlQ/Y/jjQRBJt8CSWfi4SAiATF0ThYXYgxgTD5R6iR2uD6tVPQEQKywUOSZr83ZC8MQ=="}]},"_npmUser":{"name":"elimeleth","email":"juancapuanolopez@gmail.com"},"directories":{},"maintainers":[{"name":"elimeleth","email":"juancapuanolopez@gmail.com"}],"_npmOperationalInternal":{"host":"s3://npm-registry-packages","tmp":"tmp/builderbot-langchain_1.3.2-alpha.1_1713537075820_0.9248986414411673"},"_hasShrinkwrap":false}},"time":{"created":"2024-04-14T15:09:45.923Z","1.0.0-alpha.0":"2024-04-14T15:09:46.239Z","modified":"2024-04-19T14:31:16.203Z","1.0.1-alpha.0":"2024-04-14T22:24:21.795Z","1.2.0-alpha.0":"2024-04-15T21:48:34.465Z","1.3.1-alpha.1":"2024-04-16T15:41:31.769Z","1.3.2-alpha.1":"2024-04-19T14:31:15.995Z"},"maintainers":[{"name":"elimeleth","email":"juancapuanolopez@gmail.com"}],"description":"Interface para crear chatbot con Builderbot & LangChain","keywords":["chatbot","builderbot","langchain","whatsapp","telegram"],"author":{"name":"Elimeleth Capuano","email":"elimeleth.contacto@gmail.com"},"readme":"","readmeFilename":""}