From 0c704fff74af2bb8d54e33840dd13fef69e054a5 Mon Sep 17 00:00:00 2001 From: d-pamneja Date: Wed, 25 Feb 2026 14:12:10 +0530 Subject: [PATCH] Fix Templates --- kits/.gitignore | 2 +- templates/indexation/templates.json | 364 ---------------------------- 2 files changed, 1 insertion(+), 365 deletions(-) diff --git a/kits/.gitignore b/kits/.gitignore index 7985f24..9fd7822 100644 --- a/kits/.gitignore +++ b/kits/.gitignore @@ -1,3 +1,3 @@ /special/ -*/stock-analysis/ +./kits/agentic/stock-analysis/ .next diff --git a/templates/indexation/templates.json b/templates/indexation/templates.json index fd6037c..2d8afd1 100644 --- a/templates/indexation/templates.json +++ b/templates/indexation/templates.json @@ -4499,176 +4499,6 @@ "complexity": "beginner", "enrichedDescription": "This flow acts as an introduction to RAG, where you can ask a query based on a given text and get your answers from that specific knowledge base. Industries: Technology & Software, Education. Use cases: Document Q&A. Roles: Engineer. Complexity: beginner." }, - { - "id": "40551442-2e32-408b-8599-cbfd41c4435d", - "name": "Invoice Summariser", - "description": "This AI-powered invoice summarization workflow processes invoices, extracts key details like total amounts, due dates, and vendor information, and generates structured JSON output.", - "deployUrl": "https://studio.lamatic.ai/_?templateSlug=invoice-summariser", - "rawNodes": [ - { - "id": "triggerNode_1", - "type": "triggerNode", - "position": { - "x": 0, - "y": 0 - }, - "data": { - "nodeId": "graphqlNode", - "trigger": true, - "values": { - "nodeName": "API Request", - "responeType": "realtime", - "advance_schema": "{\n \"url\": \"string\"\n}" - } - } - }, - { - "id": "extractFromFileNode_525", - "type": "dynamicNode", - "position": { - "x": 0, - "y": 0 - }, - "data": { - "nodeId": "extractFromFileNode", - "values": { - "nodeName": "Extract from File", - "trim": false, - "ltrim": false, - "quote": "\"", - "rtrim": false, - "format": "pdf", - "comment": "null", - "fileUrl": "{{triggerNode_1.output.url}}", - "headers": true, - "maxRows": "0", - "encoding": "utf8", - "password": "", - "skipRows": "0", - "delimiter": ",", - "joinPages": true, - "ignoreEmpty": false, - "returnRawText": false, - "encodeAsBase64": false, - "discardUnmappedColumns": false - } - } - }, - { - "id": "LLMNode_103", - "type": "dynamicNode", - "position": { - "x": 0, - "y": 0 - }, - "data": { - "nodeId": "LLMNode", - "values": { - "nodeName": "Generate Text", - "tools": [], - "prompts": [ - { - "id": "187c2f4b-c23d-4545-abef-73dc897d6b7b", - "role": "system", - "content": "Extract structured JSON data from this invoice data from a pdf.\n\nInstructions:\n\n1. Convert the provided invoice PDF into a structured JSON format.\n2. Ensure the JSON output captures all relevant details, including company, customer, metadata, services, totals, payment, and transaction details. These are just examples, you can make the relevant keys and their respective values\n3. Include validation warnings if there are missing or inconsistent details.\n4. Do not return any output except the JSON.\n5. No leading statements or backticks with json written, just give the JSON object directly as it will be processed later.\n\nInput : {{extractFromFileNode_764.output.files}}" - } - ], - "memories": "[]", - "messages": "[]", - "generativeModelName": {} - } - } - }, - { - "id": "graphqlResponseNode_866", - "type": "dynamicNode", - "position": { - "x": 0, - "y": 0 - }, - "data": { - "nodeId": "graphqlResponseNode", - "values": { - "nodeName": "API Response", - "outputMapping": "{\n \"output\": \"{{LLMNode_103.output.generatedResponse}}\"\n}" - } - } - } - ], - "edges": [ - { - "id": "triggerNode_1-extractFromFileNode_525", - "source": "triggerNode_1", - "target": "extractFromFileNode_525", - "sourceHandle": "bottom", - "targetHandle": "top", - "type": "defaultEdge" - }, - { - "id": "extractFromFileNode_525-LLMNode_103", - "source": "extractFromFileNode_525", - "target": "LLMNode_103", - "sourceHandle": "bottom", - "targetHandle": "top", - "type": "defaultEdge" - }, - { - "id": "LLMNode_103-graphqlResponseNode_866", - "source": "LLMNode_103", - "target": "graphqlResponseNode_866", - "sourceHandle": "bottom", - "targetHandle": "top", - "type": "defaultEdge" - }, - { - "id": "response-graphqlResponseNode_866", - "source": "triggerNode_1", - "target": "graphqlResponseNode_866", - "sourceHandle": "to-response", - "targetHandle": "from-trigger", - "type": "responseEdge" - } - ], - "available_nodes": { - "triggerNode": [ - { - "nodeName": "API Request", - "nodeId": "graphqlNode", - "trigger": true - } - ], - "dynamicNode": [ - { - "nodeName": "Extract from File", - "nodeId": "extractFromFileNode", - "trigger": false - }, - { - "nodeName": "Generate Text", - "nodeId": "LLMNode", - "trigger": false - }, - { - "nodeName": "API Response", - "nodeId": "graphqlResponseNode", - "trigger": false - } - ] - }, - "industries": [ - "Finance", - "Retail" - ], - "useCases": [ - "Data extraction" - ], - "roles": [ - "Operations", - "Manager" - ], - "complexity": "intermediate", - "enrichedDescription": "This AI-powered invoice summarization workflow processes invoices, extracts key details like total amounts, due dates, and vendor information, and generates structured JSON output. Industries: Finance, Retail. Use cases: Data extraction. Roles: Operations, Manager. Complexity: intermediate." - }, { "id": "f6c86618-b178-4e58-a178-0b6a9fcfe59f", "name": "JSON Summariser", @@ -6110,200 +5940,6 @@ "complexity": "beginner", "enrichedDescription": "This AI-powered recipe generation system processes user-provided image links, identifies food items, and generates structured output, enabling seamless analysis and recipe ideation from food images. Industries: Other. Use cases: Content generation. Roles: Other. Complexity: beginner." }, - { - "id": "3c4658d3-2717-4bc2-8e11-2ae5dcbeccda", - "name": "Recipe Maker with Memory", - "description": "This AI-powered recipe generation system retains user preferences, dietary restrictions, and past interactions to generate personalised recipes with customised cooking instructions tailored to individual needs.", - "deployUrl": "https://studio.lamatic.ai/_?templateSlug=recipe-maker-with-memory", - "rawNodes": [ - { - "id": "triggerNode_1", - "type": "triggerNode", - "position": { - "x": 0, - "y": 0 - }, - "data": { - "nodeId": "graphqlNode", - "trigger": true, - "values": { - "nodeName": "API Request", - "responeType": "realtime", - "advance_schema": "{\n \"query\": \"string\",\n \"id\": \"int\"\n}" - } - } - }, - { - "id": "memoryNode_396", - "type": "dynamicNode", - "position": { - "x": 0, - "y": 0 - }, - "data": { - "nodeId": "memoryNode", - "values": { - "nodeName": "Memory Add", - "uniqueId": "{{triggerNode_1.output.id}}", - "sessionId": "", - "memoryValue": [ - { - "role": "user", - "content": "{{triggerNode_1.output.query}}" - } - ], - "memoryCollection": "receipeTest", - "embeddingModelName": {}, - "generativeModelName": {} - } - } - }, - { - "id": "memoryRetrieveNode_711", - "type": "dynamicNode", - "position": { - "x": 0, - "y": 0 - }, - "data": { - "nodeId": "memoryRetrieveNode", - "values": { - "nodeName": "Memory Retrieve", - "limit": 10, - "filters": "[]", - "searchQuery": "What are the user preferences and what all have they told about their needs?", - "memoryCollection": "receipeTest", - "embeddingModelName": {}, - "generativeModelName": {} - } - } - }, - { - "id": "LLMNode_730", - "type": "dynamicNode", - "position": { - "x": 0, - "y": 0 - }, - "data": { - "nodeId": "LLMNode", - "values": { - "nodeName": "Generate Text", - "tools": [], - "prompts": [ - { - "id": "187c2f4b-c23d-4545-abef-73dc897d6b7b", - "role": "system", - "content": "You are a recipe expert who aids the user solve their meal requirements given the past memories you have of the user. Make sure it has no leading statements, just the final receipe.\n\nQUERY : {{triggerNode_1.output.query}}" - } - ], - "memories": "{{memoryRetrieveNode_711.output.memories}}", - "messages": "[]", - "generativeModelName": {} - } - } - }, - { - "id": "graphqlResponseNode_127", - "type": "dynamicNode", - "position": { - "x": 0, - "y": 0 - }, - "data": { - "nodeId": "graphqlResponseNode", - "values": { - "nodeName": "API Response", - "outputMapping": "{\n \"recipe\": \"{{LLMNode_730.output.generatedResponse}}\"\n}" - } - } - } - ], - "edges": [ - { - "id": "triggerNode_1-memoryNode_396", - "source": "triggerNode_1", - "target": "memoryNode_396", - "sourceHandle": "bottom", - "targetHandle": "top", - "type": "defaultEdge" - }, - { - "id": "memoryNode_396-memoryRetrieveNode_711", - "source": "memoryNode_396", - "target": "memoryRetrieveNode_711", - "sourceHandle": "bottom", - "targetHandle": "top", - "type": "defaultEdge" - }, - { - "id": "memoryRetrieveNode_711-LLMNode_730", - "source": "memoryRetrieveNode_711", - "target": "LLMNode_730", - "sourceHandle": "bottom", - "targetHandle": "top", - "type": "defaultEdge" - }, - { - "id": "LLMNode_730-graphqlResponseNode_127", - "source": "LLMNode_730", - "target": "graphqlResponseNode_127", - "sourceHandle": "bottom", - "targetHandle": "top", - "type": "defaultEdge" - }, - { - "id": "response-graphqlResponseNode_127", - "source": "triggerNode_1", - "target": "graphqlResponseNode_127", - "sourceHandle": "to-response", - "targetHandle": "from-trigger", - "type": "responseEdge" - } - ], - "available_nodes": { - "triggerNode": [ - { - "nodeName": "API Request", - "nodeId": "graphqlNode", - "trigger": true - } - ], - "dynamicNode": [ - { - "nodeName": "Memory Add", - "nodeId": "memoryNode", - "trigger": false - }, - { - "nodeName": "Memory Retrieve", - "nodeId": "memoryRetrieveNode", - "trigger": false - }, - { - "nodeName": "Generate Text", - "nodeId": "LLMNode", - "trigger": false - }, - { - "nodeName": "API Response", - "nodeId": "graphqlResponseNode", - "trigger": false - } - ] - }, - "industries": [ - "Other" - ], - "useCases": [ - "Content generation" - ], - "roles": [ - "Other" - ], - "complexity": "intermediate", - "enrichedDescription": "This AI-powered recipe generation system retains user preferences, dietary restrictions, and past interactions to generate personalised recipes with customised cooking instructions tailored to individual needs. Industries: Other. Use cases: Content generation. Roles: Other. Complexity: intermediate." - }, { "id": "0c5067cb-7bb6-40b6-98ae-2384ac248ca5", "name": "Resume Parser",