La validation des contrats, devis ou fiches techniques est essentielle pour garantir la conformité et limiter les erreurs. Automatisez chaque étape du processus avec des notifications, des relances et des circuits de validation adaptés à vos règles internes.
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"content": "## 1. API to Trigger Workflown[Read more about using Webhooks](https://docs.n8n.io/integrations/builtin/core-nodes/n8n-nodes-base.webhook/)nnThis workflow requires the user to submit the RFP document via an API request. It's a common pattern to use the webhook node for this purpose. Be sure to secure this webhook endpoint in production!"
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"jsonOutput": "={n "doc_title": "{{ $('Wait for Request').item.json.body.title }}",n "doc_filename": "{{ $('Wait for Request').item.json.body.id }} | {{ $('Wait for Request').item.json.body.title }} | {{ $now.format('yyyyMMddhhmmss') }}| RFP Response",n "reply_to": "{{ $('Wait for Request').item.json.body.reply_to }}"n}n"
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"content": "## 2. Create a new Doc to Capture Responses For RFP Questionsn[Read more about working with Google Docs](https://docs.n8n.io/integrations/builtin/app-nodes/n8n-nodes-base.googledocs/)nnFor each RFP we process, let's create its very own document to store the results. It will serve as a draft document for the RFP response."
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"content": "## 3. Identifying Questions using AIn[Read more about Question & Answer Chain](https://docs.n8n.io/integrations/builtin/cluster-nodes/root-nodes/n8n-nodes-langchain.chainretrievalqa/)nnUsing the power of LLMs, we're able to extract the RFP questionnaire regardless of original formatting or layout. This allows AutoRFP to handle a wide range of RFPs without requiring explicit extraction rules for edge cases.nnAdditionally, We'll use the Input List Output Parser to return a list of questions for further processing."
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"content": "## 4. Generating Question & Answer Pairs with AIn[Read more about using OpenAI Assistants in n8n](https://docs.n8n.io/integrations/builtin/app-nodes/n8n-nodes-langchain.openai/)nnBy preparing an OpenAI Assistant with marketing material and sales documents about our company and business, we are able to use AI to answer RFP questions with the accurate and relevant context. Potentially allowing sales teams to increase the number of RFPs they can reply to.nnThis portion of the workflow loops through and answers each question individually for better answers. We can record the Question and Answer pairings to the RFP response document we created earlier."
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"content": "## Try It Out!nn**This workflow does the following:**n* Receives a RFP document via webhookn* Creates a new RFP response document via Google Docsn* Uses LLMs to extract the questions from the RFP document into a questions listn* Loops through each question and uses an OpenAI Assistant to generate an answer. Saving each answer into the response document.n* Once complete, sends a gmail and slack notification to the team.nnnud83dudcc3**Example Documents**nTo run this workflow, you'll need to following 2 documents:n* [RFP Document](https://drive.google.com/file/d/1G42h4Vz2lBuiNCnOiXF_-EBP1MaIEVq5/view?usp=sharing)n* [Example Company Document](https://drive.google.com/file/d/16WywCYcxBgYHXB3TY3wXUTyfyG2n_BA0/view?usp=sharing)nn### Need Help?nJoin the [Discord](https://discord.com/invite/XPKeKXeB7d) or ask in the [Forum](https://community.n8n.io/)!nnHappy Hacking!"
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"content": "## 5. Send Notification Once Completedn[Read more about using Slack](https://docs.n8n.io/integrations/builtin/app-nodes/n8n-nodes-base.slack)nnnFinally, we can use a number of ways to notify the sales team when the process is complete. Here, we've opted to send the requesting user an email with a link to the RFP response document."
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"sendTo": "={{ $('Set Variables').item.json.reply_to }}",
"message": "=Your RFP document "{{ $('Set Variables').item.json.title }}" is now complete!",
"options": {},
"subject": "=RFP Questionnaire "{{ $('Set Variables').item.json.title }}" Completed!",
"emailType": "text"
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"name": "Gmail account"
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"name": "Add Metadata to Response Doc",
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"text": "=Title: {{ $('Set Variables').item.json.doc_title }}nDate generated: {{ $now.format("yyyy-MM-dd @ hh:mm") }}nRequested by: {{ $('Set Variables').item.json.reply_to }}nExecution Id: http://localhost:5678/workflow/{{ $workflow.id }}/executions/{{ $execution.id }}nn---nn",
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"documentURL": "={{ $json.id }}"
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"content": "nnnnnnnnnnnnnnnud83dudea8**Required**n* Use a tool such as Postman to send data to the webhook."
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"content": "nnnnnnnnnnnnnnnnnud83dudea8**Required**nYou'll need to create an OpenAI Assistant to use this workflow.n* Sign up for [OpenAI Dashboard](https://platform.openai.com) if you haven't already.n* Create an [OpenAI Assistant](https://platform.openai.com/playground/assistants)n* Upload the [example company doc](https://drive.google.com/file/d/16WywCYcxBgYHXB3TY3wXUTyfyG2n_BA0/view?usp=sharing) to the assistant.nnThe assistant will use the company doc to answer the questions."
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"text": "={{ $json.response.text }}",
"prompt": "define",
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"resource": "assistant",
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"__rl": true,
"mode": "list",
"value": "asst_QBI5lLKOsjktr3DRB4MwrgZd",
"cachedResultName": "Nexus Digital Solutions Bot"
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"webhookId": "35e874df-2904-494e-a9f5-5a3f20f517f8",
"parameters": {
"path": "35e874df-2904-494e-a9f5-5a3f20f517f8",
"options": {},
"httpMethod": "POST"
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"name": "Extract Questions From RFP",
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"parameters": {
"text": "=You have been given a RFP document as part of a tender process of a buyer. Please extract all questions intended for the supplier. You must ensure the questions extracted are exactly has they are written in the RFP document.nn{{ $('Get RFP Data').item.json.text }}",
"promptType": "define",
"hasOutputParser": true
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"typeVersion": 1.4
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"content": "### Example Webhook Requestncurl --location 'https://' \n--form 'id="RFP001"' \n--form 'title="BlueChip Travel and StarBus Web Services"' \n--form 'reply_to="jim@example.com"' \n--form 'data=@"k9pnbALxX/RFP Questionnaire.pdf"'n"
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