Guido X Jansen
Workflows by Guido X Jansen
Generate consensus answers with multiple AI models & peer review system
## AI Council: Multi-Model Consensus with Peer Review **Inspired by [Andrej Karpathy's LLM Council](https://github.com/karpathy/llm-council)**, but rebuilt in n8n. This workflow creates a "council" of AI models that independently answer your question, then peer-review each other's responses before a final arbiter synthesizes the best answer. --- ## Who is this for? - If you want to prepare for an upcoming meeting with different people and prep for their different views - find any "blind spots" in your view on a certain subject - Researchers wanting more robust AI-generated answers - Developers exploring multi-model architectures - Anyone seeking higher-quality responses through AI consensus, potentially with faster/cheaper models. - Teams evaluating different LLM capabilities side-by-side --- ## How it works 1. **Ask a Question** — Submit your query via the Chat Trigger 2. **Individual Answers** — Four different models (Gemini, Llama, Gemma, Mistral) independently generate responses 3. **Peer Review** — Each model reviews ALL answers, identifying pros, cons, and overall assessment 4. **Final Synthesis** — DeepSeek R1 analyzes all peer reviews and produces a refined, consensus-based final answer --- ## Setup Instructions ### Prerequisites - Access to an LLM (e.g. [OpenRouter](https://openrouter.ai/) account with API credits) ### Steps 1. **Create OpenRouter credentials** in n8n: - Go to *Settings → Credentials → Add Credential* - Select "OpenRouter" and paste your API key 2. **Connect all model nodes** to your OpenRouter credential. In this example I used Gemini, Llama, Gemma, Mistral and Deepseek, but you can use whatever you want. You can also use the same models, but change their parameters. Play around to find out what suits you best. 3. **Activate the workflow** and open the Chat interface to test --- ## Customization Ideas - You can add as many answer and review models as you want. Do note that each AI node is executed in series, so each will add to the total duration. - Swap models via OpenRouter's model selector (e.g., use Claude, GPT-4, etc.) - Adjust the peer review prompt to represent a certain persona or with domain-specific evaluation criteria - Add memory nodes for multi-turn conversations - Connect to Slack/Discord instead of the Chat Trigger
Enrich LinkedIn profiles in NocoDB CRM with Apify scraper
# Introduction **Manual LinkedIn data collection is time-consuming, error-prone, and results in inconsistent data quality across CRM/database records.** This workflow is great for organizations that struggle with: - Incomplete contact records with only LinkedIn URLs but missing profile details - Hours spent manually copying LinkedIn information into databases - Inconsistent data formats due to copy-paste from LinkedIn (emojis, styled text, special characters) - Outdated profile information that doesn't reflect current roles/companies - No systematic way to enrich contacts at scale ## Primary Users 1. Sales & Marketing Teams 2. Event Organizers & Conference Managers for event materials 4. Recruitment & HR Professionals 5. CRM Administrators ## Specific Problems Addressed 1. Data Completeness: Automatically fills missing profile fields (headline, bio, skills, experience) 2. Data Quality: Sanitizes problematic characters that break databases/exports 3. Time Efficiency: Reduces hours of manual data entry to automated monthly updates 4. Error Handling: Gracefully manages invalid/deleted LinkedIn profiles 5. Scalability: Processes multiple profiles in batch without manual intervention 6. Standardization: Ensures consistent data format across all records ## Cost Each URL scraped by Apify costs $0.01 to get all the data above. Apify charges per scrape, regardless of how much dta or fields you extract/use. # Setup Instructions ## Prerequisites 1. **n8n Instance:** Access to a running n8n instance (self-hosted or cloud) 2. **NocoDB Account:** Database with a table containing LinkedIn URLs 3. **Apify Account:** Free or paid account for LinkedIn scraping ## Required fields in NocoDB table ### Input: * single LinkedIn URL *NocoDB Field name* ``` LinkedIn ``` ### Output: * first/last/full name * e-mail * bio * headline * profile pic URL * current role * country * skills * current employer * employer URL * experiences (all previous jobs) * personal website * publications (articles) *NocoDB Field names* ``` linkedin_full_name linkedin_first_name: linkedin_headline: linkedin_email: linkedin_bio: linkedin_profile_pic linkedin_current_role linkedin_current_company linkedin_country linkedin_skills linkedin_company_website linkedin_experiences linkedin_personal_website linkedin_publications linkedin_scrape_error_reason linkedin_scrape_last_attempt linkedin_scrape_status linkedin_last_modified ``` Technically you also need an Id field, but that is always there so no need to add it :) ## n8n Setup ### 1. Import the Workflow - Copy the workflow JSON from the template - In n8n, click "Add workflow" → "Import from JSON" - Paste the workflow and click "Import" ### 2. Configure NocoDB Connection - Click on any NocoDB node in the workflow - Add new credentials → "NocoDB Token account" - Enter your NocoDB API token (found in NocoDB → User Settings → API Tokens) - Update the projectId and table parameters in all NocoDB nodes ### 3. Set Up Apify Integration - Create an Apify account at apify.com - Generate an API token (Settings → Integrations → API) - In the workflow, update the Apify token in the "Get Scraper Results" node - Configure HTTP Query Auth credentials with your token ### 4. Map Your Database Fields - Review the "Transform & Sanitize Data" node - Update field mappings to match your NocoDB table structure - Ensure these fields exist in your table: - LinkedIn (URL field) - linkedin_headline, linkedin_full_name, linkedin_bio, etc. - linkedin_scrape_status, linkedin_last_modified ### 5. Configure the Filter - In "Get Guests with LinkedIn" node - Adjust the filter to match your requirements - Default: (LinkedIn,isnot,null)~and(linkedin_headline,is,null) ### 6. Test the Workflow - Click "Execute Workflow" with Manual Trigger - Monitor execution for any errors - Verify data is properly updated in NocoDB ### 7. Activate Automated Schedule - Configure the Schedule Trigger node (default: monthly) - Toggle the workflow to "Active" - Monitor executions in n8n dashboard # Customization Options ## 1. Data Source Modifications - Different Database: Replace NocoDB nodes with Airtable, Google Sheets, or PostgreSQL - Multiple Tables: Add parallel branches to process different contact tables - Custom Filters: Modify the WHERE clause to target specific record subsets ## 2. Enrichment Fields - Add Fields: Include additional LinkedIn data like education, certifications, or recommendations - Remove Fields: Simplify by removing unnecessary fields (publications, skills) - Custom Transformations: Add business logic for field calculations or formatting ## 3. Scheduling Options - Frequency: Change from monthly to daily, weekly, or hourly - Time-based: Set specific times for different timezones - Event-triggered: Replace with webhook trigger for on-demand processing **4. Error Handling Enhancement** - Notifications: Add email/Slack nodes to alert on failures - Retry Logic: Implement wait and retry for temporary failures - Logging: Add database logging for audit trails ## 5. Data Quality Rules - Validation: Add IF nodes to validate data before updates - Duplicate Detection: Check for existing records before creating new ones - Data Standardization: Add custom sanitization rules for industry-specific needs ## 6. Integration Extensions - CRM Sync: Add nodes to push data to Salesforce, HubSpot, or Pipedrive - AI Enhancement: Use OpenAI to summarize bios or extract key skills - Image Processing: Download and store profile pictures locally ## 7. Performance Optimization - Batch Size: Adjust the number of profiles processed per run - Rate Limiting: Add delays between API calls to avoid limits - Parallel Processing: Split large datasets across multiple workflow executions ## 8. Compliance Additions - GDPR Compliance: Add consent checking before processing - Data Retention: Implement automatic cleanup of old records - Audit Logging: Track who accessed what data and when These customizations allow the workflow to adapt from simple contact enrichment to complex data pipeline scenarios across various industries and use cases.