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Parse CVs from Emails with OCR & GPT for Notion Database
https://n8nworkflows.xyz/workflows/parse-cvs-from-emails-with-ocr---gpt-for-notion-database-6326
# Parse CVs from Emails with OCR & GPT for Notion Database
### 1. Workflow Overview
This workflow automates the processing of CVs (resumes) received via email attachments, extracting candidate information using OCR and AI, and storing it in a Notion database. It is designed for HR teams or recruiters who want to streamline candidate data collection from emails.
The workflow is logically divided into the following blocks:
- **1.1 Email Input Reception**
Watches a Gmail inbox for incoming emails with attachments.
- **1.2 PDF Attachment Filtering and OCR Processing**
Filters PDF attachments from emails and extracts their text content using the OCR.space API.
- **1.3 AI-Powered CV Parsing**
Sends the extracted OCR text to OpenAI’s GPT model to detect if the document is a CV and to extract structured candidate fields.
- **1.4 Data Mapping and Duplicate Verification**
Maps extracted fields to the workflow's internal structure and queries the Notion database to check for existing entries by email to avoid duplicates.
- **1.5 Notion Database Entry Creation**
Creates a new candidate record in Notion if no duplicate is found.
---
### 2. Block-by-Block Analysis
#### 2.1 Email Input Reception
**Overview:**
This block triggers the workflow upon receiving a new email with attachments in a Gmail inbox.
**Nodes Involved:**
- Gmail Trigger
- Code (Attachment Filter)
**Node Details:**
- **Gmail Trigger**
- Type: Trigger node for Gmail
- Configuration: Filters emails with attachments (`has:attachment`), downloads attachments, polls every minute.
- Input: None (trigger)
- Output: Email data including attachments in binary form.
- Edge Cases: OAuth2 token expiration, Gmail API rate limits.
- **Code (Attachment Filter)**
- Type: Function (JavaScript) node
- Role: Filters email attachments to only PDF files.
- Key Logic: Iterates over binary attachments and outputs only those with mime type `application/pdf`.
- Input: Gmail Trigger output
- Output: One item per PDF attachment with binary data.
- Edge Cases: Emails without PDFs lead to empty output; code assumes `binary` data exists; malformed emails might cause errors.
#### 2.2 PDF Attachment Filtering and OCR Processing
**Overview:**
This block sends the PDF attachment binary data to OCR.space to extract textual content.
**Nodes Involved:**
- HTTP Request (OCR API)
- If1 (HTTP status check)
**Node Details:**
- **HTTP Request**
- Type: HTTP Request node
- Role: Sends PDF binary data as multipart/form-data to OCR.space API for OCR text extraction.
- Configuration:
- URL: `https://api.ocr.space/parse/image`
- Method: POST
- Headers: API key dynamically read from variable `OCR_SPACE_API_KEY`
- Timeout: 40 seconds
- Input: PDF binary from Code node
- Output: OCR response including parsed text.
- Edge Cases: API timeouts, invalid API key, malformed PDF files, OCR errors.
- **If1**
- Type: Conditional node
- Role: Checks HTTP response status code is between 200 and 299 (success).
- Input: HTTP Request output
- Output: Proceeds to AI parsing if success, terminates otherwise.
- Edge Cases: Handles non-2xx responses gracefully by skipping downstream.
#### 2.3 AI-Powered CV Parsing
**Overview:**
Sends OCR text content to a GPT model to classify if the document is a CV and extract structured candidate data fields.
**Nodes Involved:**
- Message a model (OpenAI GPT node)
- If (CV check)
**Node Details:**
- **Message a model**
- Type: OpenAI GPT node (via LangChain integration)
- Role: Provides instructions and OCR text to GPT-4.1-NANO model to parse CV fields.
- Key prompt details:
- Check if document is a CV
- Extract fields: full_name, email, phone, location, job_title, years_experience, skills (array), education (array), languages, certifications, linkedin, availability
- Return JSON or `{ "is_cv": false }` if not a CV
- Input: OCR parsed text (`ParsedResults[0].ParsedText`) from HTTP Request
- Output: JSON with candidate data or `is_cv: false`
- Credentials: OpenAI API key
- Edge Cases: Model misinterpretation, rate limiting, incomplete data extraction.
- **If**
- Type: Conditional node
- Role: Checks if the OpenAI response contains a non-null email field (indicating a CV was detected).
- Input: GPT output
- Output: Continues if CV detected, stops otherwise.
- Edge Cases: False negatives if email missing; expression errors if response malformed.
#### 2.4 Data Mapping and Duplicate Verification
**Overview:**
Maps GPT-extracted fields into a structured format and queries Notion to check for existing candidate entries by email.
**Nodes Involved:**
- Map Fields (Set node)
- Get many entries (Notion query)
- If2 (Duplicate check)
**Node Details:**
- **Map Fields**
- Type: Set node
- Role: Assigns GPT-extracted fields to a structured JSON format under `message.content` namespace, e.g., `full_name`, `email`, `phone`, `location`, `years_experience`, `education` (array), `languages` (array), `linkedin`.
- Input: GPT output JSON
- Output: Mapped structured data for downstream use
- Edge Cases: Null or missing fields handled with defaults (`null` or empty arrays).
- **Get many entries**
- Type: Notion node (database query)
- Role: Queries Notion "Candidates" database filtering by email to find duplicates.
- Input: Mapped data from Map Fields
- Output: List of matching entries (empty if none)
- Credentials: Notion API integration
- Edge Cases: Notion API errors, rate limits, incorrect database ID.
- **If2**
- Type: Conditional node
- Role: Checks if No duplicates exist (result length = 0) to proceed with creation.
- Input: Notion query output
- Output: Creates new entry if no duplicates found, skips otherwise.
- Edge Cases: Duplicate detection logic relies on exact email match; partial duplicates may be missed.
#### 2.5 Notion Database Entry Creation
**Overview:**
Creates a new candidate record in the Notion database with the parsed and mapped candidate data.
**Nodes Involved:**
- Create entry (Notion create database page)
**Node Details:**
- **Create entry**
- Type: Notion node (create database page)
- Role: Inserts a new page in the "Candidates" database with mapped candidate properties.
- Properties mapped:
- Name (title)
- Email (email)
- Phone (phone_number)
- Location (rich_text)
- Years of Experience (rich_text)
- Education (joined string from array)
- Languages (joined string)
- LinkedIn (url)
- Application Date (current date/time in Europe/Madrid timezone)
- Credentials: Notion API integration
- Edge Cases: Notion API errors, improper data formatting, missing required fields.
---
### 3. Summary Table
| Node Name | Node Type | Functional Role | Input Node(s) | Output Node(s) | Sticky Note |
|-------------------|---------------------------------|-----------------------------------------|-----------------------|----------------------|--------------------------------------------------------------------------------------------------------------|
| Gmail Trigger | Gmail Trigger | Trigger workflow on new email with attachments | None | Code | ### 🧠 CV Parser - Email to Notion: Workflow overview and purpose |
| Code | Function (Code) | Filter attachments to PDFs only | Gmail Trigger | HTTP Request | ### 📌 Notes: Only processes emails with PDF attachments; skips non-CV docs automatically |
| HTTP Request | HTTP Request | Send PDF binary to OCR.space API for text extraction | Code | If1 | |
| If1 | If Condition | Check OCR API HTTP status (200-299) | HTTP Request | Message a model | |
| Message a model | OpenAI GPT (LangChain node) | Parse OCR text to detect CV and extract candidate data | If1 | If | |
| If | If Condition | Check if AI detected a CV (email present) | Message a model | Map Fields | |
| Map Fields | Set | Map AI-extracted candidate fields to structured format | If | Get many entries | |
| Get many entries | Notion (Database query) | Query Notion database for duplicates by email | Map Fields | If2 | |
| If2 | If Condition | Proceed only if no duplicate found | Get many entries | Create entry | |
| Create entry | Notion (Create database page) | Create new candidate record in Notion | If2 | None | |
| Sticky Note | Sticky Note | Documentation and workflow overview | None | None | ### 🧠 CV Parser - Email to Notion: This workflow automates extraction and organization of candidate data. |
| Sticky Note1 | Sticky Note | Additional notes on processing and duplicates | None | None | ### 📌 Notes: Only processes emails with PDF attachments; skips non-CV; checks duplicates by email. |
| Sticky Note2 | Sticky Note | Requirements and setup notes | None | None | ### ✅ Requirements: Gmail OAuth2, OCR.space API Key, OpenAI API Key, Notion integration with proper fields. |
---
### 4. Reproducing the Workflow from Scratch
1. **Create Gmail Trigger Node**
- Type: Gmail Trigger
- Configure OAuth2 credentials for Gmail.
- Set filter query: `has:attachment`
- Enable attachment download.
- Set polling interval to every minute.
2. **Add Code Node to Filter PDF Attachments**
- Type: Function (Code) node
- Paste JavaScript code to filter attachments with mime type `application/pdf`.
- Connect Gmail Trigger output to this node.
3. **Add HTTP Request Node to OCR.space API**
- Type: HTTP Request
- Set URL: `https://api.ocr.space/parse/image`
- Method: POST
- Content-Type: multipart/form-data
- Add header parameter `apikey` with value from variable `OCR_SPACE_API_KEY` (create this variable in n8n or set manually).
- Configure body to send binary data under field `file`.
- Set timeout to 40000 ms.
- Connect Code node output to this node.
4. **Add If Node to Check OCR API Response Status**
- Type: If node (version 2)
- Condition: `statusCode >= 200 AND statusCode < 300`
- Connect HTTP Request node output to this node.
5. **Add OpenAI GPT Node (LangChain OpenAi)**
- Type: OpenAi (LangChain) node
- Model: `gpt-4.1-nano`
- Credentials: Configure with OpenAI API Key.
- Message content:
```
You're an HR assistant. I will provide you with text from a PDF document.
1. First, determine if it's a CV/resume.
2. If it is, extract the following fields:
- full_name
- email
- phone
- location
- job_title
- years_experience
- skills (as an array)
- education (as an array of strings)
- languages
- certifications
- linkedin
- availability
3. Return the result as a JSON object with those fields.
If it's not a CV, just return: { "is_cv": false }
Here is the document text:
{{ $json.body.ParsedResults[0].ParsedText }}
```
- Connect the successful branch of the If node (OCR response check) to this node.
6. **Add If Node to Check if Email Field Exists in GPT Output**
- Type: If node (version 2)
- Condition: Check if `message.content.email !== null`
- Connect GPT node output to this node.
7. **Add Set Node to Map Fields**
- Type: Set node
- Map fields from GPT output JSON to structured keys under `message.content` for: full_name, email, phone, location, years_experience, education, languages, linkedin, etc.
- Connect positive branch of previous If node.
8. **Add Notion Node to Query Database for Existing Entries**
- Type: Notion (Database Page - Get All)
- Credentials: Connect to Notion integration with access to your Candidates database.
- Set database ID to your Notion Candidates DB.
- Filter: `Email` equals `={{ $json.message.content.email }}`
- Connect Map Fields node output to this node.
9. **Add If Node to Check for Duplicates**
- Type: If node (version 2)
- Condition: Check if the number of returned entries is zero (no duplicates).
- Connect Notion query output to this node.
10. **Add Notion Node to Create New Candidate Entry**
- Type: Notion (Create Database Page)
- Credentials: Same Notion integration.
- Database ID: Candidates DB.
- Map properties from mapped fields to Notion properties: Name, Email, Phone, Location, Years of Experience, Education (joined by `/`), Languages (joined by `, `), LinkedIn URL, Application Date (set current date/time, timezone Europe/Madrid).
- Connect positive branch of previous If node.
---
### 5. General Notes & Resources
| Note Content | Context or Link |
|-----------------------------------------------------------------------------------------------------------|-----------------------------------------------------------|
| Workflow automates CV extraction from Gmail attachments, including OCR and GPT-powered parsing into Notion | Sticky Note on workflow overview |
| Only processes PDF attachments; skips non-CV documents automatically; checks duplicates by email | Sticky Note1 |
| Requires Gmail OAuth2 credentials, OCR.space API key, OpenAI API key, and Notion integration with proper database fields | Sticky Note2 |
| Notion database should contain fields: Name, Email, Phone, Location, Experience, Education, Languages, LinkedIn | Configured in Notion create and query nodes |
---
This structured documentation provides a comprehensive understanding of the workflow, enabling reproduction, modification, and anticipation of potential errors or integration issues.