receive local file events and default data loader and recursive character text splitter
Configured with Aggregate, Chain LLM, Chain Retrieval Qa, Chain Summarization, and additional nodes. Review the connections and setup before adapting this template.
Node categories in this workflow
- Trigger
- Files / media
- Transform
- AI & models
- Routing
- Data store
- Wait
Icons describe general node roles, inferred from node types. Inspect the parameters for the configured action.
Drag to pan; use + and − to zoom. Reconstructed from the exported node positions; nothing runs here. Dashed lines represent non-main connections. Full node names and notes appear below.
How it works
The exported workflow contains the following configured nodes. Their connections are shown above; inspect the JSON for the complete logic, expressions, and external actions.
| Node | Category | Type | Operation |
|---|---|---|---|
| Local File Trigger | Trigger | Local File Trigger | See node parameters |
| Default Data Loader | Files / media | Document Default Data Loader | See node parameters |
| Recursive Character Text Splitter | Transform | Text Splitter Recursive Character Text Splitter | See node parameters |
| Embeddings Mistral Cloud | AI & models | Embeddings Mistral Cloud | See node parameters |
| Mistral Cloud Chat Model | AI & models | LM Chat Mistral Cloud | See node parameters |
| Mistral Cloud Chat Model1 | AI & models | LM Chat Mistral Cloud | See node parameters |
| Prep Incoming Doc | Transform | Edit Fields | See node parameters |
| Settings | Transform | Edit Fields | See node parameters |
| Merge | Transform | Merge | See node parameters |
| Get Doc Types | Transform | Edit Fields | See node parameters |
| Split Out Doc Types | Transform | Split Out | See node parameters |
| For Each Doc Type... | Routing | Loop Over Items | See node parameters |
| Item List Output Parser | Transform | Output Parser Item List | See node parameters |
| Vector Store Retriever | AI & models | Retriever Vector Store | See node parameters |
| Embeddings Mistral Cloud1 | AI & models | Embeddings Mistral Cloud | See node parameters |
| Qdrant Vector Store1 | Data store | Vector Store Qdrant | See node parameters |
| Mistral Cloud Chat Model2 | AI & models | LM Chat Mistral Cloud | See node parameters |
| Split Out | Transform | Split Out | See node parameters |
| Aggregate | Transform | Aggregate | See node parameters |
| Mistral Cloud Chat Model3 | AI & models | LM Chat Mistral Cloud | See node parameters |
| Discover | AI & models | Chain Retrieval Qa | See node parameters |
| 2secs | Wait | Wait | See node parameters |
| Get Generated Documents | Transform | Edit Fields | See node parameters |
| Generate | AI & models | Chain LLM | See node parameters |
| Prep For AI | Transform | Edit Fields | See node parameters |
| To Binary | Transform | Convert To File | toText |
| Export to Folder | Files / media | Read Write File | write |
| Get FileType | Routing | Switch | See node parameters |
| Import File | Files / media | Read Write File | See node parameters |
| Extract from PDF | Transform | Extract From File | |
| Extract from DOCX | Transform | Extract From File | ods |
| Extract from TEXT | Transform | Extract From File | text |
| Summarization Chain | AI & models | Chain Summarization | See node parameters |
| Qdrant Vector Store | Data store | Vector Store Qdrant | See node parameters |
| Interview | AI & models | Chain LLM | See node parameters |
Setup
- Download the JSON and import it into an isolated n8n instance. Leave the workflow inactive.
- Connect your own credentials through n8n’s credential store. Replace
REPLACE_WITH_*values with your resource identifiers. - Inspect API destinations, Code nodes, database queries, file paths, and outbound actions.
- Run with synthetic data and harmless destinations. Enable triggers only after checking the actual outputs.
Requirements
An n8n instance with the listed node types and compatible versions. Service-connected workflows may require accounts, credentials, or paid APIs.
Credential types declared in the source
mistralCloudApiqdrantApi
Workflow notes
Step 1. Watch Folder and Import New Documents
Step 1. Watch Folder and Import New Documents
Read more about Local File Trigger
With n8n's local file trigger, we're able to trigger the workflow when files are created in our target folder. We still have to import them however as the trigger will only give the file's path. The "Extract From" node is used to get at the file's contents.
Step 2. Summarise and Vectorise Document Contents
Step 2. Summarise and Vectorise Document Contents
Learn more about using the Qdrant VectorStore
Capturing the document into our vector store is intended for a technique we'll use later known as Retrieval Augumented Generation or "RAG" for short. For our scenario, this allows our LLM to retrieve context more efficiently which produces better respsonses.
Step 3. Loop through Templates
Step 3. Loop through Templates
We'll ask the LLM to help us generate 3 types of notes from the imported source document. These notes are intended to breakdown the content for faster study. Our templates for this demo are: (1) Study guide (2) Briefing document (3) Timeline
Step 4. Use AI Agents to Query and Generate Template Documents
Step 4. Use AI Agents to Query and Generate Template Documents
Read more about using the Question & Answer Retrieval Chain
n8n allows us to easily use a chain of LLMs as agents which can work together to handle any task! Here the agents generate questions to explore the content of the source document and use the answers to generate the template.
Step 5. Export Generated Templates To Folder
Step 5. Export Generated Templates To Folder
Learn more about writing to the local filesystem
Finally, the AI generated documents can now be exported to disk. This workflow makes it easy to generate any kind of document from various source material and can be used for training and sales.
Try It Out!
Try It Out!
This workflow automates generating notes from a source document.
- It watches a target folder to pick up new files.
- When a new file is detected, it saves the contents of the file in a vectorstore.
- multiple AI agents guided by a templates list, generate the predetermined notes.
- These notes are then export alongside the original source file for the user.
Need Help?
Join the Discord or ask in the Forum!
Happy Hacking!
receive local file events and default data loader and recursive character text splitter
receive local file events and default data loader and recursive character text splitter
Purpose and structure
This folder contains the receive local file events and default data loader and recursive character text splitter workflow. Its executable nodes use aggregate, chainLlm, chainRetrievalQa, chainSummarization, convertToFile, documentDefaultDataLoader, embeddingsMistralCloud, extractFromFile, lmChatMistralCloud, localFileTrigger, merge, outputParserItemList, readWriteFile, retrieverVectorStore, set, splitInBatches, splitOut, switch, textSplitterRecursiveCharacterTextSplitter, vectorStoreQdrant, wait. The table and connection map below are derived from the JSON, not an inferred guarantee of behavior.
Setup
Import inactive. Configure your own credentials and replace REPLACE_WITH_* values. Review external destinations and Code nodes before running.
Entry points
Local File Trigger
Verification
Sanitized source candidate; not runtime-tested. This overview is generated from node metadata. Read the folder README for the connection map, credential types, and license.
Attribution
https://github.com/Zie619/n8n-workflows/blob/94007c1445d9258a7da116646b79473e7c7c3282/workflows/Localfile/0537_Localfile_Wait_Create_Triggered.json MIT; preserve source notices.
Canvas section labels
These name areas of the original canvas; they do not include explanatory instructions.
- 💡Add your own templates here!