Telegram RAG pdf
20 nodes · telegram, embeddingsOpenAi, documentDefaultDataLoader, textSplitterRecursiveCharacterTextSplitter, stopAndError, chainRetrievalQa
- Engine
- n8n
- Nodes
- 20
- Trigger
- scheduled/triggered
- Source file
- 1689_Stopanderror_Telegram_Automation_Triggered.json
Workflow flow
Telegram Trigger
Telegram
Embeddings OpenAI
@n8n/n8n-nodes-langchain.embeddingsOpenAi
Default Data Loader
@n8n/n8n-nodes-langchain.documentDefaultDataLoader
Recursive Character Text Splitter
@n8n/n8n-nodes-langchain.textSplitterRecursiveCharacterTextSplitter
Vector Store Retriever
@n8n/n8n-nodes-langchain.retrieverVectorStore
Pinecone Vector Store1
@n8n/n8n-nodes-langchain.vectorStorePinecone
Groq Chat Model
@n8n/n8n-nodes-langchain.lmChatGroq
Embeddings
@n8n/n8n-nodes-langchain.embeddingsOpenAi
Check If is a document
IF
Question and Answer Chain
@n8n/n8n-nodes-langchain.chainRetrievalQa
Telegram get File
Telegram
Change to application/pdf
Code
Telegram Response
Telegram
Stop and Error
StopAndError
Pinecone Vector Store
@n8n/n8n-nodes-langchain.vectorStorePinecone
Limit to 1
Limit
Telegram Response about Database
Telegram
Stop and Error1
StopAndError
18 steps · flows top to bottom, branches left to right
Browse by integration
Import into n8n
- Download the n8n JSON file (full or sanitized).
- In n8n: Workflows → Import from file.
- Open each node and reconnect credentials to your accounts.
- Test with manual execution before enabling triggers.
Sanitized JSON removes credential IDs — safer for sharing. Flow graph JSON is OpenRuna's lightweight format for diagrams and other tools, not n8n import.
Overview
Free n8n workflow: Telegram RAG pdf. 20 nodes across telegram, embeddingsOpenAi, documentDefaultDataLoader, textSplitterRecursiveCharacterTextSplitter, stopAndError, chainRetrievalQa, retrieverVectorStore, vectorStorePinecone, with a downloadable JSON and a visual flow diagram on OpenRuna.
What this workflow does
Built in n8n, "Telegram RAG pdf" chains 20 nodes to move data between telegram, embeddingsOpenAi, documentDefaultDataLoader, textSplitterRecursiveCharacterTextSplitter, stopAndError, chainRetrievalQa, retrieverVectorStore, vectorStorePinecone. 20 nodes · telegram, embeddingsOpenAi, documentDefaultDataLoader, textSplitterRecursiveCharacterTextSplitter, stopAndError, chainRetrievalQa It starts from a scheduled/triggered trigger and routes data through every node in order. On OpenRuna you get the visual graph, the integration list, and a downloadable JSON ready to import into n8n. Use it to learn integration patterns, fork it for your own use case, or deploy it quickly after reconnecting credentials.
Use cases
- Fork it to add error handling, retries, or a notification step without designing the 20-node flow from scratch.
- Benchmark it against your current telegram integration to spot missing steps or redundant nodes.
- Study how data moves from telegram to embeddingsOpenAi before building your own variant.
- Share it with your team as a documented reference for scheduled/triggered automations in the telegram stack.
Example output
Imported into n8n, "Telegram RAG pdf" exposes 20 configured nodes. Trigger type: scheduled/triggered. Integrations: telegram, embeddingsOpenAi, documentDefaultDataLoader, textSplitterRecursiveCharacterTextSplitter, stopAndError, chainRetrievalQa, retrieverVectorStore, vectorStorePinecone. Open each node after import to map credentials to your own telegram and embeddingsOpenAi accounts. Run it once in test mode to verify any branch logic (Switch/IF nodes) before enabling production triggers.
Tips by platform
Claude
Ask Claude to turn the "Telegram RAG pdf" JSON into a plain-English runbook, node by node. It can flag where telegram rate limits or missing retries might bite before you go live.
ChatGPT
Drop the workflow JSON or this OpenRuna page URL into ChatGPT and ask for a step-by-step runbook: triggers, branches, and which fields to customise for telegram, embeddingsOpenAi, documentDefaultDataLoader, textSplitterRecursiveCharacterTextSplitter, stopAndError, chainRetrievalQa, retrieverVectorStore, vectorStorePinecone. Handy for onboarding teammates new to n8n.
Cursor
In Cursor, ask Agent mode to parameterise "Telegram RAG pdf" — extract telegram IDs and secrets into environment variables without changing the 20-node structure.
Frequently asked questions
- How do I import "Telegram RAG pdf" into n8n?
- Click Download n8n JSON on this page, then in n8n choose Workflows → Import from file and select the downloaded file. Reconnect credentials on each node — the export carries credential IDs from the original author's instance, not working secrets.
- Which integrations does "Telegram RAG pdf" use?
- It uses: telegram, embeddingsOpenAi, documentDefaultDataLoader, textSplitterRecursiveCharacterTextSplitter, stopAndError, chainRetrievalQa, retrieverVectorStore, vectorStorePinecone. The flow diagram above shows how each service connects across the 20 nodes. Filter OpenRuna by integration to find related workflows and tools.
- Can I import a sanitized export without credentials?
- Yes. Use "Download sanitized JSON" to strip credential references before sharing internally. You will still add your own telegram and embeddingsOpenAi credentials in n8n after import.
- What trigger type does "Telegram RAG pdf" use?
- Trigger type: scheduled/triggered. After import, confirm the trigger node (webhook, schedule, or app event) matches your environment, then activate the workflow when you are ready to run it.
- Is "Telegram RAG pdf" free to use?
- OpenRuna catalogs community n8n workflows under open licenses. Check the source corpus link for the original license; commercial use may require verifying the third-party API terms for telegram, embeddingsOpenAi, documentDefaultDataLoader, textSplitterRecursiveCharacterTextSplitter, stopAndError, chainRetrievalQa, retrieverVectorStore, vectorStorePinecone.
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