more detailed explanation of index_graph its purpose and how it should be used. #2

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2026-02-16T06:17:56-05:00

yindo commented

2026-02-16 06:17:56 -05:00

Originally created by @vkulionis0 on GitHub (Jan 21, 2025).

Currently not very clear how it should be used. Once the retriever is setup, what is the use of index_graph?

Originally created by @vkulionis0 on GitHub (Jan 21, 2025). Currently not very clear how it should be used. Once the retriever is setup, what is the use of index_graph?

yindo commented

2026-02-16 06:17:56 -05:00

@vbarda commented on GitHub (Jan 27, 2025):

Once you've set up your retriever and saved your model secrets, it's time to try it out! First, let's add some information to the index. Open studio, select the "indexer" graph from the dropdown in the top-left, and then add some content to chat over. You can just invoke it with an empty list (default) to index sample documents from LangChain and LangGraph documentation.

Does this part from the README help with your question?

@vbarda commented on GitHub (Jan 27, 2025): > Once you've set up your retriever and saved your model secrets, it's time to try it out! First, let's add some information to the index. Open studio, select the "indexer" graph from the dropdown in the top-left, and then add some content to chat over. You can just invoke it with an empty list (default) to index sample documents from LangChain and LangGraph documentation. Does this part from the README help with your question?

yindo commented

2026-02-16 06:17:56 -05:00

@vkulionis0 commented on GitHub (Jan 28, 2025):

When you set up a retriever (e.g., MongoDB) with access to a vectorstore, why do you still need to use index_graph? Shouldn't you be able to start querying the agent as soon as the retriever is configured and has access to the vectorstore?

@vkulionis0 commented on GitHub (Jan 28, 2025): When you set up a retriever (e.g., MongoDB) with access to a vectorstore, why do you still need to use index_graph? Shouldn't you be able to start querying the agent as soon as the retriever is configured and has access to the vectorstore?

yindo commented

2026-02-16 06:17:57 -05:00

@vbarda commented on GitHub (Jan 28, 2025):

if you have an existing database with some data, you don't need to use index_graph - i don't think README is saying that?

@vbarda commented on GitHub (Jan 28, 2025): if you have an existing database with some data, you don't need to use `index_graph` - i don't think README is saying that?

yindo commented

2026-02-16 06:17:57 -05:00

@hocokahu commented on GitHub (Apr 20, 2025):

Once you've set up your retriever and saved your model secrets, it's time to try it out! First, let's add some information to the index. Open studio, select the "indexer" graph from the dropdown in the top-left, and then add some content to chat over. You can just invoke it with an empty list (default) to index sample documents from LangChain and LangGraph documentation.

Does this part from the README help with your question?

@vbarda I didn't get a chance to dig deep into this but I got this error following the instructions:

In index_docs

BlockingError("Blocking call to io.TextIOWrapper.read\n\nHeads up! LangGraph dev identified a synchronous blocking call in your code. When running in an ASGI web server, blocking calls can degrade performance for everyone since they tie up the event loop.\n\nHere are your options to fix this:\n\n1. Best approach: Convert any blocking code to use async/await patterns\n   For example, use 'await aiohttp.get()' instead of 'requests.get()'\n\n2. Quick fix: Move blocking operations to a separate thread\n   Example: 'await asyncio.to_thread(your_blocking_function)'\n\n3. Override (if you can't change the code):\n   - For development: Run 'langgraph dev --allow-blocking'\n   - For deployment: Set 'BG_JOB_ISOLATED_LOOPS=true' environment variable\n\nThese blocking operations can prevent health checks and slow down other runs in your deployment. Following these recommendations will help keep your LangGraph application running smoothly!")

@hocokahu commented on GitHub (Apr 20, 2025): > > Once you've set up your retriever and saved your model secrets, it's time to try it out! First, let's add some information to the index. Open studio, select the "indexer" graph from the dropdown in the top-left, and then add some content to chat over. You can just invoke it with an empty list (default) to index sample documents from LangChain and LangGraph documentation. > > Does this part from the README help with your question? @vbarda I didn't get a chance to dig deep into this but I got this error following the instructions: In `index_docs` ``` BlockingError("Blocking call to io.TextIOWrapper.read\n\nHeads up! LangGraph dev identified a synchronous blocking call in your code. When running in an ASGI web server, blocking calls can degrade performance for everyone since they tie up the event loop.\n\nHere are your options to fix this:\n\n1. Best approach: Convert any blocking code to use async/await patterns\n For example, use 'await aiohttp.get()' instead of 'requests.get()'\n\n2. Quick fix: Move blocking operations to a separate thread\n Example: 'await asyncio.to_thread(your_blocking_function)'\n\n3. Override (if you can't change the code):\n - For development: Run 'langgraph dev --allow-blocking'\n - For deployment: Set 'BG_JOB_ISOLATED_LOOPS=true' environment variable\n\nThese blocking operations can prevent health checks and slow down other runs in your deployment. Following these recommendations will help keep your LangGraph application running smoothly!") ``` <img width="1429" alt="Image" src="https://github.com/user-attachments/assets/77e0bd4a-5c6b-428d-985e-287993440b8b" />

yindo referenced this issue

2026-02-16 06:17:58 -05:00

[PR #2] [MERGED] update reducer #7

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Reference: langchain-ai/rag-research-agent-template#2