Comments (7)
Smarter models do better at such tasks.
https://github.com/h2oai/enterprise-h2ogpte/blob/main/rag_benchmark/results/test_client_e2e.md
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If you can give me an example repro of your case using some set of public documents, where it shows sources are at bottom of list, I can take a look.
The sources are scored based upon standard semantic similarity search and the distance metric 'l2'. The LLM then decides what is most relevant from that. As you might imagine, that's why LLMs are so useful, is because they actually find the relevant info, when semantic similarity cannot fully. That's why we fill the context with various info the let the LLM decide.
There's no easy way to extract which text/sources the LLM used, that's an area of active research. In some cases a simple ngram check may help, but it also might hurt for non-keyword related cases. There may be a way to back-prop through the model to see why it decided, but nobody has figured that out for auto-regressive case, only classification.
If the user has to verify the answer, best is to present the sources more cleanly like in our Enterprise h2oGPT https://h2o.ai/resources/video/enterprise-h2ogpt/ that shows full page references with highlighted text regions. But that doesn't really solve your problem when there are numerous documents.
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how does one get the highlighted text in the source when one clicks in the opensource version?
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There's no highlighted text in OSS version.
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How does one resolve the "detail": "File not allowed" error , when one clicks on the sources?
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^ #1512
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A further question: the LLM is unable to provide the information from the document which is given in a Table in the PDF. Even after asking specifically which table to see it is unable to give the results.
For example if one wants to know what all are the company's investments it is unable to list it down (See table 3B in the 2023 pdf).
Going forward, aim was to find out which new investments happened during the year which could be done by comparing annual reports of 2 years, the LLM is unable to to that even after pointing which 2 tables to compare.
Annual Reports: https://www.infoedge.in/InvestorRelations/IR_Annual_Report
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Related Issues (20)
- Is there a plan to incorporate a Knowledge Graph RAG Query Engine? HOT 1
- Option to place relavent documents chunks in system prompt instead of user prompt
- AutoGPT issue running on Local LLM HOT 2
- Running H2ogpt with Ollama inference Server HOT 2
- Unable to Programmatically Receive Sources with Prompts & Responses HOT 1
- h2o Windows installer "Web Search" and "Q/A" HOT 1
- Source Link opened in the same tab HOT 2
- KeyError: images_num_max HOT 3
- tab visibility flag like --visible_system_tab=False not working HOT 7
- Chunk should open on the same page from it has been taken HOT 2
- can't add personal data db/collection to auth.json HOT 6
- sidebar display control HOT 2
- h2ogpt tries to download model from hugging face when using local inference server HOT 2
- ModuleNotFoundError: No module named 'tenacity.asyncio' HOT 5
- Failed to load models HOT 1
- Traceback: 'NoneType' object is not iterable (gen.py, line 2435) HOT 1
- Gradio Client - Repeated WebSocket Connection Rejection (HTTP 403) HOT 1
- Can we query Qdrant directly without needing sources? HOT 4
- Offline mode is still attempting to fetch from HF HOT 4
- Use auto ingest with openai Api HOT 1
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