Comments (3)
Haste171
commented on June 6, 2024
Reducing the amount of sources used sometimes helps with this problem, not exactly sure why it happens but it's mainly thought to occur because the retrievalchain inputted to much context in a chunk to the llm
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Haste171
commented on June 6, 2024
You can also use gpt-4 with the 8k token limit if you have it
from langchain-chatbot.
Haste171
commented on June 6, 2024
Use the map_reduce method
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Related Issues (19)
- Please add compatibility with offline models HOT 9
- Typo in the qa prompt HOT 1
- pinecone key not recognized HOT 2
- Is there a tutorial for using it through docker? HOT 4
- ImportError: cannot import name 'CONDENSE_PROMPT' from 'templates.condense_prompt' HOT 1
- chromadb.errors.NoIndexException HOT 3
- I need to get the pinecone id HOT 1
- chat history in streamlit doesn't seem to work HOT 5
- It seems the template is not taken into account HOT 2
- sh: cls: command not found HOT 2
- Sweep: Convert Langchain Chatbot to an API HOT 1
- Thank you! Is chat interface available yet? I see there is a snapshot :-) HOT 2
- Sweep: Update readme to include info about usage of poetry HOT 2
- Update Langchain Chatbot HOT 3
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- error while installing via pip install -r requirements.txt HOT 5
- Rate limit while ingesting HOT 1
- Unable to use the chat function
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