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Dat Tran
Offline, last seen 3 months ago
Joined September 25, 2024
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Dat Tran
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Gpt-4o

Can we use query engine with GPT-4o yet
5 comments
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if model is gpt-3.5-turbo it works fine but if I have it as gpt-4 like above it gives me
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"I'm unable to provide the current status of property owned by DONAHOO, MECHELLE as I cannot execute SQL queries or access live databases to retrieve real-time data. My capabilities are limited to providing information, answering questions, and generating responses based on the knowledge I was trained on up until my last update in 2023. If you're looking for specific details about property ownership or status, I recommend checking with local property records, a real estate database, or a legal professional who can access up-to-date information. If you have any other questions or need further assistance, feel free to ask!"
2 comments
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I just want to pop in and complain real quick, I had an absolutely horrible time following tutorials. Half of the guides are outdated and all the github file references are 404. I know it's April's fool but this is not very funny.
10 comments
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Hello again, I have a question about DocumentSummaryIndex
8 comments
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I recently updated llama-index-llms-openai 0.1.26 to use 4o-mini. On openai's website they said CONTEXT WINDOW 128k tokens but when I tried to set the limit it said
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Error code: 400 - {\'error\': {\'message\': \'max_tokens is too large: 120000. This model supports at most 16384 completion tokens, whereas you provided 120000.\', \'type\': \'invalid_request_error\', \'param\': \'max_tokens\', \'code\': None}}\n'}
8 comments
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Hello, I would like to ask for some help on updating prompt
https://docs.llamaindex.ai/en/stable/examples/prompts/prompt_mixin/#put-into-query-engine-get-response
according to this guide you can do query_engine.update_prompts() to update prompt but they use the high level query_engine = index.as_query_engine(response_mode="tree_summarize")
What I am using is
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query_engine = SQLTableRetrieverQueryEngine(
    sql_database,
    obj_index.as_retriever(similarity_top_k=1),
    llm=function_llm,
)

and
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query_engine.update_prompts(
    {"response_synthesizer:summary_template": qa_prompt_tmpl}
)
returns
ValueError: Module response_synthesizer not found.
What is the correct key for this update?
32 comments
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