A minimalistic LLM agent for Exploratory Data Analysis (EDA) using pandas library
Task: given a CSV or a XLSX file, respond to user's query about this table by generating a python code and executing it.
- Using LangChain routers/tagging, a prompt type will be established: to produce a plot or to compute the numerical values.
- The GPT model breaks down the user's request into several subtasks.
- The LLM generates code based on these subtasks.
- The code is executed using the python REPL.
- If the REPL throws an error, GPT will begin debugging until resolved.
- The result is the string output of the code 'print(result)' + optionally, saved image with a plot.
Query example: 'Find correlation between GDP and happiness index, subtract 0.4 and multiply by 1e6.'
1 maintainer
Release files for agenttobenamed 0.1.14
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
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| agenttobenamed-0.1.14.tar.gz | 9.2 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| agenttobenamed-0.1.14-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 19.6 kB
Release files / agenttobenamed-0.1.14.tar.gz
| Download URL | agenttobenamed-0.1.14.tar.gz |
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| Size | 9.2 kB |
| Tags | Source |
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Release files / agenttobenamed-0.1.14-py3-none-any.whl
| Download URL | agenttobenamed-0.1.14-py3-none-any.whl |
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| Size | 10.4 kB |
| Tags | Python 3 |
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