Load & save data & chat with LLMs
Project description
Pitchoune
A Python library on top of Polars to load & save (normal or streaming mode) data from files & chat with LLM.
Features
-
Load / save dataframe :
- Handle files types : xlsx, csv, tsv, jsonl
- Possibility to register your own file types (see custom_io_example)
-
Read / write stream :
- Handle files types : jsonl (soon csv/tsv)
- Call the decorated function for each row of the streamed file
- Inject each column as a parameter of the function
- Provide as parameters the current_row and total_row
- Can handle recovery (in case of error or process stopping) with the parameter "recover_from". Just set it to the output file path and it will use the right row for the read_stream function.
- Multiple outputs (see multiple_outputs_example.py)
-
Current workdir for filepaths : set PITCHOUNE_WORKDIR env variable
-
token replacement in filepaths
-
conf: token replacement in filepaths (read value from key in .conf file)
-
handle .conf file in PITCHOUNE_WORKDIR
-
Save to a file with human check option enabled :
- Open the file with the default editor
- Then wait for the user to review it & save it
-
Use chat :
- Ollama chat (see chat_example)
- OpenAI chat (you must then set OPENAI_API_KEY env variable)
Todo
- Testing
Project details
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