Louis-François Bouchard Omar Solano Omar Solano commited on
Commit
897ca82
·
unverified ·
1 Parent(s): 257aaef

Add time data (#49)

Browse files

* Openai activeloop data (#37)

* adding openai and activeloop data

* fixing issues with names

* concurrency

* black

* black

* revert to gradio3.50 for concurrency

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Co-authored-by: Omar Solano <[email protected]>

* ensure gradio version for HF

* Updates to files

* Push to advanced rag course

* edits to prompt

* Add datetime to mongodb logs

---------

Co-authored-by: Omar Solano <[email protected]>
Co-authored-by: Omar Solano <[email protected]>

Files changed (1) hide show
  1. app.py +8 -2
app.py CHANGED
@@ -2,6 +2,7 @@ import logging
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  import os
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  from typing import Optional
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  import time
 
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  import gradio as gr
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  import pandas as pd
@@ -57,14 +58,19 @@ logging.basicConfig(level=logging.INFO)
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  def save_completion(completion: Completion, question: gr.Textbox):
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  collection = "completion_data-hf"
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  completion_json = completion.to_json(
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  columns_to_ignore=["embedding", "similarity", "similarity_to_answer"]
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  )
 
 
 
 
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  try:
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  cfg.mongo_db[collection].insert_one(completion_json)
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  logger.info("Completion saved to db")
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- except:
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- logger.info("Something went wrong logging completion to db")
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  def log_likes(completion: Completion, like_data: gr.LikeData):
 
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  import os
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  from typing import Optional
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  import time
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+ from datetime import datetime
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  import gradio as gr
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  import pandas as pd
 
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  def save_completion(completion: Completion, question: gr.Textbox):
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  collection = "completion_data-hf"
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+ # Convert completion to JSON and ignore certain columns
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  completion_json = completion.to_json(
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  columns_to_ignore=["embedding", "similarity", "similarity_to_answer"]
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  )
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+
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+ # Add the current date and time to the JSON
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+ completion_json["timestamp"] = datetime.utcnow().isoformat()
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+
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  try:
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  cfg.mongo_db[collection].insert_one(completion_json)
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  logger.info("Completion saved to db")
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+ except Exception as e:
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+ logger.info(f"Something went wrong logging completion to db: {e}")
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  def log_likes(completion: Completion, like_data: gr.LikeData):