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Store Results as JSON file + Fix Providers Supported to OpenAI, Azure, and Huggingface #39

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Store Results as JSON file + Fix Providers Supported to OpenAI, Azure, and Huggingface #39

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f6e678d
Fix Other Providers Issue
saikolasani Jun 28, 2024
dc59a83
Stores queries ran as a json file
saikolasani Jun 28, 2024
c0b7d14
Fix issue with providers
saikolasani Jun 28, 2024
74ff64b
Fix formatting
saikolasani Jun 28, 2024
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22 changes: 13 additions & 9 deletions ragulate/pipelines/query_pipeline.py
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Original file line number Diff line number Diff line change
Expand Up @@ -2,17 +2,16 @@
import signal
import time
from typing import Any, Dict, List, Optional
import pandas as pd

from tqdm import tqdm
from trulens_eval import Tru, TruChain
from trulens_eval.feedback.provider import (
AzureOpenAI,
Bedrock,
Huggingface,
Langchain,
LiteLLM,
OpenAI,
)
from trulens_eval.feedback.provider import OpenAI
from trulens_eval.feedback.provider.base import LLMProvider
from trulens_eval.schema.feedback import FeedbackMode, FeedbackResultStatus

Expand Down Expand Up @@ -116,13 +115,24 @@ def start_evaluation(self):
self._tru.start_evaluator(disable_tqdm=True)
self._evaluation_running = True

def export_results(self):
records = self._tru.get_records_and_feedbacks()
data = [record.__dict__ for record in records]

# Convert to DataFrame
df = pd.DataFrame(data)

# Export to JSON
df.to_json('results.json', orient='records')

def stop_evaluation(self, loc: str):
if self._evaluation_running:
try:
logger.debug(f"Stopping evaluation from: {loc}")
self._tru.stop_evaluator()
self._evaluation_running = False
self._tru.delete_singleton()
self.export_results()
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@epinzur epinzur Jun 28, 2024

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we probably only want this if the test is complete... not if someone ctrl-c in the middle of a run.

except Exception as e:
logger.error(f"issue stopping evaluator: {e}")
finally:
Expand Down Expand Up @@ -158,12 +168,6 @@ def get_provider(self) -> LLMProvider:
return OpenAI(model_engine=model_name)
elif llm_provider == "azureopenai":
return AzureOpenAI(deployment_name=model_name)
elif llm_provider == "bedrock":
return Bedrock(model_id=model_name)
elif llm_provider == "litellm":
return LiteLLM(model_engine=model_name)
elif llm_provider == "Langchain":
return Langchain(model_engine=model_name)
elif llm_provider == "huggingface":
return Huggingface(name=model_name)
else:
Expand Down