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feat: ✨ OpenAI parser #245
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3aba61f
feat: :sparkles: OpenAI parser
chadell a4eec2e
refinement in logic
chadell e7ace76
logic refinement
chadell c98bf4c
Update README.md
chadell 0f9dcf6
Update circuit_maintenance_parser/parser.py
chadell 5eec491
improve question
chadell 6094f3f
make more explicit the text parsing
chadell 86f8154
Automate token management for local tests
chadell de559e8
Make openai library an extra
chadell 38c43bf
Adopt OpenAI library changes
chadell 1656bef
fix mypy
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Original file line number | Diff line number | Diff line change |
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@@ -0,0 +1,51 @@ | ||
"""OpenAI Parser.""" | ||
import os | ||
import logging | ||
import json | ||
from typing import List, Optional | ||
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import openai | ||
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from circuit_maintenance_parser.parser import LLM | ||
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logger = logging.getLogger(__name__) | ||
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class OpenAIParser(LLM): | ||
"""Notifications Parser powered by OpenAI ChatGPT.""" | ||
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def get_llm_response(self, content) -> Optional[List]: | ||
"""Get LLM processing from OpenAI.""" | ||
openai.api_key = os.getenv("OPENAI_TOKEN") | ||
openai_model = os.getenv("OPENAI_MODEL", "gpt-3.5-turbo") | ||
try: | ||
response = openai.ChatCompletion.create( | ||
model=openai_model, | ||
messages=[ | ||
{ | ||
"role": "system", | ||
"content": self._llm_question, | ||
}, | ||
{ | ||
"role": "user", | ||
"content": content, | ||
}, | ||
], | ||
) | ||
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# TODO: Maybe asking again about the generated response could refine it | ||
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except openai.error.InvalidRequestError as err: | ||
logger.error(err) | ||
return None | ||
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logger.info("Used OpenAI tokens: %s", response["usage"]) | ||
generated_text = response.choices[0].message["content"] | ||
logger.info("Response from LLM: %s", generated_text) | ||
try: | ||
return json.loads(generated_text) | ||
except ValueError as err: | ||
logger.error(err) | ||
return None | ||
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return None |
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What purpose does this method serve? When would subclasses need/want to override it?
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I made it more explicit why it is used. the final parsers could have a different way to decode bytes to string