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Merge pull request #249 from tigergraph/GML-1767-watsonx-integration
Gml 1767 watsonx integration
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,50 @@ | ||
| import logging | ||
| import os | ||
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| from common.llm_services import LLM_Model | ||
| from common.logs.log import req_id_cv | ||
| from common.logs.logwriter import LogWriter | ||
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| logger = logging.getLogger(__name__) | ||
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| class IBMWatsonX(LLM_Model): | ||
| def __init__(self, config): | ||
| super().__init__(config) | ||
| for auth_detail in config["authentication_configuration"].keys(): | ||
| os.environ[auth_detail] = config["authentication_configuration"][ | ||
| auth_detail | ||
| ] | ||
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| from langchain_ibm import ChatWatsonx | ||
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| model_name = config["llm_model"] | ||
| self.llm = ChatWatsonx( | ||
| params={"temperature": config["model_kwargs"]["temperature"], "max_new_tokens": config["model_kwargs"]["max_new_tokens"]}, | ||
| url=config["authentication_configuration"]["WATSONX_URL"], | ||
| apikey=config["authentication_configuration"]["WATSONX_APIKEY"], | ||
| model_id=model_name, | ||
| project_id=config["model_kwargs"]["project_id"] | ||
| ) | ||
| self.prompt_path = config["prompt_path"] | ||
| LogWriter.info( | ||
| f"request_id={req_id_cv.get()} instantiated WatsonX model_name={model_name}" | ||
| ) | ||
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| @property | ||
| def map_question_schema_prompt(self): | ||
| return self._read_prompt_file(self.prompt_path + "map_question_to_schema.txt") | ||
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| @property | ||
| def generate_function_prompt(self): | ||
| return self._read_prompt_file(self.prompt_path + "generate_function.txt") | ||
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| @property | ||
| def entity_relationship_extraction_prompt(self): | ||
| return self._read_prompt_file( | ||
| self.prompt_path + "entity_relationship_extraction.txt" | ||
| ) | ||
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| @property | ||
| def model(self): | ||
| return self.llm |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,59 @@ | ||
| import os | ||
| import unittest | ||
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| import pytest | ||
| from fastapi.testclient import TestClient | ||
| from test_service import CommonTests | ||
| import wandb | ||
| import parse_test_config | ||
| import sys | ||
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| @pytest.mark.skip(reason="All tests in this class are currently skipped by the pipeline, but used by the LLM regression tests.") | ||
| class TestWithWatsonX(CommonTests, unittest.TestCase): | ||
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| @classmethod | ||
| def setUpClass(cls) -> None: | ||
| from main import app | ||
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| cls.client = TestClient(app) | ||
| cls.llm_service = "mistralai/mistral-large" | ||
| if USE_WANDB: | ||
| cls.table = wandb.Table(columns=columns) | ||
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| def test_config_read(self): | ||
| resp = self.client.get("/") | ||
| self.assertEqual(resp.json()["config"], "mistral-large") | ||
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| if __name__ == "__main__": | ||
| parser = parse_test_config.create_parser() | ||
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| args = parser.parse_known_args()[0] | ||
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| USE_WANDB = args.wandb | ||
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| schema = args.schema | ||
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| if USE_WANDB: | ||
| columns = [ | ||
| "LLM_Service", | ||
| "Dataset", | ||
| "Question Type", | ||
| "Question Theme", | ||
| "Question", | ||
| "True Answer", | ||
| "True Function Call", | ||
| "Retrieved Natural Language Answer", | ||
| "Retrieved Answer", | ||
| "Answer Source", | ||
| "Answer Correct", | ||
| "Answered Question", | ||
| "Response Time (seconds)", | ||
| ] | ||
| CommonTests.setUpClass(schema) | ||
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| # clean up args before unittesting | ||
| del sys.argv[1:] | ||
| unittest.main() |