From 9b3e97cec7ff7c8ed190df2468af7220a8b161ca Mon Sep 17 00:00:00 2001 From: Teddy Yan Date: Tue, 22 Oct 2024 21:40:30 -0500 Subject: [PATCH 01/13] #692 integrate dspy into sql generation --- .../eval/dspy_modules/ask_generation.py | 33 ++++++++++ wren-ai-service/eval/optimized/.gitignore | 1 + wren-ai-service/pyproject.toml | 1 + .../pipelines/generation/sql_generation.py | 60 ++++++++++++++++++- 4 files changed, 92 insertions(+), 3 deletions(-) create mode 100644 wren-ai-service/eval/dspy_modules/ask_generation.py create mode 100644 wren-ai-service/eval/optimized/.gitignore diff --git a/wren-ai-service/eval/dspy_modules/ask_generation.py b/wren-ai-service/eval/dspy_modules/ask_generation.py new file mode 100644 index 000000000..c21db8863 --- /dev/null +++ b/wren-ai-service/eval/dspy_modules/ask_generation.py @@ -0,0 +1,33 @@ +import dspy + + +class AskGenerationSignatureV1(dspy.Signature): + """Given a user query that is ambiguous in nature, your task is to interpret the query in various plausible ways and \ +generate three SQL statements that could potentially answer each interpreted version of the queries and within-10-words summary. \ +Provide three different interpretations and corresponding SQL queries that reflect these interpretations. \ +Ensure that your SQL queries are diverse, covering a range of possible meanings behind the ambiguous query. \ + +The output should be in the following JSON format: + +{ + "results": [ + {"sql": , "summary": }, + {"sql": , "summary": }, + {"sql": , "summary": } + ] +} +""" + + question = dspy.InputField() + context = dspy.InputField(description="List of database schema documents") + answer = dspy.OutputField() + + +class AskGenerationV1(dspy.Module): + def __init__(self): + super().__init__() + self.generate_answer = dspy.ChainOfThought(AskGenerationSignatureV1) + + def forward(self, question, context): + prediction = self.generate_answer(question=question, context=context) + return dspy.Prediction(context=context, answer=prediction.answer) diff --git a/wren-ai-service/eval/optimized/.gitignore b/wren-ai-service/eval/optimized/.gitignore new file mode 100644 index 000000000..a6c57f5fb --- /dev/null +++ b/wren-ai-service/eval/optimized/.gitignore @@ -0,0 +1 @@ +*.json diff --git a/wren-ai-service/pyproject.toml b/wren-ai-service/pyproject.toml index 851d4c4c1..9e2a1528f 100644 --- a/wren-ai-service/pyproject.toml +++ b/wren-ai-service/pyproject.toml @@ -50,6 +50,7 @@ ipykernel = "==6.29.5" itables = "==2.2.1" gdown = "==5.2.0" nltk = "==3.9.1" +dspy-ai = "==2.5.15" [tool.poetry.group.demo.dependencies] requests = "==2.32.2" diff --git a/wren-ai-service/src/pipelines/generation/sql_generation.py b/wren-ai-service/src/pipelines/generation/sql_generation.py index e75f398e0..28c15192c 100644 --- a/wren-ai-service/src/pipelines/generation/sql_generation.py +++ b/wren-ai-service/src/pipelines/generation/sql_generation.py @@ -20,6 +20,12 @@ ) from src.utils import async_timer, timer from src.web.v1.services.ask import AskConfigurations +import dspy +import dspy.evaluate +import dspy.teleprompt +import os +import json +from eval.dspy_modules.ask_generation import AskGenerationV1 logger = logging.getLogger("wren-ai-service") @@ -110,20 +116,68 @@ def prompt( f"exclude: {orjson.dumps(exclude, option=orjson.OPT_INDENT_2).decode()}" ) logger.debug(f"configurations: {configurations}") - return prompt_builder.run( + result_dict = prompt_builder.run( query=query, documents=documents, exclude=exclude, alert=alert, instructions=construct_instructions(configurations), ) + context = [] + for doc in documents: + context.append(str(doc)) + result_dict['context'] = context + result_dict['question'] = query + return result_dict + +# Validation logic: check that the predicted answer is correct. +# Also check that the retrieved context does actually contain that answer. +def validate_context_and_answer(example: dspy.Example, pred : dspy.Example) -> bool: + answer_EM = dspy.evaluate.answer_exact_match(example, pred) + answer_PM = dspy.evaluate.answer_passage_match(example, pred) + return answer_EM and answer_PM + +def configure_llm_provider(llm: str, api_key: str) -> None: + dspy.settings.configure(lm=dspy.OpenAI(model=llm, api_key=api_key,max_tokens=4096)) @async_timer @observe(as_type="generation", capture_input=False) async def generate_sql(prompt: dict, generator: Any) -> dict: - logger.debug(f"prompt: {orjson.dumps(prompt, option=orjson.OPT_INDENT_2).decode()}") - return await generator.run(prompt=prompt.get("prompt")) + optimized_path = os.getenv("DSPY_OPTIMAZED_MODEL", "") + if not optimized_path: + logger.debug(f"prompt: {orjson.dumps(prompt, option=orjson.OPT_INDENT_2).decode()}") + return await generator.run(prompt=prompt.get("prompt")) + else: + # use dspy to evaluate + configure_llm_provider( + os.getenv("GENERATION_MODEL"), os.getenv("LLM_OPENAI_API_KEY") + ) + inputset = [dspy.Example( + context=str(prompt["context"]), + question=str(prompt["question"]), + answer="" + ).with_inputs("question", "context")] + evaluator = dspy.evaluate.Evaluate( + devset=inputset, + metric=validate_context_and_answer, + display_progress=True, + display_table=True, + return_outputs=True, + ) + module = AskGenerationV1() + module.load(optimized_path) + results = evaluator(module, metric=validate_context_and_answer) + + answers = None + for result in results: + if isinstance(result, list): + for item in result: + if isinstance(item, tuple): + if len(item) == 3: + cleaned_string = "".join(item[1].get('answer').split('\n')[1:-1]).strip() + answers = cleaned_string # orjson.loads(cleaned_string) + return {"replies":[answers]} @async_timer From 91cb9ea7907de2e38118ac6cfbe1fd2d899fb71f Mon Sep 17 00:00:00 2001 From: Teddy Yan Date: Wed, 23 Oct 2024 16:04:58 -0500 Subject: [PATCH 02/13] CompletionTokensDetails Type is not JSON serializable how to fix it --- .../src/pipelines/generation/sql_generation.py | 8 +++++++- 1 file changed, 7 insertions(+), 1 deletion(-) diff --git a/wren-ai-service/src/pipelines/generation/sql_generation.py b/wren-ai-service/src/pipelines/generation/sql_generation.py index ef96eed32..0e2484358 100644 --- a/wren-ai-service/src/pipelines/generation/sql_generation.py +++ b/wren-ai-service/src/pipelines/generation/sql_generation.py @@ -4,6 +4,7 @@ from pathlib import Path from typing import Any, Dict, List +from litellm import CompletionTokensDetails import orjson from hamilton import base from hamilton.experimental.h_async import AsyncDriver @@ -201,6 +202,11 @@ async def generate_sql(prompt: dict, generator: Any) -> dict: return {"replies":[answers]} +def default_serializer(obj: Any) -> Any: + if isinstance(obj, CompletionTokensDetails): + return f"{str(obj)}" + + @async_timer @observe(capture_input=False) async def post_process( @@ -209,7 +215,7 @@ async def post_process( project_id: str | None = None, ) -> dict: logger.debug( - f"generate_sql: {orjson.dumps(generate_sql, option=orjson.OPT_INDENT_2).decode()}" + f"generate_sql: {orjson.dumps(generate_sql, option=orjson.OPT_INDENT_2, default=default_serializer).decode()}" ) return await post_processor.run(generate_sql.get("replies"), project_id=project_id) From 27b8682c4a5142459e571c12da20e666eb8f9461 Mon Sep 17 00:00:00 2001 From: Teddy Yan Date: Wed, 30 Oct 2024 14:52:12 -0500 Subject: [PATCH 03/13] use wrenAI metrics --- wren-ai-service/eval/evaluation.py | 22 ++++++++- wren-ai-service/eval/prompt_optimizer.py | 59 +++++++++++++++++------- 2 files changed, 63 insertions(+), 18 deletions(-) diff --git a/wren-ai-service/eval/evaluation.py b/wren-ai-service/eval/evaluation.py index 72a750f2f..0d9cb68fa 100644 --- a/wren-ai-service/eval/evaluation.py +++ b/wren-ai-service/eval/evaluation.py @@ -2,6 +2,8 @@ import sys from pathlib import Path from typing import Tuple +import os +from prompt_optimizer import optimize, validate_context_and_answer, build_optimizing_module, optimizer_parameters, prepare_dataset, configure_llm_provider import dotenv from deepeval import evaluate @@ -57,6 +59,12 @@ def parse_args() -> Tuple[str]: action=argparse.BooleanOptionalAction, help="Whether use the LLM(OpenAI's gpt-4o-mini) to help check semantics of sqls to improve accuracy metrics", ) + parser.add_argument( + "--training-dataset", + "-T", + default=None, + help="Use the training dataset to build a dspy optimized module", + ) return parser.parse_args() @@ -149,7 +157,19 @@ def _average_score(self, meta: dict) -> None: ) evaluator = Evaluator(**metrics) - evaluator.eval(meta, predictions) + if args.training_dataset: + optimizer_parameters["evaluator"] = evaluator + optimizer_parameters["metrics"] = metrics + optimizer_parameters["meta"] = meta + optimizer_parameters["predictions"] = predictions + configure_llm_provider( + os.getenv("GENERATION_MODEL"), os.getenv("LLM_OPENAI_API_KEY") + ) + trainset, devset = prepare_dataset(args.training_dataset) + build_optimizing_module(trainset) + else: + evaluator.eval(meta, predictions) + langfuse_context.flush() diff --git a/wren-ai-service/eval/prompt_optimizer.py b/wren-ai-service/eval/prompt_optimizer.py index 3ffd1c38d..6049c752b 100644 --- a/wren-ai-service/eval/prompt_optimizer.py +++ b/wren-ai-service/eval/prompt_optimizer.py @@ -45,6 +45,13 @@ def parse_args() -> Tuple[str]: return parser.parse_args() +optimizer_parameters = { + "evaluator": None, + "metrics": None, + "meta": None, + "predictions": None +} + def configure_llm_provider(llm: str, api_key: str): dspy.settings.configure(lm=dspy.OpenAI(model=llm, api_key=api_key,max_tokens=4096)) @@ -55,7 +62,7 @@ def clean_sql(sql: str) -> str: def prepare_dataset(path: str, train_ratio: float = 0.5): - eval_dataset = parse_toml(path)["eval_dataset"] + eval_dataset = parse_toml(f"eval/dataset/{path}")["eval_dataset"] dspy_dataset = [] for data in eval_dataset: @@ -76,10 +83,23 @@ def prepare_dataset(path: str, train_ratio: float = 0.5): # Validation logic: check that the predicted answer is correct. # Also check that the retrieved context does actually contain that answer. def validate_context_and_answer(example, pred, trace=None): - answer_EM = dspy.evaluate.answer_exact_match(example, pred) - answer_PM = dspy.evaluate.answer_passage_match(example, pred) - return answer_EM and answer_PM - + if optimizer_parameters["predictions"] is None: + answer_EM = dspy.evaluate.answer_exact_match(example, pred) + answer_PM = dspy.evaluate.answer_passage_match(example, pred) + return answer_EM and answer_PM + else: + prediction = optimizer_parameters["predictions"][0] + prediction.input = example.question + prediction.expected_output = example.answer + prediction.context = example.context + prediction["type"] = "shallow" + prediction.actual_output = pred.answer + # reuse the first predict result to optimize the dspy module + optimizer_parameters["evaluator"].eval(optimizer_parameters["meta"], [prediction]) + sum_score = 0 + for metric in optimizer_parameters["metrics"].get("metrics"): + sum_score += metric.score + return sum_score def optimize( module: dspy.Module, @@ -91,6 +111,21 @@ def optimize( return optimizer.compile(module(), trainset=trainset) +def build_optimizing_module(trainset): + module = optimize( + AskGenerationV1, + dspy.teleprompt.BootstrapFewShot, + trainset=trainset, + metric=validate_context_and_answer, + ) + path = f"eval/optimized/{AskGenerationV1.__name__}_optimized_{datetime.now().strftime("%Y_%m_%d_%H%M%S")}.json" + directory = os.path.dirname(path) + if directory and not os.path.exists(directory): + os.makedirs(directory) + module.save(path) + return module + + if __name__ == "__main__": args = parse_args() path = f"eval/dataset/{args.file}" @@ -109,19 +144,9 @@ def optimize( if optimized_program_file: module = AskGenerationV1() - module.load(f"/home/teddy/github/text2sql/WrenAI/wren-ai-service/{optimized_program_file}") + module.load(f"eval/optimized/{optimized_program_file}") elif should_optimize: - module = optimize( - AskGenerationV1, - dspy.teleprompt.BootstrapFewShot, - trainset=trainset, - metric=validate_context_and_answer, - ) - path = f"eval/optimized/{AskGenerationV1.__name__}_optimized_{datetime.now().strftime("%Y_%m_%d_%H%M%S")}.json" - directory = os.path.dirname(path) - if directory and not os.path.exists(directory): - os.makedirs(directory) - module.save(path) + module = build_optimizing_module(trainset) else: module = AskGenerationV1() From 6669ba1a68853a2717bb6eb282cde5fdf5d90e00 Mon Sep 17 00:00:00 2001 From: Teddy Yan Date: Wed, 30 Oct 2024 15:55:05 -0500 Subject: [PATCH 04/13] use predict in sql_generate instead of evaluate --- wren-ai-service/pyproject.toml | 2 +- wren-ai-service/src/core/engine.py | 1 + .../pipelines/generation/sql_generation.py | 61 ++++++------------- 3 files changed, 19 insertions(+), 45 deletions(-) diff --git a/wren-ai-service/pyproject.toml b/wren-ai-service/pyproject.toml index 6fdcfd8e6..84b46701e 100644 --- a/wren-ai-service/pyproject.toml +++ b/wren-ai-service/pyproject.toml @@ -50,7 +50,7 @@ ipykernel = "==6.29.5" itables = "==2.2.1" gdown = "==5.2.0" nltk = "==3.9.1" -dspy-ai = "==2.5.15" +dspy-ai = "==2.5.20" [tool.poetry.group.demo.dependencies] requests = "==2.32.2" diff --git a/wren-ai-service/src/core/engine.py b/wren-ai-service/src/core/engine.py index 7b5fb28ba..07902ccc3 100644 --- a/wren-ai-service/src/core/engine.py +++ b/wren-ai-service/src/core/engine.py @@ -35,6 +35,7 @@ def _normalize_whitespace(s: str) -> str: _normalize_whitespace(result) .replace("\\n", " ") .replace("```sql", "") + .replace("```json", "") .replace('"""', "") .replace("'''", "") .replace("```", "") diff --git a/wren-ai-service/src/pipelines/generation/sql_generation.py b/wren-ai-service/src/pipelines/generation/sql_generation.py index 0e2484358..606bb0819 100644 --- a/wren-ai-service/src/pipelines/generation/sql_generation.py +++ b/wren-ai-service/src/pipelines/generation/sql_generation.py @@ -23,11 +23,10 @@ ) from src.utils import async_timer, timer from src.web.v1.services.ask import AskConfigurations -import dspy -import dspy.evaluate -import dspy.teleprompt + import os -import json +import dspy + from eval.dspy_modules.ask_generation import AskGenerationV1 logger = logging.getLogger("wren-ai-service") @@ -151,12 +150,6 @@ def prompt( result_dict['question'] = query return result_dict -# Validation logic: check that the predicted answer is correct. -# Also check that the retrieved context does actually contain that answer. -def validate_context_and_answer(example: dspy.Example, pred : dspy.Example) -> bool: - answer_EM = dspy.evaluate.answer_exact_match(example, pred) - answer_PM = dspy.evaluate.answer_passage_match(example, pred) - return answer_EM and answer_PM def configure_llm_provider(llm: str, api_key: str) -> None: dspy.settings.configure(lm=dspy.OpenAI(model=llm, api_key=api_key,max_tokens=4096)) @@ -164,42 +157,13 @@ def configure_llm_provider(llm: str, api_key: str) -> None: @async_timer @observe(as_type="generation", capture_input=False) -async def generate_sql(prompt: dict, generator: Any) -> dict: - optimized_path = os.getenv("DSPY_OPTIMAZED_MODEL", "") - if not optimized_path: +async def generate_sql(prompt: dict, generator: Any, dspy_module: Any) -> dict: + if not dspy_module: logger.debug(f"prompt: {orjson.dumps(prompt, option=orjson.OPT_INDENT_2).decode()}") return await generator.run(prompt=prompt.get("prompt")) else: - # use dspy to evaluate - configure_llm_provider( - os.getenv("GENERATION_MODEL"), os.getenv("LLM_OPENAI_API_KEY") - ) - inputset = [dspy.Example( - context=str(prompt["context"]), - question=str(prompt["question"]), - answer="" - ).with_inputs("question", "context")] - evaluator = dspy.evaluate.Evaluate( - devset=inputset, - metric=validate_context_and_answer, - display_progress=True, - display_table=True, - return_outputs=True, - ) - module = AskGenerationV1() - module.load(optimized_path) - results = evaluator(module, metric=validate_context_and_answer) - - answers = None - for result in results: - if isinstance(result, list): - for item in result: - if isinstance(item, tuple): - if len(item) == 3: - # remove prefix and suffix ```json` - cleaned_string = "".join(item[1].get('answer').split('\n')[1:-1]).strip() - answers = cleaned_string # orjson.loads(cleaned_string) - return {"replies":[answers]} + prediction = dspy_module(question=prompt["question"].as_string(), context=prompt["context"][0]) + return {"replies":[prediction.answer] } def default_serializer(obj: Any) -> Any: @@ -239,7 +203,6 @@ class GenerationResults(BaseModel): } } - class SQLGeneration(BasicPipeline): def __init__( self, @@ -247,6 +210,15 @@ def __init__( engine: Engine, **kwargs, ): + self.dspy_module = None + optimized_path = os.getenv("DSPY_OPTIMAZED_MODEL", "") + if not optimized_path: + # use dspy to evaluate + configure_llm_provider( + os.getenv("GENERATION_MODEL"), os.getenv("LLM_OPENAI_API_KEY") + ) + self.dspy_module = AskGenerationV1() + self.dspy_module.load(optimized_path) self._components = { "generator": llm_provider.get_generator( system_prompt=sql_generation_system_prompt, @@ -256,6 +228,7 @@ def __init__( template=sql_generation_user_prompt_template ), "post_processor": SQLGenPostProcessor(engine=engine), + "dspy_module": self.dspy_module } self._configs = { From e2247a3839787f8b00c58608e0348b1bd5bd4bd8 Mon Sep 17 00:00:00 2001 From: Teddy Yan Date: Sat, 2 Nov 2024 11:08:56 -0500 Subject: [PATCH 05/13] fixed two bugs --- wren-ai-service/pyproject.toml | 2 +- wren-ai-service/src/pipelines/generation/sql_generation.py | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/wren-ai-service/pyproject.toml b/wren-ai-service/pyproject.toml index 84b46701e..d2d3b5818 100644 --- a/wren-ai-service/pyproject.toml +++ b/wren-ai-service/pyproject.toml @@ -31,6 +31,7 @@ cachetools = "==5.5.0" pyyaml = "==6.0.2" pydantic-settings = "==2.5.2" google-auth = "==2.35.0" +dspy-ai = "==2.5.20" [tool.poetry.group.dev.dependencies] pre-commit = "==3.7.1" @@ -50,7 +51,6 @@ ipykernel = "==6.29.5" itables = "==2.2.1" gdown = "==5.2.0" nltk = "==3.9.1" -dspy-ai = "==2.5.20" [tool.poetry.group.demo.dependencies] requests = "==2.32.2" diff --git a/wren-ai-service/src/pipelines/generation/sql_generation.py b/wren-ai-service/src/pipelines/generation/sql_generation.py index 606bb0819..35efb880e 100644 --- a/wren-ai-service/src/pipelines/generation/sql_generation.py +++ b/wren-ai-service/src/pipelines/generation/sql_generation.py @@ -212,7 +212,7 @@ def __init__( ): self.dspy_module = None optimized_path = os.getenv("DSPY_OPTIMAZED_MODEL", "") - if not optimized_path: + if optimized_path: # use dspy to evaluate configure_llm_provider( os.getenv("GENERATION_MODEL"), os.getenv("LLM_OPENAI_API_KEY") From 1bc791ac3929a0e5d00d8584205fde0922b9ea89 Mon Sep 17 00:00:00 2001 From: Teddy Yan Date: Sat, 2 Nov 2024 14:32:56 -0500 Subject: [PATCH 06/13] remove import CompletionTokensDetails --- wren-ai-service/src/pipelines/common.py | 4 ++-- .../src/pipelines/generation/sql_generation.py | 8 +------- 2 files changed, 3 insertions(+), 9 deletions(-) diff --git a/wren-ai-service/src/pipelines/common.py b/wren-ai-service/src/pipelines/common.py index cc1253c0d..dedd21d88 100644 --- a/wren-ai-service/src/pipelines/common.py +++ b/wren-ai-service/src/pipelines/common.py @@ -181,8 +181,8 @@ async def _task(result: Dict[str, str]): { "sql": quoted_sql, "type": "DRY_RUN", - "error": addition["error_message"], - "correlation_id": addition["correlation_id"], + "error": addition.get("error_message", ""), + "correlation_id": addition.get("correlation_id", ""), } ) else: diff --git a/wren-ai-service/src/pipelines/generation/sql_generation.py b/wren-ai-service/src/pipelines/generation/sql_generation.py index f8ea678c6..916237251 100644 --- a/wren-ai-service/src/pipelines/generation/sql_generation.py +++ b/wren-ai-service/src/pipelines/generation/sql_generation.py @@ -3,7 +3,6 @@ from pathlib import Path from typing import Any, Dict, List -from litellm import CompletionTokensDetails import orjson from hamilton import base from hamilton.experimental.h_async import AsyncDriver @@ -166,11 +165,6 @@ async def generate_sql(prompt: dict, generator: Any, dspy_module: Any) -> dict: return {"replies":[prediction.answer] } -def default_serializer(obj: Any) -> Any: - if isinstance(obj, CompletionTokensDetails): - return f"{str(obj)}" - - @async_timer @observe(capture_input=False) async def post_process( @@ -179,7 +173,7 @@ async def post_process( project_id: str | None = None, ) -> dict: logger.debug( - f"generate_sql: {orjson.dumps(generate_sql, option=orjson.OPT_INDENT_2, default=default_serializer).decode()}" + f"generate_sql: {orjson.dumps(generate_sql, option=orjson.OPT_INDENT_2).decode()}" ) return await post_processor.run(generate_sql.get("replies"), project_id=project_id) From d0426a2b1e1789272e89136f4baf06d923b3db8c Mon Sep 17 00:00:00 2001 From: Teddy Yan Date: Thu, 7 Nov 2024 23:57:13 -0600 Subject: [PATCH 07/13] regenerate poetry.lock --- wren-ai-service/poetry.lock | 1936 ++++++++++++++++++++++------------- 1 file changed, 1212 insertions(+), 724 deletions(-) diff --git a/wren-ai-service/poetry.lock b/wren-ai-service/poetry.lock index f3a931970..095a92248 100644 --- a/wren-ai-service/poetry.lock +++ b/wren-ai-service/poetry.lock @@ -152,6 +152,25 @@ files = [ [package.dependencies] frozenlist = ">=1.1.0" +[[package]] +name = "alembic" +version = "1.14.0" +description = "A database migration tool for SQLAlchemy." +optional = false +python-versions = ">=3.8" +files = [ + {file = "alembic-1.14.0-py3-none-any.whl", hash = "sha256:99bd884ca390466db5e27ffccff1d179ec5c05c965cfefc0607e69f9e411cb25"}, + {file = "alembic-1.14.0.tar.gz", hash = "sha256:b00892b53b3642d0b8dbedba234dbf1924b69be83a9a769d5a624b01094e304b"}, +] + +[package.dependencies] +Mako = "*" +SQLAlchemy = ">=1.3.0" +typing-extensions = ">=4" + +[package.extras] +tz = 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diff --git a/wren-ai-service/eval/prompt_optimizer.py b/wren-ai-service/eval/dspy_modules/prompt_optimizer.py similarity index 97% rename from wren-ai-service/eval/prompt_optimizer.py rename to wren-ai-service/eval/dspy_modules/prompt_optimizer.py index 6049c752b..95b699c5c 100644 --- a/wren-ai-service/eval/prompt_optimizer.py +++ b/wren-ai-service/eval/dspy_modules/prompt_optimizer.py @@ -54,7 +54,7 @@ def parse_args() -> Tuple[str]: def configure_llm_provider(llm: str, api_key: str): - dspy.settings.configure(lm=dspy.OpenAI(model=llm, api_key=api_key,max_tokens=4096)) + dspy.settings.configure(lm=dspy.LM(model=llm, api_key=api_key)) def clean_sql(sql: str) -> str: @@ -84,6 +84,7 @@ def prepare_dataset(path: str, train_ratio: float = 0.5): # Also check that the retrieved context does actually contain that answer. def validate_context_and_answer(example, pred, trace=None): if optimizer_parameters["predictions"] is None: + # if we don't have metric from eval module, we use the default metric answer_EM = dspy.evaluate.answer_exact_match(example, pred) answer_PM = dspy.evaluate.answer_passage_match(example, pred) return answer_EM and answer_PM diff --git a/wren-ai-service/eval/evaluation.py b/wren-ai-service/eval/evaluation.py index 0d9cb68fa..57f24c632 100644 --- a/wren-ai-service/eval/evaluation.py +++ b/wren-ai-service/eval/evaluation.py @@ -3,8 +3,6 @@ from pathlib import Path from typing import Tuple import os -from prompt_optimizer import optimize, validate_context_and_answer, build_optimizing_module, optimizer_parameters, prepare_dataset, configure_llm_provider - import dotenv from deepeval import evaluate from deepeval.evaluate import TestResult @@ -12,6 +10,9 @@ from langfuse import Langfuse from langfuse.decorators import langfuse_context, observe +from dspy_modules.prompt_optimizer import build_optimizing_module, optimizer_parameters, prepare_dataset, configure_llm_provider + + sys.path.append(f"{Path().parent.resolve()}") import traceback diff --git a/wren-ai-service/src/pipelines/generation/sql_generation.py b/wren-ai-service/src/pipelines/generation/sql_generation.py index af1dfdafb..bea7c7f47 100644 --- a/wren-ai-service/src/pipelines/generation/sql_generation.py +++ b/wren-ai-service/src/pipelines/generation/sql_generation.py @@ -27,6 +27,7 @@ import dspy from eval.dspy_modules.ask_generation import AskGenerationV1 +from eval.dspy_modules.prompt_optimizer import configure_llm_provider logger = logging.getLogger("wren-ai-service") @@ -92,6 +93,7 @@ def prompt( prompt_builder: PromptBuilder, configurations: AskConfigurations | None = None, samples: List[Dict] | None = None, + dspy_module: dspy.Module = None ) -> dict: logger.debug(f"query: {query}") logger.debug(f"documents: {documents}") @@ -101,7 +103,18 @@ def prompt( logger.debug(f"configurations: {configurations}") if samples: logger.debug(f"samples: {samples}") - result_dict = prompt_builder.run( + + if dspy_module: + # use dspy to predict, the input is question and context + context = [] + dspy_inputs = {} + for doc in documents: + context.append(str(doc)) + dspy_inputs['context'] = context + dspy_inputs['question'] = query + return dspy_inputs + + return prompt_builder.run( query=query, documents=documents, exclude=exclude, @@ -110,28 +123,19 @@ def prompt( samples=samples, current_time=show_current_time(configurations.timezone), ) - context = [] - for doc in documents: - context.append(str(doc)) - result_dict['context'] = context - result_dict['question'] = query - return result_dict - - -def configure_llm_provider(llm: str, api_key: str) -> None: - dspy.settings.configure(lm=dspy.OpenAI(model=llm, api_key=api_key,max_tokens=4096)) @async_timer @observe(as_type="generation", capture_input=False) -async def generate_sql(prompt: dict, generator: Any, dspy_module: Any) -> dict: - if not dspy_module: - logger.debug(f"prompt: {orjson.dumps(prompt, option=orjson.OPT_INDENT_2).decode()}") - return await generator.run(prompt=prompt.get("prompt")) - else: - prediction = dspy_module(question=prompt["question"].as_string(), context=prompt["context"][0]) +async def generate_sql(prompt: dict, generator: Any, dspy_module: dspy.Module) -> dict: + if dspy_module: + # use dspy to predict, the input is question and context + prediction = dspy_module(question=prompt["question"].as_string(), context=" ".join(prompt["context"])) return {"replies":[prediction.answer] } + logger.debug(f"prompt: {orjson.dumps(prompt, option=orjson.OPT_INDENT_2).decode()}") + return await generator.run(prompt=prompt.get("prompt")) + @async_timer @observe(capture_input=False) From 119a26f700437288258eace78913a50ebecd5224 Mon Sep 17 00:00:00 2001 From: Teddy Yan Date: Sat, 9 Nov 2024 13:52:11 -0600 Subject: [PATCH 09/13] add README --- wren-ai-service/eval/README.md | 52 +++++++++++++++++++++++++ wren-ai-service/src/pipelines/common.py | 6 +-- 2 files changed, 55 insertions(+), 3 deletions(-) diff --git a/wren-ai-service/eval/README.md b/wren-ai-service/eval/README.md index 082f6b142..e5c3a3e1b 100644 --- a/wren-ai-service/eval/README.md +++ b/wren-ai-service/eval/README.md @@ -68,6 +68,58 @@ The evaluation results will be presented on Langfuse as follows: ![shallow_trace_example](../docs/imgs/shallow_trace_example.png) + +## How to use Dspy in Wren AI +### Step 1: Generate evaluation dataset + +Please use eval.py and the spider2 v1 dataset to train an optimized dspy module (https://github.com/taoyds/spider/tree/master/evaluation_examples/examples) +The `prediction_eval_ask_9df57d69-250c-4a10-b6a5-6595509fed6b_2024_10_23_132136.toml` is a predict dataset generated without dspy + +``` +wren-ai-service/eval/dspy_modules/prompt_optimizer.py --training-dataset spider_car_1_eval_dataset.toml --file prediction_eval_ask_9df57d69-250c-4a10-b6a5-6595509fed6b_2024_10_23_132136.toml +``` + +output: `eval/optimized/AskGenerationV1_optimized_2024_10_21_181426.json` This is the module + +### Step 2: Use dspy in pipeline + +1. set an environment variable `DSPY_OPTIMAZED_MODEL` which is the trained dspy module above step + +``` +export DSPY_OPTIMAZED_MODEL=eval/optimized/AskGenerationV1_optimized_2024_10_21_181426.json +``` + +2. start predict pipeline and get the predicted result + +``` +just predict eval/dataset/spider_car_1_eval_dataset.toml +``` + +The output is genereated by Dspy + +``` +outputs/predictions/prediction_eval_ask_f5103405-09b2-448c-829d-cedd3c3b12d0_2024_10_22_184950.toml + +``` + +### Step 3: (Optional) + +1. Start to evaluate the predicted result + +``` +just eval prediction_eval_ask_f5103405-09b2-448c-829d-cedd3c3b12d0_2024_10_22_184950.toml + +``` + +2. Compare the two results with Dspy and without Dspy + +![image](https://github.com/user-attachments/assets/34ee0c25-dcdc-45b7-8cc0-cb2fe55211af) + + +Notes: +wren-ai-service/eval/dspy_modules/prompt_optimizer.py can be improved by incorporating additional training examples or use other modules in dspy + + ## Terms This section describes the terms used in the evaluation framework: diff --git a/wren-ai-service/src/pipelines/common.py b/wren-ai-service/src/pipelines/common.py index 8b91c4e52..69e2fbe79 100644 --- a/wren-ai-service/src/pipelines/common.py +++ b/wren-ai-service/src/pipelines/common.py @@ -175,7 +175,7 @@ async def _task(result: Dict[str, str]): valid_generation_results.append( { "sql": quoted_sql, - "correlation_id": addition.get("correlation_id", ""), + "correlation_id": addition.get("correlation_id", "") if isinstance(addition, dict) else addition } ) else: @@ -183,8 +183,8 @@ async def _task(result: Dict[str, str]): { "sql": quoted_sql, "type": "DRY_RUN", - "error": addition.get("error_message", ""), - "correlation_id": addition.get("correlation_id", ""), + "error": addition.get("error_message", "") if isinstance(addition, dict) else addition, + "correlation_id": addition.get("correlation_id", "") if isinstance(addition, dict) else addition } ) else: From e06dd8cd9185c8656648f7a33fdaea02df7e43f6 Mon Sep 17 00:00:00 2001 From: Teddy Yan Date: Tue, 12 Nov 2024 17:25:56 -0600 Subject: [PATCH 10/13] updated README --- wren-ai-service/eval/README.md | 25 ++++++++++++++++--------- 1 file changed, 16 insertions(+), 9 deletions(-) diff --git a/wren-ai-service/eval/README.md b/wren-ai-service/eval/README.md index e5c3a3e1b..0370643fd 100644 --- a/wren-ai-service/eval/README.md +++ b/wren-ai-service/eval/README.md @@ -69,19 +69,26 @@ The evaluation results will be presented on Langfuse as follows: ![shallow_trace_example](../docs/imgs/shallow_trace_example.png) -## How to use Dspy in Wren AI -### Step 1: Generate evaluation dataset +## How to use DSPy in Wren AI +### Step 1: Generate optimized DSPy module -Please use eval.py and the spider2 v1 dataset to train an optimized dspy module (https://github.com/taoyds/spider/tree/master/evaluation_examples/examples) -The `prediction_eval_ask_9df57d69-250c-4a10-b6a5-6595509fed6b_2024_10_23_132136.toml` is a predict dataset generated without dspy +1. Prepare a predict result and training dataset +Generate a predict dataset without dspy. It's used to initialized evaluation pipeline (Metrics). Refer to https://github.com/Canner/WrenAI/blob/main/wren-ai-service/eval/README.md#eval-dataset-preparationif-using-spider-10-dataset +``` +just predict +``` +The output is a predict result. such as `prediction_eval_ask_9df57d69-250c-4a10-b6a5-6595509fed6b_2024_10_23_132136.toml` + +2. Train an DSPy module. +Using above predict result and training dataset to train a DSPy module. ``` wren-ai-service/eval/dspy_modules/prompt_optimizer.py --training-dataset spider_car_1_eval_dataset.toml --file prediction_eval_ask_9df57d69-250c-4a10-b6a5-6595509fed6b_2024_10_23_132136.toml ``` -output: `eval/optimized/AskGenerationV1_optimized_2024_10_21_181426.json` This is the module +output: `eval/optimized/AskGenerationV1_optimized_2024_10_21_181426.json` This is the trained DSPy module -### Step 2: Use dspy in pipeline +### Step 2: Use the optimized module in pipeline 1. set an environment variable `DSPY_OPTIMAZED_MODEL` which is the trained dspy module above step @@ -95,7 +102,7 @@ export DSPY_OPTIMAZED_MODEL=eval/optimized/AskGenerationV1_optimized_2024_10_21_ just predict eval/dataset/spider_car_1_eval_dataset.toml ``` -The output is genereated by Dspy +The output is genereated by DSPy ``` outputs/predictions/prediction_eval_ask_f5103405-09b2-448c-829d-cedd3c3b12d0_2024_10_22_184950.toml @@ -104,14 +111,14 @@ outputs/predictions/prediction_eval_ask_f5103405-09b2-448c-829d-cedd3c3b12d0_202 ### Step 3: (Optional) -1. Start to evaluate the predicted result +1. Evaluate the DSPy prodiction result ``` just eval prediction_eval_ask_f5103405-09b2-448c-829d-cedd3c3b12d0_2024_10_22_184950.toml ``` -2. Compare the two results with Dspy and without Dspy +2. Compare the two results with DSPy and without DSPy ![image](https://github.com/user-attachments/assets/34ee0c25-dcdc-45b7-8cc0-cb2fe55211af) From 0d9646763d0b89b9f963c170ad266f4d9b8ad017 Mon Sep 17 00:00:00 2001 From: Teddy Yan Date: Tue, 12 Nov 2024 17:35:10 -0600 Subject: [PATCH 11/13] updated README 2 --- wren-ai-service/src/pipelines/common.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/wren-ai-service/src/pipelines/common.py b/wren-ai-service/src/pipelines/common.py index 69e2fbe79..1e7b71c3e 100644 --- a/wren-ai-service/src/pipelines/common.py +++ b/wren-ai-service/src/pipelines/common.py @@ -175,7 +175,7 @@ async def _task(result: Dict[str, str]): valid_generation_results.append( { "sql": quoted_sql, - "correlation_id": addition.get("correlation_id", "") if isinstance(addition, dict) else addition + "correlation_id": addition.get("correlation_id", "") } ) else: From ff61bed27af4d81d2ad5192b32bd6ef5a06fae87 Mon Sep 17 00:00:00 2001 From: Teddy Yan Date: Tue, 12 Nov 2024 17:35:43 -0600 Subject: [PATCH 12/13] updated README 3 --- wren-ai-service/src/pipelines/common.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/wren-ai-service/src/pipelines/common.py b/wren-ai-service/src/pipelines/common.py index 1e7b71c3e..cc093c084 100644 --- a/wren-ai-service/src/pipelines/common.py +++ b/wren-ai-service/src/pipelines/common.py @@ -175,7 +175,7 @@ async def _task(result: Dict[str, str]): valid_generation_results.append( { "sql": quoted_sql, - "correlation_id": addition.get("correlation_id", "") + "correlation_id": addition.get("correlation_id", ""), } ) else: From fd9915d63c46880d9579d416cd7d40a2ac234b9f Mon Sep 17 00:00:00 2001 From: Teddy Yan Date: Tue, 12 Nov 2024 17:58:53 -0600 Subject: [PATCH 13/13] move dspy out of eval --- wren-ai-service/{eval => }/dspy_modules/__init__.py | 0 .../{eval => }/dspy_modules/ask_generation.py | 0 .../{eval => }/dspy_modules/prompt_optimizer.py | 10 +++++++--- .../src/pipelines/generation/sql_generation.py | 4 ++-- 4 files changed, 9 insertions(+), 5 deletions(-) rename wren-ai-service/{eval => }/dspy_modules/__init__.py (100%) rename wren-ai-service/{eval => }/dspy_modules/ask_generation.py (100%) rename wren-ai-service/{eval => }/dspy_modules/prompt_optimizer.py (95%) diff --git a/wren-ai-service/eval/dspy_modules/__init__.py b/wren-ai-service/dspy_modules/__init__.py similarity index 100% rename from wren-ai-service/eval/dspy_modules/__init__.py rename to wren-ai-service/dspy_modules/__init__.py diff --git a/wren-ai-service/eval/dspy_modules/ask_generation.py b/wren-ai-service/dspy_modules/ask_generation.py similarity index 100% rename from wren-ai-service/eval/dspy_modules/ask_generation.py rename to wren-ai-service/dspy_modules/ask_generation.py diff --git a/wren-ai-service/eval/dspy_modules/prompt_optimizer.py b/wren-ai-service/dspy_modules/prompt_optimizer.py similarity index 95% rename from wren-ai-service/eval/dspy_modules/prompt_optimizer.py rename to wren-ai-service/dspy_modules/prompt_optimizer.py index 95b699c5c..51e3c4ae4 100644 --- a/wren-ai-service/eval/dspy_modules/prompt_optimizer.py +++ b/wren-ai-service/dspy_modules/prompt_optimizer.py @@ -13,8 +13,12 @@ sys.path.append(f"{Path().parent.resolve()}") import src.utils as utils -from eval.dspy_modules.ask_generation import AskGenerationV1 -from eval.utils import parse_toml +from dspy_modules.ask_generation import AskGenerationV1 +from tomlkit import parse + +def parse_toml(path: str) -> dict[str, any]: + with open(path) as file: + return parse(file.read()) def parse_args() -> Tuple[str]: @@ -62,7 +66,7 @@ def clean_sql(sql: str) -> str: def prepare_dataset(path: str, train_ratio: float = 0.5): - eval_dataset = parse_toml(f"eval/dataset/{path}")["eval_dataset"] + eval_dataset = parse_toml(f"{path}")["eval_dataset"] dspy_dataset = [] for data in eval_dataset: diff --git a/wren-ai-service/src/pipelines/generation/sql_generation.py b/wren-ai-service/src/pipelines/generation/sql_generation.py index bea7c7f47..192914829 100644 --- a/wren-ai-service/src/pipelines/generation/sql_generation.py +++ b/wren-ai-service/src/pipelines/generation/sql_generation.py @@ -26,8 +26,8 @@ import os import dspy -from eval.dspy_modules.ask_generation import AskGenerationV1 -from eval.dspy_modules.prompt_optimizer import configure_llm_provider +from dspy_modules.ask_generation import AskGenerationV1 +from dspy_modules.prompt_optimizer import configure_llm_provider logger = logging.getLogger("wren-ai-service")