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This commit is contained in:
Anibal Angulo
2026-02-23 17:23:22 +00:00
parent fd07f4a3e3
commit 099f6a50d1
7 changed files with 109 additions and 35 deletions
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1
.gitignore vendored
View File

@@ -216,3 +216,4 @@ __marimo__/
.streamlit/secrets.toml .streamlit/secrets.toml
ref/ ref/
tmp/

6
pyproject.toml
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@@ -24,3 +24,9 @@ va-evaluator = "va_evaluator.cli:app"
[build-system] [build-system]
requires = ["uv_build>=0.8.3,<0.9.0"] requires = ["uv_build>=0.8.3,<0.9.0"]
build-backend = "uv_build" build-backend = "uv_build"
[dependency-groups]
dev = [
"ruff>=0.15.2",
"ty>=0.0.18",
]

8
src/va_evaluator/config.py
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@@ -22,8 +22,8 @@ class IndexSettings(BaseModel):
class AgentSettings(BaseModel): class AgentSettings(BaseModel):
name: str = "default" name: str = "default"
language_model: str = "gemini-2.0-flash" language_model: str = "gemini-2.5-flash"
embedding_model: str = "text-embedding-004" embedding_model: str = "gemini-embedding-001"
class BigQuerySettings(BaseModel): class BigQuerySettings(BaseModel):
@@ -41,7 +41,9 @@ class BigQuerySettings(BaseModel):
class Settings(BaseSettings): class Settings(BaseSettings):
model_config = SettingsConfigDict(env_nested_delimiter="__") model_config = SettingsConfigDict(
env_nested_delimiter="__", env_file=".env", extra="ignore"
)
project_id: str project_id: str
location: str = "us-central1" location: str = "us-central1"

14
src/va_evaluator/keypoint_metrics_evaluator.py
View File

@@ -186,9 +186,7 @@ class KeypointRAGEvaluator:
generated_answer: str, generated_answer: str,
keypoints: list[str], keypoints: list[str],
) -> tuple[dict[str, float], list[dict]]: ) -> tuple[dict[str, float], list[dict]]:
keypoints_list = "\n".join( keypoints_list = "\n".join([f"{i + 1}. {kp}" for i, kp in enumerate(keypoints)])
[f"{i + 1}. {kp}" for i, kp in enumerate(keypoints)]
)
prompt = EVALUATE_KEYPOINTS_PROMPT.format( prompt = EVALUATE_KEYPOINTS_PROMPT.format(
generated_answer=generated_answer, generated_answer=generated_answer,
keypoints_list=keypoints_list, keypoints_list=keypoints_list,
@@ -343,14 +341,13 @@ def load_data_from_bigquery(
df.dropna(subset=["input", "expected_output", "response"], inplace=True) df.dropna(subset=["input", "expected_output", "response"], inplace=True)
console.print(f"Loaded {len(df)} rows for evaluation.") console.print(f"Loaded {len(df)} rows for evaluation.")
if df.empty: if df.empty:
console.print( console.print("[bold yellow]Warning: No data found in BigQuery.[/bold yellow]")
"[bold yellow]Warning: No data found in BigQuery.[/bold yellow]"
)
return df return df
# --- Core Logic --- # --- Core Logic ---
def evaluate( def evaluate(
input_file: str | None = None, input_file: str | None = None,
output_file: str | None = None, output_file: str | None = None,
@@ -429,9 +426,7 @@ def evaluate(
) )
) )
else: else:
console.print( console.print(f"[bold red]Error evaluating row: {e}[/bold red]")
f"[bold red]Error evaluating row: {e}[/bold red]"
)
all_results.append( all_results.append(
{ {
"query": row["input"], "query": row["input"],
@@ -555,4 +550,3 @@ def evaluate(
f"[bold red]An error occurred while saving to BigQuery: {e}[/bold red]" f"[bold red]An error occurred while saving to BigQuery: {e}[/bold red]"
) )
raise typer.Exit(code=1) raise typer.Exit(code=1)

1
src/va_evaluator/search_metrics_evaluator.py
View File

@@ -253,4 +253,3 @@ def evaluate(
f"[bold red]An error occurred while saving to BigQuery: {e}[/bold red]" f"[bold red]An error occurred while saving to BigQuery: {e}[/bold red]"
) )
raise typer.Exit(code=1) raise typer.Exit(code=1)

49
src/va_evaluator/synthetic_question_generator.py
View File

@@ -4,12 +4,12 @@ import random
import pandas as pd import pandas as pd
import typer import typer
import vertexai from google import genai
from google.cloud import storage from google.cloud import storage
from google.genai import types
from pydantic import BaseModel from pydantic import BaseModel
from rich.console import Console from rich.console import Console
from rich.progress import track from rich.progress import track
from vertexai.generative_models import GenerationConfig, GenerativeModel
from va_evaluator.config import Settings from va_evaluator.config import Settings
@@ -89,20 +89,25 @@ class MultiStepResponseSchema(BaseModel):
def generate_structured( def generate_structured(
model: GenerativeModel, client: genai.Client,
model: str,
prompt: str, prompt: str,
response_model: type[BaseModel], response_model: type[BaseModel],
) -> BaseModel: ) -> BaseModel:
generation_config = GenerationConfig( response = client.models.generate_content(
model=model,
contents=prompt,
config=types.GenerateContentConfig(
response_mime_type="application/json", response_mime_type="application/json",
response_schema=response_model, response_schema=response_model,
),
) )
response = model.generate_content(prompt, generation_config=generation_config)
return response_model.model_validate_json(response.text) return response_model.model_validate_json(response.text)
def generate_synthetic_question( def generate_synthetic_question(
model: GenerativeModel, client: genai.Client,
model: str,
file_content: str, file_content: str,
file_path: str, file_path: str,
q_type: str, q_type: str,
@@ -111,11 +116,12 @@ def generate_synthetic_question(
prompt = PROMPT_TEMPLATE.format( prompt = PROMPT_TEMPLATE.format(
context=file_content, id=file_path, qtype=q_type, qtype_def=q_def context=file_content, id=file_path, qtype=q_type, qtype_def=q_def
) )
return generate_structured(model, prompt, ResponseSchema) return generate_structured(client, model, prompt, ResponseSchema)
def generate_synthetic_conversation( def generate_synthetic_conversation(
model: GenerativeModel, client: genai.Client,
model: str,
file_content: str, file_content: str,
file_path: str, file_path: str,
num_turns: int, num_turns: int,
@@ -123,7 +129,7 @@ def generate_synthetic_conversation(
prompt = MULTI_STEP_PROMPT_TEMPLATE.format( prompt = MULTI_STEP_PROMPT_TEMPLATE.format(
context=file_content, num_turns=num_turns context=file_content, num_turns=num_turns
) )
return generate_structured(model, prompt, MultiStepResponseSchema) return generate_structured(client, model, prompt, MultiStepResponseSchema)
def generate( def generate(
@@ -134,8 +140,12 @@ def generate(
console = Console() console = Console()
settings = Settings() settings = Settings()
vertexai.init(project=settings.project_id, location=settings.location) client = genai.Client(
model = GenerativeModel(settings.agent.language_model) vertexai=True,
project=settings.project_id,
location=settings.location,
)
model_name = settings.agent.language_model
gcs_client = storage.Client(project=settings.project_id) gcs_client = storage.Client(project=settings.project_id)
bucket = gcs_client.bucket(settings.require_bucket) bucket = gcs_client.bucket(settings.require_bucket)
@@ -165,9 +175,7 @@ def generate(
console.print("[yellow]No files found. Skipping.[/yellow]") console.print("[yellow]No files found. Skipping.[/yellow]")
return "" return ""
files_to_process = random.sample( files_to_process = random.sample(all_files, k=min(num_questions, len(all_files)))
all_files, k=min(num_questions, len(all_files))
)
console.print( console.print(
f"Randomly selected {len(files_to_process)} files to generate questions from." f"Randomly selected {len(files_to_process)} files to generate questions from."
) )
@@ -182,7 +190,7 @@ def generate(
conversation_data = None conversation_data = None
for attempt in range(3): for attempt in range(3):
conversation_data = generate_synthetic_conversation( conversation_data = generate_synthetic_conversation(
model, file_content, file_path, num_turns client, model_name, file_content, file_path, num_turns
) )
if ( if (
conversation_data conversation_data
@@ -219,7 +227,7 @@ def generate(
generated_data = None generated_data = None
for attempt in range(3): for attempt in range(3):
generated_data = generate_synthetic_question( generated_data = generate_synthetic_question(
model, file_content, file_path, q_type, q_def client, model_name, file_content, file_path, q_type, q_def
) )
if ( if (
generated_data generated_data
@@ -249,7 +257,9 @@ def generate(
all_rows.append(row) all_rows.append(row)
except Exception as e: except Exception as e:
console.print(f"[bold red]Error processing file {file_path}: {e}[/bold red]") console.print(
f"[bold red]Error processing file {file_path}: {e}[/bold red]"
)
if not all_rows: if not all_rows:
console.print("[bold yellow]No questions were generated.[/bold yellow]") console.print("[bold yellow]No questions were generated.[/bold yellow]")
@@ -262,7 +272,9 @@ def generate(
f"\n[bold green]Saving {len(df)} generated questions to {output_csv}...[/bold green]" f"\n[bold green]Saving {len(df)} generated questions to {output_csv}...[/bold green]"
) )
df.to_csv(output_csv, index=False, encoding="utf-8-sig") df.to_csv(output_csv, index=False, encoding="utf-8-sig")
console.print("[bold green]Synthetic question generation complete.[/bold green]") console.print(
"[bold green]Synthetic question generation complete.[/bold green]"
)
else: else:
console.print( console.print(
f"\n[bold green]Saving {len(df)} generated questions to BigQuery...[/bold green]" f"\n[bold green]Saving {len(df)} generated questions to BigQuery...[/bold green]"
@@ -295,4 +307,3 @@ def generate(
console.print(f"[bold yellow]Finished run with ID: {run_id}[/bold yellow]") console.print(f"[bold yellow]Finished run with ID: {run_id}[/bold yellow]")
return run_id return run_id

61
uv.lock generated
View File

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[[package]] [[package]]
name = "typer" name = "typer"
version = "0.24.1" version = "0.24.1"
@@ -2581,6 +2630,12 @@ dependencies = [
{ name = "typer" }, { name = "typer" },
] ]
[package.dev-dependencies]
dev = [
{ name = "ruff" },
{ name = "ty" },
]
[package.metadata] [package.metadata]
requires-dist = [ requires-dist = [
{ name = "google-cloud-aiplatform" }, { name = "google-cloud-aiplatform" },
@@ -2596,6 +2651,12 @@ requires-dist = [
{ name = "typer" }, { name = "typer" },
] ]
[package.metadata.requires-dev]
dev = [
{ name = "ruff", specifier = ">=0.15.2" },
{ name = "ty", specifier = ">=0.0.18" },
]
[[package]] [[package]]
name = "warc3-wet" name = "warc3-wet"
version = "0.2.5" version = "0.2.5"