Merge branch 'main' into inardini--batch-pipeline-rag

.github/CODEOWNERS

@@ -71,3 +71,4 @@
 /generative-ai/open-models/serving         @polong-lin @GoogleCloudPlatform/generative-ai-devrel
 /generative-ai/open-models/serving/cloud_run_ollama_gemma2_rag_qa.ipynb       @eliasecchig @GoogleCloudPlatform/generative-ai-devrel
 /generative-ai/open-models/serving/vertex_ai_text_generation_inference_gemma.ipynb  @alvarobartt @philschmid @pagezyhf @jeffboudier
+/generative-ai/gemini/use-cases/applying-llms-to-data/semantic-search-in-bigquery/stackoverflow_questions_semantic_search.ipynb     @sethijaideep @GoogleCloudPlatform/generative-ai-devrel

.github/actions/spelling/allow.txt

@@ -426,6 +426,7 @@ ipynb
 isa
 itables
 iterrows
+ivf
 jegadesh
 jetbrains
 jsonify

gemini/prompts/prompt_optimizer/vapo_lib.py

@@ -13,6 +13,7 @@
 # limitations under the License.
 
 """Utility functions and classes for the VAPO notebook."""
+import csv
 import io
 import json
 import re
@@ -61,17 +62,89 @@ def is_run_target_required(eval_metric_types: list[str], source_model: str) -> b
 _TARGET_KEY = "target"
 
 
+def load_file_from_gcs(dataset: str) -> str:
+    """Loads the file from GCS and returns it as a string."""
+    if dataset.startswith("gs://"):
+        with gfile.GFile(dataset, "r") as f:
+            return f.read()
+    else:
+        raise ValueError(
+            "Unsupported file location. Only GCS paths starting with 'gs://' are"
+            " supported."
+        )
+
+
+def parse_jsonl(data_str: str) -> list[dict[str, str]]:
+    """Parses the content of a JSONL file and returns a list of dictionaries."""
+    data = []
+    lines = data_str.splitlines()
+    for line in lines:
+        if line:
+            try:
+                data.append(json.loads(line))
+            except json.JSONDecodeError as e:
+                raise ValueError(
+                    f"Error decoding JSON on line: {line}. Error: {e}"
+                ) from e
+    return data
+
+
+def parse_and_validate_csv(data_str: str) -> list[dict[str, str]]:
+    """Parses and validates the content of a CSV file and returns a list of dictionaries."""
+    data = []
+    csv_reader = csv.reader(io.StringIO(data_str))
+
+    # Extract and validate headers
+    try:
+        headers = next(csv_reader)
+        if not headers:
+            raise ValueError("The CSV file has an empty or invalid header row.")
+    except StopIteration as e:
+        raise ValueError("The CSV file is empty.") from e
+
+    # Validate and process rows
+    for row_number, row in enumerate(csv_reader, start=2):
+        if len(row) != len(headers):
+            raise ValueError(
+                f"Row {row_number} has an inconsistent number of fields. "
+                f"Expected {len(headers)} fields but found {len(row)}."
+            )
+        # Create dictionary for each row using headers as keys
+        item = dict(zip(headers, row))
+        data.append(item)
+
+    return data
+
+
+def load_dataset(dataset: str) -> list[dict[str, str]]:
+    """Loads and parses the dataset based on its file type ('.jsonl' or '.csv')."""
+    # Load the file from GCS
+    data_str = load_file_from_gcs(dataset)
+
+    # Parse based on file type
+    if dataset.endswith(".jsonl"):
+        return parse_jsonl(data_str)
+
+    if dataset.endswith(".csv"):
+        return parse_and_validate_csv(data_str)
+
+    raise ValueError(
+        "Unsupported file type. Please provide a file with '.jsonl' or '.csv'"
+        " extension."
+    )
+
+
 def validate_prompt_and_data(
     template: str,
     dataset_path: str,
     placeholder_to_content: str,
     label_enforced: bool,
 ) -> None:
     """Validates the prompt template and the dataset."""
-    placeholder_to_content = json.loads(placeholder_to_content)
-    with gfile.GFile(dataset_path, "r") as f:
-        data = [json.loads(line) for line in f.readlines()]
-
+    data = load_dataset(dataset_path)
+    placeholder_to_content_json = json.loads(placeholder_to_content)
+    template = re.sub(r"(?<!{){(?!{)", "{{", template)
+    template = re.sub(r"(?<!})}(?!})", "}}", template)
     env = jinja2.Environment()
     try:
         parsed_content = env.parse(template)
@@ -81,7 +154,7 @@ def validate_prompt_and_data(
     template_variables = jinja2.meta.find_undeclared_variables(parsed_content)
     extra_keys = set()
     for ex in data:
-        ex.update(placeholder_to_content)
+        ex.update(placeholder_to_content_json)
         missing_keys = [key for key in template_variables if key not in ex]
         extra_keys.update([key for key in ex if key not in template_variables])
         if label_enforced:
@@ -99,7 +172,7 @@ def validate_prompt_and_data(
             )
     if extra_keys:
         raise Warning(
-            "Warning: extra keys in the examples not used in the context/task"
+            "Warning: extra keys in the examples not used in the prompt template"
             f" template {extra_keys}"
         )
 
@@ -189,8 +262,10 @@ def generate_dataframe(filename: str) -> pd.DataFrame:
         return pd.DataFrame()
 
     with gfile.GFile(filename, "r") as f:
-        data = json.load(f)
-
+        try:
+            data = json.load(f)
+        except json.JSONDecodeError:
+            return pd.DataFrame()
     return pd.json_normalize(data)
 
 
@@ -227,6 +302,15 @@ class ProgressForm:
 
     def __init__(self, params: dict[str, str]) -> None:
         """Initialize the progress form."""
+        self.instruction_progress_bar = None
+        self.instruction_display = None
+        self.instruction_best = None
+        self.instruction_score = None
+        self.demo_progress_bar = None
+        self.demo_display = None
+        self.demo_best = None
+        self.demo_score = None
+
         self.job_state_display = display(
             HTML("<span>Job State: Not Started!</span>"), display_id=True
         )
@@ -262,7 +346,7 @@ def __init__(self, params: dict[str, str]) -> None:
     # pylint: disable=too-many-arguments
     def update_progress(
         self,
-        progress_bar: widgets.IntProgress,
+        progress_bar: widgets.IntProgress | None,
         templates_file: str,
         df: pd.DataFrame | None,
         df_display: DisplayHandle,

gemini/prompts/prompt_optimizer/vertex_ai_prompt_optimizer_ui.ipynb

@@ -113,9 +113,7 @@
       "outputs": [],
       "source": [
         "SYSTEM_INSTRUCTION = \"Answer the following question. Let's think step by step.\\n\"  # @param {type:\"string\"}\n",
-        "PROMPT_TEMPLATE = (\n",
-        "    \"Question: {{question}}\\n\\nAnswer:{{target}}\"  # @param {type:\"string\"}\n",
-        ")"
+        "PROMPT_TEMPLATE = \"Question: {question}\\n\\nAnswer:{target}\"  # @param {type:\"string\"}"
       ]
     },
     {
@@ -203,9 +201,9 @@
         "# @markdown * Number of the demonstrations to include in each prompt.\n",
         "\n",
         "# @markdown **Model Configs**: <br/>\n",
-        "TARGET_MODEL_QPS = 3  # @param {type:\"integer\"}\n",
-        "SOURCE_MODEL_QPS = 3  # @param {type:\"integer\"}\n",
-        "EVAL_MODEL_QPS = 3  # @param {type:\"integer\"}\n",
+        "TARGET_MODEL_QPS = 3.0  # @param {type:\"number\"}\n",
+        "SOURCE_MODEL_QPS = 3.0  # @param {type:\"number\"}\n",
+        "EVAL_QPS = 3.0  # @param {type:\"number\"}\n",
         "# @markdown * The QPS for calling the eval model, which is currently gemini-1.5-pro-001.\n",
         "\n",
         "# @markdown **Multi-metric Configs**: <br/>\n",
@@ -280,15 +278,15 @@
         "params = {\n",
         "    \"project\": PROJECT_ID,\n",
         "    \"num_steps\": NUM_INST_OPTIMIZATION_STEPS,\n",
-        "    \"prompt_template\": SYSTEM_INSTRUCTION,\n",
-        "    \"demo_and_query_template\": PROMPT_TEMPLATE,\n",
+        "    \"system_instruction\": SYSTEM_INSTRUCTION,\n",
+        "    \"prompt_template\": PROMPT_TEMPLATE,\n",
         "    \"target_model\": TARGET_MODEL,\n",
         "    \"target_model_qps\": TARGET_MODEL_QPS,\n",
         "    \"target_model_location\": LOCATION,\n",
         "    \"source_model\": SOURCE_MODEL,\n",
         "    \"source_model_qps\": SOURCE_MODEL_QPS,\n",
         "    \"source_model_location\": LOCATION,\n",
-        "    \"eval_model_qps\": EVAL_MODEL_QPS,\n",
+        "    \"eval_qps\": EVAL_QPS,\n",
         "    \"eval_model_location\": LOCATION,\n",
         "    \"optimization_mode\": OPTIMIZATION_MODE,\n",
         "    \"num_demo_set_candidates\": NUM_DEMO_OPTIMIZATION_STEPS,\n",
@@ -346,7 +344,7 @@
       "source": [
         "from IPython.display import HTML, display\n",
         "\n",
-        "RESULT_PATH = \"gs://prompt_design_demo\"  # @param {type:\"string\"}\n",
+        "RESULT_PATH = \"[OUTPUT_PATH]\"  # @param {type:\"string\"}\n",
         "# @markdown * Specify a GCS path that contains artifacts of a single or multiple VAPO runs.\n",
         "\n",
         "results_ui = vapo_lib.ResultsUI(RESULT_PATH)\n",