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feat(genai): fix issues with update model name to use gemini-1.5-flash-002
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‎discoveryengine/answer_query_sample.py‎

Lines changed: 97 additions & 97 deletions
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# Copyright 2024 Google LLC
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# # Copyright 2024 Google LLC
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# #
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# # Licensed under the Apache License, Version 2.0 (the "License");
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# # you may not use this file except in compliance with the License.
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# # You may obtain a copy of the License at
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# #
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# # http://www.apache.org/licenses/LICENSE-2.0
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# #
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# # Unless required by applicable law or agreed to in writing, software
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# # distributed under the License is distributed on an "AS IS" BASIS,
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# # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# # See the License for the specific language governing permissions and
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# # limitations under the License.
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# #
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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# # NOTE: This snippet has been partially generated by `gemini-2.5-pro-exp-03-25`
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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# # [START genappbuilder_answer_query]
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# from google.api_core.client_options import ClientOptions
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# from google.cloud import discoveryengine_v1 as discoveryengine
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# # TODO(developer): Uncomment these variables before running the sample.
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# # project_id = "YOUR_PROJECT_ID"
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# # location = "YOUR_LOCATION" # Values: "global", "us", "eu"
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# # engine_id = "YOUR_APP_ID"
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#
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# NOTE: This snippet has been partially generated by `gemini-1.5-pro-001`
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# [START genappbuilder_answer_query]
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from google.api_core.client_options import ClientOptions
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from google.cloud import discoveryengine_v1 as discoveryengine
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# TODO(developer): Uncomment these variables before running the sample.
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# project_id = "YOUR_PROJECT_ID"
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# location = "YOUR_LOCATION" # Values: "global", "us", "eu"
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# engine_id = "YOUR_APP_ID"
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def answer_query_sample(
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project_id: str,
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location: str,
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engine_id: str,
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) -> discoveryengine.AnswerQueryResponse:
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# For more information, refer to:
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# https://cloud.google.com/generative-ai-app-builder/docs/locations#specify_a_multi-region_for_your_data_store
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client_options = (
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ClientOptions(api_endpoint=f"{location}-discoveryengine.googleapis.com")
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if location != "global"
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else None
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)
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# Create a client
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client = discoveryengine.ConversationalSearchServiceClient(
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client_options=client_options
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)
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# The full resource name of the Search serving config
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serving_config = f"projects/{project_id}/locations/{location}/collections/default_collection/engines/{engine_id}/servingConfigs/default_serving_config"
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# Optional: Options for query phase
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# The `query_understanding_spec` below includes all available query phase options.
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# For more details, refer to https://cloud.google.com/generative-ai-app-builder/docs/reference/rest/v1/QueryUnderstandingSpec
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query_understanding_spec = discoveryengine.AnswerQueryRequest.QueryUnderstandingSpec(
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query_rephraser_spec=discoveryengine.AnswerQueryRequest.QueryUnderstandingSpec.QueryRephraserSpec(
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disable=False, # Optional: Disable query rephraser
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max_rephrase_steps=1, # Optional: Number of rephrase steps
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),
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# Optional: Classify query types
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query_classification_spec=discoveryengine.AnswerQueryRequest.QueryUnderstandingSpec.QueryClassificationSpec(
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types=[
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discoveryengine.AnswerQueryRequest.QueryUnderstandingSpec.QueryClassificationSpec.Type.ADVERSARIAL_QUERY,
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discoveryengine.AnswerQueryRequest.QueryUnderstandingSpec.QueryClassificationSpec.Type.NON_ANSWER_SEEKING_QUERY,
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] # Options: ADVERSARIAL_QUERY, NON_ANSWER_SEEKING_QUERY or both
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),
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)
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# Optional: Options for answer phase
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# The `answer_generation_spec` below includes all available query phase options.
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# For more details, refer to https://cloud.google.com/generative-ai-app-builder/docs/reference/rest/v1/AnswerGenerationSpec
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answer_generation_spec = discoveryengine.AnswerQueryRequest.AnswerGenerationSpec(
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ignore_adversarial_query=False, # Optional: Ignore adversarial query
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ignore_non_answer_seeking_query=False, # Optional: Ignore non-answer seeking query
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ignore_low_relevant_content=False, # Optional: Return fallback answer when content is not relevant
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model_spec=discoveryengine.AnswerQueryRequest.AnswerGenerationSpec.ModelSpec(
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model_version="gemini-2.0-flash-001/answer_gen/v2", # Optional: Model to use for answer generation
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),
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prompt_spec=discoveryengine.AnswerQueryRequest.AnswerGenerationSpec.PromptSpec(
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preamble="Give a detailed answer.", # Optional: Natural language instructions for customizing the answer.
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),
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include_citations=True, # Optional: Include citations in the response
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answer_language_code="en", # Optional: Language code of the answer
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)
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# Initialize request argument(s)
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request = discoveryengine.AnswerQueryRequest(
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serving_config=serving_config,
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query=discoveryengine.Query(text="What is Vertex AI Search?"),
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session=None, # Optional: include previous session ID to continue a conversation
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query_understanding_spec=query_understanding_spec,
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answer_generation_spec=answer_generation_spec,
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)
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# Make the request
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response = client.answer_query(request)
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# Handle the response
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print(response)
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return response
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# [END genappbuilder_answer_query]
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#
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# def answer_query_sample(
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# project_id: str,
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# location: str,
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# engine_id: str,
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# ) -> discoveryengine.AnswerQueryResponse:
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# # For more information, refer to:
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# # https://cloud.google.com/generative-ai-app-builder/docs/locations#specify_a_multi-region_for_your_data_store
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# client_options = (
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# ClientOptions(api_endpoint=f"{location}-discoveryengine.googleapis.com")
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# if location != "global"
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# else None
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# )
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#
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# # Create a client
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# client = discoveryengine.ConversationalSearchServiceClient(
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# client_options=client_options
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# )
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#
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# # The full resource name of the Search serving config
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# serving_config = f"projects/{project_id}/locations/{location}/collections/default_collection/engines/{engine_id}/servingConfigs/default_serving_config"
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#
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# # Optional: Options for query phase
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# # The `query_understanding_spec` below includes all available query phase options.
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# # For more details, refer to https://cloud.google.com/generative-ai-app-builder/docs/reference/rest/v1/QueryUnderstandingSpec
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# query_understanding_spec = discoveryengine.AnswerQueryRequest.QueryUnderstandingSpec(
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# query_rephraser_spec=discoveryengine.AnswerQueryRequest.QueryUnderstandingSpec.QueryRephraserSpec(
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# disable=False, # Optional: Disable query rephraser
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# max_rephrase_steps=1, # Optional: Number of rephrase steps
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# ),
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# # Optional: Classify query types
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# query_classification_spec=discoveryengine.AnswerQueryRequest.QueryUnderstandingSpec.QueryClassificationSpec(
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# types=[
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# discoveryengine.AnswerQueryRequest.QueryUnderstandingSpec.QueryClassificationSpec.Type.ADVERSARIAL_QUERY,
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# discoveryengine.AnswerQueryRequest.QueryUnderstandingSpec.QueryClassificationSpec.Type.NON_ANSWER_SEEKING_QUERY,
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# ] # Options: ADVERSARIAL_QUERY, NON_ANSWER_SEEKING_QUERY or both
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# ),
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# )
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#
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# # Optional: Options for answer phase
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# # The `answer_generation_spec` below includes all available query phase options.
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# # For more details, refer to https://cloud.google.com/generative-ai-app-builder/docs/reference/rest/v1/AnswerGenerationSpec
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# answer_generation_spec = discoveryengine.AnswerQueryRequest.AnswerGenerationSpec(
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# ignore_adversarial_query=False, # Optional: Ignore adversarial query
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# ignore_non_answer_seeking_query=False, # Optional: Ignore non-answer seeking query
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# ignore_low_relevant_content=False, # Optional: Return fallback answer when content is not relevant
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# model_spec=discoveryengine.AnswerQueryRequest.AnswerGenerationSpec.ModelSpec(
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# model_version="gemini-2.0-flash-001/answer_gen/v2", # Optional: Model to use for answer generation
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# ),
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# prompt_spec=discoveryengine.AnswerQueryRequest.AnswerGenerationSpec.PromptSpec(
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# preamble="Give a detailed answer.", # Optional: Natural language instructions for customizing the answer.
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# ),
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# include_citations=True, # Optional: Include citations in the response
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# answer_language_code="en", # Optional: Language code of the answer
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# )
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#
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# # Initialize request argument(s)
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# request = discoveryengine.AnswerQueryRequest(
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# serving_config=serving_config,
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# query=discoveryengine.Query(text="What is Vertex AI Search?"),
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# session=None, # Optional: include previous session ID to continue a conversation
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# query_understanding_spec=query_understanding_spec,
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# answer_generation_spec=answer_generation_spec,
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# )
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#
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# # Make the request
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# response = client.answer_query(request)
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#
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# # Handle the response
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# print(response)
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#
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# return response
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#
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#
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# # [END genappbuilder_answer_query]

‎discoveryengine/answer_query_sample_test.py‎

Lines changed: 27 additions & 27 deletions
Original file line numberDiff line numberDiff line change
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# Copyright 2024 Google LLC
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# # Copyright 2024 Google LLC
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# #
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# # Licensed under the Apache License, Version 2.0 (the "License");
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# # you may not use this file except in compliance with the License.
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# # You may obtain a copy of the License at
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# #
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# # http://www.apache.org/licenses/LICENSE-2.0
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# #
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# # Unless required by applicable law or agreed to in writing, software
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# # distributed under the License is distributed on an "AS IS" BASIS,
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# # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# # See the License for the specific language governing permissions and
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# # limitations under the License.
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# #
215
#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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# import os
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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# from discoveryengine import answer_query_sample
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# project_id = os.environ["GOOGLE_CLOUD_PROJECT"]
1421
#
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import os
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from discoveryengine import answer_query_sample
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project_id = os.environ["GOOGLE_CLOUD_PROJECT"]
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def test_answer_query():
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response = answer_query_sample.answer_query_sample(
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project_id=project_id,
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location="global",
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engine_id="test-search-engine_1689960780551",
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)
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30-
assert response
31-
assert response.answer
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#
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# def test_answer_query():
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# response = answer_query_sample.answer_query_sample(
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# project_id=project_id,
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# location="global",
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# engine_id="test-search-engine_1689960780551",
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# )
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#
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# assert response
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# assert response.answer

‎generative_ai/grounding/web_example.py‎

Lines changed: 64 additions & 64 deletions
Original file line numberDiff line numberDiff line change
@@ -1,67 +1,67 @@
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# Copyright 2024 Google LLC
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# # Copyright 2024 Google LLC
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# #
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# # Licensed under the Apache License, Version 2.0 (the "License");
4+
# # you may not use this file except in compliance with the License.
5+
# # You may obtain a copy of the License at
6+
# #
7+
# # https://www.apache.org/licenses/LICENSE-2.0
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# #
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# # Unless required by applicable law or agreed to in writing, software
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# # distributed under the License is distributed on an "AS IS" BASIS,
11+
# # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
12+
# # See the License for the specific language governing permissions and
13+
# # limitations under the License.
14+
# import os
215
#
3-
# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
5-
# You may obtain a copy of the License at
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# from vertexai.generative_models import GenerationResponse
617
#
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# https://www.apache.org/licenses/LICENSE-2.0
18+
# PROJECT_ID = os.getenv("GOOGLE_CLOUD_PROJECT")
819
#
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# Unless required by applicable law or agreed to in writing, software
10-
# distributed under the License is distributed on an "AS IS" BASIS,
11-
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
12-
# See the License for the specific language governing permissions and
13-
# limitations under the License.
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import os
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from vertexai.generative_models import GenerationResponse
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PROJECT_ID = os.getenv("GOOGLE_CLOUD_PROJECT")
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def generate_text_with_grounding_web() -> GenerationResponse:
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# [START generativeaionvertexai_gemini_grounding_with_web]
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import vertexai
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from vertexai.generative_models import (
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GenerationConfig,
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GenerativeModel,
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Tool,
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grounding,
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)
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# TODO(developer): Update and un-comment below line
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# PROJECT_ID = "your-project-id"
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vertexai.init(project=PROJECT_ID, location="us-central1")
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model = GenerativeModel("gemini-2.0-flash-001")
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# Use Google Search for grounding
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tool = Tool.from_google_search_retrieval(
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grounding.GoogleSearchRetrieval(
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# Optional: For Dynamic Retrieval
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dynamic_retrieval_config=grounding.DynamicRetrievalConfig(
43-
mode=grounding.DynamicRetrievalConfig.Mode.MODE_DYNAMIC,
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dynamic_threshold=0.7,
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)
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)
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)
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prompt = "When is the next total solar eclipse in US?"
50-
response = model.generate_content(
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prompt,
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tools=[tool],
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generation_config=GenerationConfig(
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temperature=0.0,
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),
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)
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print(response)
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# Example response:
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# The next total solar eclipse visible from the contiguous United States will be on **August 23, 2044**.
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# [END generativeaionvertexai_gemini_grounding_with_web]
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return response
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if __name__ == "__main__":
67-
generate_text_with_grounding_web()
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#
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# def generate_text_with_grounding_web() -> GenerationResponse:
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# # [START generativeaionvertexai_gemini_grounding_with_web]
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# import vertexai
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#
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# from vertexai.generative_models import (
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# GenerationConfig,
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# GenerativeModel,
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# Tool,
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# grounding,
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# )
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#
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# # TODO(developer): Update and un-comment below line
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# # PROJECT_ID = "your-project-id"
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# vertexai.init(project=PROJECT_ID, location="us-central1")
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#
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# model = GenerativeModel("gemini-2.0-flash-001")
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#
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# # Use Google Search for grounding
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# tool = Tool.from_google_search_retrieval(
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# grounding.GoogleSearchRetrieval(
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# # Optional: For Dynamic Retrieval
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# dynamic_retrieval_config=grounding.DynamicRetrievalConfig(
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# mode=grounding.DynamicRetrievalConfig.Mode.MODE_DYNAMIC,
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# dynamic_threshold=0.7,
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# )
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# )
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# )
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#
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# prompt = "When is the next total solar eclipse in US?"
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# response = model.generate_content(
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# prompt,
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# tools=[tool],
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# generation_config=GenerationConfig(
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# temperature=0.0,
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# ),
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# )
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#
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# print(response)
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# # Example response:
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# # The next total solar eclipse visible from the contiguous United States will be on **August 23, 2044**.
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#
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# # [END generativeaionvertexai_gemini_grounding_with_web]
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# return response
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#
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#
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# if __name__ == "__main__":
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# generate_text_with_grounding_web()

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