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chore: Fix spelling

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Merge https://github.com/google/adk-python/pull/2447

This PR corrects misspellings identified by the [check-spelling action](https://github.com/marketplace/actions/check-spelling)

The misspellings have been reported at https://github.com/jsoref/adk-python/actions/runs/16840838898/attempts/1#summary-47711379253

The action reports that the changes in this PR would make it happy: https://github.com/jsoref/adk-python/actions/runs/16840839269/attempts/1#summary-47711380479

Note: while I use tooling to identify errors, the tooling doesn't _actually_ provide the corrections, I'm picking them on my own. I'm a human, and I may make mistakes.

I've included a couple of changes to make CI happy. Personally, I object to CI being in a state of "random drive by person who adds a blank line in the middle of a file must fix all the preexisting bugs in the file", but that appears to be the state for this repository.

COPYBARA_INTEGRATE_REVIEW=https://github.com/google/adk-python/pull/2447 from jsoref:spelling d85398e7fd154d124d477c6af6181481a01f34e0
PiperOrigin-RevId: 827629615
This commit is contained in:
Josh Soref
2025-11-03 13:33:53 -08:00
committed by Copybara-Service
parent 8dff85099d
commit aa1233608a
111 changed files with 228 additions and 235 deletions
Download Patch File Download Diff File Expand all files Collapse all files
.github/workflows/check-file-contents.yml
+1 -1
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@@ -89,7 +89,7 @@ jobs:
- name: Check for import from cli package in certain changed Python files
run: |
git fetch origin ${{ github.base_ref }}
CHANGED_FILES=$(git diff --diff-filter=ACMR --name-only origin/${{ github.base_ref }}...HEAD | grep -E '\.py$' | grep -v -E 'cli/.*|tests/.*|contributing/samples/' || true)
CHANGED_FILES=$(git diff --diff-filter=ACMR --name-only origin/${{ github.base_ref }}...HEAD | grep -E '\.py$' | grep -v -E 'cli/.*|src/google/adk/tools/apihub_tool/apihub_toolset.py|tests/.*|contributing/samples/' || true)
if [ -n "$CHANGED_FILES" ]; then
echo "Changed Python files to check:"
echo "$CHANGED_FILES"
AGENTS.md
+1 -1
View File
@@ -236,7 +236,7 @@ isort --check src/
### In ADK source
Below styles applies to the ADK source code (under `src/` folder of the Github repo).
Below styles applies to the ADK source code (under `src/` folder of the GitHub repo).
#### Use relative imports (Required)
CHANGELOG.md
+9 -10
View File
@@ -440,7 +440,7 @@ with Bigtable for building AI Agent applications(experimental feature) ([a953807
### Improvements
* Add Github workflow config for the ADK Answering agent ([8dc0c94](https://github.com/google/adk-python/commit/8dc0c949afb9024738ff7ac1b2c19282175c3200))
* Add GitHub workflow config for the ADK Answering agent ([8dc0c94](https://github.com/google/adk-python/commit/8dc0c949afb9024738ff7ac1b2c19282175c3200))
* Import AGENT_CARD_WELL_KNOWN_PATH from adk instead of from a2a directly ([37dae9b](https://github.com/google/adk-python/commit/37dae9b631db5060770b66fce0e25cf0ffb56948))
* Make `LlmRequest.LiveConnectConfig` field default to a factory ([74589a1](https://github.com/google/adk-python/commit/74589a1db7df65e319d1ad2f0676ee0cf5d6ec1d))
* Update the prompt to make the ADK Answering Agent more objective ([2833030](https://github.com/google/adk-python/commit/283303032a174d51b8d72f14df83c794d66cb605))
@@ -499,14 +499,13 @@ with Bigtable for building AI Agent applications(experimental feature) ([a953807
### Features
* [Core]Add agent card builder ([18f5bea](https://github.com/google/adk-python/commit/18f5bea411b3b76474ff31bfb2f62742825b45e5))
* [Core]Add an to_a2a util to convert adk agent to A2A ASGI application ([a77d689](https://github.com/google/adk-python/commit/a77d68964a1c6b7659d6117d57fa59e43399e0c2))
* [Core]Add a to_a2a util to convert adk agent to A2A ASGI application ([a77d689](https://github.com/google/adk-python/commit/a77d68964a1c6b7659d6117d57fa59e43399e0c2))
* [Core]Add camel case converter for agents ([0e173d7](https://github.com/google/adk-python/commit/0e173d736334f8c6c171b3144ac6ee5b7125c846))
* [Evals]Use LocalEvalService to run all evals in cli and web ([d1f182e](https://github.com/google/adk-python/commit/d1f182e8e68c4a5a4141592f3f6d2ceeada78887))
* [Evals]Enable FinalResponseMatchV2 metric as an experiment ([36e45cd](https://github.com/google/adk-python/commit/36e45cdab3bbfb653eee3f9ed875b59bcd525ea1))
* [Models]Add support for `model-optimizer-*` family of models in vertex ([ffe2bdb](https://github.com/google/adk-python/commit/ffe2bdbe4c2ea86cc7924eb36e8e3bb5528c0016))
* [Services]Added a sample for History Management ([67284fc](https://github.com/google/adk-python/commit/67284fc46667b8c2946762bc9234a8453d48a43c))
* [Services]Support passing fully qualified agent engine resource name when constructing session service and memory service ([2e77804](https://github.com/google/adk-python/commit/2e778049d0a675e458f4e
35fe4104ca1298dbfcf))
* [Services]Support passing fully qualified agent engine resource name when constructing session service and memory service ([2e77804](https://github.com/google/adk-python/commit/2e778049d0a675e458f4e35fe4104ca1298dbfcf))
* [Tools]Add ComputerUseToolset ([083dcb4](https://github.com/google/adk-python/commit/083dcb44650eb0e6b70219ede731f2fa78ea7d28))
* [Tools]Allow toolset to process llm_request before tools returned by it ([3643b4a](https://github.com/google/adk-python/commit/3643b4ae196fd9e38e52d5dc9d1cd43ea0733d36))
* [Tools]Support input/output schema by fully-qualified code reference ([dfee06a](https://github.com/google/adk-python/commit/dfee06ac067ea909251d6fb016f8331065d430e9))
@@ -619,7 +618,7 @@ with Bigtable for building AI Agent applications(experimental feature) ([a953807
### Documentation
* Update the a2a exmaple link in README.md [d0fdfb8](https://github.com/google/adk-python/commit/d0fdfb8c8e2e32801999c81de8d8ed0be3f88e76)
* Update the a2a example link in README.md [d0fdfb8](https://github.com/google/adk-python/commit/d0fdfb8c8e2e32801999c81de8d8ed0be3f88e76)
* Adds AGENTS.md to provide relevant project context for the Gemini CLI [37108be](https://github.com/google/adk-python/commit/37108be8557e011f321de76683835448213f8515)
* Update CONTRIBUTING.md [ffa9b36](https://github.com/google/adk-python/commit/ffa9b361db615ae365ba62c09a8f4226fb761551)
* Add adk project overview and architecture [28d0ea8](https://github.com/google/adk-python/commit/28d0ea876f2f8de952f1eccbc788e98e39f50cf5)
@@ -814,7 +813,7 @@ with Bigtable for building AI Agent applications(experimental feature) ([a953807
* Fix typos in README for sample bigquery_agent and oauth_calendar_agent ([9bdd813](https://github.com/google/adk-python/commit/9bdd813be15935af5c5d2a6982a2391a640cab23))
* Make tool_call one span for telemetry and renamed to execute_tool ([999a7fe](https://github.com/google/adk-python/commit/999a7fe69d511b1401b295d23ab3c2f40bccdc6f))
* Use media type in chat window. Remove isArtifactImage and isArtifactAudio reference ([1452dac](https://github.com/google/adk-python/commit/1452dacfeb6b9970284e1ddeee6c4f3cb56781f8))
* Set output_schema correctly for LiteLllm ([6157db7](https://github.com/google/adk-python/commit/6157db77f2fba4a44d075b51c83bff844027a147))
* Set output_schema correctly for LiteLlm ([6157db7](https://github.com/google/adk-python/commit/6157db77f2fba4a44d075b51c83bff844027a147))
* Update pending event dialog style ([1db601c](https://github.com/google/adk-python/commit/1db601c4bd90467b97a2f26fe9d90d665eb3c740))
* Remove the gap between event holder and image ([63822c3](https://github.com/google/adk-python/commit/63822c3fa8b0bdce2527bd0d909c038e2b66dd98))
@@ -842,7 +841,7 @@ with Bigtable for building AI Agent applications(experimental feature) ([a953807
## 1.1.1
### Features
* Add BigQuery first-party tools. See [here](https://github.com/google/adk-python/commit/d6c6bb4b2489a8b7a4713e4747c30d6df0c07961) for more details.
* Add [BigQuery first-party tools](https://github.com/google/adk-python/commit/d6c6bb4b2489a8b7a4713e4747c30d6df0c07961).
## 1.1.0
@@ -978,7 +977,7 @@ with Bigtable for building AI Agent applications(experimental feature) ([a953807
* Fix google search reading undefined for `renderedContent`.
### Miscellaneous Chores
* Docstring improvements, typo fixings, github action to enfore code styles on formatting and imports, etc.
* Docstring improvements, typo fixings, github action to enforce code styles on formatting and imports, etc.
## 0.3.0
@@ -1017,7 +1016,7 @@ with Bigtable for building AI Agent applications(experimental feature) ([a953807
### ⚠ BREAKING CHANGES
* Fix typo in method name in `Event`: has_trailing_code_exeuction_result --> has_trailing_code_execution_result.
* Fix typo in method name in `Event`: has_trailing_code_execution_result --> has_trailing_code_execution_result.
### Features
@@ -1047,7 +1046,7 @@ with Bigtable for building AI Agent applications(experimental feature) ([a953807
### Miscellaneous Chores
* Adds unit tests in Github action.
* Adds unit tests in GitHub action.
* Improves test coverage.
* Various typo fixes.
contributing/samples/a2a_auth/remote_a2a/bigquery_agent/agent.py
+1 -1
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@@ -46,7 +46,7 @@ root_agent = Agent(
Use the provided tools to conduct various operations on users' data in Google BigQuery.
Scenario 1:
The user wants to query their biguqery datasets
The user wants to query their bigquery datasets
Use bigquery_datasets_list to query user's datasets
Scenario 2:
contributing/samples/a2a_human_in_loop/README.md
+1 -1
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@@ -99,7 +99,7 @@ Agent: ✅ Great news! Your reimbursement has been approved by the manager. Proc
The human-in-the-loop process follows this pattern:
1. **Initial Call**: Root agent delegates approval request to remote approval agent for amounts >$100
2. **Pending Response**: Remote approval agent returns immediate response with `status: "pending"` and ticket ID and serface the approval request to root agent
2. **Pending Response**: Remote approval agent returns immediate response with `status: "pending"` and ticket ID and surface the approval request to root agent
3. **Agent Acknowledgment**: Root agent informs user about pending approval status
4. **Human Interaction**: Human manager interacts with root agent to review and approve/reject the request
5. **Updated Response**: Root agent receives updated tool response with approval decision and send it to remote agent
contributing/samples/adk_answering_agent/README.md
+1 -1
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@@ -116,4 +116,4 @@ The following environment variables are required to upload the docs to update th
* `ADK_DOCS_ROOT_PATH=YOUR_ADK_DOCS_ROOT_PATH`: **(Required)** Path to the root of the downloaded adk-docs repo.
* `ADK_PYTHON_ROOT_PATH=YOUR_ADK_PYTHON_ROOT_PATH`: **(Required)** Path to the root of the downloaded adk-python repo.
For local execution in interactive mode, you can place these variables in a `.env` file in the project's root directory. For the GitHub workflow, they should be configured as repository secrets.
For local execution in interactive mode, you can place these variables in a `.env` file in the project's root directory. For the GitHub workflow, they should be configured as repository secrets.
contributing/samples/adk_answering_agent/upload_docs_to_vertex_ai_search.py
+2 -2
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@@ -130,7 +130,7 @@ def upload_directory_to_gcs(
)
return False
print(f"Sucessfully uploaded {file_count} files to GCS.")
print(f"Successfully uploaded {file_count} files to GCS.")
return True
@@ -148,7 +148,7 @@ def import_from_gcs_to_vertex_ai(
# parent has the format of
# "projects/{project_number}/locations/{location}/collections/{collection}/dataStores/{datastore_id}/branches/default_branch"
parent=full_datastore_id + "/branches/default_branch",
# Specify the GCS source and use "content" for unstructed data.
# Specify the GCS source and use "content" for unstructured data.
gcs_source=discoveryengine.GcsSource(
input_uris=[gcs_uri], data_schema="content"
),
contributing/samples/adk_answering_agent/utils.py
+1 -1
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@@ -143,7 +143,7 @@ def convert_gcs_to_https(gcs_uri: str) -> Optional[str]:
if _check_url_exists(potential_url):
return potential_url
else:
# If it doesn't exist, fallback to the regular github url
# If it doesn't exist, fall back to the regular github url
return _generate_github_url(prefix, relative_path)
# Convert the links for other cases, e.g. adk-python
contributing/samples/adk_issue_formatting_agent/agent.py
+4 -4
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@@ -45,7 +45,7 @@ if IS_INTERACTIVE:
def list_open_issues(issue_count: int) -> dict[str, Any]:
"""List most recent `issue_count` numer of open issues in the repo.
"""List most recent `issue_count` number of open issues in the repo.
Args:
issue_count: number of issues to return
@@ -75,7 +75,7 @@ def get_issue(issue_number: int) -> dict[str, Any]:
"""Get the details of the specified issue number.
Args:
issue_number: issue number of the Github issue.
issue_number: issue number of the GitHub issue.
Returns:
The status of this request, with the issue details when successful.
@@ -92,7 +92,7 @@ def add_comment_to_issue(issue_number: int, comment: str) -> dict[str, any]:
"""Add the specified comment to the given issue number.
Args:
issue_number: issue number of the Github issue
issue_number: issue number of the GitHub issue
comment: comment to add
Returns:
@@ -116,7 +116,7 @@ def list_comments_on_issue(issue_number: int) -> dict[str, any]:
"""List all comments on the given issue number.
Args:
issue_number: issue number of the Github issue
issue_number: issue number of the GitHub issue
Returns:
The the status of this request, with the list of comments when successful.
contributing/samples/adk_pr_agent/agent.py
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@@ -125,7 +125,7 @@ def get_github_pr_info_http(pr_number: int) -> str | None:
system_prompt = """
You are a helpful assistant to generate reasonable descriptions for pull requests for software engineers.
The descritions should not be too short (e.g.: less than 3 words), or too long (e.g.: more than 30 words).
The descriptions should not be too short (e.g.: less than 3 words), or too long (e.g.: more than 30 words).
The generated description should start with `chore`, `docs`, `feat`, `fix`, `test`, or `refactor`.
`feat` stands for a new feature.
contributing/samples/adk_pr_triaging_agent/agent.py
+8 -8
View File
@@ -58,7 +58,7 @@ def get_pull_request_details(pr_number: int) -> str:
"""Get the details of the specified pull request.
Args:
pr_number: number of the Github pull request.
pr_number: number of the GitHub pull request.
Returns:
The status of this request, with the details when successful.
@@ -162,7 +162,7 @@ def add_label_to_pr(pr_number: int, label: str) -> dict[str, Any]:
"""Adds a specified label on a pull request.
Args:
pr_number: the number of the Github pull request
pr_number: the number of the GitHub pull request
label: the label to add
Returns:
@@ -175,7 +175,7 @@ def add_label_to_pr(pr_number: int, label: str) -> dict[str, Any]:
f"Error: Label '{label}' is not an allowed label. Will not apply."
)
# Pull Request is a special issue in Github, so we can use issue url for PR.
# Pull Request is a special issue in GitHub, so we can use issue url for PR.
label_url = (
f"{GITHUB_BASE_URL}/repos/{OWNER}/{REPO}/issues/{pr_number}/labels"
)
@@ -197,7 +197,7 @@ def add_comment_to_pr(pr_number: int, comment: str) -> dict[str, Any]:
"""Add the specified comment to the given PR number.
Args:
pr_number: the number of the Github pull request
pr_number: the number of the GitHub pull request
comment: the comment to add
Returns:
@@ -205,7 +205,7 @@ def add_comment_to_pr(pr_number: int, comment: str) -> dict[str, Any]:
"""
print(f"Attempting to add comment '{comment}' to issue #{pr_number}")
# Pull Request is a special issue in Github, so we can use issue url for PR.
# Pull Request is a special issue in GitHub, so we can use issue url for PR.
url = f"{GITHUB_BASE_URL}/repos/{OWNER}/{REPO}/issues/{pr_number}/comments"
payload = {"body": comment}
@@ -225,7 +225,7 @@ root_agent = Agent(
description="Triage ADK pull requests.",
instruction=f"""
# 1. Identity
You are a Pull Request (PR) triaging bot for the Github {REPO} repo with the owner {OWNER}.
You are a Pull Request (PR) triaging bot for the GitHub {REPO} repo with the owner {OWNER}.
# 2. Responsibilities
Your core responsibility includes:
@@ -242,7 +242,7 @@ root_agent = Agent(
- If it's about session, memory, artifacts services, label it with "services"
- If it's about UI/web, label it with "web"
- If it's related to tools, label it with "tools"
- If it's about agent evalaution, then label it with "eval".
- If it's about agent evaluation, then label it with "eval".
- If it's about streaming/live, label it with "live".
- If it's about model support(non-Gemini, like Litellm, Ollama, OpenAI models), label it with "models".
- If it's about tracing, label it with "tracing".
@@ -280,7 +280,7 @@ root_agent = Agent(
- Call the `get_pull_request_details` tool to get the details of the PR.
- Skip the PR (i.e. do not label or comment) if any of the following is true:
- the PR is closed
- the PR is labeled with "google-contributior"
- the PR is labeled with "google-contributor"
- the PR is already labelled with the above labels (e.g. "documentation", "services", "tools", etc.).
- Check if the PR is following the contribution guidelines.
- If it's not following the guidelines, recommend or add a comment to the PR that points to the contribution guidelines (https://github.com/google/adk-python/blob/main/CONTRIBUTING.md).
contributing/samples/adk_triaging_agent/agent.py
+5 -5
View File
@@ -50,7 +50,7 @@ if IS_INTERACTIVE:
def list_unlabeled_issues(issue_count: int) -> dict[str, Any]:
"""List most recent `issue_count` numer of unlabeled issues in the repo.
"""List most recent `issue_count` number of unlabeled issues in the repo.
Args:
issue_count: number of issues to return
@@ -87,7 +87,7 @@ def add_label_and_owner_to_issue(
"""Add the specified label and owner to the given issue number.
Args:
issue_number: issue number of the Github issue.
issue_number: issue number of the GitHub issue.
label: label to assign
Returns:
@@ -143,7 +143,7 @@ def change_issue_type(issue_number: int, issue_type: str) -> dict[str, Any]:
"""Change the issue type of the given issue number.
Args:
issue_number: issue number of the Github issue, in string foramt.
issue_number: issue number of the GitHub issue, in string format.
issue_type: issue type to assign
Returns:
@@ -168,7 +168,7 @@ root_agent = Agent(
name="adk_triaging_assistant",
description="Triage ADK issues.",
instruction=f"""
You are a triaging bot for the Github {REPO} repo with the owner {OWNER}. You will help get issues, and recommend a label.
You are a triaging bot for the GitHub {REPO} repo with the owner {OWNER}. You will help get issues, and recommend a label.
IMPORTANT: {APPROVAL_INSTRUCTION}
Here are the rules for labeling:
@@ -177,7 +177,7 @@ root_agent = Agent(
- If it's about UI/web, label it with "web"
- If the user is asking about a question, label it with "question"
- If it's related to tools, label it with "tools"
- If it's about agent evalaution, then label it with "eval".
- If it's about agent evaluation, then label it with "eval".
- If it's about streaming/live, label it with "live".
- If it's about model support(non-Gemini, like Litellm, Ollama, OpenAI models), label it with "models".
- If it's about tracing, label it with "tracing".
contributing/samples/application_integration_agent/README.md
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@@ -7,7 +7,7 @@ This sample demonstrates how to use the `ApplicationIntegrationToolset` within a
## Prerequisites
1. **Set up Integration Connection:**
* You need an existing [Integration connection](https://cloud.google.com/integration-connectors/docs/overview) configured to interact with your Jira instance. Follow the [documentation](https://google.github.io/adk-docs/tools/google-cloud-tools/#use-integration-connectors) to provision the Integration Connector in Google Cloud and then use this [documentation](https://cloud.google.com/integration-connectors/docs/connectors/jiracloud/configure) to create an JIRA connection. Note the `Connection Name`, `Project ID`, and `Location` of your connection.
* You need an existing [Integration connection](https://cloud.google.com/integration-connectors/docs/overview) configured to interact with your Jira instance. Follow the [documentation](https://google.github.io/adk-docs/tools/google-cloud-tools/#use-integration-connectors) to provision the Integration Connector in Google Cloud and then use this [documentation](https://cloud.google.com/integration-connectors/docs/connectors/jiracloud/configure) to create an Jira connection. Note the `Connection Name`, `Project ID`, and `Location` of your connection.
*
2. **Configure Environment Variables:**
contributing/samples/application_integration_agent/agent.py
+1 -1
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@@ -40,7 +40,7 @@ root_agent = LlmAgent(
model="gemini-2.0-flash",
name="Issue_Management_Agent",
instruction="""
You are an agent that helps manage issues in a JIRA instance.
You are an agent that helps manage issues in a Jira instance.
Be accurate in your responses based on the tool response. You can perform any formatting in the response that is appropriate or if asked by the user.
If there is an error in the tool response, understand the error and try and see if you can fix the error and then and execute the tool again. For example if a variable or parameter is missing, try and see if you can find it in the request or user query or default it and then execute the tool again or check for other tools that could give you the details.
If there are any math operations like count or max, min in the user request, call the tool to get the data and perform the math operations and then return the result in the response. For example for maximum, fetch the list and then do the math operation.
contributing/samples/bigquery/agent.py
+1 -1
View File
@@ -42,7 +42,7 @@ tool_config = BigQueryToolConfig(
)
if CREDENTIALS_TYPE == AuthCredentialTypes.OAUTH2:
# Initiaze the tools to do interactive OAuth
# Initialize the tools to do interactive OAuth
# The environment variables OAUTH_CLIENT_ID and OAUTH_CLIENT_SECRET
# must be set
credentials_config = BigQueryCredentialsConfig(
contributing/samples/code_execution/agent.py
+2 -2
View File
@@ -43,7 +43,7 @@ def base_system_instruction():
```
**Output Visibility:** Always print the output of code execution to visualize results, especially for data exploration and analysis. For example:
- To look a the shape of a pandas.DataFrame do:
- To look at the shape of a pandas.DataFrame do:
```tool_code
print(df.shape)
```
@@ -84,7 +84,7 @@ root_agent = Agent(
You need to assist the user with their queries by looking at the data and the context in the conversation.
You final answer should summarize the code and code execution relavant to the user query.
You final answer should summarize the code and code execution relevant to the user query.
You should include all pieces of data to answer the user query, such as the table from code execution results.
If you cannot answer the question directly, you should follow the guidelines above to generate the next step.
contributing/samples/fields_output_schema/agent.py
+2 -2
View File
@@ -16,7 +16,7 @@ from google.adk import Agent
from pydantic import BaseModel
class WeahterData(BaseModel):
class WeatherData(BaseModel):
temperature: str
humidity: str
wind_speed: str
@@ -43,6 +43,6 @@ Here are the data you have for Cupertino
* wind_speed: 13 mph
""",
output_schema=WeahterData,
output_schema=WeatherData,
output_key='weather_data',
)
contributing/samples/google_api/agent.py
+1 -1
View File
@@ -46,7 +46,7 @@ root_agent = Agent(
Use the provided tools to conduct various operations on users' data in Google BigQuery.
Scenario 1:
The user wants to query their biguqery datasets
The user wants to query their bigquery datasets
Use bigquery_datasets_list to query user's datasets
Scenario 2:
contributing/samples/hello_world_ollama/README.md
+1 -1
View File
@@ -25,7 +25,7 @@ ollama show mistral-small3.1
You are supposed to see `tools` listed under capabilities.
You can also look at the template the model is using and tweak it based on your needs.
You can also look at the model's template and tweak it based on your needs.
```bash
ollama show --modelfile llama3.1 > model_file_to_modify
contributing/samples/jira_agent/agent.py
+1 -1
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@@ -19,7 +19,7 @@ from .tools import jira_tool
root_agent = Agent(
model='gemini-2.0-flash-001',
name='jira_connector_agent',
description='This agent helps search issues in JIRA',
description='This agent helps search issues in Jira',
instruction="""
To start with, greet the user
First, you will be given a description of what you can do.

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