chore: fix typos

CHANGELOG.md

@@ -45,12 +45,12 @@
 * Initial release of the Agent Development Kit (ADK).
 * Multi-agent, agent-as-workflow, and custom agent support
 * Tool authentication support
-* Rich tool support, e.g. bult-in tools, google-cloud tools, third-party tools, and MCP tools
+* Rich tool support, e.g. built-in tools, google-cloud tools, third-party tools, and MCP tools
 * Rich callback support
 * Built-in code execution capability
 * Asynchronous runtime and execution
 * Session, and memory support
 * Built-in evaluation support
-* Development UI that makes local devlopment easy
+* Development UI that makes local development easy
 * Deploy to Google Cloud Run, Agent Engine
 * (Experimental) Live(Bidi) auido/video agent support and Compositional Function Calling(CFC) support

pylintrc

@@ -45,7 +45,7 @@ confidence=
 # can either give multiple identifiers separated by comma (,) or put this
 # option multiple times (only on the command line, not in the configuration
 # file where it should appear only once).You can also use "--disable=all" to
-# disable everything first and then reenable specific checks. For example, if
+# disable everything first and then re-enable specific checks. For example, if
 # you want to run only the similarities checker, you can use "--disable=all
 # --enable=similarities". If you want to run only the classes checker, but have
 # no Warning level messages displayed, use"--disable=all --enable=classes

src/google/adk/cli/cli_eval.py

@@ -256,7 +256,7 @@ def run_evals(
         )
 
         if final_eval_status == EvalStatus.PASSED:
-          result = "✅ Passsed"
+          result = "✅ Passed"
         else:
           result = "❌ Failed"
 

src/google/adk/evaluation/agent_evaluator.py

@@ -55,7 +55,7 @@ def load_json(file_path: str) -> Union[Dict, List]:
 
 
 class AgentEvaluator:
-  """An evaluator for Agents, mainly intented for helping with test cases."""
+  """An evaluator for Agents, mainly intended for helping with test cases."""
 
   @staticmethod
   def find_config_for_test_file(test_file: str):
@@ -91,7 +91,7 @@ def evaluate(
         look for 'root_agent' in the loaded module.
       eval_dataset: The eval data set. This can be either a string representing
         full path to the file containing eval dataset, or a directory that is
-        recusively explored for all files that have a `.test.json` suffix.
+        recursively explored for all files that have a `.test.json` suffix.
       num_runs: Number of times all entries in the eval dataset should be
         assessed.
       agent_name: The name of the agent.

src/google/adk/evaluation/response_evaluator.py

@@ -35,7 +35,7 @@ def evaluate(
     Args:
       raw_eval_dataset: The dataset that will be evaluated.
       evaluation_criteria: The evaluation criteria to be used. This method
-        support two criterias, `response_evaluation_score` and
+        support two criteria, `response_evaluation_score` and
         `response_match_score`.
       print_detailed_results: Prints detailed results on the console. This is
         usually helpful during debugging.
@@ -56,7 +56,7 @@ def evaluate(
         Value range: [0, 5], where 0 means that the agent's response is not
         coherent, while 5 means it is . High values are good.
     A note on raw_eval_dataset:
-      The dataset should be a list session, where each sesssion is represented
+      The dataset should be a list session, where each session is represented
       as a list of interaction that need evaluation. Each evaluation is
       represented as a dictionary that is expected to have values for the
       following keys:

src/google/adk/evaluation/trajectory_evaluator.py

@@ -31,10 +31,9 @@ def evaluate(
   ):
     r"""Returns the mean tool use accuracy of the eval dataset.
 
-    Tool use accuracy is calculated by comparing the expected and actuall tool
-    use trajectories. An exact match scores a 1, 0 otherwise. The final number
-    is an
-    average of these individual scores.
+    Tool use accuracy is calculated by comparing the expected and the actual
+    tool use trajectories. An exact match scores a 1, 0 otherwise. The final
+    number is an average of these individual scores.
 
     Value range: [0, 1], where 0 is means none of the too use entries aligned,
     and 1 would mean all of them aligned. Higher value is good.
@@ -45,7 +44,7 @@ def evaluate(
         usually helpful during debugging.
 
     A note on eval_dataset:
-      The dataset should be a list session, where each sesssion is represented
+      The dataset should be a list session, where each session is represented
       as a list of interaction that need evaluation. Each evaluation is
       represented as a dictionary that is expected to have values for the
       following keys:

src/google/adk/flows/llm_flows/agent_transfer.py

@@ -94,7 +94,7 @@ def _build_target_agents_instructions(
 
 If another agent is better for answering the question according to its
 description, call `{_TRANSFER_TO_AGENT_FUNCTION_NAME}` function to transfer the
-question to that agent. When transfering, do not generate any text other than
+question to that agent. When transferring, do not generate any text other than
 the function call.
 """
 

src/google/adk/flows/llm_flows/base_llm_flow.py

@@ -115,7 +115,7 @@ async def run_live(
           yield event
           # send back the function response
           if event.get_function_responses():
-            logger.debug('Sending back last function resonse event: %s', event)
+            logger.debug('Sending back last function response event: %s', event)
             invocation_context.live_request_queue.send_content(event.content)
           if (
               event.content

src/google/adk/flows/llm_flows/contents.py

@@ -111,7 +111,7 @@ def _rearrange_events_for_latest_function_response(
   """Rearrange the events for the latest function_response.
 
   If the latest function_response is for an async function_call, all events
-  bewteen the initial function_call and the latest function_response will be
+  between the initial function_call and the latest function_response will be
   removed.
 
   Args:

src/google/adk/flows/llm_flows/instructions.py

@@ -52,15 +52,15 @@ async def run_async(
     # Appends global instructions if set.
     if (
         isinstance(root_agent, LlmAgent) and root_agent.global_instruction
-    ):  # not emtpy str
+    ):  # not empty str
       raw_si = root_agent.canonical_global_instruction(
           ReadonlyContext(invocation_context)
       )
       si = _populate_values(raw_si, invocation_context)
       llm_request.append_instructions([si])
 
     # Appends agent instructions if set.
-    if agent.instruction:  # not emtpy str
+    if agent.instruction:  # not empty str
       raw_si = agent.canonical_instruction(ReadonlyContext(invocation_context))
       si = _populate_values(raw_si, invocation_context)
       llm_request.append_instructions([si])

src/google/adk/models/gemini_llm_connection.py

@@ -152,7 +152,7 @@ async def receive(self) -> AsyncGenerator[LlmResponse, None]:
         ):
           # TODO: Right now, we just support output_transcription without
           # changing interface and data protocol. Later, we can consider to
-          # support output_transcription as a separete field in LlmResponse.
+          # support output_transcription as a separate field in LlmResponse.
 
           # Transcription is always considered as partial event
           # We rely on other control signals to determine when to yield the
@@ -179,7 +179,7 @@ async def receive(self) -> AsyncGenerator[LlmResponse, None]:
         # in case of empty content or parts, we sill surface it
         # in case it's an interrupted message, we merge the previous partial
         # text. Other we don't merge. because content can be none when model
-        # safty threshold is triggered
+        # safety threshold is triggered
         if message.server_content.interrupted and text:
           yield self.__build_full_text_response(text)
           text = ''

src/google/adk/sessions/database_session_service.py

@@ -217,7 +217,7 @@ def __init__(self, db_url: str):
     """
     # 1. Create DB engine for db connection
     # 2. Create all tables based on schema
-    # 3. Initialize all properies
+    # 3. Initialize all properties
 
     try:
       db_engine = create_engine(db_url)

src/google/adk/sessions/state.py

@@ -26,7 +26,7 @@ def __init__(self, value: dict[str, Any], delta: dict[str, Any]):
     """
     Args:
       value: The current value of the state dict.
-      delta: The delta change to the current value that hasn't been commited.
+      delta: The delta change to the current value that hasn't been committed.
     """
     self._value = value
     self._delta = delta

src/google/adk/tools/load_artifacts_tool.py

@@ -89,7 +89,7 @@ def _append_artifacts_to_llm_request(
   than the function call.
   """])
 
-    # Attache the content of the artifacts if the model requests them.
+    # Attach the content of the artifacts if the model requests them.
     # This only adds the content to the model request, instead of the session.
     if llm_request.contents and llm_request.contents[-1].parts:
       function_response = llm_request.contents[-1].parts[0].function_response

src/google/adk/tools/openapi_tool/auth/credential_exchangers/oauth2_exchanger.py

@@ -66,7 +66,7 @@ def generate_auth_token(
 
     Returns:
         An AuthCredential object containing the HTTP bearer access token. If the
-        HTTO bearer token cannot be generated, return the origianl credential
+        HTTP bearer token cannot be generated, return the original credential.
     """
 
     if "access_token" not in auth_credential.oauth2.token: