Fix/typo (microsoft#1034)

* fix: typo

* fix: typo

* fix: typo of function name

* fix: typo of function name of test file

* Update test_token_count.py

---------

Co-authored-by: Eric Zhu <[email protected]>

autogen/agentchat/assistant_agent.py

@@ -70,7 +70,7 @@ def __init__(
             **kwargs,
         )
 
-        # Update the provided desciption if None, and we are using the default system_message,
+        # Update the provided description if None, and we are using the default system_message,
         # then use the default description.
         if description is None:
             if system_message == self.DEFAULT_SYSTEM_MESSAGE:

autogen/agentchat/contrib/compressible_agent.py

@@ -225,7 +225,7 @@ def _manage_history_on_token_limit(self, messages, token_used, max_token_allowed
         # 1. mode = "TERMINATE", terminate the agent if no token left.
         if self.compress_config["mode"] == "TERMINATE":
             if max_token_allowed - token_used <= 0:
-                # Teminate if no token left.
+                # Terminate if no token left.
                 print(
                     colored(
                         f'Warning: Terminate Agent "{self.name}" due to no token left for oai reply. max token for {model}: {max_token_allowed}, existing token count: {token_used}',
@@ -320,7 +320,7 @@ def on_oai_token_limit(
                         cmsg["role"] = "user"
                     sender._oai_messages[self][i] = cmsg
 
-            # sucessfully compressed, return False, None for generate_oai_reply to be called with the updated messages
+            # successfully compressed, return False, None for generate_oai_reply to be called with the updated messages
             return False, None
         return final, None
 
@@ -332,7 +332,7 @@ def compress_messages(
         """Compress a list of messages into one message.
 
         The first message (the initial prompt) will not be compressed.
-        The rest of the messages will be compressed into one message, the model is asked to distinuish the role of each message: USER, ASSISTANT, FUNCTION_CALL, FUNCTION_RETURN.
+        The rest of the messages will be compressed into one message, the model is asked to distinguish the role of each message: USER, ASSISTANT, FUNCTION_CALL, FUNCTION_RETURN.
         Check out the compress_sys_msg.
 
         TODO: model used in compression agent is different from assistant agent: For example, if original model used by is gpt-4; we start compressing at 70% of usage, 70% of 8092 = 5664; and we use gpt 3.5 here max_toke = 4096, it will raise error. choosinng model automatically?

autogen/agentchat/contrib/gpt_assistant_agent.py

@@ -203,7 +203,7 @@ def _get_run_response(self, thread, run):
                                 new_messages.append(
                                     {
                                         "role": msg.role,
-                                        "content": f"Recieved file id={content.image_file.file_id}",
+                                        "content": f"Received file id={content.image_file.file_id}",
                                     }
                                 )
                 return new_messages
@@ -219,7 +219,7 @@ def _get_run_response(self, thread, run):
                     }
 
                     logger.info(
-                        "Intermediate executing(%s, Sucess: %s) : %s",
+                        "Intermediate executing(%s, Success: %s) : %s",
                         tool_response["name"],
                         is_exec_success,
                         tool_response["content"],

autogen/agentchat/contrib/img_utils.py

@@ -26,7 +26,7 @@ def get_image_data(image_file: str, use_b64=True) -> bytes:
         return content
 
 
-def llava_formater(prompt: str, order_image_tokens: bool = False) -> Tuple[str, List[str]]:
+def llava_formatter(prompt: str, order_image_tokens: bool = False) -> Tuple[str, List[str]]:
     """
     Formats the input prompt by replacing image tags and returns the new prompt along with image locations.
 

autogen/agentchat/contrib/llava_agent.py

@@ -10,7 +10,7 @@
 from regex import R
 
 from autogen.agentchat.agent import Agent
-from autogen.agentchat.contrib.img_utils import get_image_data, llava_formater
+from autogen.agentchat.contrib.img_utils import get_image_data, llava_formatter
 from autogen.agentchat.contrib.multimodal_conversable_agent import MultimodalConversableAgent
 from autogen.code_utils import content_str
 
@@ -162,7 +162,7 @@ def llava_call(prompt: str, llm_config: dict) -> str:
     Makes a call to the LLaVA service to generate text based on a given prompt
     """
 
-    prompt, images = llava_formater(prompt, order_image_tokens=False)
+    prompt, images = llava_formatter(prompt, order_image_tokens=False)
 
     for im in images:
         if len(im) == 0:

autogen/agentchat/conversable_agent.py

@@ -676,7 +676,7 @@ def generate_code_execution_reply(
                 else:
                     messages_to_scan += 1
 
-        # iterate through the last n messages reversly
+        # iterate through the last n messages reversely
         # if code blocks are found, execute the code blocks and return the output
         # if no code blocks are found, continue
         for i in range(min(len(messages), messages_to_scan)):
@@ -1292,7 +1292,7 @@ def update_function_signature(self, func_sig: Union[str, Dict], is_remove: None)
 
         Args:
             func_sig (str or dict): description/name of the function to update/remove to the model. See: https://platform.openai.com/docs/api-reference/chat/create#chat/create-functions
-            is_remove: whether removing the funciton from llm_config with name 'func_sig'
+            is_remove: whether removing the function from llm_config with name 'func_sig'
         """
 
         if not self.llm_config:

autogen/oai/client.py

@@ -136,7 +136,7 @@ def _separate_create_config(self, config):
         return create_config, extra_kwargs
 
     def _client(self, config, openai_config):
-        """Create a client with the given config to overrdie openai_config,
+        """Create a client with the given config to override openai_config,
         after removing extra kwargs.
         """
         openai_config = {**openai_config, **{k: v for k, v in config.items() if k in self.openai_kwargs}}
@@ -244,7 +244,7 @@ def yes_or_no_filter(context, response):
                         try:
                             response.cost
                         except AttributeError:
-                            # update atrribute if cost is not calculated
+                            # update attribute if cost is not calculated
                             response.cost = self.cost(response)
                             cache.set(key, response)
                         self._update_usage_summary(response, use_cache=True)
@@ -349,7 +349,7 @@ def _completions_create(self, client, params):
     def _update_usage_summary(self, response: ChatCompletion | Completion, use_cache: bool) -> None:
         """Update the usage summary.
 
-        Usage is calculated no mattter filter is passed or not.
+        Usage is calculated no matter filter is passed or not.
         """
 
         def update_usage(usage_summary):

autogen/oai/completion.py

@@ -430,7 +430,7 @@ def _eval(cls, config: dict, prune=True, eval_only=False):
                     if previous_num_completions:
                         n_tokens_list[i] += n_output_tokens
                         responses_list[i].extend(responses)
-                        # Assumption 1: assuming requesting n1, n2 responses separatively then combining them
+                        # Assumption 1: assuming requesting n1, n2 responses separately then combining them
                         # is the same as requesting (n1+n2) responses together
                     else:
                         n_tokens_list.append(n_output_tokens)

samples/apps/autogen-assistant/README.md

@@ -77,7 +77,7 @@ Now that you have AutoGen Assistant installed and running, you are ready to expl
 
 This demo focuses on the research assistant use case with some generalizations:
 
-- **Skills**: The agent is provided with a list of skills that it can leverage while attempting to address a user's query. Each skill is a python function that may be in any file in a folder made availabe to the agents. We separate the concept of global skills available to all agents `backend/files/global_utlis_dir` and user level skills `backend/files/user/<user_hash>/utils_dir`, relevant in a multi user environment. Agents are aware skills as they are appended to the system message. A list of example skills is available in the `backend/global_utlis_dir` folder. Modify the file or create a new file with a function in the same directory to create new global skills.
+- **Skills**: The agent is provided with a list of skills that it can leverage while attempting to address a user's query. Each skill is a python function that may be in any file in a folder made available to the agents. We separate the concept of global skills available to all agents `backend/files/global_utlis_dir` and user level skills `backend/files/user/<user_hash>/utils_dir`, relevant in a multi user environment. Agents are aware skills as they are appended to the system message. A list of example skills is available in the `backend/global_utlis_dir` folder. Modify the file or create a new file with a function in the same directory to create new global skills.
 
 - **Conversation Persistence**: Conversation history is persisted in an sqlite database `database.sqlite`.
 

samples/apps/autogen-assistant/autogenra/utils/utils.py

@@ -250,7 +250,7 @@ def get_all_skills(user_skills_path: str, global_skills_path: str, dest_dir: str
     }
 
     if dest_dir:
-        # chcek if dest_dir exists
+        # check if dest_dir exists
         if not os.path.exists(dest_dir):
             os.makedirs(dest_dir)
         # copy all skills to dest_dir

samples/apps/autogen-assistant/frontend/src/components/header.tsx

@@ -94,7 +94,7 @@ const Header = ({ meta, link }: any) => {
                     return (
                       <div
                         key={index + "linkrow"}
-                        className={`text-primary  items-center hover:text-accent hovder:bg-secondary px-1 pt-1 block   text-sm font-medium `}
+                        className={`text-primary  items-center hover:text-accent hover:bg-secondary px-1 pt-1 block   text-sm font-medium `}
                       >
                         <Link
                           className="hover:text-accent h-full flex flex-col"

samples/apps/autogen-assistant/frontend/src/components/utils.ts

@@ -169,7 +169,7 @@ export const ColorTween = (
   endColor: string,
   percent: number
 ) => {
-  // exaple startColor = "#ff0000" endColor = "#0000ff" percent = 0.5
+  // example startColor = "#ff0000" endColor = "#0000ff" percent = 0.5
   const start = {
     r: parseInt(startColor.substring(1, 3), 16),
     g: parseInt(startColor.substring(3, 5), 16),

samples/apps/autogen-assistant/frontend/src/components/views/gallery/gallery.tsx

@@ -129,7 +129,7 @@ const GalleryView = ({ location }: any) => {
           </div>
           <div className="text-xs">
             {" "}
-            {item.messages.length} messsage{item.messages.length > 1 && "s"}
+            {item.messages.length} message{item.messages.length > 1 && "s"}
           </div>
           <div className="my-2 border-t border-dashed w-full pt-2 inline-flex gap-2 ">
             <TagsView tags={item.tags} />{" "}

samples/tools/testbed/README.md

@@ -6,7 +6,7 @@ This Testbed sample has been tested in, and is known to work with, Autogen versi
 
 ## Setup
 
-Before you begin, you must configure your API keys for use with the Testbed. As with other Autogen applications, the Testbed will look for the OpenAI keys in a file in the current working directy, or environment variable named, OAI_CONFIG_LIST. This can be overrriden using a command-line parameter described later.
+Before you begin, you must configure your API keys for use with the Testbed. As with other Autogen applications, the Testbed will look for the OpenAI keys in a file in the current working directory, or environment variable named, OAI_CONFIG_LIST. This can be overridden using a command-line parameter described later.
 
 For some scenarios, additional keys may be required (e.g., keys for the Bing Search API). These can be added to an `ENV` file in the `includes` folder. A sample has been provided in ``includes/ENV.example``. Edit ``includes/ENV`` as needed.
 
@@ -56,7 +56,7 @@ options:
 
 ## Results
 
-By default, the Testbed stores results in a folder heirarchy with the following template:
+By default, the Testbed stores results in a folder hierarchy with the following template:
 
 ``./results/[scenario]/[instance_id]/[repetition]``
 

samples/tools/testbed/run_scenarios.py

@@ -119,7 +119,7 @@ def expand_scenario(scenario_dir, scenario, output_dir):
 
     template = scenario["template"]
 
-    # Either key works for finding the substiturions list. "values" may be deprecated in the future
+    # Either key works for finding the substitutions list. "values" may be deprecated in the future
     substitutions = scenario["substitutions"] if "substitutions" in scenario else scenario["values"]
 
     # Older versions are only one-level deep. Convert them,
@@ -159,7 +159,7 @@ def expand_scenario(scenario_dir, scenario, output_dir):
                 # If the destination is a directory, use the same filename
                 shutil.copyfile(src_path, os.path.join(dest_path, os.path.basename(src_path)))
             else:
-                # Otherwuse use the filename provided
+                # Otherwise use the filename provided
                 shutil.copyfile(src_path, dest_path)
 
     # Expand templated files
@@ -184,7 +184,7 @@ def run_scenario_natively(work_dir):
     Run a scenario in the native environment.
 
     Args:
-        work_dir (path): the path to the working directory previously created to house this sceario instance
+        work_dir (path): the path to the working directory previously created to house this scenario instance
     """
 
     # Get the current working directory
@@ -253,7 +253,7 @@ def run_scenario_in_docker(work_dir, requirements, timeout=600, docker_image=Non
     Run a scenario in a Docker environment.
 
     Args:
-        work_dir (path): the path to the working directory previously created to house this sceario instance
+        work_dir (path): the path to the working directory previously created to house this scenario instance
         timeout (Optional, int): the number of seconds to allow a Docker container to run before timing out
     """
 
@@ -462,7 +462,7 @@ def build_default_docker_image(docker_client, image_tag):
         if not os.path.isfile(req_file):
             raise FileNotFoundError(errno.ENOENT, os.strerror(errno.ENOENT), req_file)
 
-    # Warn aboit a common error
+    # Warn about a common error
     env_file = os.path.join(GLOBAL_INCLUDES_DIR, "ENV")
     example_file = os.path.join(GLOBAL_INCLUDES_DIR, "ENV.example")
     if not os.path.isfile(env_file):

samples/tools/testbed/scenarios/AutoGPT/Templates/TwoAgents/scenario.py

@@ -5,7 +5,7 @@
 testbed_utils.init()
 
 work_dir = "coding"
-target_folder = "__TARGET_FOLDER__"  # path to the arifact folder
+target_folder = "__TARGET_FOLDER__"  # path to the artifact folder
 
 config_list = config_list_from_json("OAI_CONFIG_LIST", filter_dict={"model": ["__MODEL__"]})
 

samples/tools/testbed/scenarios/AutoGPT/challenges/3_qa_small_csv/data.json

@@ -28,5 +28,5 @@
         ]
     },
     "name": "AnswerQuestionSmallCsv",
-    "task": "Read and analyze 'file1.csv', then answer the quetion: How much was spent on utilities in total? Write the answer in file 'output.txt'."
+    "task": "Read and analyze 'file1.csv', then answer the question: How much was spent on utilities in total? Write the answer in file 'output.txt'."
 }

samples/tools/testbed/scenarios/MATH/problems_to_json.py

@@ -46,7 +46,7 @@ def problem_to_json():
     with open("problems.jsonl", "w") as f:
         for i, problem in enumerate(problems):
             # a = {
-            #     'id': f'problem{i}',
+            #     'id': problem{i}',
             #     'template': 'scenario.py',
             #     'substitutions': {
             #         '__PROMPT__': problem,

samples/tools/testbed/utils/collate_autogpt.py

@@ -93,7 +93,7 @@ def collate(results_dir="results"):
 Test_M, x_M0,   x_M1,   ...,    X_MN
 
 
-Where x_ij is the number of AsssitantAgent conversation turns needed to pass all the tests for problem i, in Trial/repetition j. If the agent was not able to pass the tests by the end of the conversation, the value will be -1. If data for the trial is missing, the value will be an empty string "".
+Where x_ij is the number of AssistantAgent conversation turns needed to pass all the tests for problem i, in Trial/repetition j. If the agent was not able to pass the tests by the end of the conversation, the value will be -1. If data for the trial is missing, the value will be an empty string "".
 """.strip(),
         formatter_class=argparse.RawTextHelpFormatter,
     )

samples/tools/testbed/utils/collate_gaia_csv.py

@@ -27,15 +27,15 @@ def collate(results_dir):
     for test_id in os.listdir(results_dir):
         test_path = os.path.join(results_dir, test_id)
 
-        # Collect the reslts vector
+        # Collect the results vector
         results = [test_id]
 
         instance = 0
         instance_dir = os.path.join(test_path, str(instance))
         while os.path.isdir(instance_dir):
             expected_answer_file = os.path.join(instance_dir, "expected_answer.txt")
             if not os.path.isfile(expected_answer_file):
-                # Expected ansewr is missing
+                # Expected answer is missing
                 results.append("")
 
                 instance += 1

samples/tools/testbed/utils/collate_gaia_jsonl.py

@@ -15,10 +15,10 @@ def normalize_answer(a):
 
 def collate(results_dir, instance=0):
     """
-    Collate the results of running GAIA. Print the results in the format acceped by the leaderboard.
+    Collate the results of running GAIA. Print the results in the format accepted by the leaderboard.
 
     Args:
-        results_dir (path): The folder were results were be saved.
+        results_dir (path): The folder where results were be saved.
     """
 
     for test_id in os.listdir(results_dir):
@@ -61,7 +61,7 @@ def collate(results_dir, instance=0):
         description=f"""
 {script_name} will collate the results of the GAIA scenarios into the jsonl format that can be submit to the GAIA leaderboard.
 
-NOTE: You will likely need to concatenate resuls for level 1, level 2 and level 3 to form a complete submission.
+NOTE: You will likely need to concatenate results for level 1, level 2 and level 3 to form a complete submission.
 """.strip(),
         formatter_class=argparse.RawTextHelpFormatter,
     )

samples/tools/testbed/utils/collate_human_eval.py

@@ -83,7 +83,7 @@ def collate(results_dir):
 HumanEval_M, x_M0,   x_M1,   ...,    X_MN
 
 
-Where x_ij is the number of AsssitantAgent conversation turns needed to pass all the tests for problem i, in Trial/repetition j. If the agent was not able to pass the tests by the end of the conversation, the value will be -1. If data for the trial is missing, the value will be an empty string "".
+Where x_ij is the number of AssistantAgent conversation turns needed to pass all the tests for problem i, in Trial/repetition j. If the agent was not able to pass the tests by the end of the conversation, the value will be -1. If data for the trial is missing, the value will be an empty string "".
 """.strip(),
         formatter_class=argparse.RawTextHelpFormatter,
     )

test/agentchat/contrib/test_compressible_agent.py

@@ -138,7 +138,7 @@ def constrain_num_messages(messages):
     sys.platform in ["darwin", "win32"] or not OPENAI_INSTALLED,
     reason="do not run on MacOS or windows or dependency is not installed",
 )
-def test_compress_messsage():
+def test_compress_message():
     assistant = CompressibleAgent(
         name="assistant",
         llm_config={
@@ -202,5 +202,5 @@ def test_mode_terminate():
 if __name__ == "__main__":
     test_mode_compress()
     test_mode_customized()
-    test_compress_messsage()
+    test_compress_message()
     test_mode_terminate()

test/agentchat/contrib/test_gpt_assistant.py

@@ -42,7 +42,7 @@ def test_gpt_assistant_chat():
             },
             "required": ["question"],
         },
-        "description": "This is an API endpoint allowing users (analysts) to input question about GitHub in text format to retrieve the realted and structured data.",
+        "description": "This is an API endpoint allowing users (analysts) to input question about GitHub in text format to retrieve the related and structured data.",
     }
 
     name = "For test_gpt_assistant_chat"
@@ -202,13 +202,13 @@ def test_get_assistant_files():
     )
 
     files = assistant.openai_client.beta.assistants.files.list(assistant_id=assistant.assistant_id)
-    retrived_file_ids = [fild.id for fild in files]
+    retrieved_file_ids = [fild.id for fild in files]
     expected_file_id = file.id
 
     assistant.delete_assistant()
     openai_client.files.delete(file.id)
 
-    assert expected_file_id in retrived_file_ids
+    assert expected_file_id in retrieved_file_ids
 
 
 @pytest.mark.skipif(