Download history agent

The “default” Agent Profile enables “-HistoryVerboseLevel 1” which provides limited detail in the Distribution database history tracking tables. Using Replication Agent Profile “Verbose history agent profile.” enables “-HistoryVerboseLevel 2” which provides additional diagnostic data while troubleshooting SQL Server Replication. The “Verbose history agent profile.” can be set using Replication Monitor for all types of SQL Replication Agent. Use the “verbose” setting while troubleshooting connectivity or agent performance problem. Once resolved, set the Profile back to “default” to reduce Agent tracking overhead.The detailed Agent history and runtime statistics can also be written to a TEXT file using the “-output” parameter. See KB article 312292 How to enable replication agents for logging to output files in SQL Server.How to enable “Verbose history agent profile.”In Replication Monitor “right-click” a Replication Agent and select “Agent Profile”.Click on “Verbose history agent profile.” to enable detailed logging by the Replication Agent. You will need to stop and restart the Replication Agent for the setting to take effect.Click the details “. . . “ button to review the Agent Profile settings.As shown in the screen shot below, selecting “View Details” after setting “Verbose history agent profile.” provides detailed agent run history along with an Agent summary recorded every 10 minutes.Select the “STATISTICS SINCE AGENT STARTED”, then CTRL-C to copy stats to clipboard. Then PASTE into Notepad.exe.The detailed Agent statistics can be used to troubleshoot SQL Server Replication performance. See Troubleshooting Transactional Replication for more details on using Agent Statistics along with other performance monitoring tools for troubleshooting SQL Server Replication.logread.exe Statistics appear automatically when executing, then stopping LogRead.exe via CMD-prompt providing immediate feedback on throughput while adjusting Log Reader parameters. Output includes a breakout by article showing table\article and type of command was being processed by the Log Reader.With SQL Agent Log Reader job stopped, paste the job parameters along with LogRead.exe into admin cmd-prompt>: C:\Program Files\Microsoft SQL Server\130\COM\logread.exe Allow Log Reader to run for period of time, then stop with CTRL-C, statistics appear in the cmd-console.Sample Log Reader Agent Output******************** STATISTICS SINCE AGENT STARTED ***************************Execution time (ms): 736234 --- about 12 minutesWork time (ms): 736093Distribute Repl

'required': True }] def call(self, params: str, **kwargs) -> str: # `params` are the arguments generated by the LLM agent. prompt = json5.loads(params)['prompt'] prompt = urllib.parse.quote(prompt) return json5.dumps( {'image_url': f' ensure_ascii=False)# Step 2: Configure the LLM you are using.llm_cfg = { # Use the model service provided by DashScope: 'model': 'qwen-max', 'model_server': 'dashscope', # 'api_key': 'YOUR_DASHSCOPE_API_KEY', # It will use the `DASHSCOPE_API_KEY' environment variable if 'api_key' is not set here. # Use a model service compatible with the OpenAI API, such as vLLM or Ollama: # 'model': 'Qwen2-7B-Chat', # 'model_server': ' # base_url, also known as api_base # 'api_key': 'EMPTY', # (Optional) LLM hyperparameters for generation: 'generate_cfg': { 'top_p': 0.8 }}# Step 3: Create an agent. Here we use the `Assistant` agent as an example, which is capable of using tools and reading files.system_instruction = '''You are a helpful assistant.After receiving the user's request, you should:- first draw an image and obtain the image url,- then run code `request.get(image_url)` to download the image,- and finally select an image operation from the given document to process the image.Please show the image using `plt.show()`.'''tools = ['my_image_gen', 'code_interpreter'] # `code_interpreter` is a built-in tool for executing code.files = ['./examples/resource/doc.pdf'] # Give the bot a PDF file to read.bot = Assistant(llm=llm_cfg, system_message=system_instruction, function_list=tools, files=files)# Step 4: Run the agent as a chatbot.messages = [] # This stores the chat history.while True: # For example, enter the query "draw a dog and rotate it 90 degrees". query = input('user query: ') # Append the user query to the chat history. messages.append({'role': 'user', 'content': query}) response = [] for response in bot.run(messages=messages): # Streaming output. print('bot response:') pprint.pprint(response, indent=2) # Append the bot responses to the chat history. messages.extend(response)In addition to using built-in agent implementations such as class Assistant, you can also develop your own agent implemetation by inheriting from class Agent.The framework also provides a convenient GUI interface, supporting the rapid deployment of Gradio Demos for Agents.For example, in the case above, you can quickly launch a Gradio Demo using the following code:from qwen_agent.gui import WebUIWebUI(bot).run() # bot is the agent defined in the above

Over the years working with BizTalk Server I have discovered a couple of things that have been left out of the base BizTalk Server Product, the 1st and foremost is that the Backup BizTalk Server SQL Agent job does not delete the backup files, it has a step to delete the backup history from the database, but not the files from the file system. The other 2 things that can cause issues are related to BAM, when a BAM activity is deployed into BizTalk, it creates a SSIS package that does the Archiving and Deleting of the BAM data, but if you don’t remember to schedule this SSIS package it never happens, the last BAM related one is Scheduled Aggregations. If you are using SQL Server Standard Edition, you cannot enable Real Time Aggregation in your BAM Activity and you must schedule the created Scheduled Aggregation SSIS package to run.Now that we have discussed these 3 missing components to the base BizTalk Server product, lets look at how to solve these issues.SSIS Package to Delete BizTalk Server Database BackupsIn the past I have created a replace stored procedure that will delete the history and files created by the BizTalk Server Backup SQL agent job, the issue with this SQL Stored Procedure was that it required SQL Command Exec to be enabled on the SQL Server and this is considered a security risk by many SQL DBAs.So to please the SQL DBAs I decided that an SSIS package could do the same thing, without needing SQL Command Exec to be enabled, this SSIS package uses that same SQL query as the Clear Backup History step of the default Backup BizTalk Server SQL Agent Job. Below are the instructions to install the SSIS package:Download the DeleteBackupHistoryAndFiles SSIS package for your version of BizTalk and SQL from hereImport SSIS Package into SQL Integration ServicesSelect the SSIS Package from your download locationChange the Protection Level to “Rely on server storage and roles for access control”, Click OKOpen the Backup BizTalk Server SQL Agent Job, Click Steps, Click Clear Backup History, Configure as Shown (replace Server name with your SQL Server Name), Click Data SourcesIn the Data Sources update the name of the SQL Server, Click Set valuesIn the Set values, enter the following 2 values (UseLocalTime should set to the value in Backup Full, DaysToKeep is up to you), Click OK\Package.Variables[User::UseLocalTime].Properties[Value]\Package.Variables[User::DaysToKeep].Properties[Value]The Backup BizTalk Server is now updated, test to make sure it is workingTrouble Shootingmake sure the account the SQL Agent is running under has permissions to delete the backup filesMake sure the Backup BizTalk Server is creating full backups, the job will not delete any files newer than the last full backupSSIS Package