Automatic data processing system and method based on artificial intelligence

Abstract

According to the automatic data processing system and method based on artificial intelligence, a client provides inquiry information to an artificial intelligence platform, so that the inquiry information is provided to a large language model through a decision agent to generate at least one task and select a corresponding task agent; the task agent executes the selected task to generate a task result and a task completion instruction and feeds back the task completion instruction to the decision agent, the decision agent selects the task agent corresponding to the continuous task, and the answer agent generates an answer result from the task results of all the tasks by using an artificial intelligence generation technology and feeds back the answer result to the client; therefore, the technical effect of providing convenient and automatic data processing based on artificial intelligence can be achieved.

Description

Technical Field

[0001] A data processing system and method thereof, particularly an automated data processing system and method based on artificial intelligence. Background Technology

[0002] Existing data processing includes processes such as data querying, data generation, data analysis, and chart / report generation. Data querying involves database administrators or data analysts extracting the required data from the database using SQL and interacting with users through interfaces or dashboards. Data analysis involves data analysts using statistical analysis software (such as SPSS, Python, etc.) to perform data analysis. Chart / report generation involves using professional data visualization tools (such as Tableau, Grafana, etc.) to display the data and generate corresponding reports.

[0003] Existing data processing methods require professional personnel at each stage, resulting in high labor costs. Communication and coordination between different stages take time, making the overall process relatively slow. With diverse and constantly changing needs, existing methods are unable to respond quickly to demands.

[0004] In summary, it is evident that existing data processing technologies have long suffered from the problem of excessive coordination, time-consuming processes, and inability to respond quickly to demands. Therefore, it is necessary to propose improved technical methods to address this issue. Summary of the Invention

[0005] In view of the problems of existing technologies, such as the need for extensive coordination which is time-consuming and unable to respond quickly to demands, this invention discloses an automated data processing system and method based on artificial intelligence, wherein:

[0006] The automated data processing system based on artificial intelligence disclosed in this invention includes: a client and an artificial intelligence platform, wherein the artificial intelligence platform further includes: a decision agent, a task agent and a response agent.

[0007] The client provides and displays query information and obtains and displays the answer results; the artificial intelligence platform establishes a connection with the client to obtain query information from the client and provide the answer results to the client.

[0008] The decision agent, upon receiving query information from the client, provides the query information to the Large Language Model (LLM) to generate at least one task and its corresponding sequence number. The decision agent selects the task agent corresponding to the first task numbered. When a task completion instruction is received, the decision agent selects the task agent corresponding to the next numbered task, until all tasks are completed. The task agents execute the selected tasks to generate task results and task completion instructions, and then feed the task completion instructions back to the decision agent. The response agent uses artificial intelligence generation technology to generate response results from all task results.

[0009] The automated data processing method based on artificial intelligence disclosed in this invention includes the following steps:

[0010] First, the client provides and displays query information. Next, the AI ​​platform further includes a decision agent, multiple task agents, and a response agent. Then, the AI ​​platform establishes a connection with the client to obtain query information from the client. Next, the decision agent provides the query information to a large language model to generate at least one task and its corresponding sequence number. Next, the decision agent selects the task agent corresponding to the first numbered task. Next, the task agent executes the selected task to generate task results and task completion instructions, feeding the task completion instructions back to the decision agent. Next, when a task completion instruction is received, the decision agent selects the task agent corresponding to the next numbered task until all tasks are completed. Next, the response agent uses AI generation technology to generate response results from the task results of all tasks. Finally, the AI ​​platform provides and displays the response results to the client.

[0011] The system and method disclosed in this invention are as described above. The client provides query information to the artificial intelligence platform, which then provides the query information to a large language model through a decision agent to generate at least one task and select a corresponding task agent. The task agent executes the selected task to generate task results and task completion instructions, and feeds back the task completion instructions to the decision agent. The decision agent selects the task agent corresponding to the next task, and the response agent uses artificial intelligence generation technology to generate response results for all task results and feeds them back to the client.

[0012] Through the above-mentioned technical means, the present invention can achieve the technical effect of providing convenient and automated data processing based on artificial intelligence. Attached Figure Description

[0013] Figure 1 The diagram illustrates a system block diagram of the AI-based automated data processing system of this invention.

[0014] Figure 2A as well as Figure 2BThe diagram illustrates a flowchart of the automated data processing method based on artificial intelligence according to the present invention.

[0015] The annotations in the attached figures are explained as follows:

[0016] 10: Client

[0017] 20: Artificial Intelligence Platform

[0018] 21: Decision-making agency

[0019] 22: Task Agent

[0020] 23: Answer the agent

[0021] Step 301: The client provides and displays query information.

[0022] Step 302: The artificial intelligence platform further includes a decision agent, multiple task agents, and a response agent.

[0023] Step 303: The AI ​​platform establishes a connection with the client to obtain query information from the client.

[0024] Step 304: The decision agent provides the query information to the large language model to generate at least one task and its corresponding sequence number.

[0025] Step 305: The decision agent selects the task agent corresponding to the first task number.

[0026] Step 306: The task agent executes the selected task to generate task results and task completion instructions, and sends the task completion instructions back to the decision agent.

[0027] Step 307: When a task completion instruction is received, the decision agent selects the task agent corresponding to the task with the successor label, until all tasks are completed.

[0028] Step 308: The response agent uses artificial intelligence generation technology to generate response results from all task results.

[0029] Step 309: The AI ​​platform provides and displays the answer results to the client. Detailed Implementation

[0030] The following will describe in detail the implementation of the present invention with reference to the accompanying drawings and embodiments, thereby enabling a full understanding of how the present invention uses technical means to solve technical problems and achieve technical effects, and allowing for its implementation.

[0031] The following section will first describe the artificial intelligence-based automated data processing system disclosed in this invention, and please refer to [reference needed]. Figure 1 As shown, Figure 1The diagram illustrates a system block diagram of the AI-based automated data processing system of this invention.

[0032] The automated data processing system based on artificial intelligence disclosed in this invention includes: a client 10 and an artificial intelligence platform 20, wherein the artificial intelligence platform 20 further includes: a decision agent 21, a task agent 22 and a response agent 23.

[0033] Client 10 and artificial intelligence platform 20 establish a connection through wired or wireless transmission. Client 10 is, for example, a regular computer, laptop, tablet, etc. The aforementioned wired transmission methods are, for example, cable networks, fiber optic networks, etc., and the aforementioned wireless transmission methods are, for example, Wi-Fi, mobile communication networks (e.g., 3G, 4G, 5G, etc.). These are merely examples and are not intended to limit the scope of application of the present invention.

[0034] Client 10 provides and displays query information to AI platform 20 through a page provided by AI platform 20. When AI platform 20 obtains query information from client 10, decision agent 21 can provide the query information to large language model to generate at least one task and a corresponding sequence number. Decision agent 21 selects the task agent 22 corresponding to the first numbered task.

[0035] Specifically, assuming the query information is "to query the product yield rate of the last seven days", the decision agent 21 provides the query information "to query the product yield rate of the last seven days" to the large language model to generate a task "query task" and a corresponding sequence number "1". The decision agent 21 selects the task numbered 1 as the "query task" and the corresponding task agent 22 is "execute_sql_agent". This is only an example and is not intended to limit the application scope of the present invention.

[0036] Specifically, assuming the query information is "Analyze the reasons for the low yield from day A to day B", the decision agent 21 provides the query information "Analyze the reasons for the low yield on the third day" to the large language model to generate tasks as "Query Task" with corresponding sequential number "1", "Data Generation Task" with corresponding sequential number "2", "Analysis Task" with corresponding sequential number "3", and "Chart Generation Task" with corresponding sequential number "4". The decision agent 21 first selects task number 1, "Query Task", and the task agent 22 corresponding to it is "execute_sql_agent". This is only an example and is not intended to limit the application scope of the present invention.

[0037] Task agent 22 executes the selected task to generate task results and task completion instructions, and sends the task completion instructions back to decision agent 21. Continuing with the example above, task agent 22 (i.e., execute_sql_agent) executes the "query task" to generate the task result "defective details data from day A to day B" and task completion instructions, and sends the task completion instructions back to decision agent 21.

[0038] When decision agent 21 receives a task completion instruction from task agent 22, it selects the task agent corresponding to the next task number until all tasks are completed. Continuing with the example above, when decision agent 21 receives a task completion instruction from task agent 22, it then selects task number 2, "Data Generation Task," and the corresponding task agent 22 is "sql_to_csv_agent." Task agent 22 (i.e., sql_to_csv_agent) executes the "Data Generation Task" to generate a download file and download path as the task result and task completion instruction based on the specified file format (e.g., CSV file format, DOCX file format, etc.) of "defective detail data from day A to day B." The task completion instruction is then fed back to decision agent 21.

[0039] When decision agent 21 receives the task completion instruction from task agent 22, decision agent 21 then selects task number 3 as the "analysis task" and the corresponding task agent 22 is "call_python_data_analyze_agent". Task agent 22 (i.e., call_python_data_analyze_agent) executes the "analysis task" to autonomously encode the data of "defective details data from day A to day B" in Python, and the analysis result of the clustering characteristics of the defective details is the task result and the task completion instruction. The task completion instruction is fed back to decision agent 21.

[0040] When decision agent 21 receives the task completion instruction from task agent 22, decision agent 21 then selects task number 4 as "chart generation task" and the corresponding task agent 22 is "call_data_drawing_agent". Task agent 22 (i.e., call_data_drawing_agent) executes the "chart generation task" to generate the corresponding chart as the task result and task completion instruction from the data of "defective details data from day A to day B" according to the specified chart type (e.g., line chart, histogram, etc., which is only an example and does not limit the application scope of the present invention), and feeds back the task completion instruction to decision agent 21.

[0041] After the decision agent 21 has selected all the task agents 22 corresponding to the tasks and received the task completion instructions, the response agent 23 uses artificial intelligence generation technology to generate response results for all the task results. The artificial intelligence platform 20 then provides the response results to the client 10, and the client 10 obtains the response results from the artificial intelligence platform 20 and displays them.

[0042] Next, the operation method of the present invention will be described below, and please refer to the following: Figure 2A as well as Figure 2B As shown, Figure 2A as well as Figure 2B The diagram illustrates a flowchart of the automated data processing method based on artificial intelligence according to the present invention.

[0043] The automated data processing method based on artificial intelligence disclosed in this invention includes the following steps:

[0044] First, the client provides and displays query information (step 301); then, the AI ​​platform further includes a decision agent, multiple task agents, and a response agent (step 302); next, the AI ​​platform establishes a connection with the client to obtain query information from the client (step 303); next, the decision agent provides the query information to a large language model to generate at least one task and its corresponding sequence number (step 304); next, the decision agent selects the task agent corresponding to the first numbered task (step 305); next, the task agent executes the selected task to generate task results and task completion instructions, and feeds back the task completion instructions to the decision agent (step 306); next, when a task completion instruction is obtained, the decision agent selects the task agent corresponding to the next numbered task until all tasks are completed (step 307); next, the response agent uses AI generation technology to generate response results for all task results (step 308); and finally, the AI ​​platform provides the response results to the client and displays them (step 309).

[0045] In summary, the client provides query information to the artificial intelligence platform, which then provides the query information to a large language model through a decision agent to generate at least one task and select a corresponding task agent. The task agent executes the selected task to generate task results and task completion instructions, and feeds back the task completion instructions to the decision agent. The decision agent selects the task agent corresponding to the next task, and the response agent uses artificial intelligence generation technology to generate response results for all task results and feeds them back to the client.

[0046] This technology can solve the problems of existing data processing technologies, such as the need for extensive coordination, excessive time consumption, and inability to respond quickly to demands, thereby achieving the technical effect of providing convenient and automated data processing based on artificial intelligence.

[0047] While the embodiments disclosed in this invention are as described above, the content is not intended to directly limit the scope of patent protection of this invention. Any person skilled in the art can make modifications in form and detail without departing from the spirit and scope of this invention. The scope of patent protection of this invention shall still be determined by the scope defined in the appended claims.

Claims

1. An automated data processing system based on artificial intelligence, characterized in that, Include: The client provides and displays query information, and obtains and displays response results; and An artificial intelligence platform establishes a connection with the client to obtain the query information from the client and provides the answer result to the client. The artificial intelligence platform further includes: When the decision agent receives the query information from the client, it provides the query information to a large language model to generate at least one task and a corresponding sequence number. The decision agent selects the task agent corresponding to the first number of the task. When a task completion instruction is received, the decision agent selects the task agent corresponding to the next number of the task, until all tasks are completed. The task agent executes the selected task to generate a task result and a task completion instruction, and feeds back the task completion instruction to the decision agent. and The response agent uses artificial intelligence generation technology to generate the response results for all tasks.

2. The automated data processing system based on artificial intelligence as described in claim 1, characterized in that, When the task agent executes the selected task as a query task, it generates the query result as the task result.

3. The automated data processing system based on artificial intelligence as described in claim 1, characterized in that, When the task agent executes the selected task as a data generation task, it generates a download file and a download path as the task result according to the specified file format.

4. The automated data processing system based on artificial intelligence as described in claim 1, characterized in that, When the task agent executes the selected task as an analysis task, the analysis result of statistical analysis or specified algorithm analysis of the data is the task result.

5. The automated data processing system based on artificial intelligence as described in claim 1, characterized in that, When the task agent executes the selected task as a chart generation task, it generates a corresponding chart based on the specified chart type as the task result.

6. An automated data processing method based on artificial intelligence, characterized in that, Includes the following steps: The client provides and displays the query information; The artificial intelligence platform further includes decision-making agents, multi-task agents, and response agents; The artificial intelligence platform establishes a connection with the client to obtain the query information from the client; The decision agent provides the query information to a large language model to generate at least one task and a corresponding sequence number; The decision agent selects the task agent corresponding to the first numbered task; The task agent executes the selected task to generate task results and task completion instructions, and feeds back the task completion instructions to the decision agent. When the task completion instruction is received, the decision agent selects the task agent corresponding to the task with the successive label, until all tasks are completed; The answer agent uses artificial intelligence generation technology to generate answer results for all tasks; and The artificial intelligence platform provides the answer result to the client and displays it.

7. The automated data processing method based on artificial intelligence as described in claim 6, characterized in that, When the task agent executes the selected task as a query task, it generates the query result as the task result.

8. The automated data processing method based on artificial intelligence as described in claim 6, characterized in that, When the task agent executes the selected task as a data generation task, it generates a download file and a download path as the task result according to the specified file format.

9. The automated data processing method based on artificial intelligence as described in claim 6, characterized in that, When the task agent executes the selected task as an analysis task, the analysis result of statistical analysis or specified algorithm analysis of the data is the task result.

10. The automated data processing method based on artificial intelligence as described in claim 6, characterized in that, When the task agent executes the selected task as a chart generation task, it generates a corresponding chart based on the specified chart type as the task result.

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