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CN-122018966-A - Task processing method, code task processing method and task platform

CN122018966ACN 122018966 ACN122018966 ACN 122018966ACN-122018966-A

Abstract

The embodiment of the specification provides a task processing method, a code task processing method and a task platform, wherein the task processing method comprises the steps of obtaining task data and task description information of a target task, screening task guide information of the target task from a plurality of candidate guide information based on the task description information, wherein the task guide information is used for describing task processing logic of the target task, determining model prompt information and a task processing model of the target task according to the task description information and the task guide information, and inputting the task data and the model prompt information into the task processing model to obtain a task processing result of the target task. By utilizing the task guide information of the target task, accurate model prompt information is automatically generated for the target task and automatically routed to a task processing model matched with the target task, so that the task processing process is more flexible, and the task processing efficiency is improved.

Inventors

  • ZHANG XINDONG
  • LIU LIHUA

Assignees

  • 阿里云计算有限公司

Dates

Publication Date
20260512
Application Date
20241111

Claims (15)

  1. 1. A task processing method, comprising: Acquiring task data and task description information of a target task; task guide information of the target task is screened from a plurality of candidate guide information based on the task description information, wherein the task guide information is used for describing task processing logic of the target task; Determining model prompt information and a task processing model of the target task according to the task description information and the task guide information; And inputting the task data and the model prompt information into the task processing model to obtain a task processing result of the target task.
  2. 2. The method of claim 1, wherein determining the model hint information and the task processing model for the target task based on the task description information and the task guidance information comprises: Analyzing the task guide information, and determining a model prompt template and a plurality of candidate processing models of the target task; Integrating the task description information and the model prompt template to obtain model prompt information of the target task; and screening the task processing model of the target task from the plurality of candidate processing models according to the task description information.
  3. 3. The method of claim 2, the candidate processing model carrying candidate descriptive information including at least one of task type, request object behavior, request resource information, task processing requirements; the task processing model for the target task is screened from the plurality of candidate processing models according to the task description information, and the task processing model comprises the following steps: Matching the task description information with the candidate description information to obtain a first matching result, wherein the first matching result corresponds to the candidate processing model one by one; and screening the task processing model of the target task from the plurality of candidate processing models according to the first matching result.
  4. 4. The method of claim 1, the candidate guidance information comprising a candidate processing logic graph, the task guidance information comprising a task processing logic graph; the task guide information of the target task is selected from a plurality of candidate guide information based on the task description information, and the task guide information comprises: obtaining a plurality of candidate processing logic diagrams, wherein the candidate processing logic diagrams carry candidate task identifications; Matching the target task with the candidate task identifier to obtain a second matching result, wherein the second matching result corresponds to the candidate processing logic diagram one by one; And screening task processing logic diagrams of the target task from the candidate processing logic diagrams according to the second matching result.
  5. 5. The method of claim 4, the obtaining a plurality of candidate processing logic graphs, comprising: candidate processing logic for respectively acquiring a plurality of candidate tasks; Extracting, for a first candidate task, a plurality of processing nodes from candidate processing logic of the first candidate task, wherein the plurality of processing nodes include a hint node and a plurality of model nodes, the first candidate task being any one of the plurality of candidate tasks; constructing an initial processing logic diagram by taking the plurality of processing nodes as diagram nodes and taking logic relations among the plurality of processing nodes as edges, wherein the initial processing logic diagram is used for describing candidate processing logic of the first candidate task; and configuring a model prompt template of the first candidate task on the prompt node, and configuring candidate processing models of the first candidate task on the plurality of model nodes to obtain a candidate processing logic diagram of the first candidate task.
  6. 6. The method of claim 1, wherein the acquiring task data and task description information of the target task includes: responding to a task processing request aiming at a target task, and acquiring task data of the target task; And extracting key information from the task data to obtain task description information of the target task, wherein the task description information comprises at least one of task type, request object behavior, request resource information and task processing requirements.
  7. 7. The method of any one of claims 1 to 6, the task description information comprising model configuration parameters; The step of inputting the task data and the model prompt information into the task processing model, and before obtaining the task processing result of the target task, further comprises the steps of: Performing parameter configuration on the task processing model according to the model configuration parameters to obtain an updated task processing model; Inputting the task data and the model prompt information into the task processing model to obtain a task processing result of the target task, wherein the task processing result comprises the following steps: And inputting the task data and the model prompt information into the updated task processing model to obtain a task processing result of the target task.
  8. 8. The method according to any one of claims 1 to 6, wherein the inputting the task data and the model prompt information into the task processing model, before obtaining the task processing result of the target task, further comprises: under the condition that the task processing model does not meet the task processing conditions, analyzing from the task guide information to obtain a plurality of candidate processing models of the target task; Screening out a target switching model of the target task from the candidate processing models except the task processing model; Inputting the task data and the model prompt information into the task processing model to obtain a task processing result of the target task, wherein the task processing result comprises the following steps: And inputting the task data and the model prompt information into the target switching model to obtain a task processing result of the target task.
  9. 9. The method according to any one of claims 1 to 6, wherein the inputting the task data and the model prompt information into the task processing model, after obtaining the task processing result of the target task, further comprises: Receiving result feedback information sent by a client for the task processing result; And generating a model test result of the task processing model according to the result feedback information.
  10. 10. The method according to claim 9, further comprising, after generating the model test result of the task processing model according to the result feedback information: adjusting the task guide information of the target task under the condition that the model test result does not meet the model test condition, or And under the condition that the model test result does not meet the model test condition, adjusting the model parameters of the task processing model.
  11. 11. A code task processing method, comprising: Acquiring task data and task description information of a target code task; Task guide information of the target code task is screened from a plurality of candidate guide information based on the task description information, wherein the task guide information is used for describing task processing logic of the target code task; determining model prompt information and a task processing model of the target code task according to the task description information and the task guide information; And inputting the task data and the model prompt information into the task processing model to obtain a task processing result of the target code task.
  12. 12. A task platform comprising a request interface and a response unit; The request interface is used for receiving a task processing request aiming at a target task; The response unit is used for responding to the task processing request, acquiring task data and task description information of the target task, screening task guide information of the target task from a plurality of candidate guide information based on the task description information, wherein the task guide information is used for describing task processing logic of the target task, determining model prompt information and task processing models of the target task according to the task description information and the task guide information, and inputting the task data and the model prompt information into the task processing models to obtain task processing results of the target task.
  13. 13. A computing device, comprising: A memory and a processor; The memory is adapted to store a computer program/instruction, the processor being adapted to execute the computer program/instruction, which when executed by the processor, performs the steps of the method of any of claims 1 to 11.
  14. 14. A computer readable storage medium storing a computer program/instruction which, when executed by a processor, implements the steps of the method of any one of claims 1 to 11.
  15. 15. A computer program product comprising computer programs/instructions which, when executed by a processor, implement the steps of the method of any of claims 1 to 11.

Description

Task processing method, code task processing method and task platform Technical Field The embodiment of the specification relates to the technical field of computers, in particular to a task processing method, a code task processing method and a task platform. Background With the development of computer technology, a large model starts to enlarge the wonderful colors, has remarkable capability in terms of language understanding, generation, interaction and reasoning, and is widely applied to the processing fields of dialogue, translation, code processing and the like. Taking the field of code processing as an example, the large model can provide intelligent capabilities such as code completion, code annotation and the like for a developer, so that the development is becoming an important point. Currently, because code tasks such as code completion and code annotation are highly complex, large models suitable for the code tasks are usually manually selected and processed by a human, and corresponding model prompt information is manually written to guide the task processing process of the large models. However, manually selecting a suitable large model and writing model prompts requires a lot of manpower, resulting in extremely low efficiency, and therefore, an efficient task processing scheme is needed. Disclosure of Invention In view of this, the present embodiment provides a task processing method. One or more embodiments of the present specification relate to a code task processing method, a task platform, a task processing device, a code task processing device, a computing device, a computer-readable storage medium, and a computer program product, which solve the technical drawbacks existing in the prior art. According to a first aspect of embodiments of the present specification, there is provided a task processing method, including: Acquiring task data and task description information of a target task; task guide information of a target task is screened out from a plurality of candidate guide information based on the task description information, wherein the task guide information is used for describing task processing logic of the target task; Determining model prompt information and a task processing model of a target task according to the task description information and the task guide information; and inputting the task data and the model prompt information into a task processing model to obtain a task processing result of the target task. According to a second aspect of embodiments of the present specification, there is provided a code task processing method, including: Acquiring task data and task description information of a target code task; Task guide information of the target code task is screened from a plurality of candidate guide information based on the task description information, wherein the task guide information is used for describing task processing logic of the target code task; Determining model prompt information and a task processing model of the target code task according to the task description information and the task guide information; And inputting the task data and the model prompt information into a task processing model to obtain a task processing result of the target code task. According to a third aspect of embodiments of the present specification, there is provided a task processing device including: The first acquisition module is configured to acquire task data and task description information of a target task; The first screening module is configured to screen task guide information of a target task from a plurality of candidate guide information based on task description information, wherein the task guide information is used for describing task processing logic of the target task; the first determining module is configured to determine model prompt information and a task processing model of the target task according to the task description information and the task guide information; The first input module is configured to input task data and model prompt information into a task processing model to obtain a task processing result of a target task. According to a fourth aspect of embodiments of the present specification, there is provided a code task processing device including: the second acquisition module is configured to acquire task data and task description information of the target code task; The second screening module is configured to screen task guide information of the target code task from the plurality of candidate guide information based on the task description information, wherein the task guide information is used for describing task processing logic of the target code task; the second determining module is configured to determine model prompt information and a task processing model of the target code task according to the task description information and the task guide information; and the second input module is configured to input the task data an