Mail processing method and device, electronic equipment and storage medium

Abstract

The invention provides a mail processing method and device, electronic equipment and a storage medium, and relates to the technical field of computers, in particular to the technical field of artificial intelligence such as deep learning and large models. According to the specific scheme, firstly, a mail processing request is received, then, a target mailbox is logged in in a simulation server based on mailbox login information, candidate mails to be processed are obtained from the target mailbox, then, the candidate mails and mail processing rules are input into a large model, a target processing mode output by the large model is obtained, and finally, the candidate mails are processed based on the target processing mode. And processing the candidate mails.

Description

Technical Field

[0001] The present disclosure relates to the field of computer technology, in particular to the field of artificial intelligence technology such as deep learning and large models, and specifically to an email processing method, device, electronic device and storage medium. Background Art

[0002] With the continuous development of computer technology, users have more and more ways to obtain information, and the types of information obtained are also increasing. Among them, the email system is a channel for obtaining information. How to accurately and reliably process the obtained information is a problem that urgently needs to be solved. Summary of the invention

[0003] The present disclosure aims to solve one of the technical problems in the related art at least to some extent.

[0004] The first embodiment of the present disclosure provides a mail processing method, including:

[0005] Receiving an email processing request, wherein the processing request includes email login information of a target email address;

[0006] Based on the mailbox login information, log in to the target mailbox in the simulation server;

[0007] Obtain candidate emails to be processed from the target mailbox;

[0008] Input the candidate emails and email processing rules into the big model to obtain the target processing method output by the big model;

[0009] The candidate emails are processed based on the target processing method.

[0010] The second aspect of the present disclosure provides a mail processing device, including:

[0011] A first receiving module, configured to receive an email processing request, wherein the processing request includes email login information of a target email address;

[0012] A login module, used to log in the target mailbox in the simulation server based on the mailbox login information;

[0013] An acquisition module, used for acquiring candidate emails to be processed from the target mailbox;

[0014] An input module, used for inputting the candidate emails and email processing rules into the big model to obtain the target processing method output by the big model;

[0015] A processing module is used to process the candidate emails based on the target processing method.

[0016] The third aspect of the present disclosure provides a computer device, including: a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, the mail processing method provided in the first aspect of the present disclosure is implemented.

[0017] The fourth aspect of the present disclosure provides a computer-readable storage medium storing a computer program. When the computer program is executed by a processor, the mail processing method provided in the first aspect of the present disclosure is implemented.

[0018] The fifth aspect of the present disclosure provides a computer program product, including a computer program. When the computer program is executed by a processor, the computer program implements the mail processing method provided in the first aspect of the present disclosure.

[0019] The mail processing method, device, electronic device and storage medium provided by the present disclosure have the following beneficial effects:

[0020] In the disclosed embodiment, first, a mail processing request is received, then based on the mailbox login information, the target mailbox is logged in in the simulation server, and candidate mails to be processed are obtained from the target mailbox, and then the candidate mails and mail processing rules are input into the big model to obtain the target processing method output by the big model, and finally, the candidate mails are processed based on the target processing method. Thus, by logging in to the target mailbox in the simulation server based on the mailbox login information, and inputting the candidate mails to be processed in the target mailbox and the mail processing rules into the big model, the processing method of the candidate mails is obtained, and the candidate mails are processed based on the processing method, thereby improving the reliability and efficiency of mail processing and enhancing the user experience.

[0021] It should be understood that the content described in this section is not intended to identify the key or important features of the embodiments of the present disclosure, nor is it intended to limit the scope of the present disclosure. Other features of the present disclosure will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] The accompanying drawings are used to better understand the present solution and do not constitute a limitation of the present disclosure.

[0023] Figure 1 A flowchart of a mail processing method provided by an embodiment of the present disclosure;

[0024] Figure 2 A flowchart of a mail processing method provided by an embodiment of the present disclosure;

[0025] Figure 3 A flowchart of a mail processing method provided by an embodiment of the present disclosure;

[0026] Figure 4 A flowchart of a mail processing method provided by an embodiment of the present disclosure;

[0027] Figure 5 A flowchart of a mail processing method provided by an embodiment of the present disclosure;

[0028] Figure 6 A flowchart of a mail processing method provided by an embodiment of the present disclosure;

[0029] Figure 7 A flowchart of a mail processing method provided by an embodiment of the present disclosure;

[0030] Figure 8 A flowchart of a mail processing method provided by an embodiment of the present disclosure;

[0031] Fig. 9 A schematic diagram of the structure of a mail processing device provided by an embodiment of the present disclosure;

[0032] Fig.10 A block diagram of an exemplary computer device suitable for implementing embodiments of the present disclosure is shown. DETAILED DESCRIPTION

[0033] The following is a description of exemplary embodiments of the present disclosure in conjunction with the accompanying drawings, including various details of the embodiments of the present disclosure to facilitate understanding, which should be considered as merely exemplary. Therefore, it should be recognized by those of ordinary skill in the art that various changes and modifications may be made to the embodiments described herein without departing from the scope and spirit of the present disclosure. Similarly, for the sake of clarity and conciseness, descriptions of well-known functions and structures are omitted in the following description.

[0034] The present disclosure relates to the fields of artificial intelligence technologies such as deep learning and large models.

[0035] Artificial Intelligence (AI) is a new technical science that studies and develops theories, methods, technologies and application systems for simulating, extending and expanding human intelligence.

[0036] Deep Learning (DL) is the process of learning the inherent laws and representation levels of sample data. The information obtained in the learning process is very helpful for interpreting data such as text, images, and sounds. The ultimate goal of deep learning is to enable machines to have analytical learning capabilities like humans and to recognize data such as text, images, and sounds.

[0037] The large model can also be called the Foundation Model. The model extracts knowledge through billions of corpora or images, learns and then produces a large model with billions of parameters.

[0038] In the technical solution of the present disclosure, the collection, storage, use, processing, transmission, provision and disclosure of user personal information involved are in compliance with the provisions of relevant laws and regulations and do not violate public order and good morals.

[0039] The following describes the mail processing method, device, electronic device, and storage medium according to the embodiments of the present disclosure with reference to the accompanying drawings.

[0040] Figure 1 A flowchart of an email processing method provided by an embodiment of the present disclosure.

[0041] like Figure 1 As shown, the mail processing method may include the following steps:

[0042] Step 101: receiving an email processing request, wherein the processing request includes email login information of a target email address.

[0043] The target mailbox may be a mailbox to be processed.

[0044] Among them, the mailbox login information may include the login account and login password of the target mailbox and other information used to log in to the mailbox, and the present disclosure does not limit this.

[0045] In the present disclosure, after receiving an email processing request, the mailbox login information of the target mailbox can be obtained from the request, thereby providing conditions for processing the emails in the target mailbox.

[0046] Step 102: Log into the target mailbox in the simulation server based on the mailbox login information.

[0047] It should be noted that the simulation server may be pre-set and may be used to run application services, which is not limited in the present disclosure.

[0048] In the present disclosure, after receiving an email processing request and determining the mailbox login information including the target mailbox, the target mailbox can be logged in in the simulation server based on the mailbox login information, so that the emails in the target mailbox can be processed.

[0049] Step 103: Obtain candidate emails to be processed from the target mailbox.

[0050] It should be noted that the number and content of candidate emails to be processed obtained from the target mailbox may be any number and content, and the present disclosure does not limit this.

[0051] Optionally, when obtaining candidate emails to be processed from the target mailbox, you can obtain screenshots of the candidate emails to be processed from the target mailbox, or obtain the email content of the candidate emails to be processed from the target mailbox according to pre-set settings or actual needs of the user, thereby improving the flexibility of email processing. The present disclosure does not limit this.

[0052] Step 104, input the candidate emails and email processing rules into the big model to obtain the target processing method output by the big model.

[0053] The mail processing rules may be pre-set or may be determined by the user according to actual needs, and may include rules in any aspect, such as rules for deleting mails or marking mails, etc., which are not limited in the present disclosure.

[0054] The large model may be pre-set, and may be a large model of any type and structure. For example, the large model may be of the GPT type, which is not limited in the present disclosure.

[0055] Among them, GPT is the abbreviation of Generative Pre-Training Transformer (GPT), which is a deep learning model.

[0056] The target processing method may be any pre-set method, for example, the target processing method may be deleting mail, marking mail, moving mail, reading mail, etc., which is not limited in the present disclosure.

[0057] In the present disclosure, after obtaining the candidate emails to be processed from the target mailbox, in order to accurately determine the processing method for the candidate emails, the candidate emails and the email processing rules can be input into a large model. The large model determines whether the candidate email triggers the processing rules. When the processing rules are triggered, the target processing method for the candidate email is output, thereby improving the efficiency and accuracy of determining the target processing method.

[0058] Step 105: Process the candidate emails based on the target processing method.

[0059] In the present disclosure, after obtaining the target processing method output by the large model, the candidate emails can be processed by the accessibility service based on the target processing method. For example, when the target processing method is to delete the candidate email, the accessibility service can delete the candidate email in the target mailbox, etc., and the present disclosure does not limit this.

[0060] It should be noted that the accessibility service may be an application service pre-set in the simulation server, which may process the candidate emails, such as deleting, marking, moving, reading, etc., which is not limited in the present disclosure.

[0061] In the disclosed embodiment, first, a mail processing request is received, then based on the mailbox login information, the target mailbox is logged in in the simulation server, and candidate mails to be processed are obtained from the target mailbox, and then the candidate mails and mail processing rules are input into the big model to obtain the target processing method output by the big model, and finally, the candidate mails are processed based on the target processing method. Thus, by logging in to the target mailbox in the simulation server based on the mailbox login information, and inputting the candidate mails to be processed in the target mailbox and the mail processing rules into the big model, the processing method of the candidate mails is obtained, and the candidate mails are processed based on the processing method, thereby improving the reliability and efficiency of mail processing and enhancing the user experience.

[0062] Figure 2 A flowchart of an email processing method provided by an embodiment of the present disclosure.

[0063] like Figure 2 As shown, the mail processing method may include the following steps:

[0064] Step 201: receiving an email processing request, wherein the processing request includes email login information of a target email address.

[0065] Step 202: Log into the target mailbox in the simulation server based on the mailbox login information.

[0066] The specific implementation forms of step 201 to step 202 can refer to the detailed descriptions in other embodiments of the present disclosure, and will not be described in detail here.

[0067] Step 203: traverse the record list based on the identifier of the target mailbox to obtain the first time of the latest processing record associated with the identifier of the target mailbox.

[0068] The target mailbox identifier can be used to represent the target mailbox, and can be any pre-set identifier. For example, the target mailbox identifier can be the mailbox account of the target mailbox, etc., which is not limited in the present disclosure.

[0069] The record list may be a list for recording mail processing records.

[0070] In the present disclosure, after logging into the target mailbox in the simulation server, in order to improve the accuracy of the determined candidate mails to be processed, the record list can be traversed based on the identifier of the target mailbox to obtain the first time of the latest processing record associated with the identifier of the target mailbox.

[0071] Step 204: determine each email in the target mailbox whose time is after the first time as a candidate email.

[0072] In the present disclosure, after the first time of obtaining the latest processing record associated with the identifier of the target mailbox, each email in the target mailbox located after the first time can be determined as an email to be processed. At this time, each email located after the first time can be determined as a candidate email, thereby improving the accuracy of the obtained candidate emails.

[0073] Step 205, input the candidate emails and email processing rules into the big model to obtain the target processing method output by the big model.

[0074] Step 206: Process the candidate emails based on the target processing method.

[0075] The specific implementation forms of step 205 to step 206 can refer to the detailed descriptions in other embodiments of the present disclosure, and will not be described in detail here.

[0076] In the disclosed embodiment, firstly, a mail processing request is received, then based on the mail login information, the target mail box is logged in to the simulation server, then based on the identifier of the target mail box, the record list is traversed to obtain the first time of the latest processing record associated with the identifier of the target mail box, and each mail in the target mail box whose time is after the first time is determined as a candidate mail, and finally the candidate mail and the mail processing rules are input into the large model to obtain the target processing method output by the large model, and the candidate mail is processed based on the target processing method. Thus, after logging in to the target mail box in the simulation server, the time of the latest processing record is obtained from the record list associated with the identifier of the target mail box, and the mails after the time are determined as candidate mails, the candidate mails and the mail processing rules are input into the large model to obtain the processing method of the candidate mails, and the candidate mails are processed based on the processing method, thereby improving the accuracy and reliability of mail processing.

[0077] Figure 3 A flowchart of an email processing method provided by an embodiment of the present disclosure.

[0078] like Figure 3 As shown, the mail processing method may include the following steps:

[0079] Step 301: Receive an email processing request, wherein the processing request includes email login information of a target email address.

[0080] Step 302: Log into the target mailbox in the simulation server based on the mailbox login information.

[0081] Step 303: Obtain candidate emails to be processed from the target mailbox.

[0082] The specific implementation forms of steps 301 to 303 can refer to the detailed descriptions in other embodiments of the present disclosure, and will not be described in detail here.

[0083] Step 304: determine the association relationship between the rules in the processing rule base.

[0084] The processing rule base may be a rule base for storing email processing rules, may be a database, or may be pre-set, which is not limited in the present disclosure.

[0085] It should be noted that the rules in the processing rule base can be pre-set or can also be determined according to the actual needs of the user. For example, after determining the newly added rules, modified rules, or deleted rules in the processing rule base, the user can call the database service through the access service to adjust the rules in the processing rule base, wherein the access service can be pre-set and used to call the corresponding service based on the user's request, which is not limited in this disclosure.

[0086] It should be noted that when storing rules, the processing rule library may record the rules in the form of a rule table <rule identifier, rule content, processing method>, and the present disclosure does not limit this.

[0087] In the present disclosure, after obtaining candidate emails to be processed from the target mailbox, in order to determine the processing method for the candidate emails, the association relationship between the rules in the processing rule library can be determined first. For example, when there are multiple rules in the processing rule library that are all rules for deleting emails, it can be determined that there is an association relationship between the multiple rules, or when there is a rule in the processing rule library that is a rule for marking emails and another rule that is a rule for moving emails, then there is no association relationship between the two rules, etc., and the present disclosure does not limit this.

[0088] Step 305: When there is no correlation between the rules in the processing rule library, a prompt message is generated based on the candidate email and an email processing rule.

[0089] In the present disclosure, after determining the association relationship between the rules in the processing rule base, if there is no association relationship between the rules in the processing rule base, a large model prompt information can be generated based on the candidate email and an email processing rule, thereby providing conditions for determining the processing method of the candidate email under the one email rule.

[0090] It should be noted that when generating prompt information based on candidate emails and an email processing rule, since the candidate email can be a screenshot of the candidate email, or can also be the email content of the candidate email, the present disclosure can either splice the screenshot of the candidate email with the rule to generate prompt information, or splice the email content of the candidate email with the rule to generate prompt information, and the present disclosure does not limit this.

[0091] It should be noted that, when there is no correlation between the rules in the processing rule base, prompt information can be generated based on the candidate email and each rule in the processing rule base, and the present disclosure does not limit this.

[0092] Step 306, input the prompt information into the big model, and obtain the target processing method under the email processing rule output by the big model.

[0093] In the present disclosure, after the prompt information is generated and input into the large model, the target processing method under the one email processing rule output by the large model can be obtained, thereby improving the efficiency and reliability of determining the target processing method for the candidate email.

[0094] Step 307: Process the candidate emails based on the target processing method.

[0095] The specific implementation form of step 307 can refer to the detailed description in other embodiments of the present disclosure, and will not be described in detail here.

[0096] In the disclosed embodiment, first, a mail processing request is received, then based on the mailbox login information, the target mailbox is logged in in the simulation server, and candidate mails to be processed are obtained from the target mailbox, and then the association between the rules in the processing rule library is determined. In the case where there is no association between the rules in the processing rule library, prompt information is generated based on the candidate mail and a mail processing rule, and the prompt information is input into the large model to obtain the target processing method under the mail processing rule output by the large model, and finally the candidate mail is processed based on the target processing method. Thus, after logging in to the target mailbox in the simulation server and obtaining the candidate mails to be processed in the target mailbox, in the case where there is no association between the rules in the processing rule library, prompt information is generated based on the candidate mail and each rule, respectively, and input into the large model to obtain the processing method for the candidate mail, and the candidate mail is processed based on the processing method, thereby improving the efficiency and accuracy of mail processing.

[0097] Figure 4 A flowchart of an email processing method provided by an embodiment of the present disclosure.

[0098] like Figure 4As shown, the mail processing method may include the following steps:

[0099] Step 401: Receive an email processing request, wherein the processing request includes mailbox login information of a target mailbox.

[0100] Step 402, based on the mailbox login information, log in to the target mailbox in the simulation server.

[0101] Step 403: Obtain candidate emails to be processed from the target mailbox.

[0102] Step 404: determine the association relationship between the rules in the processing rule base.

[0103] The specific implementation forms of steps 401 to 404 can refer to the detailed descriptions in other embodiments of the present disclosure, and will not be described in detail here.

[0104] Step 405: When there is an association relationship between at least two processing rules, the at least two processing rules are spliced ​​based on the association relationship to obtain a spliced ​​processing rule.

[0105] In the present disclosure, after determining the association relationship between the rules in the processing rule library, when there is an association relationship between at least two processing rules, in order to improve the accuracy and reliability of candidate email processing, at least two processing rules can be spliced ​​based on the association relationship to obtain the spliced ​​processing rules.

[0106] Step 406: Generate prompt information based on the combined processing rules and candidate emails.

[0107] In the present disclosure, after obtaining the spliced ​​processing rules, prompt information can be generated based on the spliced ​​processing rule set candidate emails, thereby improving the reliability of the processing method of the large model output.

[0108] Step 407, input the prompt information into the large model, and obtain the target processing method under the spliced ​​email processing rules output by the large model.

[0109] In the present disclosure, after the prompt information is generated, the prompt information can be input into the big model to obtain the target processing method under the spliced ​​mailbox processing rules output by the big model, thereby improving the accuracy of the determined target processing rules.

[0110] Step 408: Process the candidate emails based on the target processing method.

[0111] The specific implementation of step 408 can be referred to the detailed description in other embodiments of the present disclosure, and will not be described in detail here.

[0112] In the disclosed embodiment, first, a mail processing request is received, then based on the mailbox login information, the target mailbox is logged in in the simulation server, and the candidate mails to be processed are obtained from the target mailbox, and then the association relationship between the rules in the processing rule library is determined, and in the case where there is an association relationship between at least two processing rules, at least two processing rules are spliced ​​based on the association relationship to obtain the spliced ​​processing rules, and prompt information is generated based on the spliced ​​processing rules and the candidate mails, and finally the prompt information is input into the large model to obtain the target processing method under the spliced ​​mail processing rules output by the large model, and the candidate mails are processed based on the target processing method. Thus, by logging in to the target mailbox in the simulation server and obtaining the candidate mails to be processed, in the case where there is an association relationship between at least two processing rules in the processing rule library, at least two processing rules are spliced ​​based on the association relationship, and based on the spliced ​​processing rule set candidate mails, the prompt information of the large model is generated, the processing method under the spliced ​​processing rules output by the large model is obtained, and the candidate mails are processed, thereby improving the reliability and accuracy of mail processing.

[0113] Figure 5 A flowchart of an email processing method provided by an embodiment of the present disclosure.

[0114] like Figure 5 As shown, the mail processing method may include the following steps:

[0115] Step 501: Receive an email processing request, wherein the processing request includes mailbox login information of a target mailbox.

[0116] Step 502: Log into the target mailbox in the simulation server based on the mailbox login information.

[0117] Step 503: Obtain candidate emails to be processed from the target mailbox.

[0118] Step 504, input the candidate emails and email processing rules into the big model to obtain the target processing method output by the big model.

[0119] Step 505: Process the candidate emails based on the target processing method.

[0120] The specific implementation forms of steps 501 to 505 can refer to the detailed descriptions in other embodiments of the present disclosure, and will not be described in detail here.

[0121] Step 506: Generate a processing record based on the subject, processing time and target processing method of the candidate email.

[0122] The subject of the candidate email may be the title of the candidate email, which is not limited in the present disclosure.

[0123] In the present disclosure, after processing a candidate email, a processing record of the candidate email can be generated based on the subject, processing time and target processing method of the candidate email, so that the next time the target mailbox is processed, the candidate email to be processed can be quickly and efficiently determined, thereby improving email processing efficiency.

[0124] Step 507: Store the processing record into the record list associated with the target mailbox.

[0125] In the present disclosure, after the processing record of the candidate mail is generated, the processing record can be stored in the record list associated with the target mailbox, thereby updating the data in the record list associated with the target mailbox and improving the accuracy and reliability of the data in the record list.

[0126] In the disclosed embodiment, firstly, an email processing request is received, then based on the email login information, the target email is logged in in the simulation server, and the candidate emails to be processed are obtained from the target email. Then, the candidate emails and the email processing rules are input into the large model to obtain the target processing method output by the large model, and based on the target processing method, the candidate emails are processed. Finally, based on the subject, processing time and target processing method of the candidate email, a processing record is generated, and the processing record is stored in the record list associated with the target email. Thus, after logging in to the target email in the simulation server and determining the candidate email to be processed, the candidate emails and the email processing rules are processed through the large model, the processing method is obtained, the candidate emails are processed, and the processing record of the candidate emails is generated and stored in the record list associated with the target email, thereby improving the efficiency and accuracy of email processing.

[0127] Figure 6 A flowchart of an email processing method provided by an embodiment of the present disclosure.

[0128] like Figure 6 As shown, the mail processing method may include the following steps:

[0129] Step 601: Receive an email processing request, wherein the processing request includes email login information of a target email address.

[0130] Step 602, based on the mailbox login information, log in to the target mailbox in the simulation server.

[0131] The specific implementation forms of step 601 to step 602 can refer to the detailed descriptions in other embodiments of the present disclosure, and will not be described in detail here.

[0132] Step 603: When the second time corresponding to the latest email in the target mailbox is less than the first time of the latest processed record in the record list associated with the target mailbox, it is determined that there is no candidate email to be processed in the target mailbox.

[0133] In the present disclosure, after logging into the target mailbox in the simulation server, if the second time corresponding to the latest email in the target mailbox is less than the first time of the latest record in the record list associated with the target mailbox, it can be determined that the latest email has been processed. At this time, it can be determined that there are no candidate emails to be processed in the target mailbox, thereby reducing resource waste and improving the reliability of email processing.

[0134] Step 604, based on a preset cycle, returns to execute the operation of logging into the target mailbox in the simulation server based on the mailbox login information.

[0135] The preset period may be a period for processing mails in the target mailbox, which may be preset or determined according to actual needs of the user, and the present disclosure does not limit this.

[0136] In the present disclosure, after determining that there are no candidate emails to be processed in the target mailbox, the operation of logging into the target mailbox in the simulation server based on the mailbox login record can be returned based on a preset period, thereby achieving periodic processing of emails and improving the reliability of email processing.

[0137] In the disclosed embodiment, firstly, a mail processing request is received, then based on the mail login information, the target mail box is logged in in the simulation server, and when the second time corresponding to the latest mail in the target mail box is less than the first time of the latest processing record in the record list associated with the target mail box, it is determined that there are no candidate mails to be processed in the target mail box, and finally based on a preset cycle, the operation of logging in to the target mail box in the simulation server based on the mail login information is returned to be executed. Thus, after the target mail box is always logged in to the simulation server, when the time of the latest mail in the target mail box is less than the time of the latest processing record of the target mail box, it is determined that there are no mails to be processed in the target mail box, and based on the mail processing cycle, the operation of logging in to the target mail box in the simulator is returned to be executed, thereby improving the reliability of mail processing.

[0138] Figure 7 A flowchart of an email processing method provided by an embodiment of the present disclosure.

[0139] like Figure 7 As shown, the mail processing method may include the following steps:

[0140] Step 701: Receive a processing rule update instruction, wherein the update instruction includes the email processing rule to be updated.

[0141] It should be noted that the update instruction may be an instruction for adding, deleting, replacing, etc. the rules in the rule base, and the present disclosure does not limit this.

[0142] It should be noted that the email processing rules to be updated included in the update instruction can be determined according to actual needs of the user, for example, email processing rules to be deleted or added in the processing rule library, and the present disclosure does not limit this.

[0143] In the present disclosure, in order to ensure the accuracy and reliability of the rules in the processing rule base, a processing rule update instruction may be received to obtain the mail processing rules to be updated, so as to update the rule base.

[0144] Step 702: Update the rule base based on the email processing rule to be updated.

[0145] In the present disclosure, after receiving a processing rule update instruction, the rule base can be updated to ensure the accuracy and reliability of the processing rules in the rule base and improve the accuracy of email processing.

[0146] Combine the following Figure 8 , an example is given to illustrate the mail processing method proposed in the present disclosure, Figure 8 A flowchart of the email processing method provided in an embodiment of the present disclosure.

[0147] like Figure 8 As shown, after logging into the mailbox in the simulation server, the accessibility service can be used to access the mail in the mailbox, and obtain the mail screenshot or mail content, and then obtain the processing rules for mail processing through the database service, and splice the processing rules and the mail screenshot or content into prompt information, which is input into the big model, and the big model determines whether the corresponding mail triggers the processing rules. If the processing rules are triggered, the big model outputs the processing method for the mail, and the accessibility service can process the mail based on the processing method, and can call the database service to store the mail processing record, thereby improving the efficiency and reliability of mail processing. The present disclosure does not limit this.

[0148] It should be noted that when logging into multiple mailboxes in the simulation server, you can also process the mails in the mailboxes one by one through multiple accessibility services, such as Figure 7 Accessibility service 1 processes mails in mailbox 1, accessibility service 2 processes mails in mailbox 2, accessibility service n processes mails in mailbox n, and so on, which is not limited in the present disclosure.

[0149] Furthermore, users can also set and adjust the processing rules. When users operate on the processing rules, they can trigger the access service through HTTP triggers, and call the database service through the access service to operate and set the rules in the processing rule library, so that the rules in the processing rule library are more in line with user needs and the accuracy of email processing is improved. The present disclosure does not limit this.

[0150] In the disclosed embodiment, a processing rule update instruction is first received, and then the rule base is updated based on the email processing rule to be updated. Thus, by updating the rules in the processing rule base based on the rule update instruction, the data accuracy and reliability in the processing rule base are improved, providing conditions for improving the accuracy of email processing.

[0151] In order to implement the above embodiment, the present disclosure also proposes a mail processing device.

[0152] Fig. 9 A schematic diagram of the structure of a mail processing device provided in an embodiment of the present disclosure.

[0153] like Fig. 9 As shown, the mail processing device 900 includes: a first receiving module 901 , a login module 902 , an acquisition module 903 , an input module 904 , and a processing module 905 .

[0154] The first receiving module 901 is used to receive an email processing request, wherein the processing request includes the mailbox login information of the target mailbox;

[0155] A login module 902, used to log in to a target mailbox in a simulation server based on the mailbox login information;

[0156] The acquisition module 903 is used to acquire candidate emails to be processed from the target mailbox;

[0157] An input module 904 is used to input candidate emails and email processing rules into the big model to obtain a target processing method output by the big model;

[0158] The processing module 905 is used to process the candidate emails based on the target processing method.

[0159] In a possible implementation of the present disclosure, the acquisition module 903 is specifically configured to:

[0160] Traversing the record list based on the identifier of the target mailbox, obtaining the first time of the latest processed record associated with the identifier of the target mailbox;

[0161] Each email in the target mailbox whose time is after the first time is determined as a candidate email.

[0162] In a possible implementation of the present disclosure, the acquisition module 903 is specifically used for any of the following:

[0163] Take a screenshot of candidate emails to be processed from the target mailbox;

[0164] Get the message content of the candidate messages to be processed from the target mailbox.

[0165] In a possible implementation of the present disclosure, the input module 904 is specifically used to:

[0166] Determine the relationship between the rules in the processing rule base;

[0167] In the case where there is no correlation between the rules in the processing rule base, a prompt message is generated based on the candidate email and an email processing rule;

[0168] The prompt information is input into the big model, and the target processing method under the mail processing rule output by the big model is obtained.

[0169] In a possible implementation of the present disclosure, the input module 904 is further configured to:

[0170] In the case where there is an association relationship between at least two processing rules, the at least two processing rules are spliced ​​based on the association relationship to obtain a spliced ​​processing rule;

[0171] Generate prompt information based on the spliced ​​processing rules and candidate emails;

[0172] The prompt information is input into the big model to obtain the target processing method output by the big model under the spliced ​​mail processing rules.

[0173] In a possible implementation of the present disclosure, the processing module 905 is further configured to:

[0174] Generate a processing record based on the subject, processing time and target processing method of the candidate email;

[0175] Store the processed records into the record list associated with the target mailbox.

[0176] In a possible implementation of the present disclosure, the processing module 905 is further configured to:

[0177] When the second time corresponding to the latest email in the target mailbox is less than the first time of the latest processed record in the record list associated with the target mailbox, it is determined that there is no candidate email to be processed in the target mailbox.

[0178] In a possible implementation of the present disclosure, the processing module 905 is further configured to:

[0179] Based on the preset cycle, return to execute the operation of logging into the target mailbox in the simulation server based on the mailbox login information.

[0180] In a possible implementation of the present disclosure, it further includes:

[0181] A second receiving module (not shown in the figure), used for receiving a processing rule update instruction, wherein the update instruction includes the email processing rule to be updated;

[0182] The updating module (not shown in the figure) is used to update the rule base based on the mail processing rules to be updated.

[0183] The functions and specific implementation principles of the above modules in the embodiments of the present disclosure can be referred to the above method embodiments, and will not be repeated here.

[0184] In the disclosed embodiment, first, a mail processing request is received, then based on the mailbox login information, the target mailbox is logged in in the simulation server, and candidate mails to be processed are obtained from the target mailbox, and then the candidate mails and mail processing rules are input into the big model to obtain the target processing method output by the big model, and finally, the candidate mails are processed based on the target processing method. Thus, by logging in to the target mailbox in the simulation server based on the mailbox login information, and inputting the candidate mails to be processed in the target mailbox and the mail processing rules into the big model, the processing method of the candidate mails is obtained, and the candidate mails are processed based on the processing method, thereby improving the reliability and efficiency of mail processing and enhancing the user experience.

[0185] According to an embodiment of the present disclosure, the present disclosure also provides an electronic device, a readable storage medium and a computer program product.

[0186] Fig.10 A schematic block diagram of an example electronic device 1000 that can be used to implement an embodiment of the present disclosure is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present disclosure described and / or required herein.

[0187] like Fig.10As shown, the device 1000 includes a computing unit 1001, which can perform various appropriate actions and processes according to a computer program stored in a read-only memory (ROM) 1002 or a computer program loaded from a storage unit 1008 into a random access memory (RAM) 1003. In the RAM 1003, various programs and data required for the operation of the device 1000 can also be stored. The computing unit 1001, the ROM 1002, and the RAM 1003 are connected to each other via a bus 1004. An input / output (I / O) interface 1005 is also connected to the bus 1004.

[0188] A number of components in the device 1000 are connected to the I / O interface 1005, including: an input unit 1006, such as a keyboard, a mouse, etc.; an output unit 1007, such as various types of displays, speakers, etc.; a storage unit 1008, such as a disk, an optical disk, etc.; and a communication unit 1009, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 1009 allows the device 1000 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0189] The computing unit 1001 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the computing unit 1001 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, digital signal processors (DSPs), and any appropriate processors, controllers, microcontrollers, etc. The computing unit 1001 performs the various methods and processes described above, such as the mail processing method. For example, in some embodiments, the mail processing method may be implemented as a computer software program, which is tangibly contained in a machine-readable medium, such as a storage unit 1008. In some embodiments, part or all of the computer program may be loaded and / or installed on the device 1000 via ROM 1002 and / or the communication unit 1009. When the computer program is loaded into RAM 1003 and executed by the computing unit 1001, one or more steps of the mail processing method described above may be performed. Alternatively, in other embodiments, the computing unit 1001 may be configured to perform the mail processing method in any other appropriate manner (e.g., by means of firmware).

[0190] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0191] The program code for implementing the method of the present disclosure may be written in any combination of one or more programming languages. These program codes may be provided to a processor or controller of a general-purpose computer, a special-purpose computer, or other programmable mail processing device, so that when the program code is executed by the processor or controller, the functions / operations specified in the flow chart and / or block diagram are implemented. The program code may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0192] In the context of the present disclosure, a machine-readable medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, device, or equipment. A machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or equipment, or any suitable combination of the foregoing. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0193] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user can provide input to the computer. Other types of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0194] The systems and techniques described herein can be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), the Internet, and a blockchain network.

[0195] A computer system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The relationship between the client and the server is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS services ("Virtual Private Server", or "VPS" for short). The server may also be a server of a distributed system, or a server combined with a blockchain.

[0196] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps recorded in this disclosure can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solutions disclosed in this disclosure can be achieved, and this document does not limit this.

[0197] In addition, the terms "first" and "second" are used for descriptive purposes only and cannot be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, the features defined as "first" and "second" may explicitly or implicitly include at least one of the features. In the description of the present disclosure, the meaning of "multiple" is at least two, such as two, three, etc., unless otherwise clearly and specifically defined. In the description of the present disclosure, the words "if" and "if" used can be interpreted as "at the time of" or "when" or "in response to determination" or "under the circumstances of".

[0198] The above specific implementations do not constitute a limitation on the protection scope of the present disclosure. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present disclosure shall be included in the protection scope of the present disclosure.

Claims

1. A mail processing method, comprising: Receiving an email processing request, wherein the processing request includes email login information of a target email address; Based on the mailbox login information, log in to the target mailbox in the simulation server; Obtain candidate emails to be processed from the target mailbox; Input the candidate emails and email processing rules into the big model to obtain the target processing method output by the big model; The candidate emails are processed based on the target processing method.

2. The method of claim 1, wherein: The obtaining candidate emails to be processed from the target mailbox includes: Traversing the record list based on the identifier of the target mailbox, obtaining the first time of the latest processing record associated with the identifier of the target mailbox; Each email in the target mailbox whose time is after the first time is determined as a candidate email.

3. The method of claim 1, wherein: The obtaining of candidate emails to be processed from the target mailbox includes any of the following: Obtaining a screenshot of candidate emails to be processed from the target mailbox; The email content of the candidate email to be processed is obtained from the target mailbox.

4. The method of claim 1, wherein: The step of inputting the candidate emails and email processing rules into the big model to obtain the target processing method output by the big model includes: Determine the relationship between the rules in the processing rule base; In the case where there is no correlation between the rules in the processing rule library, generating prompt information based on the candidate email and one of the email processing rules; The prompt information is input into the big model to obtain the target processing method output by the big model under the mail processing rule.

5. The method of claim 4, wherein: After determining the association relationship between the rules in the processing rule base, the method further includes: In the case where there is an association relationship between at least two processing rules, the at least two processing rules are spliced ​​based on the association relationship to obtain a spliced ​​processing rule; Generate prompt information based on the spliced ​​processing rules and the candidate emails; The prompt information is input into the large model to obtain the target processing method output by the large model under the spliced ​​mail processing rules.

6. The method according to any one of claims 1 to 5, wherein: After processing the candidate emails based on the target processing method, the method further includes: Generate a processing record based on the subject, processing time and target processing method of the candidate email; The processing record is stored in a record list associated with the target mailbox.

7. The method of claim 6, wherein: After logging into the target mailbox in the simulation server based on the mailbox login information, the method further includes: When the second time corresponding to the latest email in the target mailbox is less than the first time of the latest processed record in the record list associated with the target mailbox, it is determined that there is no candidate email to be processed in the target mailbox.

8. The method of claim 7, wherein: After processing the candidate emails based on the target processing method, the method further includes: Based on a preset cycle, return to execute the operation of logging into the target mailbox in the simulation server based on the mailbox login information.

9. The method according to any one of claims 1 to 5, wherein: The method further comprises: Receiving a processing rule update instruction, wherein the update instruction includes the email processing rule to be updated; Based on the mail processing rule to be updated, the rule library is updated.

10. A mail processing device, wherein: The device comprises: A first receiving module, configured to receive an email processing request, wherein the processing request includes email login information of a target email address; A login module, used to log in the target mailbox in the simulation server based on the mailbox login information; An acquisition module, used for acquiring candidate emails to be processed from the target mailbox; An input module, used for inputting the candidate emails and email processing rules into the big model to obtain the target processing method output by the big model; A processing module is used to process the candidate emails based on the target processing method.

11. The device of claim 10, wherein: The acquisition module is specifically used for: Traversing the record list based on the identifier of the target mailbox, obtaining the first time of the latest processing record associated with the identifier of the target mailbox; Each email in the target mailbox whose time is after the first time is determined as a candidate email.

12. The device of claim 10, wherein: The acquisition module is specifically used for any of the following: Obtaining a screenshot of candidate emails to be processed from the target mailbox; The email content of the candidate email to be processed is obtained from the target mailbox.

13. The device of claim 10, wherein: The input module is specifically used for: Determine the relationship between the rules in the processing rule base; In the case where there is no correlation between the rules in the processing rule library, generating prompt information based on the candidate email and one of the email processing rules; The prompt information is input into the big model to obtain the target processing method output by the big model under the mail processing rule.

14. The device of claim 13, wherein: The input module is further used for: In the case where there is an association relationship between at least two processing rules, the at least two processing rules are spliced ​​based on the association relationship to obtain a spliced ​​processing rule; Generate prompt information based on the spliced ​​processing rules and the candidate emails; The prompt information is input into the large model to obtain the target processing method output by the large model under the spliced ​​mail processing rules.

15. The device according to any one of claims 10 to 14, wherein: The processing module is further used for: Generate a processing record based on the subject, processing time and target processing method of the candidate email; The processing record is stored in a record list associated with the target mailbox.

16. The device of claim 15, wherein: The processing module is further used for: When the second time corresponding to the latest email in the target mailbox is less than the first time of the latest processed record in the record list associated with the target mailbox, it is determined that there is no candidate email to be processed in the target mailbox.

17. The device of claim 16, wherein: The processing module is further used for: Based on a preset cycle, return to execute the operation of logging into the target mailbox in the simulation server based on the mailbox login information.

18. The device according to any one of claims 10 to 14, wherein: Also includes: A second receiving module, configured to receive a processing rule update instruction, wherein the update instruction includes the email processing rule to be updated; The updating module is used to update the rule base based on the email processing rule to be updated.

19. An electronic device, characterized in that: include: at least one processor; and, a memory communicatively coupled to the at least one processor; The memory stores instructions that may be executed by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the method according to any one of claims 1 to 9.

20. A non-transitory computer-readable storage medium storing computer instructions, wherein: The computer instructions are used to cause the computer to execute the method according to any one of claims 1-9.

21. A computer program product comprising a computer program, which, when executed by a processor, implements the method according to any one of claims 1 to 9.

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