Value list generation method and related device
Through the large language model, the problem of low traditional manual entry efficiency is solved, and fast and accurate quotation generation is achieved.
Patent Information
- Application Number
- CN202510668690.6
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-05-23
- Publication Date
- 2025-08-26
AI Technical Summary
The traditional method of generating quotations relies on manual entry of customer information, which leads to inefficiency. Customers need to re-enter when adjusting project deadlines or settlement methods, which increases workload and error risk.
The quotation form generation model based on the large language model is adopted, and the quotation form template is pre-entered. By identifying the user application page information, the quotation form is automatically generated. Combining the quotation form template and the calculation engine, a quotation form framework is quickly established and the quotation information is filled in.
It realizes automation and process simplification of quotation generation, reduces manual entry steps, improves generation efficiency, and quickly identifies and generates target quotations after users adjust information.
Smart Images
Figure CN120542401A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the field of financial technology, and in particular to a quotation generation method and related devices. Background Art
[0002] In industries such as financial leasing, customers need to know the repayment plan and total interest of different project terms and settlement methods when applying for financing. Usually, business personnel will provide customers with a quotation sheet that clearly states the quotation information expected by the customer.
[0003] The traditional approach to generating quotations is for sales personnel to enter a large amount of customer information into the business system and then generate the quotation. This information entry is cumbersome, time-consuming, and labor-intensive. Furthermore, when customers adjust the project deadline or settlement method, the information needs to be re-entered, resulting in low efficiency in generating quotations. Summary of the Invention
[0004] In response to the above problems, the present application provides a quotation generation method and related devices to improve the efficiency of quotation generation.
[0005] Based on this, this application discloses the following technical solutions:
[0006] In a first aspect, an embodiment of the present application provides a method for generating a quotation, the method comprising:
[0007] Obtaining a quotation generation model, the quotation generation model being determined based on a large language model, the quotation generation model pre-entering a quotation template, the quotation template being used to indicate a format of the quotation and a correspondence between application information and quotation information in the quotation;
[0008] In response to a user completing application information for applying for financing on an application page, identifying page elements of the application page using the quotation generation model to obtain target application information for generating a quotation, wherein the page elements of the application page include the application information;
[0009] According to the quotation template, the target application information is processed by the quotation generation model to generate the target quotation for the user.
[0010] Optionally, the quotation template includes a plurality of templates, and the target application information is processed by the quotation generation model according to the quotation template to generate the target quotation for the user, including:
[0011] Obtaining a target discrimination attribute, wherein the target discrimination attribute is used to determine a quotation template applicable to the target application information;
[0012] Determining, based on the target identification attribute, a first attribute value corresponding to the target application information and a second attribute value corresponding to each of the quotation templates;
[0013] If the difference between the first attribute value and the second attribute value of the target quotation template is less than a first threshold, the target application information is processed by the quotation generation model according to the target quotation template to generate the target quotation of the user.
[0014] Optionally, the quotation generation model includes a quotation calculation engine, wherein the quotation calculation engine has built-in calculation rules for each quotation information in the quotation, and the method further includes:
[0015] If the difference between the second attribute value of each of the quotation templates and the first attribute value exceeds the first threshold, determining the target quotation information corresponding to the target application information through the quotation calculation engine;
[0016] The target quotation is generated by the quotation generation model according to the target quotation information.
[0017] Optionally, the quotation template includes a plurality of quotation templates divided based on quotation categories, and the target application information is processed by the quotation generation model according to the quotation template to generate the target quotation for the user, including:
[0018] According to the quotation sheet templates of different quotation categories, the target application information is processed by the quotation sheet generation model to generate target quotation sheets of different quotation categories for the user.
[0019] Optionally, in response to the user completing the application information for applying for financing on the application page, identifying page elements of the application page by the quotation generation model to obtain target application information for generating a quotation includes:
[0020] In response to the user completing application information for applying for financing on the application page, identifying page elements of the application page through the quotation generation model to obtain initial application information, wherein the initial application information is in an editable state for authorized users;
[0021] In response to an editing operation on the initial application information, the initial application information is updated to target application information indicated by the editing operation.
[0022] Optionally, the method further includes:
[0023] Generate a quotation generation instruction, wherein the quotation generation instruction is used to indicate the text generation scenario, quotation generation method and quotation format of the quotation generation model;
[0024] After the quotation generation instruction is input into the quotation generation model, the target application information is processed by the quotation generation model to generate the target quotation for the user.
[0025] In a second aspect, an embodiment of the present application provides a quotation generating device, the device comprising: an acquisition unit, an identification unit, and a generation unit;
[0026] The acquisition unit is configured to acquire a quotation generation model, the quotation generation model being determined based on a large language model, the quotation generation model being pre-entered with a quotation template, the quotation template being configured to indicate a format of the quotation and a correspondence between application information and quotation information in the quotation;
[0027] The identification unit is configured to, in response to a user completing application information for applying for financing on an application page, identify page elements of the application page using the quotation generation model to obtain target application information for generating a quotation, wherein the page elements of the application page include the application information;
[0028] The generating unit is configured to process the target application information according to the quotation template and through the quotation generating model to generate a target quotation for the user.
[0029] In a third aspect, an embodiment of the present application provides a computer device, the computer device including a processor and a memory:
[0030] The memory is used to store a computer program and transmit the computer program to the processor;
[0031] The processor is configured to execute the method described in the first aspect above according to the computer program.
[0032] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, wherein the computer-readable storage medium is used to store a computer program, and the computer program is used to execute the method described in the first aspect above.
[0033] In a fifth aspect, an embodiment of the present application provides a computer program product comprising a computer program, which, when executed on a computer device, enables the computer device to execute the method described in the first aspect above.
[0034] It can be seen from the above technical solutions that this application has at least the following beneficial effects:
[0035] Obtain a quotation generation model. The quotation generation model is determined based on the large language model, and the quotation generation model pre-enters the quotation template. In response to the user completing the application information for financing on the application page, the quotation generation model identifies the page elements of the application page and obtains the target application information for generating the quotation. Through the text analysis capabilities of the large language model, when the user fills in the application information on the application page, the target application information that can be used to generate the quotation can be quickly extracted, reducing the tedious steps of manual input. At the same time, it can achieve automated recognition throughout the entire process, and even if the user re-enters, it can be quickly re-recognized. Based on the quotation template, the target application information is processed by the quotation generation model to generate the user's target quotation. The quotation template is used to indicate the format of the target quotation and the correspondence between the application information and the quotation information in the target quotation. Therefore, the quotation template can be used to quickly establish the quotation framework. Combined with the text generation capability of the quotation generation model, the corresponding quotation information is filled in the quotation framework corresponding to the quotation template to quickly generate the target quotation required by the user. This not only realizes process automation, but also saves calculation steps through the correspondence indicated by the quotation, greatly improving the efficiency of quotation generation. BRIEF DESCRIPTION OF THE DRAWINGS
[0036] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments recorded in this application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.
[0037] Figure 1 A flowchart of a method for generating a quotation provided in an embodiment of the present application;
[0038] Figure 2 A schematic diagram of the structure of a quotation generating device provided in an embodiment of the present application;
[0039] Figure 3 A schematic diagram of the structure of a computer device provided in an embodiment of the present application. DETAILED DESCRIPTION
[0040] The following describes embodiments of the present application in more detail with reference to the accompanying drawings. Although certain embodiments of the present application are shown in the accompanying drawings, it should be understood that the present application can be implemented in various forms and should not be construed as limited to the embodiments described herein. Instead, these embodiments are provided to provide a more thorough and complete understanding of the present application. It should be understood that the drawings and embodiments of the present application are for illustrative purposes only and are not intended to limit the scope of protection of the present application.
[0041] As can be seen from the above, the traditional approach to generating quotations is for sales personnel to enter a large amount of customer information into the business system and then generate quotations. This information entry is cumbersome, time-consuming, and labor-intensive. Moreover, when customers adjust the project period or settlement method, the information needs to be re-entered, resulting in low efficiency in generating quotations.
[0042] In related technologies, business programs can be developed to support business personnel in manually entering large amounts of information such as customer information, financing amount, project term, settlement method, etc. Although project quotations can be achieved, this method of manual entry by business personnel will bring additional workload and operational complexity, and entry errors are easy to occur, and the time cost is still high.
[0043] Based on this, an embodiment of the present application provides a quotation generation method and related devices for improving the efficiency of generating quotations.
[0044] The quotation generation method provided in this application can be applied to computer devices capable of generating quotation sheets, such as terminal devices and servers. Specifically, the terminal device may be a desktop computer, laptop computer, mobile phone, tablet computer, etc.; the server may be a standalone physical server, or a server cluster or distributed system composed of multiple physical servers. The terminal device and server may be connected directly or indirectly via wired or wireless communication, and this application does not impose any restrictions thereon.
[0045] See also Figure 1 , which is a flow chart of the quotation sheet generation method provided by the embodiment of the present application. For the convenience of description, the following embodiment is introduced by taking the execution subject of the quotation sheet generation method as an example. Figure 1 As shown, the quotation generating method includes S101-S103.
[0046] S101: Obtain a quotation generation model.
[0047] The quote generation model is based on the Big Language Model, a natural language processing model based on deep learning technology. Trained with massive amounts of text data, the Big Language Model is capable of understanding, generating, and predicting human language. This means the quote generation model possesses both semantic understanding and text generation capabilities. This can be achieved by obtaining a pre-trained model and then fine-tuning its parameters based on sample quote data to generate the quote generation model.
[0048] The quotation generation model pre-loads a quotation template. This template specifies the format of the quotation and the relationship between the application information and the quotation information in the quotation. Application information is the information the user fills in to obtain a quotation, such as the project amount, company name, and project duration. Quotation information is the information provided in the quotation, such as the down payment, lease start date, nominal interest rate, and repayment plan.
[0049] S102: In response to the user completing the application information for applying for financing on the application page, the page elements of the application page are identified through the quotation generation model to obtain target application information for generating the quotation.
[0050] Among them, the page elements of the application page include application information.
[0051] The application page is where users fill in their application information, such as a mini-program page, website page, or offline service terminal page. After a user completes the application information for financing on the application page, the quotation generation model identifies the various page elements on the application page, captures the user's application information, and automatically summarizes and organizes the calculation elements used for quotation generation, namely the target application information.
[0052] All data collected by this application (such as application information) is collected with the consent and authorization of the subject to which the data belongs (such as users, institutions or enterprises), and the collection, use and processing of relevant data must comply with the relevant laws, regulations and standards of relevant countries and regions.
[0053] S103: According to the quotation template, the target application information is processed by the quotation generation model to generate the user's target quotation.
[0054] After obtaining the target application information, based on the pre-entered quotation template, not only can the format of the quotation be determined, but the corresponding relationship between the application information and the quotation information can also be learned through the quotation generation model, thereby having the ability to output a quotation that can represent the corresponding relationship and generate the user's target quotation based on the target application information.
[0055] In a possible implementation, multiple quotations may be entered into a quotation generation model, and a quotation template may be generated by the quotation generation model. The quotation template is used to represent quotations whose frequency of occurrence is greater than a frequency threshold.
[0056] In a possible implementation, the quotation template includes multiple ones, and a target discrimination attribute can be obtained. The target discrimination attribute is used to determine a quotation template suitable for target application information, such as a nominal interest rate.
[0057] Based on the target discriminant attribute, a first attribute value corresponding to the target application information and a second attribute value corresponding to each quotation template are determined. If the difference between the first attribute value and the second attribute value of the target quotation template is less than a first threshold, the target application information is processed using a quotation generation model based on the target quotation template to generate a target quotation for the user. The first attribute value is the calculated value corresponding to the target discriminant attribute of the target application information, the second attribute value is the actual value of the target discriminant attribute in each quotation template, and the first threshold is a preset upper limit on the difference between the first attribute value and the second attribute value. The target quotation template is one of multiple quotation templates.
[0058] Taking the nominal interest rate as the target discriminant attribute as an example, the nominal interest rate corresponding to the target application information is calculated, and the nominal interest rates corresponding to each quotation template are obtained. If the difference between the nominal interest rate corresponding to the target application information and the nominal interest rate of the target quotation template is less than the first threshold, it means that the target quotation template is applicable to the target application information, and thus a quotation can be generated according to the target quotation template through the quotation generation model.
[0059] Therefore, through the target discrimination attribute, it is possible to directly determine one of the target application information from multiple quotation templates, so that the format and correspondence of the target quotation template can be directly adopted to generate a quotation. While ensuring that quotations corresponding to various templates for business scenarios can be generated, the screening speed of quotations is improved, the calculation time of quotation information is saved, and the efficiency of quotation generation is improved.
[0060] In one possible implementation, the quotation generation model includes a quotation calculation engine, which has built-in calculation rules for each quotation information in the quotation. That is, the quotation calculation engine is an independent quotation information generation unit that generates quotation information.
[0061] If the difference between the second attribute value and the first attribute value of each quotation template exceeds a first threshold, indicating that none of the pre-entered quotation templates are applicable to the target application information, the quotation calculation engine can determine the target quotation information corresponding to the target application information. Based on the target quotation information, the quotation generation model generates a target quotation.
[0062] Therefore, the quotation calculation engine can prevent errors in quotation information calculation due to the lack of adapted templates, thereby enhancing the robustness of the quotation generation process.
[0063] To provide users with more personalized quotation solutions, pre-entered quotation forms can also include multiple quotation templates based on quotation categories. Different quotation categories correspond to different quotation forms for the same application information. For example, the quotation category could be project duration, and the quotation forms for 12 periods and 24 periods would be different. Based on the quotation templates for different quotation categories, the quotation generation model can process the target application information and generate target quotations for different quotation categories.
[0064] In this way, while ensuring efficient generation, we can provide users with more diverse quotation solutions, such as quotations for different project deadlines, to improve user experience.
[0065] To prevent users from entering incorrect information, business personnel can make timely adjustments. In response to a user completing the application information for financing on the application page, the quotation generation model identifies the page elements of the application page and obtains the initial application information. The initial application information is modifiable and is editable by authorized users, such as business personnel. As a possible implementation method, an interface for editing application information is provided to the authorized user's client. This interface is called upon receiving an edit instruction, allowing the authorized user to edit the initial application information. In response to the edit operation on the initial application information, the initial application information is updated to the target application information indicated by the edit operation.
[0066] This not only improves the flexibility of obtaining application information, but also enables the application information to be recognized again through the quotation generation model after editing, quickly extracting the application information and generating the target quotation.
[0067] In one possible implementation, a quotation generation instruction may be generated, which is used to indicate the text generation scenario, quotation generation method, and quotation format of the quotation generation model. The following are quotation generation instructions A and B.
[0068] Quotation generation instruction A: As a seasoned account manager, you (the large model) compare the customer's input of financing amount, settlement method, project term, and repayment method (equal installments of principal, equal installments of principal and interest) with the quotation template. If any similarities are found, the template is output in the following format:
[0069] Company Name: xxxx
[0070] Financing amount: xxxx
[0071] Project deadline: xxxx
[0072] Down payment: xxxx
[0073] Lease start date: xxxx
[0074] Nominal interest rate: xxxx
[0075] Accounting rate of return: xxxx
[0076] Repayment plan: 1-3 periods: xxx yuan; 4-6 periods: xxx yuan; 7-9 periods: xxx yuan.
[0077] Quotation generation instruction B: When the captured project deadline is empty, quotations for different project deadlines can also be generated.
[0078] After the quotation generation instruction is input into the quotation generation model, the target application information is processed by the quotation generation model to generate the user's target quotation.
[0079] Since the quotation generation model is determined based on a large language model, it has the ability of semantic understanding. This semantic understanding ability can not only be used to identify application information, but also to understand the content of quotation generation instructions, thereby strengthening the understanding of the generation goal and improving the accuracy of quotation generation.
[0080] It can be seen from the above technical solution that a quotation generation model is obtained, and the quotation generation model is determined based on a large language model, and the quotation generation model pre-enters a quotation template. In response to the user completing the application information for applying for financing on the application page, the quotation generation model identifies the page elements of the application page and obtains the target application information for generating the quotation. Through the text analysis capability of the large language model, when the user fills in the application information on the application page, it can quickly extract the target application information that can be used to generate the quotation, reducing the tedious steps of manual entry, and at the same time, it can realize full-process automatic recognition, and even if the user re-enters, it can be quickly re-recognized. According to the quotation template, the target application information is processed by the quotation generation model to generate the user's target quotation. The quotation template is used to indicate the format of the quotation and the correspondence between the application information and the quotation information in the quotation. Therefore, the quotation template can be used to quickly establish the quotation framework. Combined with the text generation capability of the quotation generation model, the corresponding quotation information is filled in the quotation framework corresponding to the quotation template, and the target quotation required by the user is quickly generated. This not only realizes process automation, but also saves calculation steps through the correspondence indicated by the quotation, greatly improving the efficiency of quotation generation.
[0081] See also Figure 2 , Figure 2 The embodiment of the present application provides a quotation generating device, wherein the device 200 includes an acquiring unit 201, an identifying unit 202, and a generating unit 203;
[0082] The acquisition unit 201 is configured to acquire a quotation generation model, the quotation generation model being determined based on a large language model and pre-entering a quotation template, the quotation template being configured to indicate a format of the quotation and a correspondence between application information and quotation information in the quotation;
[0083] The identification unit 202 is configured to, in response to a user completing application information for applying for financing on an application page, identify page elements of the application page using the quotation generation model to obtain target application information for generating a quotation, wherein the page elements of the application page include the application information;
[0084] The generating unit 203 is configured to process the target application information according to the quotation template and through the quotation generating model to generate a target quotation for the user.
[0085] It can be seen from the above technical solution that a quotation generation model is obtained, and the quotation generation model is determined based on a large language model, and the quotation generation model pre-enters a quotation template. In response to the user completing the application information for applying for financing on the application page, the quotation generation model identifies the page elements of the application page and obtains the target application information for generating the quotation. Through the text analysis capability of the large language model, when the user fills in the application information on the application page, it can quickly extract the target application information that can be used to generate the quotation, reducing the tedious steps of manual entry, and at the same time, it can realize full-process automatic recognition, and even if the user re-enters, it can be quickly re-recognized. According to the quotation template, the target application information is processed by the quotation generation model to generate the user's target quotation. The quotation template is used to indicate the format of the quotation and the correspondence between the application information and the quotation information in the quotation. Therefore, the quotation template can be used to quickly establish the quotation framework. Combined with the text generation capability of the quotation generation model, the corresponding quotation information is filled in the quotation framework corresponding to the quotation template, and the target quotation required by the user is quickly generated. This not only realizes process automation, but also saves calculation steps through the correspondence indicated by the quotation, greatly improving the efficiency of quotation generation.
[0086] As a possible implementation, the quotation template includes multiple templates, and the generating unit 203 is specifically configured to:
[0087] Obtaining a target discrimination attribute, wherein the target discrimination attribute is used to determine a quotation template applicable to the target application information;
[0088] Determining, based on the target identification attribute, a first attribute value corresponding to the target application information and a second attribute value corresponding to each of the quotation templates;
[0089] If the difference between the first attribute value and the second attribute value of the target quotation template is less than a first threshold, the target application information is processed by the quotation generation model according to the target quotation template to generate the target quotation of the user.
[0090] As a possible implementation, the quotation generation model includes a quotation calculation engine, wherein the quotation calculation engine has built-in calculation rules for each quotation information in the quotation, and the device further includes a calculation unit for:
[0091] If the difference between the second attribute value of each of the quotation templates and the first attribute value exceeds the first threshold, determining the target quotation information corresponding to the target application information through the quotation calculation engine;
[0092] The target quotation is generated by the quotation generation model according to the target quotation information.
[0093] As a possible implementation, the quotation template includes multiple templates divided based on quotation categories. The generating unit 203 is specifically configured to:
[0094] According to the quotation sheet templates of different quotation categories, the target application information is processed by the quotation sheet generation model to generate target quotation sheets of different quotation categories for the user.
[0095] As a possible implementation, the identification unit 202 is specifically configured to:
[0096] In response to the user completing application information for applying for financing on the application page, identifying page elements of the application page through the quotation generation model to obtain initial application information, wherein the initial application information is in an editable state for authorized users;
[0097] In response to an editing operation on the initial application information, the initial application information is updated to target application information indicated by the editing operation.
[0098] As a possible implementation manner, the apparatus further includes an instruction generating unit, configured to:
[0099] Generate a quotation generation instruction, wherein the quotation generation instruction is used to indicate the text generation scenario, quotation generation method and quotation format of the quotation generation model;
[0100] After the quotation generation instruction is input into the quotation generation model, the target application information is processed by the quotation generation model to generate the target quotation for the user.
[0101] See also Figure 3, an embodiment of the present application further provides a computer device, the computer device comprising a memory 301 and a processor 302:
[0102] The memory is used to store a computer program and transmit the computer program to the processor;
[0103] The processor is configured to execute the method of the above method embodiment according to the computer program.
[0104] An embodiment of the present application further provides a computer-readable storage medium, characterized in that the computer-readable storage medium is used to store a computer program, and the computer program is used to execute the method of the above method embodiment.
[0105] An embodiment of the present application further provides a computer program product including a computer program, which, when executed on a computer device, enables the computer device to execute the method of the above method embodiment.
[0106] It should be noted that the various embodiments in this specification are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. Reference can be made to the common and similar parts between the various embodiments. For the systems or devices disclosed in the embodiments, since they correspond to the methods disclosed in the embodiments, the description is relatively simple, and the relevant parts can be referred to the method description.
[0107] As used herein, the term "including" and its variations are open-ended, i.e., "including but not limited to." The term "based on" means "based, at least in part, on." The term "one embodiment" means "at least one embodiment," the term "another embodiment" means "at least one additional embodiment," and the term "some embodiments" means "at least some embodiments." Other terms are defined in the following description.
[0108] It should be understood that in this application, "at least one (item)" means one or more, and "plurality" means two or more. "And / or" is used to describe the association relationship of associated objects, indicating that three relationships can exist. For example, "A and / or B" can mean: only A exists, only B exists, and A and B exist at the same time, where A and B can be singular or plural. The character " / " generally indicates that the previous and next associated objects are in an "or" relationship. "At least one of the following items" or similar expressions refers to any combination of these items, including any combination of single or plural items. For example, at least one of a, b or c can mean: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, c can be single or plural.
[0109] It should also be noted that, in this document, relational terms such as first and second, etc., are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "comprises," "comprising," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or device comprising a series of elements includes not only those elements, but also other elements not explicitly listed, or elements inherent to such process, method, article, or device. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not exclude the presence of additional identical elements in the process, method, article, or device comprising the element.
[0110] The steps of the methods or algorithms described in conjunction with the embodiments disclosed herein may be implemented directly using hardware, a software module executed by a processor, or a combination of the two. The software module may be placed in random access memory (RAM), internal memory, read-only memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, a hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art.
[0111] The above description of the disclosed embodiments is intended to enable one skilled in the art to implement or use the present application. Various modifications to these embodiments will be readily apparent to one skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application is not limited to the embodiments shown herein, but is intended to conform to the widest scope consistent with the principles and novel features disclosed herein.
Claims
1. A method for generating a quotation, characterized in that: The method comprises: Obtaining a quotation generation model, the quotation generation model being determined based on a large language model, the quotation generation model pre-entering a quotation template, the quotation template being used to indicate a format of the quotation and a correspondence between application information and quotation information in the quotation; In response to a user completing application information for applying for financing on an application page, identifying page elements of the application page using the quotation generation model to obtain target application information for generating a quotation, wherein the page elements of the application page include the application information; According to the quotation template, the target application information is processed by the quotation generation model to generate the target quotation for the user.
2. The method according to claim 1, characterized in that The quotation templates include a plurality of templates, and the target application information is processed by the quotation generation model according to the quotation templates to generate the target quotation for the user, including: Obtaining a target discrimination attribute, wherein the target discrimination attribute is used to determine a quotation template applicable to the target application information; Determining, based on the target identification attribute, a first attribute value corresponding to the target application information and a second attribute value corresponding to each of the quotation templates; If the difference between the first attribute value and the second attribute value of the target quotation template is less than a first threshold, the target application information is processed by the quotation generation model according to the target quotation template to generate the target quotation of the user.
3. The method according to claim 2, characterized in that The quotation generation model includes a quotation calculation engine, wherein the quotation calculation engine has built-in calculation rules for each quotation information in the quotation, and the method further includes: If the difference between the second attribute value of each of the quotation templates and the first attribute value exceeds the first threshold, determining the target quotation information corresponding to the target application information through the quotation calculation engine; The target quotation is generated by the quotation generation model according to the target quotation information.
4. The method according to claim 1, wherein The quotation templates include a plurality of quotation templates divided based on quotation categories. The target application information is processed by the quotation generation model according to the quotation templates to generate the target quotation for the user, including: According to the quotation sheet templates of different quotation categories, the target application information is processed by the quotation sheet generation model to generate target quotation sheets of different quotation categories for the user.
5. The method according to claim 1, wherein In response to the user completing the application information for applying for financing on the application page, identifying page elements of the application page by the quotation generation model to obtain target application information for generating a quotation includes: In response to the user completing application information for applying for financing on the application page, identifying page elements of the application page through the quotation generation model to obtain initial application information, wherein the initial application information is in an editable state for authorized users; In response to an editing operation on the initial application information, the initial application information is updated to target application information indicated by the editing operation.
6. The method according to claim 1, characterized in that The method further comprises: Generate a quotation generation instruction, wherein the quotation generation instruction is used to indicate the text generation scenario, quotation generation method and quotation format of the quotation generation model; After the quotation generation instruction is input into the quotation generation model, the target application information is processed by the quotation generation model to generate the target quotation for the user.
7. A quotation generating device, characterized in that: The device comprises: an acquisition unit, an identification unit and a generation unit; The acquisition unit is configured to acquire a quotation generation model, the quotation generation model being determined based on a large language model, the quotation generation model being pre-entered with a quotation template, the quotation template being configured to indicate a format of the quotation and a correspondence between application information and quotation information in the quotation; The identification unit is configured to, in response to a user completing application information for applying for financing on an application page, identify page elements of the application page using the quotation generation model to obtain target application information for generating a quotation, wherein the page elements of the application page include the application information; The generating unit is configured to process the target application information according to the quotation template and through the quotation generating model to generate a target quotation for the user.
8. A computer device, characterized in that: The computer device includes a processor and a memory: The memory is used to store a computer program and transmit the computer program to the processor; The processor is configured to execute the method according to any one of claims 1 to 6 according to the computer program.
9. A computer-readable storage medium, characterized in that The computer-readable storage medium is used to store a computer program, and the computer program is used to execute the method according to any one of claims 1 to 6.
10. A computer program product comprising a computer program, characterized in that When the method is executed on a computer device, the computer device is enabled to execute the method according to any one of claims 1 to 6.