Solution generation method, system and equipment based on generative artificial intelligence

Abstract

The invention discloses a solution generation method, system and device based on generative artificial intelligence, and the method comprises the steps: obtaining a target demand in response to the received target content sent by a target user; obtaining a target demand parameter corresponding to the target demand according to the target demand; obtaining at least one target supplier based on a supplier database according to the target demand parameter; according to the at least one target supplier, supplier data is obtained; and obtaining at least one solution for the target demand based on a generative artificial intelligence model according to the target demand and the supplier data. The problems that in the process of general digital transformation, more and more subjects participate in supply and demand transactions, and a traditional supply and demand transaction platform faces large data volume and low processing efficiency and cannot provide personalized solutions for a demand side are at least solved.

Description

TECHNICAL FIELD

[0001] The application relates to the technical field of Internet, in particular to a solution generation method, system and device based on generative artificial intelligence. BACKGROUND

[0002] The supply and demand management platform is a tool based on information technology, which is used to optimize the coordination of supply and demand relationship and resource allocation, and aims to improve market operation efficiency and reduce information asymmetry in transactions. With the continuous advancement of globalization and digital transformation, the role of the supply and demand management platform becomes increasingly important. Through the platform, enterprises can more efficiently connect suppliers and demanders, achieve precise matching of resources and intelligent management of demand. At present, there are many problems in supply and demand matching and solution generation. First, information asymmetry is still one of the biggest challenges in current supply and demand management. Many suppliers and demanders have difficulty in quickly and accurately obtaining real-time information of the other party, especially in complex market environment with multiple participants, information lag and error will lead to supply and demand matching failure, causing resource waste and market fluctuations. Second, the accuracy of supply and demand matching algorithm still needs to be improved. Existing matching algorithms usually rely on rule-driven or simple machine learning models, but these methods often cannot provide intelligent and accurate solutions when facing diversified demand and complex supply chain. Especially in the case of diversified, nonlinear and time-varying characteristics of demand and supply, traditional matching algorithms are difficult to capture the complex market rules, resulting in unsatisfactory matching results. Finally, the dynamic changes in market demand also make it difficult for supply and demand solutions to be stable in the long term. Due to the frequent changes in market environment, consumer behavior and supply chain conditions, the supply and demand management platform needs to have high flexibility and adaptability. However, existing platforms often have difficulty in quickly responding to these changes, resulting in insufficient timely dynamic adjustment of supply and demand relationship, affecting the maintenance of overall supply and demand balance.

[0003] In the process of inclusive digital transformation, more and more subjects participate in supply and demand transactions, and traditional supply and demand transaction platforms face large data volume, low processing efficiency, and cannot provide personalized solutions for demanders. SUMMARY

[0004] The application provides a solution generation method, system and device based on generative artificial intelligence, which at least solves the problem that in the process of inclusive digital transformation, more and more subjects participate in supply and demand transactions, and traditional supply and demand transaction platforms face large data volume, low processing efficiency, and cannot provide personalized solutions for demanders.

[0005] The application provides a solution generation method based on generative artificial intelligence, comprising: obtaining target demand in response to receiving target content sent by a target user; obtaining a target demand parameter corresponding to the target demand according to the target demand; obtaining at least one target supplier based on a supplier database according to the target demand parameter; obtaining supplier data according to the at least one target supplier; obtaining at least one solution for the target demand based on a generative artificial intelligence model according to the target demand and the supplier data.

[0006] Optionally, the obtaining of the target demand in response to receiving target content sent by a target user comprises: analyzing the target content using a pre-set NLP model to determine whether the target content includes complete demand information in response to receiving target content sent by a target user; obtaining a target demand according to the complete demand information when the target content includes complete demand information; obtaining a target demand after guiding the target user to complete the demand information according to the missing demand information when the target content does not include complete demand information.

[0007] Optionally, the obtaining of the target demand parameter corresponding to the target demand according to the target demand comprises: obtaining a key indicator parameter based on a pre-set key indicator according to the target demand; obtaining an additional indicator parameter based on additional demand according to the target demand, the additional demand being configured as demand in the target demand that is not directly associated with the key indicator; obtaining a target demand parameter according to the key indicator parameter and / or the additional indicator parameter.

[0008] Optionally, the obtaining of the at least one target supplier based on the supplier database according to the target demand parameter comprises: obtaining user information of the target user according to the target user; obtaining a user restriction parameter according to the user information of the target user; obtaining at least one target supplier based on a supplier database according to the user restriction parameter and the target demand parameter.

[0009] Optionally, the obtaining of the supplier data according to the at least one target supplier comprises: obtaining a unique address corresponding to each target supplier according to the at least one target supplier; accessing the unique address corresponding to each target supplier to obtain products and / or services offered by each supplier according to the unique address corresponding to each target supplier. obtaining supplier data according to products and / or services provided by each supplier.

[0010] Optionally, the step of obtaining at least one solution for the target demand based on the generative artificial intelligence model according to the target demand and the supplier data comprises: obtaining a target knowledge base according to the supplier data, and inputting the target knowledge base into the generative artificial intelligence model; generating a target prompt corresponding to the target demand according to the target demand; obtaining at least one solution for the target demand based on the generative artificial intelligence model to which the target knowledge base is inputted according to the target prompt.

[0011] Optionally, after the step of obtaining at least one solution for the target demand based on the generative artificial intelligence model according to the target demand and the supplier data, the method further comprises: obtaining an elected supplier corresponding to the target solution in response to receiving the target solution selected by the user; placing an order for the elected supplier according to the elected supplier and the target solution.

[0012] In another aspect, a solution generation method based on generative artificial intelligence comprises a user terminal, a demand platform, a supply platform, and a solution management platform. The user terminal is configured to: receive target content inputted by a target user and send the target content inputted by the target user to the demand platform; receive at least one solution for the target demand sent by the solution management platform and display the at least one solution for the target demand to the user; The demand platform is configured to: obtain a target demand in response to receiving target content sent by the target user through the user terminal; obtain target demand parameters corresponding to the target demand according to the target demand; send the target demand parameters to the solution management platform; The solution management platform is configured to: obtain at least one target supplier based on a supplier database of the supply platform according to the target demand parameters in response to receiving the target demand parameters sent by the demand platform; obtain supplier data according to the at least one target supplier; obtaining at least one solution for the target demand based on a generative artificial intelligence model according to the target demand and the supplier data; sending the at least one solution for the target demand to a target terminal; The supply platform is configured to: manage a supplier database configured to at least store a supplier list and supplier information of each supplier, and the target supplier belongs to the suppliers.

[0013] Optionally, the suppliers include at least one of direct operation suppliers, franchise suppliers and individual suppliers.

[0014] Optionally, the supply platform further comprises a supplier terminal; The supplier terminal is configured to: in response to receiving an input of a supplier, send a supplier database operation request according to the input of the supplier to the supply platform; The supply platform is configured to: in response to receiving the supplier database operation request sent by the supplier terminal, audit the supplier database operation request, and operate the supplier database according to the audited supplier database operation request.

[0015] Optionally, the obtaining at least one solution for the target demand based on a generative artificial intelligence model according to the target demand and the supplier data comprises: obtaining a target knowledge base according to the supplier data, and inputting the target knowledge base into the generative artificial intelligence model; generating a target prompt word corresponding to the target demand according to the target demand; obtaining at least one solution for the target demand based on the generative artificial intelligence model inputted with the target knowledge base according to the target prompt word.

[0016] Optionally, the solution management platform is further configured to: in response to receiving a target solution selected by a user, obtaining an elected supplier corresponding to the target solution; placing an order for the elected supplier through the supply platform according to the elected supplier and the target solution.

[0017] In another aspect, the embodiments of the present application also provide a device, which comprises a memory and a processor, the memory stores a computer program, and the processor executes the computer program to implement the above method.

[0018] In still another aspect, the embodiments of the present application further provide a computer readable storage medium, and the computer readable storage medium stores a computer program, and a processor executes the computer program to implement the above method.

[0019] Compared with the prior art, the present application has the following advantages and beneficial effects: The application discloses a solution generation method and system based on generative artificial intelligence, and a device thereof, and relates to the technical field of artificial intelligence. BRIEF DESCRIPTION OF DRAWINGS

[0020] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly introduced. In all the drawings, similar elements or parts are generally identified by similar reference numerals. In the drawings, each element or part is not necessarily drawn according to the actual proportion.

[0021] Figure 1 The flowchart of the solution generation method based on generative artificial intelligence in the present application is shown in the figure. Figure 2 The structural diagram of the device in the present application is shown in the figure. Marked in the figure: 101-processor, 102-communication bus, 103-network interface, 104-user interface, 105-memory.

[0022] The implementation, functional features and advantages of the present application will be further described with reference to the drawings in combination with the embodiments. DETAILED DESCRIPTION

[0023] In order to enable the persons skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below in combination with the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, but not all the embodiments. Based on the embodiments in the present application, all the other embodiments obtained by the persons skilled in the art without creative labor should belong to the protection scope of the present application.

[0024] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and in the above drawings are used to distinguish similar objects, and do not necessarily have to describe a specific order or sequence. It should be understood that the data thus used can be interchanged under appropriate circumstances, so that the embodiments of the present application described herein can be implemented in an order other than that illustrated or described herein. In addition, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusion, for example, a process, method, system, product or device including a series of steps or units does not have to be limited to those steps or units clearly listed, but can include other steps or units not clearly listed or inherent to these processes, methods, products or devices.

[0025] Embodiment 1 As Figure 1 shown, a generative artificial intelligence-based solution generation method includes: S1, in response to receiving target content sent by a target user, obtaining target demand.

[0026] S2, according to the target demand, obtaining target demand parameters corresponding to the target demand.

[0027] S3, according to the target demand parameters, obtaining at least one target supplier based on the supplier database.

[0028] S4, according to at least one target supplier, obtaining supplier data.

[0029] S5, according to the target demand and the supplier data, obtaining at least one solution for the target demand based on a generative artificial intelligence model.

[0030] Traditional supply and demand platforms usually have the following problems: Large amount of data, with the expansion of market size, transaction data and supplier information grow exponentially, leading to insufficient system processing capacity; Low processing efficiency, traditional matching algorithms are usually based on static rules or simple machine learning models, which cannot quickly respond to massive data and complex demands; Insufficient personalization, demanders' demands are often diverse and dynamic, and traditional platforms fail to provide customized solutions effectively; The purpose of the present solution is to provide personalized, intelligent and real-time solutions for demanders based on a generative artificial intelligence-based model, and to improve the processing efficiency of the system.

[0031] Based on the above problems, the present embodiment provides a generative artificial intelligence-based solution generation method for solving the above problems, which specifically includes: S1, in response to receiving the target user sent the target content, obtain the target demand; In the supply and demand platform, first of all, in response to user requests, obtain the demand of the demand side, that is, the target user. This can be done through natural language processing technology.

[0032] Specifically: Users input their own demand information through the platform, which may include text description, pictures or other formats of data; Using natural language processing technology, the input demand is analyzed semantically, and key information such as target product, quantity, delivery time, budget, etc. is extracted; For complex requirements, further interaction with users can be used to confirm and refine the requirements.

[0033] Optionally, the NLP tool used in step S1 can be Hugging Face Transformers library, and the dialogue model used can be OpenAI GPT model.

[0034] S2, according to the target demand, obtain the target demand parameter corresponding to the target demand; Once the demand is clear, the platform needs to extract the corresponding demand parameters from it and filter the suppliers according to these parameters.

[0035] Specifically: The target demand is structured and the demand information is converted into parameters. For example, if the demand is "buy 10 smart phones, budget 50,000 yuan, delivery time 3 days", the demand parameters such as product type, quantity, budget, delivery time are extracted, including "product: smart phone", "quantity: 10", unit "unit", budget "50000", "delivery time: 3 days"; Based on these demand parameters, the platform will use knowledge graph or rule engine to further refine the parameters to facilitate subsequent matching of suppliers. For example, combined with product attributes, supplier capabilities and service range, determine the parameter range; Through feature engineering processing demand parameters, converted into data format available for subsequent machine learning model.

[0036] Optionally, the knowledge graph used in step S2 can be Neo4j, and the rule engine used can be Drools.

[0037] S3, according to the target demand parameter, based on the supplier database, obtain at least one target supplier; By matching the extracted demand parameters with the information in the supplier database, the supplier that best meets the demand is selected.

[0038] Specifically: In the supplier database, according to the demand parameters such as product category, quantity, budget, etc., screening is carried out, and a batch of potential suppliers are obtained using multi-condition query technology; Using regular matching method, collaborative filtering algorithm and / or content-based recommendation system, according to the historical transaction records of suppliers, customer feedback, delivery capacity and other indicators, the most suitable suppliers are further screened out; If the demand is very specific, special skills or customized services of suppliers need to be considered, at this time, the matching degree of suppliers can be evaluated through machine learning model.

[0039] The collaborative filtering algorithm used in step S3 can be Matrix Factorization or Alternating Least Squares, and the recommendation algorithm used can be Collaborative Filtering or Content-based Filtering.

[0040] S4, obtaining supplier data according to at least one target supplier; After screening out the target suppliers, the detailed data of these suppliers need to be collected to understand their products, quotations, delivery cycle, etc.

[0041] Specifically: Data mining is performed on the screened suppliers to obtain their product catalog, inventory situation, price list, service content, etc. Related data is extracted from the supplier database or external data sources such as supply chain management platform, ERP system, etc. through API interface; The data is cleaned and processed to ensure that it can be used for subsequent analysis and solution generation.

[0042] Optionally, the data crawling tool used in step S4 can be BeautifulSoup or Scrapy, and the data cleaning method used can be Pandas or OpenRefine.

[0043] S5, obtaining at least one solution for the target demand based on the generated artificial intelligence model according to the target demand and supplier data; Based on the collected target demand and supplier data, a personalized solution is generated using a generative artificial intelligence model.

[0044] Specifically: Model selection: Select a suitable generative AI model such as GPT-4 or DeepSeek to generate solutions, which can be trained based on a large amount of historical data to learn how to generate optimized solutions according to specific needs and supplier conditions; Input the demand parameters and supplier data into the generative model, and the model automatically generates one or more solutions that meet the demand through deep learning. The solution content can include recommended suppliers, product configurations, quotes, delivery dates, etc. Further optimize the solution through interaction with the user, adjust the generated solution based on user preferences, historical behavior, etc., and provide personalized customization.

[0045] Optionally, the generative AI model used in step S5 can be GPT-4 or DeepSeek, and the deep learning framework used can be TensorFlow or PyTorch.

[0046] Using the above method, by first screening suppliers and then inputting the screened suppliers into the generative artificial intelligence model as a knowledge base, the problem of existing supply and demand platforms being unable to efficiently generate personalized solutions due to too many suppliers is effectively solved.

[0047] Embodiment 2 This embodiment is based on Embodiment 1, and a solution generation method based on generative artificial intelligence includes: S1, in response to receiving target content sent by a target user, obtaining target demand.

[0048] Optionally, in response to receiving target content sent by a target user, obtaining target demand includes: In response to receiving target content sent by a target user, using a preposed NLP model to analyze the target content and determine whether the target content includes complete demand information; When the target content includes complete demand information, obtaining the target demand according to the complete demand information; When the target content does not include complete demand information, obtaining the target demand after guiding the target user to complete the demand information according to the missing demand information.

[0049] By performing completeness verification on the target content sent by the target user, it is avoided that the final solution has problems due to inaccurate demand proposed by the target user.

[0050] S2, obtaining target demand parameters corresponding to the target demand according to the target demand.

[0051] Optionally, obtaining target demand parameters corresponding to the target demand according to the target demand includes: According to the target demand, based on the preset key indicators, obtain key indicator parameters; According to the target demand, based on additional demand, obtain additional indicator parameters, and the additional demand is configured as a demand in the target demand that is not directly associated with the key indicators; According to the key indicator parameters and / or additional indicator parameters, obtain target demand parameters.

[0052] Optionally, the additional demand can be a supplement to the key indicators, such as brand, model, etc. Optionally, the additional demand can be the inclination of the target user to the solution, such as local suppliers, factory direct supply, etc.

[0053] By using the above method, the demand can be further refined, and the final solution is more in line with the actual demand of the user.

[0054] S3, according to the target demand parameters, based on the supplier database, obtain at least one target supplier.

[0055] Optionally, according to the target demand parameters, based on the supplier database, obtain at least one target supplier, including: According to the target user, obtain user information of the target user; According to the user information of the target user, obtain user limit parameters; According to the user limit parameters and the target demand parameters, based on the supplier database, obtain at least one target supplier.

[0056] Specifically, the user information of the target user can include user address, user preference, etc., and the suppliers can be further screened according to the user information.

[0057] Optionally, according to the target demand parameters, based on the supplier database, obtain at least one target supplier, including: According to the target user, obtain a user portrait of the target user; According to the user portrait of the target user, obtain user preferences; According to the user preference and the target demand parameter, based on the supplier database, obtain at least one target supplier.

[0058] S4, according to at least one target supplier, obtain supplier data.

[0059] Optionally, according to at least one target supplier, obtain supplier data, including: According to at least one target supplier, obtain a unique address corresponding to each target supplier; According to the unique address corresponding to each target supplier, access the unique address corresponding to each target supplier to obtain the products and / or services provided by each supplier; Obtaining supplier data according to products and / or services provided by each supplier.

[0060] S5, obtaining at least one solution for the target demand based on a generative artificial intelligence model according to the target demand and the supplier data.

[0061] Optionally, obtaining at least one solution for the target demand based on a generative artificial intelligence model according to the target demand and the supplier data includes: Obtaining a target knowledge base according to the supplier data, and inputting the target knowledge base into the generative artificial intelligence model; Generating a target prompt word corresponding to the target demand according to the target demand; Obtaining at least one solution for the target demand based on the generative artificial intelligence model inputted with the target knowledge base according to the target prompt word.

[0062] Optionally, after the step of obtaining at least one solution for the target demand based on a generative artificial intelligence model according to the target demand and the supplier data, the method further includes: In response to receiving a target solution selected by the user, obtaining an elected supplier corresponding to the target solution; Placing an order for the elected supplier according to the elected supplier and the target solution.

[0063] By using the above method, the problem that existing supply and demand platforms cannot efficiently generate personalized solutions due to too many suppliers is effectively solved by initially screening suppliers and inputting the screened suppliers into a generative artificial intelligence model as a knowledge base.

[0064] Embodiment 3 A solution generation method system based on a generative artificial intelligence includes a user terminal, a demand platform, a supply platform, and a solution management platform. The user terminal is configured to: Receive target content inputted by a target user, and send the target content inputted by the target user to the demand platform; Receive at least one solution for a target demand sent by the solution management platform, and display the at least one solution for the target demand to the user; The demand platform is configured to: In response to receiving target content sent by the target user through the user terminal, obtain a target demand; Obtain target demand parameters corresponding to the target demand according to the target demand; Send the target demand parameters to the solution management platform; The solution management platform is configured to: In response to receiving the target demand parameter sent by the demand platform, at least one target supplier is obtained based on the supplier database of the supply platform according to the target demand parameter; Supplier data is obtained according to the at least one target supplier; At least one solution for the target demand is obtained based on a generative artificial intelligence model according to the target demand and the supplier data; The at least one solution for the target demand is sent to the target terminal; The supply platform is configured to: Manage the supplier database, which is configured to at least store a list of suppliers and supplier information of each supplier, and the target supplier belongs to the suppliers.

[0065] The system is further described in detail as follows: The user terminal is configured to receive user input demand information and display the generated solution; The demand platform is configured to process user demand, generate demand parameters, and send them to the solution management platform; The supply platform is configured to manage the supplier database and provide supplier data for matching demand; The solution management platform is configured to process demand parameters, select appropriate suppliers, and generate customized solutions.

[0066] The specific steps of the user terminal receiving the demand content input by the target user, sending the demand content to the demand platform for processing, receiving the generated solution, and displaying it to the user include: The user inputs his / her own demand through a user terminal such as a mobile phone, a webpage, etc. The demand can be a natural language description or structured data in the form of a form. The user terminal sends the demand content to the demand platform through an API interface; The user terminal displays multiple personalized solutions returned from the solution management platform and provides a feedback mechanism to improve subsequent recommendations.

[0067] Optionally, the user terminal can understand and classify the demand through a natural language processing model, and use React and Vue to develop the interactive interface to realize the above functions.

[0068] The specific steps of the demand platform responding to user demand, extracting key demand parameters, and sending the parameters to the solution management platform include: After the user's demand is received through an API interface, the demand platform performs preliminary processing on the demand data, mainly including natural language analysis and structured conversion; If the user input is in natural language, use natural language processing techniques to extract key information such as product category, quantity, budget, and time; If the user input is in form format, directly extract the fields and standardize them; Convert these parameters into a format that can be used for supplier matching, demand parameters can include one or more of product type, quantity, budget, time limit, and special requirements; The demand platform sends the demand parameters to the solution management platform through the API for further processing.

[0069] Optionally, the demand platform can use RESTful API for data exchange with other modules.

[0070] The supply platform manages the supplier database, stores the supplier list and its detailed information, and provides database access services to the solution management platform. The specific steps include: The supply platform maintains a structured supplier database containing the following information: Supplier basic information, such as company name, contact information, address, etc. Product or service list, such as specifications, prices, production capacity, etc. Supplier historical records, such as delivery time, customer satisfaction, return rate, etc. Available inventory, such as the current inventory status of each supplier; The supply platform provides an API interface for the solution management platform to obtain supplier data.

[0071] Optionally, the demand platform can store supplier data through a relational database such as MySQL, PostgreSQL, etc.; it can interact with the solution management platform through a database API such as GraphQL or RESTful API.

[0072] The database regularly updates the supplier data to ensure the accuracy of the inventory information and the status of the suppliers. The database update can be completed by the database administrator or each supplier can maintain their own data.

[0073] The solution management platform obtains target suppliers from the supply platform according to demand parameters, generates at least one personalized solution based on generative artificial intelligence according to demand and supplier data, and sends the solution to the user terminal. The specific steps include: Receive demand parameters: receive structured demand parameters from the demand platform; Use recommendation systems and collaborative filtering algorithms to match demand parameters with information in the supplier database; for example, use historical order data, product types, and supplier ratings to recommend the most suitable suppliers; using a generative artificial intelligence model to generate one or more customized solutions based on the demand and supplier data, the solutions including recommended suppliers, products, prices, delivery times, etc.; multiple factors such as budget, delivery time, user preferences, etc. can be considered during the generation process; Optionally, a multi-objective optimization algorithm such as genetic algorithm, particle swarm optimization, etc. is also used to balance the trade-off between multiple objectives to generate the optimal solution.

[0074] The generated solution is sent to the user terminal through the API for the user to view and select.

[0075] The system uses generative artificial intelligence technology to effectively solve the inefficiency of traditional supply and demand platforms when faced with large amounts of data, and provides personalized solutions through the coordinated work of multiple modules. Each module relies on modern technologies such as NLP, recommendation algorithms, and generative models to achieve intelligent and customized transaction matching and solution generation. In this way, users can get efficient and personalized transaction solutions, improving the user experience and market competitiveness of the platform.

[0076] Embodiment 4 This embodiment is based on the solution generation method system based on generative artificial intelligence of embodiment 3, including user terminal, demand platform, supply platform and solution management platform; The user terminal is configured to: receive target content input by the target user and send the target content input by the target user to the demand platform; receive at least one solution for the target demand sent by the solution management platform and display the at least one solution for the target demand to the user; The demand platform is configured to: obtain the target demand in response to receiving the target content sent by the target user through the user terminal; obtain target demand parameters corresponding to the target demand according to the target demand; send the target demand parameters to the solution management platform; The solution management platform is configured to: obtain at least one target supplier based on the supplier database of the supply platform according to the target demand parameters in response to receiving the target demand parameters sent by the demand platform; obtain supplier data according to the at least one target supplier; obtain at least one solution for the target demand based on the generative artificial intelligence model according to the target demand and the supplier data; send the at least one solution for the target demand to the target terminal; The supply platform is configured to: manage a supplier database, the supplier database being configured to store at least a supplier list and supplier information of each supplier, the target supplier belonging to the suppliers.

[0077] Optionally, the suppliers include at least one of a direct management supplier, a franchise supplier, and an individual supplier.

[0078] Specifically, in a supplier system, the direct management supplier organization includes a head office, provincial subsidiaries, and district and county subsidiaries; the franchise supplier organization includes digital supply and demand service stations, including community, park, and township scenarios, source end enterprises, and shared experience stores; and the individual suppliers include family suppliers and individual suppliers.

[0079] Optionally, it further includes a supplier terminal; The supplier terminal is configured to: in response to receiving an input of the supplier, send a supplier database operation request to the supply platform according to the input of the supplier; The supply platform is configured to: in response to receiving the supplier database operation request sent by the supplier terminal, audit the supplier database operation request, and operate the supplier database according to the supplier database operation request that passes the audit.

[0080] Specifically, the individual supplier terminal can implement: management of supply and demand transaction functions, supplier information management, and management of supplier operations.

[0081] Specifically, the franchise supplier can implement: supplier information management, supply and demand transaction information release management, supply and demand transaction order management, customer management, electronic contract management, invoice management, etc.

[0082] Specifically, the direct management supplier terminal can implement: service station expansion management, service station management, after-sales dispute management, order information analysis, etc.

[0083] Optionally, according to the target demand and the supplier data, at least one solution for the target demand is obtained based on a generative artificial intelligence model, including: According to the supplier data, a target knowledge base is obtained, and the target knowledge base is connected to the generative artificial intelligence model; According to the target demand, a target prompt word corresponding to the target demand is generated; According to the target prompt word, at least one solution for the target demand is obtained based on the generative artificial intelligence model to which the target knowledge base is connected.

[0084] Optionally, in response to receiving the target content sent by the target user, the target demand is obtained, including: In response to receiving the target content sent by the target user, the target content is parsed using a preposed NLP model, and it is determined whether the target content includes complete demand information; When the target content includes complete demand information, the target demand is obtained according to the complete demand information; When the target content does not include complete demand information, the target demand is obtained after the target user is guided to complete the demand information according to the missing demand information.

[0085] Optionally, according to the target demand, a target demand parameter corresponding to the target demand is obtained, including: According to the target demand, a key indicator parameter is obtained based on a preset key indicator; According to the target demand, an additional indicator parameter is obtained based on an additional demand, and the additional demand is configured as a demand in the target demand that is not directly associated with the key indicator; According to the key indicator parameter and / or the additional indicator parameter, the target demand parameter is obtained.

[0086] Optionally, according to the target demand parameter, at least one target supplier is obtained based on a supplier database, including: According to the target user, user information of the target user is obtained; According to the user information of the target user, a user limit parameter is obtained; According to the user limit parameter and the target demand parameter, at least one target supplier is obtained based on the supplier database.

[0087] Optionally, according to the at least one target supplier, supplier data is obtained, including: According to the at least one target supplier, a unique address corresponding to each target supplier is obtained; According to the unique address corresponding to each target supplier, each target supplier corresponding unique address is accessed to obtain products and / or services on each supplier; According to the products and / or services on each supplier, the supplier data is obtained.

[0088] Optionally, according to the target demand and the supplier data, at least one solution for the target demand is obtained based on a generative artificial intelligence model, including: According to the supplier data, a target knowledge base is obtained, and the target knowledge base is connected to the generative artificial intelligence model; According to the target demand, a target prompt word corresponding to the target demand is generated; According to the target prompt word, at least one solution for the target demand is obtained based on the generative artificial intelligence model to which the target knowledge base is connected.

[0089] Optionally, after the step of obtaining at least one solution for the target demand based on the generative artificial intelligence model according to the target demand and the supplier data, the method further comprises: obtaining an elected supplier corresponding to the target solution in response to receiving the target solution selected by the user; placing an order for the elected supplier according to the elected supplier and the target solution.

[0090] Optionally, the solution management platform is further configured to: obtain an elected supplier corresponding to the target solution in response to receiving the target solution selected by the user; place an order for the elected supplier through the supply platform according to the elected supplier and the target solution.

[0091] Embodiment 5 This embodiment includes a plurality of examples that can be matched with the above-mentioned scheme.

[0092] Example 1, the business process of the supplier proposing a supply demand, comprising: S101, proposing a sales target.

[0093] The supplier needs to propose a clear supply demand, i.e. a sales target. This demand should be clear and explicit, specifically covering the following contents: Commodity information: detailed description of the specific type, name, specification or key attributes of the commodity.

[0094] Sales quantity: clear expected sales quantity range.

[0095] Price information: give a budget range or phased price.

[0096] Supply time: determine the expected supply time period.

[0097] The supply and demand service party first conducts a comprehensive analysis of the supplier data, checks whether the standard data, quality data and related certificates are complete. If the data is not complete, the sales plan cannot be developed; if the data is relatively complete, the supply and demand service party will develop three plans for the supplier to choose from. If the plan is not recognized, the supply and demand service party needs to communicate with the supplier again and develop a new plan until the plan is recognized, and then the follow-up work can be carried out. The plan mainly describes the promotion channel, sales volume and price information, and can be dynamically adjusted according to market feedback and supply and demand changes.

[0098] S102, trial sale.

[0099] For the first time into the platform of the supply side commodity, need to market small-scale test marketing, to test its sales effect, and sales report. If the sales report shows poor results, supply and demand service providers need to adjust the program, after adjustment continue to test marketing; if the effect is good, then into the next step process. If the supply side of the commodity has a mature sales example, then no need to test marketing.

[0100] S103, signing a contract.

[0101] The total channel fee contract: the supply side needs to sign an electronic contract with the supply and demand service providers, and clearly promote the total channel fee to several experience stores.

[0102] Three-party sales contract: the supply side, supply and demand service providers and several experience stores need to sign a three-party contract, that is, the combination of "paving, collecting, and one piece of delivery" sales contract.

[0103] Logistics distribution contract: the supply side, supply and demand service providers and several logistics companies need to sign a commodity distribution logistics contract.

[0104] Distribution channel fee contract: the supply and demand service providers and experience stores sign a contract to determine the distribution channel fee.

[0105] S104, payment.

[0106] Total channel fee payment: the supply side needs to pay the total channel fee of several experience stores to the supply and demand service providers according to the contract, and the payment method can be diversified, such as prepayment of a certain percentage of deposit or full discount, and the supply and demand service providers can provide customized payment plan according to the basic information of the enterprise.

[0107] Experience store purchase fee payment: experience stores need to pave first, at least buy two or three samples for display, or collect according to the plan, and pay the purchase fee to the supply side according to the contract; if using one piece of delivery mode, then collect the commission.

[0108] Distribution channel fee payment: the supply and demand service providers need to pay the distribution channel fee to the experience stores.

[0109] S105, formal sales.

[0110] If the test marketing data analysis meets the standard, the supply and demand service providers need to conduct in-depth analysis on the supply side of the sales target, including the purchase demand of the experience store demand side users, and carry out sales promotion work. The specific way includes: the demand side users see the goods in the experience store and generate purchase intention and place an order; the supply and demand service providers directly push the goods information through the demand side APP, form the purchase intention and place an order.

[0111] S106, sales expansion.

[0112] The supply-demand service party processes the commodity order aggregation according to the purchase demand of the demand party user. If the order quantity is insufficient, the supply-demand service party can adopt an intelligent allocation strategy to allow more experience stores to share the sales volume, or expand the sales of other channels, or even allow the family users with Douyin e-commerce accounts to apply for goods.

[0113] S107, logistics distribution.

[0114] The supplier delivers the goods to the demand party through logistics or express delivery. After the demand party confirms the receipt and has no dispute, it is considered that the delivery is completed.

[0115] S108, balance and final payment.

[0116] The supply-demand service party aggregates the collected funds on the platform, deducts the corresponding commission and management fee, and transfers them to the supplier, and settles the channel fee for the experience store.

[0117] S109, evaluation and feedback.

[0118] The parties to the transaction need to evaluate this transaction. The platform collects evaluation information for improving services and establishing a credit system, marking the end of the complete business process of this supply-demand.

[0119] Example II, the business process of the demand party proposing a purchase demand, including: S201, propose the subject.

[0120] The demand party needs to propose a clear purchase demand, i.e. the purchase subject. If the purchase subject content is relatively vague, the system will automatically guide and optimize the demand to clarify the demand, which specifically includes: Commodity information: the specific type, name, specification or key attributes of the required commodity.

[0121] Purchase quantity: the expected quantity range.

[0122] Price information: budget range or target price.

[0123] Delivery information: expected delivery time / location.

[0124] Special requirements: specific quality requirements, certification requirements or other special requirements.

[0125] The supply-demand service party first analyzes the demand party data to check whether the demand party basic information, demand portrait, etc. are complete. If the information is vague or incomplete, the demand party will be contacted for clarification or supplement, otherwise the purchase plan cannot be developed.

[0126] S202, matching and plan development.

[0127] The supply and demand service party searches for matching goods in the platform database based on the requirements of the demand party. At the same time, the enterprise / family portrait of the demand party is analyzed, and combined with the current market supply situation, price trend, logistics cost and other factors, a procurement plan is formulated, and one or more recommended procurement plans are formed. The plan content includes: Supplier and commodity information: recommended supplier and commodity information.

[0128] Price quantity suggestion: specific price and quantity suggestion.

[0129] Distribution channel suggestion: optional distribution channel.

[0130] Delivery information: expected delivery time and method.

[0131] Contract term suggestion: relevant contract term suggestion.

[0132] The supply and demand service party submits the plan to the demand party for review. If the demand party is not satisfied or needs to adjust, the parties will communicate to modify the plan; if the plan is approved, the next step is confirmed. The demand party needs to select the final procurement goods, experience store and plan details.

[0133] S203, sign a contract.

[0134] The demand party needs to select the procurement plan and sign an electronic contract with the supplier / experience store: Through the experience store: the demand party signs a purchase contract with the selected experience store; the demand party purchases directly through the APP in the experience store.

[0135] Through the platform directly connected supplier: the demand party may directly sign an electronic procurement contract with the supplier.

[0136] Platform service agreement: the demand party needs to confirm the service agreement with the supply and demand service party.

[0137] S204, payment.

[0138] The demand party needs to pay the payment according to the payment method and terms agreed in the contract, which may include prepayment of deposit to the supplier / experience store, cash on delivery or full prepayment. In the mode of one piece of delivery, the full payment may be made at the time of ordering.

[0139] After the transaction is completed, the supply and demand service party will settle the platform service fee, including commission, channel fee, etc.

[0140] S205, order generation and delivery.

[0141] After the demand party's purchase intention is converted into a formal order, it is delivered to the corresponding supplier and logistics party through the platform.

[0142] S206, goods preparation and delivery.

[0143] The supplier or logistics / experience store cooperated by the supplier prepares the goods according to the order and sends them out.

[0144] S207, logistics distribution and tracking.

[0145] The logistics company delivers the goods to the designated delivery location of the demand side, and the demand side can track the logistics status through the platform.

[0146] S208, acceptance of goods.

[0147] After receiving the goods, the demand side needs to check the goods and confirm that the quantity, specifications, quality, etc. meet the contract requirements. If there is no problem, the platform confirms the receipt of goods; if there is a problem, the platform initiates the objection or return / exchange process.

[0148] S209, transaction completion and settlement.

[0149] After the demand side confirms the receipt of goods and has no disputes, the platform settles the demand side's payment to the supplier. If there is a channel fee or commission involved, the platform will also make the corresponding settlement.

[0150] S210, demand side completes payment.

[0151] If the full payment has not been made before, the demand side needs to complete the payment of the remaining goods at this time.

[0152] S211, evaluation and feedback.

[0153] The demand side needs to evaluate the parties involved in this transaction on the platform, including the quality of the goods and services of the supplier, the services of the logistics company, the services of the experience store (if purchased through it), and the platform services, matching efficiency, and solution quality of the supply and demand service providers. The platform collects evaluation information for improving services and establishing a credit system, marking the end of the complete business process of this purchase demand.

[0154] Example three, the business process of the demand side proposing to exchange goods / services, including: S301, propose exchange demand.

[0155] The demand side, which is also a potential supplier, needs to clearly propose exchange demand on the platform APP or to the supply and demand service provider. The demand content needs to be clear and specific, including: Desired goods / services: specific type, name, specifications, quantity, key attributes, expected quality, service standards, etc. The system can be intelligently optimized to reduce information input.

[0156] Willing to provide goods / services: specific type, name, specifications, quantity, key attributes, quality status, service capability description, relevant certificates, etc. The system can be intelligently optimized to reduce information input.

[0157] Value expectation: The value estimation of the provided goods / services and the expected value range of the acquired goods / services, which can be measured by monetary units or platform points.

[0158] Expected delivery information: The expected delivery time, location, and method.

[0159] Specific preferences or constraints: Such as only accepting specific industries, specific regions, or special requirements for the exchanged goods / services.

[0160] The platform needs to review the completeness and clarity of the exchange requirements, focusing on whether the description of the "provided goods / services" is sufficient and whether relevant proofs are available, such as photos of physical goods, service qualification certificates, and test reports.

[0161] S302, Value assessment and matching.

[0162] Goods / service evaluation: The supply and demand service providers use platform data such as market trends, historical transactions, and professional evaluation models to objectively evaluate the value of the "provided goods / services" provided by the demand side, and give a reference value range.

[0163] Goods / service matching: Search for matching "acquired goods / services" in the platform database, supply-side sales targets, other demand-side exchange requirements, and inventory resources.

[0164] Value balance analysis: Analyze whether the value of "provided goods / services" is equivalent to the value of matched "acquired goods / services", and the platform needs to provide value balance suggestions.

[0165] S303, Develop exchange plan.

[0166] Based on the matching results and value analysis, the supply and demand service providers develop an exchange plan, which includes: Potential exchange object information: Recommended potential exchange objects and their provided "acquired goods / services" matching information.

[0167] Value assessment comparison and balance suggestion: Value assessment comparison and balance suggestion of "provided goods / services" and "acquired goods / services", such as whether to make up the difference, how much to make up, or direct equivalent exchange.

[0168] Exchange method suggestion: Specific exchange method suggestions such as direct exchange, through platform transit guarantee, and phased delivery.

[0169] Logistics / service delivery plan: Recommended logistics / service delivery plan.

[0170] Contract term suggestion: Related contract term suggestion.

[0171] The supply-demand service party submits the scheme to the demand party for review. If the demand party is not satisfied with the matching object or the value assessment, it can communicate adjustment or re-matching; if it approves the scheme, it confirms the next step and selects the final exchange object and scheme details.

[0172] S303, sign the exchange contract.

[0173] Sign a multi-party electronic contract Under the support of the platform, the exchange parties sign the main contract of the exchange of goods / services, and clearly define the following: Goods / service description: detailed description, quantity, quality / service standards of the goods / services provided by both parties.

[0174] Value identification and price difference: value identification of the exchange and whether the price difference needs to be made up.

[0175] Delivery information: time, place, method, and acceptance standard of goods delivery / service provision.

[0176] Logistics responsibility and cost: logistics responsibility party and cost bearing.

[0177] Liability for breach of contract and dispute resolution: liability for breach of contract and dispute resolution mechanism.

[0178] The exchange parties need to sign a service agreement with the supply-demand service party respectively or jointly, clearly defining the role of the platform in the exchange, service fee, and responsibility.

[0179] S304, delivery and delivery.

[0180] The supply-demand service party associates the demand party and the matched supply party, carries out the exchange of goods / services, and supervises and manages the entire process.

[0181] Price difference payment: if the exchange value is not equal and needs to be made up, the price difference party needs to pay the difference to the other party according to the contract, and the platform is responsible for managing the process.

[0182] Two-way delivery execution: Goods delivery: both parties deliver their goods to the designated location of the other party according to the contract, through logistics or offline methods, simultaneously or in the order agreed upon. The platform can coordinate logistics or provide delivery witness.

[0183] Service delivery: both parties provide the agreed services to the other party at the designated time and place according to the contract. The platform can provide process records or acceptance confirmation tools.

[0184] Acceptance confirmation: After receiving the goods / services of the other party, both parties need to conduct acceptance confirmation on the platform.

[0185] If the contract requirements are met, the delivery is confirmed to be completed.

[0186] If there is a dispute, the platform initiates the exchange dispute process, and the platform intervenes in mediation or handles it according to the contract.

[0187] S305, final settlement.

[0188] After both parties confirm that the delivery is completed and there is no dispute: The platform releases the managed difference to the payee.

[0189] The platform completes the settlement of service fees.

[0190] If the registration of the ownership transfer of the goods is involved, the platform can provide guidance or auxiliary services.

[0191] S306, evaluation and feedback Both parties need to evaluate the goods / services provided by the trading counterpart on the platform.

[0192] Both parties need to evaluate the platform service, matching efficiency, evaluation fairness, dispute handling ability, etc. of the supply and demand service party.

[0193] Evaluate the logistics party involved.

[0194] The platform collects evaluation information, perfects the credit system and matching algorithm, and marks the end of the exchange demand business process.

[0195] Embodiment 6 The embodiment provides a device, which comprises a memory and a processor, the memory stores a computer program, and the processor executes the computer program to realize any of the above methods.

[0196] Specifically, as shown in Figure 2 , the device comprises a memory and a processor, the memory stores a computer program, and the processor executes the computer program to realize any of the above methods. Figure 2This is a schematic diagram of the device structure of the hardware operating environment involved in the embodiments of this application. The device is an electronic device and may include: a processor 101, such as a central processing unit (CPU), a communication bus 102, a user interface 104, a network interface 103, and a memory 105. The communication bus 102 is used to realize the connection and communication between these components. The user interface 104 may include a display screen and an input unit such as a keyboard. Optionally, the user interface 104 may also include a standard wired interface and a wireless interface. The network interface 103 may optionally include a standard wired interface and a wireless interface (such as a Wi-Fi interface). The memory 105 may be a storage device independent of the aforementioned processor 101. The memory 105 may be a high-speed random access memory (RAM) or a stable non-volatile memory (NVM), such as at least one disk storage device. The processor 101 may be a general-purpose processor, including a central processing unit, a network processor, etc., or it may be a digital signal processor, an application-specific integrated circuit, a field-programmable gate array or other programmable logic device, discrete gate or transistor logic device, or discrete hardware component.

[0197] Those skilled in the art will understand that the appendix Figure 2 The structure shown does not constitute a limitation on the electronic device and may include more or fewer components than shown, or combine certain components, or have different component arrangements.

[0198] like Figure 2 As shown, the memory 105, which serves as a storage medium, may include an operating system, a network communication module, a user interface module, and an application for implementing a solution generation method based on generative artificial intelligence.

[0199] exist Figure 2 In the electronic device shown, the network interface 103 is mainly used for data communication with the network server; the user interface 104 is mainly used for data interaction with the user; the processor 101 and the memory 105 in this application can be set in the electronic device, and the electronic device can call the application program stored in the memory 105 through the processor 101 to implement a solution generation method based on generative artificial intelligence to implement the above method.

[0200] Example 7 This embodiment provides a computer-readable storage medium on which a computer program is stored, and a processor executes the computer program to implement any of the methods described above.

[0201] In some embodiments, the computer readable storage medium can be FRAM, ROM, PROM, EPROM, EEPROM, flash memory, magnetic surface memory, optical disc, or CD-ROM memory, etc. It can also be various devices including one or any combination of the above memories. The computer can be various computing devices including smart terminals and servers.

[0202] In the above embodiments of the present disclosure, the description of each embodiment is focused on, and the parts not described in detail in a certain embodiment can be referred to the relevant description of other embodiments.

[0203] In several embodiments provided in the present application, it should be understood that the disclosed technical contents can be implemented by other ways. Among them, the above-described device embodiments are only schematic, for example, the division of units can be a logical function division, and actual implementation can have another division way, for example, a plurality of units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the coupling or direct coupling or communication connection between the displayed or discussed each other can be through some interface, indirect coupling or communication connection between units or modules, which can be electrical or other forms.

[0204] The units described as separate components can or can not be physically separated, and the components shown as units can or can not be physical units, that is, they can be located in one place, or they can be distributed to multiple units. Part or all of the units can be selected according to actual needs to achieve the purpose of the present embodiment scheme.

[0205] In addition, each functional unit in each embodiment of the present disclosure can be integrated in one processing unit, or each unit can be physically present alone, or two or more units can be integrated in one unit. The above integrated unit can be realized in the form of hardware or in the form of software functional unit.

[0206] The integrated unit, if implemented in the form of a software function unit and sold or used as an independent product, can be stored in a computer-readable nonvolatile storage medium. Based on such understanding, the technical solutions of the present disclosure, essentially or in other words, the part that contributes to the prior art or the whole or part of the technical solutions can be embodied in the form of a software product. The computer software product is stored in a nonvolatile storage medium, including a number of instructions to make a device (which can be a personal computer, a server, or a network device, etc.) execute all or part of the steps of the methods in the various embodiments of the present disclosure. The aforementioned nonvolatile storage medium includes: a U disk, a read-only memory (ROM, Read-Only Memory), a random access memory (RAM, Random Access Memory), a mobile hard disk, a magnetic disk or an optical disk, and various media that can store program codes.

[0207] The above is only the preferred embodiment of the present disclosure, and it should be pointed out that for those skilled in the art, without departing from the principles of the present disclosure, a number of improvements and refinements can be made, and these improvements and refinements should be considered as the protection scope of the present disclosure.

Claims

1. A generative artificial intelligence-based solution generation method, characterized by, The method comprises the following steps: obtaining a target demand in response to receiving target content sent by a target user; obtaining a target demand parameter corresponding to the target demand according to the target demand; obtaining at least one target supplier based on a supplier database according to the target demand parameter; obtaining supplier data according to the at least one target supplier; obtaining at least one solution for the target demand based on a generative artificial intelligence model according to the target demand and the supplier data.

2. The generative artificial intelligence-based solution generation method of claim 1, wherein, The step of obtaining a target demand in response to receiving target content sent by a target user comprises the following steps: analyzing the target content using a pre-set NLP model to determine whether the target content includes complete demand information in response to receiving target content sent by a target user; obtaining a target demand according to complete demand information when the target content includes complete demand information; obtaining a target demand after guiding the target user to complete the demand information when the target content does not include complete demand information.

3. The method of claim 1, wherein the method further comprises: The step of obtaining a target demand parameter corresponding to the target demand according to the target demand comprises the following steps: obtaining a key indicator parameter based on a pre-set key indicator according to the target demand; obtaining an additional indicator parameter based on additional demand according to the target demand, wherein the additional demand is configured as demand in the target demand that is not directly related to the key indicator; obtaining a target demand parameter according to the key indicator parameter and / or the additional indicator parameter.

4. The method of claim 1, wherein the method further comprises: The step of obtaining at least one target supplier based on a supplier database according to the target demand parameter comprises the following steps: obtaining user information of the target user according to the target user; obtaining a user limit parameter according to the user information of the target user; obtaining at least one target supplier based on a supplier database according to the user limit parameter and the target demand parameter.

5. The method of claim 1, wherein the method further comprises: The step of obtaining supplier data according to the at least one target supplier comprises the following steps: obtaining a unique address corresponding to each target supplier according to the at least one target supplier; accessing the unique address corresponding to each target supplier to obtain products and / or services listed by each supplier according to the unique address corresponding to each target supplier; obtaining supplier data according to the products and / or services listed by each supplier.

6. The method of claim 1, wherein the method further comprises: The step of obtaining at least one solution for the target demand based on a generative artificial intelligence model according to the target demand and the supplier data comprises the following steps: obtaining a target knowledge base according to the supplier data, and inputting the target knowledge base into a generative artificial intelligence model; generating a target prompt word corresponding to the target demand according to the target demand; obtaining at least one solution for the target demand based on the generative artificial intelligence model with the input target knowledge base according to the target prompt word.

7. The method of claim 1, wherein the method further comprises: The method further comprises the following steps after the step of obtaining at least one solution for the target demand based on a generative artificial intelligence model according to the target demand and the supplier data: obtaining an elected supplier corresponding to a target solution in response to receiving a target solution selected by a user. According to the selected supplier and the target solution, placing an order for the selected supplier. 8.A method system for generating a solution based on generative artificial intelligence, characterized by, The system comprises a user terminal, a demand platform, a supply platform, and a solution management platform; The user terminal is configured to: receive target content input by a target user, and send the target content input by the target user to the demand platform; receive at least one solution for the target demand sent by the solution management platform, and display the at least one solution for the target demand to the user; The demand platform is configured to: obtain a target demand in response to receiving target content sent by a target user through a user terminal; obtain target demand parameters corresponding to the target demand according to the target demand; send the target demand parameters to the solution management platform; The solution management platform is configured to: obtain at least one target supplier based on a supplier database of the supply platform according to the target demand parameters in response to receiving the target demand parameters from the demand platform; obtain supplier data according to the at least one target supplier; obtain at least one solution for the target demand based on a generative artificial intelligence model according to the target demand and the supplier data; send the at least one solution for the target demand to the target terminal; The supply platform is configured to: manage a supplier database configured to store at least a list of suppliers and supplier information of each supplier, and the target supplier belongs to the suppliers.

9. The generative artificial intelligence-based solution generation method system according to claim 8, characterized in that, The suppliers include at least one of direct operation suppliers, franchise suppliers, and individual suppliers.

10. The generative artificial intelligence-based solution generation method system according to claim 9, characterized in that, Further comprising a supplier terminal; The supplier terminal is configured to: send a supplier database operation request to the supply platform according to the input of the supplier in response to receiving the input of the supplier; The supply platform is configured to: respond to the supplier database operation request sent by the supplier terminal, audit the supplier database operation request, and operate the supplier database according to the audited supplier database operation request.

11. The generative artificial intelligence-based solution generation method system according to claim 8, characterized in that, The method of obtaining at least one solution for the target demand based on a generative artificial intelligence model according to the target demand and the supplier data comprises: obtaining a target knowledge base according to the supplier data, and inputting the target knowledge base into the generative artificial intelligence model; generating a target prompt word corresponding to the target demand according to the target demand; obtaining at least one solution for the target demand based on the generative artificial intelligence model with the input target knowledge base according to the target prompt word.

12. The generative artificial intelligence-based solution generation method system according to claim 8, characterized in that, The solution management platform is further configured to: obtain a selected supplier corresponding to a target solution selected by a user in response to receiving the target solution selected by the user; place an order for the selected supplier through the supply platform according to the selected supplier and the target solution.

13. An apparatus, comprising: The device comprises a memory and a processor, the memory stores a computer program, and the processor executes the computer program to implement the method according to any one of claims 1-7.

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