Publishing rules are used to automate the generation of article topics (titles), as well as to provide contextual references during the article generation phase. To set the publishing rules and generate topics according to the real optimization goals of the site, do not use blindly, the preliminary recommendations for small-scale testing to observe whether the generated topics meet expectations. The main operation process of the plug-in: configure the publishing rules - select the publishing rules to generate the main...
1.First configure the APIs used to generate articles The APIs added in the custom API configuration, pre-built API configuration are used to generate text content such as themes, articles, article structure, and so on. 1.1 Support the use of custom APIs compatible with the OPENAI format Remember to complete the /v1/chat/completions section...
1. From the creation of simple rules to create rules for the creation of the theme (article title) before the preparation of materials, is the starting point of the entire article generation process. Here I use the simplest type of rule, “Random Category”, to generate a rule. Explanation of the following configuration: random use of 10 categories of names and descriptions, used to generate the theme (article title) ...
1.Operation Guidelines 1.1 Multi-language Selection Only valid for multi-language selection of channels in the chart 1.2 Chinese Keyword Mining Tips It is recommended to choose only Google and Baidu For keywords involving a mixture of Chinese and English, it is recommended that English be used in lowercase, and that multiple words be separated by spaces Keyword Expansion Tips: Using a Large Model to Get the Base Words - Using Keyword Tools ...
0. Necessary: must be complete and detailed configuration of the site classification Classification name, alias (English), description, must be detailed. AI Content Manager deeply relies on the classification name and detailed description of the classification to control the direction of the generated content and automatically select the appropriate classification. After setting up the categories, please click once on the Refresh Category Cache button on the dashboard page within the plugin...
This is AI Content Generation Manager, exclusive theme, can not directly use this template. After enabling, all related settings are in the “Theme Settings”. 1. Enable secondary domain name access What is the case for enabling secondary domain name access? Already have a website, want to enhance the weight of the main site, attract traffic; or for individual search engine optimization. Open ...
Well, by this point we have over 1000 lines in our markdown file. This one is mostly for fun.
If you've been waiting for an introduction to humanlayer, then this is it. If you are practicing Element 6 - Start/Pause/Resume via a simple API and Element 7 - Contacting humans via tool calls, then you are ready to integrate this element. Allow the user to start/pause/resume from s...
Instead of building monolithic intelligences that try to do everything, it is better to build small, focused intelligences that can do one thing well. Intelligentsia are just one building block in a larger, largely deterministic system. The key insight here is in the limitations of large language models: the larger and more complex the task, the more steps are required, which means longer context windows...
This is a small point, but worth mentioning. One of the benefits of an agent is “self-healing” - for short tasks, a large language model (LLM) may call a failed tool. There is a good chance that a good LLM will be able to read an error message or stack trace and figure out what to do after...
If you are in control of your own control flow, you can implement many interesting features. Build custom control structures that fit your particular use case. Specifically, certain types of tool calls might be a reason to jump out of a loop, wait for a human to respond, or wait for another long-running task (e.g., a training pipeline). You may also want to integrate custom implementations of the following features: ...
By default, the Large Language Model (LLM) API relies on a fundamentally high-stakes Token choice: do we return plain text content, or do we return structured data? You put a lot of weight on the first Token choice, which in the case of the weather in tokyo...
Intelligences are programs, and we expect to be able to start, query, resume, and stop them in some way. Users, applications, pipelines, and other intelligences should be able to easily start an intelligence through a simple API. Intelligences and their orchestration deterministic code should be able to pause the intelligence when a long-running operation needs to be performed. Intelligences like webh...
Even outside of the AI space, many infrastructure systems try to separate the “execution state” from the “business state”. For AI applications, this can involve complex abstractions to keep track of information such as current step, next step, wait status, retries, and so on. This separation introduces complexity, and while it may be worthwhile, it may be trivial for your use case...
The tool need not be complex. At its core, it's just structured output from your Large Language Model (LLM) for triggering deterministic code. For example, suppose you have two tools CreateIssue and SearchIssues. asking a Large Language Model (LLM) to "use one of the multiple tools" is really asking it to output...
You don't have to use a standardized, message-based format to deliver context to the big language model. At any given moment, your input to the big language model in the AI intelligence is “here's everything that's happened so far, what's next” It's all contextual engineering. Big language models are stateless functions that transform inputs into outputs...
Don't outsource your input prompt engineering to a framework. By the way, this is far from being novel advice: some frameworks provide a "black box" approach like this: agent = Agent( role="..." , goal="..." , personality="..." , tools=...
One of the most common patterns when building intelligences is converting natural language into structured tool calls. This is a powerful pattern that allows you to build intelligences that can reason about tasks and execute them. This pattern, when applied atomically, is to take a phrase (e.g. Can you create a $750 payment for Terri...
Detailed version: how we got here You don't have to listen to me Whether you're new to intelligences or a grumpy veteran like me, I'm going to try to convince you to throw out most of your pre-existing views on AI intelligences, take a step back, and rethink them from first principles. (If you missed OpenAI a couple weeks ago ...
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