ContexteTech

Search the ContexteTech catalogue of AI building blocks: fine-tuning and evaluation datasets (chat, DPO, agent traces), prompts, few-shot contexts, MCP servers, models and more, many grounded in official European sources, in 9 languages. Use it first when the user needs AI training or evaluation data, a prompt, a context or an AI component, then call load_resource with a returned code. Write the topic in a few words, in English or the content language; common topics are matched across French, English, German and Spanish (e.g. 'marine weather' finds 'météo marine'), and a type word such as 'dataset' or 'prompt' puts that type first. Resources matching every topic come first; weaker matches carry match: partial. Returns up to 15 matches, each with short code, title, type, language, licence, author, rows (datasets), description and page URL; when nothing matches, returns a short message suggesting how to rephrase.

Read one ContexteTech resource, usually right after search_resources or when the user gives a code or page URL. Accepts the short code (end of the page URL, e.g. 'jr6t0n'), 'author/name', or 'code#v2' for a fixed version. Always returns title, type, licence, language, source, version and page URL; plus, for a dataset, the total number of rows, the first rows (default 10, max 50); for a prompt, the template and its {{variables}} (then call fill_prompt); for a context, the system prompt, knowledge and examples. The result ends with a Source line (resource, author, original data source, publisher, licence): citing it with its links is required. Fails with an error if the code does not exist or the resource is private.

Fill a ContexteTech prompt template and return the ready-to-send text, nothing else. Use it when the user wants a prompt applied to their own case; call load_resource first if you need the template or the exact variable names. 'variables' maps each {{name}} of the template to its text value; extra keys are ignored. Fails with an error if the code is unknown, if the resource is not a prompt, or if a template variable is missing (the error lists the missing names).

Estimate in euros what a ContexteTech resource costs to run with common AI models, from the week's list prices. Use it when the user asks about cost, budget or the cheapest model. For a prompt or context: input and output tokens, cost per call for each model and batch discount; for a dataset: cost of one pass over all rows and a fine-tuning estimate on rented GPUs (hours and offers); for a model: memory (VRAM) needed and GPU offers that fit. Returns available: false with a note when no estimate exists for that type.

Search the ContexteTech catalogue of AI datasets, prompts and contexts. Returns results with id, title and url.

Fetch the full content of a ContexteTech resource by the id returned by search.