Reliable Gemini Requests Start With Clear Content Boundaries

A reliable Gemini request separates several distinct responsibilities

A Gemini generateContent request is easier to reason about when you separate conversation content, persistent instructions, available capabilities, and generation controls. These are different responsibilities, not interchangeable places to put the same prompt. Build the request in that order, then add safety settings and caching only when needed.

The model selection sits outside the request body in the native Gemini API. Choosing Gemini 2.5 Flash, for example, does not mean adding a model field beside contents. Keep the native Gemini contract distinct from an OpenAI-compatible interface, whose field names and routing conventions differ.

The contents field establishes the conversation being continued

Start with contents, the ordered collection of conversation turns. Each turn is a Content object containing a role and parts. For ordinary dialogue, use user for incoming messages and model for previous model replies. A single request can contain one user turn or an accumulated conversation.

Order matters because the model receives the supplied conversation as context. Prior replies are not automatically remembered between independent requests. Include the history your application needs, while removing redundant material that consumes context without improving the next answer.

Each parts entry carries one specific content representation

Inside each turn, parts holds the actual material. A text part carries written instructions or source material. Multiple parts let a single turn combine text with images, audio, video, or other supported inputs without pretending every input is plain text.

Use inlineData for embedded binary content, accompanied by its MIME type and base64-encoded data. Use fileData for a supported file reference, with its file URI and MIME type. File availability, permissions, size limits, and supported media depend on the serving environment and model. A reference is not a guarantee that arbitrary remote content can be fetched.

System instructions belong outside ordinary conversation turns

Add systemInstruction for application-level guidance such as response style, domain boundaries, and persistent behavioral requirements. It uses the Content structure, with instructions supplied through text parts. Do not treat a system role inside contents as the native Gemini equivalent.

Keep user-provided documents and untrusted excerpts in conversation content rather than promoting them into system instructions. This preserves a useful structural distinction, although placement alone does not eliminate prompt injection or replace application-side authorization.

Tools declare capabilities while configuration governs their use

The tools field declares capabilities the model may use. Function declarations describe application functions through names, descriptions, and parameter schemas. Other supported tools can provide capabilities such as search grounding or code execution, subject to model and endpoint support.

The separate toolConfig field controls applicable tool behavior, including function-calling policy. A function declaration does not execute your application code. When the model returns a functionCall part, your application validates the request, performs the authorized operation, and supplies a functionResponse part before asking the model to continue. Preserve any required thought signatures when returning conversation history.

Generation settings shape output without replacing explicit instructions

Use generationConfig for output controls such as temperature, topP, topK, maxOutputTokens, and stopSequences where supported. These settings affect sampling or termination; they do not guarantee factual accuracy. Begin with defaults, then change one setting at a time against representative tests.

For structured output, responseMimeType and responseSchema can constrain supported responses. A schema describes the expected structure, while the prompt explains the task. Schema support has limitations, so validate the result in your application. Thinking controls and output modalities also belong here when supported; their accepted settings vary across models.

Safety settings and cached context need deliberate handling

safetySettings configures supported harm-category thresholds rather than serving as a universal moderation bypass. Inspect response feedback and candidate finish reasons, because a successful HTTP exchange does not guarantee usable generated content.

cachedContent references an existing cached resource. Check its model compatibility and rules for combining cached instructions or tools with request fields. At BestRelay, a quality-first relay, requests go to the official named model without substitution. Pay-as-you-go billing follows provider-reported token counts, with cache reads and writes priced separately. Create a BestRelay account to try this workflow. Members can also earn referral commissions when invited users top up.