BeamWeaver Google

BeamWeaver includes a Gemini Developer API provider under BeamWeaver.Google.

Implemented

• BeamWeaver.Google.ChatModel implements BeamWeaver.Core.ChatModel.

• Public model identifiers use the google: provider prefix, for example google:gemini-3.7-flash.

• Bare gemini-* identifiers are intentionally rejected so Gemini Developer API and future Vertex AI adapters do not share an ambiguous namespace.

• Requests go through BeamWeaver.Transport, so fake and replay transports can exercise provider behavior without live credentials.

• Namespace constructors load defaults from config :beam_weaver, :google; put any OS environment reads in your config/runtime.exs. Custom routing can use configured :base_url, explicit :base_url, or :endpoint.

• BeamWeaver messages become Gemini contents plus top-level systemInstruction.

• Custom tools become Gemini function declarations. Google built-ins such as Google Search, Google Maps, URL context, code execution, File Search, MCP servers, and model-specific computer use are pass-through provider request values.

• Gemini function parameter schemas are provider-sanitized: local $ref entries are dereferenced, unsupported JSON Schema annotation/object keywords such as $defs, title, default, and additionalProperties are removed, and nested property schemas are cleaned recursively.

• google:gemini-3.7-flash, google:gemini-3.6-flash, and google:gemini-3.5-flash-lite are checked in with Google's published text-only output profiles. All three accept text, image, video, audio, and PDF input and support thinking, structured output, function calling, code execution, File Search, Google Maps grounding, Search grounding, URL context, computer use, caching, batch, flex, and priority inference. Computer use is currently a preview capability.

• These models use thinking_level instead of thinking_budget. Gemini 3.7 Flash supports low, medium, and high and defaults to medium; Gemini 3.6 Flash also defaults to medium, while Gemini 3.5 Flash-Lite defaults to minimal. Google deprecates and ignores temperature, top_p, and top_k for these releases and does not support candidate_count, so their checked-in profiles reject those options before transport. They also reject requests whose last non-empty content turn has the Gemini model role; append a user or tool result turn instead of prefilling model output.

• Responses include normalized usage, reasoning/thinking token metadata, safety ratings, grounding metadata, model version, request IDs, and raw provider metadata.

• Streaming supports text deltas, typed stream envelopes, and reconstructed final assistant messages.

• Checked-in model profiles cover current recommended Gemini chat models. Deprecated or near-shutdown models such as Gemini 2.0 Flash, Gemini 2.5 Flash, Gemini 2.5 Pro, and Gemini 3 Flash Preview are rejected with a :deprecated_model error and replacement metadata; explicit google:gemini-* identifiers still use the family fallback for uncataloged current model IDs.

• Gemini 3.5 Flash Cyber is not registered as a callable chat model. Google limits it to governments and trusted partners through CodeMender rather than exposing it through the Gemini Developer API, so its slug returns an :unsupported_model error before family fallback. See Google's release announcement for the stated rollout boundary.

Current Flash Profiles

Prices are USD per one million tokens for the Gemini Developer API. Cached input is the context-caching token price. Gemini 3.7 Flash and 3.6 Flash use Google's published pricing. The 3.7 Flash entry uses its introductory pricing through December 31, 2026; its standard rates double on January 1, 2027. Its introductory cache storage price is $0.50 per one million tokens per hour.

From January 1, 2027, Gemini 3.7 Flash standard input, cached input, and output rates become $1.50, $0.15, and $7.50 respectively. See the live pricing page for the corresponding batch, flex, priority, and storage rates.

See Google's model specifications and Gemini Developer API pricing for the live provider source of truth.

Usage

{:ok, model} =
  BeamWeaver.Models.init_chat_model("google:gemini-3.7-flash",
    thinking_level: :medium,
    include_thoughts: true
  )

BeamWeaver.Core.ChatModel.invoke(model, [
  BeamWeaver.Core.Message.user("Summarize the tradeoffs in one paragraph.")
])

Provider tools are request values:

tools = [
  BeamWeaver.Google.Tools.google_search(),
  BeamWeaver.Google.Tools.google_maps(),
  BeamWeaver.Google.Tools.code_execution(),
  BeamWeaver.Google.Tools.file_search(["fileSearchStores/my_store"]),
  my_local_tool
]

BeamWeaver.Core.ChatModel.invoke(model, messages, tools: tools, tool_choice: :auto)

Structured output maps to Gemini generation config:

BeamWeaver.Core.ChatModel.invoke(model, messages,
  response_format: %{
    schema: %{
      type: :object,
      properties: %{answer: %{type: :string}},
      required: [:answer]
    }
  }
)

When a structured-output request does not set :max_output_tokens, BeamWeaver uses the model profile's output limit for Gemini. For example, google:gemini-3.7-flash defaults structured-output calls to 65_536 maxOutputTokens, while an explicit max_output_tokens: value still wins.

Token counting uses Gemini's count-tokens endpoint:

BeamWeaver.Google.ChatModel.count_tokens(model, [
  BeamWeaver.Core.Message.user("Count this.")
])

Unsupported Google Surfaces

• Vertex AI. That should be a separate explicit adapter/prefix rather than an alias of google:*.

• Dedicated image, audio, and video generation model modules beyond chat response modality options.

• Exact Python class identity and serialization compatibility. BeamWeaver keeps native Elixir modules, structs, and tagged errors.