Class: SmartPrompt::SenseNovaAdapter

Inherits:
LLMAdapter show all
Includes:
HTTPClient, ImagePersistence, MultimodalMessages, OpenAIChatShaping
Defined in:
lib/smart_prompt/sensenova_adapter.rb

Overview

Adapter for SenseNova (商汤 日日新) — the SenseCore large-model platform.

One adapter owns the whole provider: all four documented model categories share the same ‘api.sensenova.cn` domain and Bearer-token auth, so a single config block serves them just by changing `model`.

1. 商量 文本对话 / 多模态 (chat + vision)  — OpenAI-compatible
     POST {url}/chat/completions     (url defaults to .../compatible-mode/v2)
     Streaming is SSE; the model may emit a `reasoning`/`delta.reasoning` field on
     reasoning models, which we remap to OpenAI's `reasoning_content` so the engine's
     stream aggregator (Engine#@stream_proc) keeps working unchanged.
2. Cupido 向量模型 (embeddings)          — native, non-OpenAI response shape
     POST {embeddings_url}          (defaults to .../v1/llm/embeddings)
     Body {model, input:[...]}; response {embeddings:[{index, embedding, ...}]}.
3. 秒画 文生图 (text-to-image)           — OpenAI-compatible /images/generations
     POST {image_url}  (native /v1 base, e.g. .../v1/images/generations;
     NOT under compatible-mode/v2, which 404s)

We talk to the endpoints directly with Net::HTTP (like the image/tts/stt adapters) rather than the ‘openai` gem, because we must surface SenseNova’s ‘reasoning` field, remap streaming deltas, and handle the native embeddings shape. No new gem deps.

Constant Summary collapse

DEFAULT_BASE_URL = 
"https://api.sensenova.cn/compatible-mode/v2".freeze
DEFAULT_EMBEDDINGS_URL = 
"https://api.sensenova.cn/v1/llm/embeddings".freeze
DEFAULT_IMAGE_URL =

秒画 text-to-image (sensenova-u1-fast) lives on the token.sensenova.cn /v1 base (confirmed working 2026-06-19). NOT under compatible-mode/v2, which 404s.

"https://token.sensenova.cn/v1/images/generations".freeze
VALID_IMAGE_SIZES =

Sizes accepted by sensenova-u1-fast (the API 400s on anything else, e.g. 1024x1024).

%w[
  1664x2496 2496x1664 1760x2368 2368x1760 1824x2272 2272x1824
  2048x2048 2752x1536 1536x2752 3072x1376 1344x3136 2560x720 3072x864
].freeze
DEFAULT_IMAGE_SIZE = 
"2048x2048".freeze
CHAT_OPTIONAL_KEYS =

SenseNova sampling parameters forwarded from config to the chat request when present.

%w[
  top_p top_k min_p presence_penalty frequency_penalty repetition_penalty
  reasoning_effort max_completion_tokens max_tokens
].freeze

Instance Attribute Summary

Attributes inherited from LLMAdapter

#last_response

Instance Method Summary collapse

Constructor Details

#initialize(config) ⇒ SenseNovaAdapter

Returns a new instance of SenseNovaAdapter.



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# File 'lib/smart_prompt/sensenova_adapter.rb', line 77

def initialize(config)
  super
  SmartPrompt.logger.info "Start create the SmartPrompt SenseNovaAdapter."

  api_key = @config["api_key"]
  if api_key.is_a?(String) && api_key.start_with?("ENV[") && api_key.end_with?("]")
    api_key = eval(api_key)
  end
  # Match the other adapters: tolerate a missing key at construction (e.g. when the
  # ENV var isn't set yet) and let the first request fail with a clear auth error.
  SmartPrompt.logger.warn "SenseNova api_key is empty — API calls will fail until it is set." if api_key.nil? || api_key.to_s.strip.empty?

  @api_key        = api_key
  @base_url       = (@config["url"] || DEFAULT_BASE_URL).to_s.chomp("/")
  @embeddings_url = (@config["embeddings_url"] || DEFAULT_EMBEDDINGS_URL).to_s
  # 秒画 image generation lives on the native /v1 base (NOT compatible-mode/v2),
  # e.g. https://api.sensenova.cn/v1/images/generations. Override per-llm if needed.
  @image_url      = (@config["image_url"] || DEFAULT_IMAGE_URL).to_s
  SmartPrompt.logger.info "SenseNova base_url=#{@base_url}"
rescue => e
  SmartPrompt.logger.error "Failed to initialize SenseNova client: #{e.message}"
  raise e.is_a?(SmartPrompt::Error) ? e : LLMAPIError, "Invalid SenseNova configuration: #{e.message}"
end

Instance Method Details

#default_image_prefix ⇒ Object 



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# File 'lib/smart_prompt/sensenova_adapter.rb', line 62

def default_image_prefix
  "sensenova_image"
end

#embeddings(text, model) ⇒ Object

Cupido embeddings. SenseNova’s native endpoint takes input: and returns embedding:, …]}; we surface the first vector.



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# File 'lib/smart_prompt/sensenova_adapter.rb', line 133

def embeddings(text, model)
  model_name = model || @config["embedding_model"] || @config["model"]
  SmartPrompt.logger.info "SenseNovaAdapter: embeddings model=#{model_name}"

  body = { "model" => model_name, "input" => [text.to_s] }
  response =
    begin
      http_post_json(@embeddings_url, body)
    rescue LLMAPIError, Error
      raise
    rescue => e
      raise LLMAPIError, "Failed to call SenseNova embeddings: #{e.message}"
    end

  items = response["embeddings"] || response["data"]
  unless items.is_a?(Array) && items.any? && items[0]["embedding"]
    raise LLMAPIError, "No embedding vector in SenseNova response: #{response.inspect}"
  end
  items[0]["embedding"]
end

#extra_top_level_fields(raw) ⇒ Object 



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# File 'lib/smart_prompt/sensenova_adapter.rb', line 73

def extra_top_level_fields(raw)
  { "system_fingerprint" => raw["system_fingerprint"] }
end

#generate_image(prompt, params = {}) ⇒ Object

秒画 text-to-image via the OpenAI-compatible /images/generations endpoint. Response is parsed defensively (OpenAI ‘data[]` or SenseNova `images[]`). Returns an Array of b64_json:, seed:.

Raises:



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# File 'lib/smart_prompt/sensenova_adapter.rb', line 157

def generate_image(prompt, params = {})
  SmartPrompt.logger.info "SenseNovaAdapter: generating image"
  raise Error, "Prompt cannot be empty" if prompt.nil? || prompt.to_s.strip.empty?

  model_name = params[:model] || @config["image_model"] || @config["model"]
  raise Error, "No model configured for image generation" if model_name.nil? || model_name.to_s.strip.empty?

  body = { "model" => model_name, "prompt" => prompt.to_s }
  body["n"]                = params[:n]                if params[:n]
  body["size"]             = resolve_image_size(params[:size] || params[:image_size])
  body["response_format"]  = params[:response_format]  if params[:response_format]
  body["negative_prompt"]  = params[:negative_prompt]  if params[:negative_prompt]
  body["seed"]             = params[:seed]             if params[:seed]
  body["num_inference_steps"] = params[:num_inference_steps] if params[:num_inference_steps]
  body["guidance_scale"]      = params[:guidance_scale]      if params[:guidance_scale]

  SmartPrompt.logger.info "SenseNova image params: #{body.except('prompt').inspect}"

  response =
    begin
      http_post_json(@image_url, body)
    rescue LLMAPIError, Error
      raise
    rescue => e
      raise Error, "Failed to call SenseNova image generation: #{e.message}"
    end

  items = response["data"] || response["images"]
  unless items.is_a?(Array) && items.any?
    SmartPrompt.logger.error "SenseNova image response had no data: #{response.inspect}"
    raise LLMAPIError, "No image data in SenseNova response"
  end

  images = items.map do |d|
    { url: d["url"], b64_json: d["b64_json"], seed: d["seed"] }
  end
  SmartPrompt.logger.info "SenseNovaAdapter: generated #{images.size} image(s)"
  images
end

#provider_label ⇒ Object

—- hooks for shared concerns ——————————————-



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# File 'lib/smart_prompt/sensenova_adapter.rb', line 58

def provider_label
  "SenseNova"
end

#reasoning_field_name ⇒ Object

SenseNova exposes the reasoning trace under ‘reasoning` (not reasoning_content) and also returns system_fingerprint — override the OpenAIChatShaping hooks so the shared shaper still produces the uniform reasoning_content / fingerprint output.



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# File 'lib/smart_prompt/sensenova_adapter.rb', line 69

def reasoning_field_name
  "reasoning"
end

#send_request(messages, model = nil, temperature = nil, tools = nil, proc = nil) ⇒ Object

Chat / multimodal request.

Non-streaming returns a full OpenAI-format hash (so last_response carries usage + reasoning); streaming calls proc with each OpenAI-shaped chunk and returns nil.



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# File 'lib/smart_prompt/sensenova_adapter.rb', line 107

def send_request(messages, model = nil, temperature = nil, tools = nil, proc = nil)
  model_name = model || @config["model"]
  body = build_chat_body(messages, model_name, temperature, tools)
  SmartPrompt.logger.info "SenseNovaAdapter: chat request model=#{model_name} stream=#{!proc.nil?}"

  if proc
    body["stream"] = true
    stream_chat("#{@base_url}/chat/completions", body) { |data| proc.call(build_stream_chunk(data), 0) }
    SmartPrompt.logger.info "SenseNovaAdapter: streaming request finished"
    nil
  else
    raw = http_post_json("#{@base_url}/chat/completions", body)
    response = build_completion_response(raw)
    @last_response = response
    SmartPrompt.logger.info "SenseNovaAdapter: received chat response"
    response
  end
rescue LLMAPIError, Error
  raise
rescue => e
  SmartPrompt.logger.error "SenseNova chat error: #{e.message}"
  raise LLMAPIError, "Failed to call SenseNova chat: #{e.message}"
end