Continue.dev su Claude, GPT ir Gemini

Pridėkite vieną models įrašą į Continue config.yaml su provider openai ir avots base URL, ir VS Code ar JetBrains asistentas veikia per avots.

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Connect in three fields

Continue skaito modelius iš config.yaml. Pridėkite openai tiekėją, kuris nukreipia į avots.

FieldValue
Base URLhttps://api.avots.ai/openai/v1
API keyav_mcp_… · get your key
Modelanthropic/claude-sonnet-4.6 or any id from the table below

Setup

1. Atidarykite config.yaml

Atidarykite ~/.continue/config.yaml, dabartinį Continue konfigūracijos formatą. Windows sistemoje tai .continue aplankas jūsų vartotojo profilyje.

2. Pridėkite openai modelį

Pridėkite įrašą po models su provider openai, apiBase nustatytu į avots base URL, savo av_mcp_ raktą ir modelio id.

3. Perkraukite ir pasirinkite modelį

Išsaugokite, perkraukite Continue ir pasirinkite naują modelį asistento išskleidžiamajame sąraše.

~/.continue/config.yaml
models:
  - name: Claude Sonnet (avots)
    provider: openai
    model: anthropic/claude-sonnet-4.6
    apiBase: https://api.avots.ai/openai/v1
    apiKey: av_mcp_YOUR_KEY

provider turi būti openai (bendras OpenAI suderinamas adapteris), o ne anthropic, kitaip Continue kreipsis į gimtąjį Anthropic API. Palikite /v1 ant apiBase. config.yaml pakeičia seną config.json; jei pasirodo srauto ar Responses-API klaidos, pridėkite useResponsesApi: false.

Example request

curl
curl https://api.avots.ai/openai/v1/chat/completions \
  -H "Authorization: Bearer av_mcp_YOUR_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "anthropic/claude-sonnet-4.6",
    "messages": [{"role": "user", "content": "Hello!"}]
  }'

Model and MCP tools in one config

Continue keeps the chat provider and MCP servers in the same file, so you paste both at once and get Claude, GPT and Gemini plus the avots creative tools (image, video, audio, talking avatars) on one av_mcp_ key. You save it yourself, nothing is added automatically.

~/.continue/config.yaml, model + MCP tools
models:
  - name: Claude Sonnet (avots)
    provider: openai
    model: anthropic/claude-sonnet-4.6
    apiBase: https://api.avots.ai/openai/v1
    apiKey: av_mcp_YOUR_KEY

mcpServers:
  - name: avots
    type: streamable-http
    url: https://mcp.avots.ai/
    requestOptions:
      headers:
        Authorization: Bearer av_mcp_YOUR_KEY

MCP setup guide →

Models and prices

Set the model field to any id below, or a lazy name like claude / gpt / gemini that maps to a sensible default.

ModelBest for⚡ / 1M tokens (in / out)
openai/gpt-5.5-proMax intelligence, hardest tasks60 000 / 360 000
anthropic/claude-opus-5Top Claude, long reasoning10 000 / 50 000
anthropic/claude-sonnet-4.6Balanced (default)6 000 / 30 000
google/gemini-3.1-pro-previewFresh Gemini Pro4 000 / 24 000
google/gemini-2.5-proStable Gemini Pro2 500 / 20 000
anthropic/claude-haiku-4.5Fast Claude2 000 / 10 000
deepseek/deepseek-r1Cheap reasoning1 400 / 5 000
google/gemini-2.5-flashFast and cheap600 / 5 000
openai/gpt-5-miniCheap OpenAI500 / 4 000
openai/gpt-oss-120b:freeFree (OpenAI open model, needs a positive balance)Free

* Price in ⚡ per 1,000,000 tokens, input / output (1000⚡ ≈ $1). Free models need a positive balance. Full list via GET /openai/v1/models.

Continue.dev su Claude, GPT ir Gemini

Generate an av_mcp_ key in Settings, paste three fields, and reach 40+ models on one balance. The same key works for MCP.

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FAQ

Klausimai

config.yaml ar config.json?
config.yaml yra dabartinis formatas ir nustelbia bet kurį seną config.json. Įdėkite avots modelį po models sąrašu.
Kodėl provider openai Claude modeliui?
Nes avots yra OpenAI suderinamas. provider openai naudoja /chat/completions kelią; provider anthropic apeitų avots.
Ir VS Code, ir JetBrains?
Taip. Continue dalijasi tuo pačiu config.yaml abiejose IDE.
Kaip apmokestinama?
Už kiekvieną užklausą iš jūsų avots balanso.
Does it support function calling and tools?
Yes. The endpoint forwards the standard OpenAI tools, tool_choice and parallel_tool_calls fields (and the legacy functions/function_call), in both streaming and non-streaming mode, so agent frameworks like LangChain, LlamaIndex, Langflow and n8n get real tool_calls back. Whether a given request uses tools depends on the model you pick: Claude, GPT and Gemini all support function calling.

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