chore: remove litellm config and new-api setup files
The diff shows the deletion of three files that were part of the old litellm configuration and new-api setup: 1. `litellm/config.yaml` - Contains the old model configuration and fallback settings 2. `new-api/CHANNELS.md` - Documentation for channel configuration in new-api 3. `new-api/init-channels.sh` - Script to initialize new-api channels and tokens These files are being removed as part of a refactor or migration away from the old setup pattern. The removal is a cleanup operation that removes the old configuration artifacts and associated setup scripts for the new-api system that was previously used for centralized model routing and channel management. None of the changes require a breaking change notice as they are removing deprecated configuration files rather than introducing breaking changes. The deletion of these files suggests a shift away from the previous litellm-based centralized model routing approach to a new system or configuration method. The removal of the init script also indicates that the automatic channel setup has been eliminated, likely replaced by a different approach to API key management and model routing.
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3 changed files with 0 additions and 598 deletions
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@ -1,233 +0,0 @@
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model_list:
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# ═══════════════════════════════════════════════
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# TIER 1: Free providers (try first)
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# ═══════════════════════════════════════════════
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# --- Groq (free tier, very fast) ---
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- model_name: llama-3.3-70b
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litellm_params:
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model: groq/llama-3.3-70b-versatile
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api_key: os.environ/GROQ_API_KEY
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# --- Cerebras (free tier, very fast) ---
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- model_name: llama-3.3-70b-cerebras
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litellm_params:
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model: cerebras/llama-3.3-70b
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api_key: os.environ/CEREBRAS_API_KEY
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# --- OpenRouter free models ---
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- model_name: deepseek-v3-free
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litellm_params:
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model: openrouter/deepseek/deepseek-chat-v3-0324:free
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api_key: os.environ/OPENROUTER_API_KEY
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# ═══════════════════════════════════════════════
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# TIER 2: DeepSeek V3.2 (cheapest first)
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# ═══════════════════════════════════════════════
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# DeepSeek V3.2 via DeepInfra ($0.26 in / $0.38 out per M)
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- model_name: deepseek-v3.2
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litellm_params:
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model: deepinfra/deepseek-ai/DeepSeek-V3.2
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api_key: os.environ/DEEPINFRA_API_KEY
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# DeepSeek V3.2 fallback via SiliconFlow ($0.27 in / $0.42 out per M)
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- model_name: deepseek-v3.2
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litellm_params:
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model: openai/deepseek-ai/DeepSeek-V3.2
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api_base: https://api.siliconflow.com/v1
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api_key: os.environ/SILICONFLOW_API_KEY
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# ═══════════════════════════════════════════════
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# TIER 3: Ultra-cheap DeepInfra models
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# ═══════════════════════════════════════════════
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# GPT-OSS-120B — OpenAI open-weight MoE ($0.05 in / $0.24 out per M)
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- model_name: gpt-oss
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litellm_params:
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model: deepinfra/openai/gpt-oss-120b
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api_key: os.environ/DEEPINFRA_API_KEY
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# GPT-OSS-20B — lower latency variant ($0.04 in / $0.16 out per M)
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- model_name: gpt-oss-20b
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litellm_params:
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model: deepinfra/openai/gpt-oss-20b
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api_key: os.environ/DEEPINFRA_API_KEY
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# Nemotron Super 49B — near-flagship quality ($0.10 in / $0.40 out per M)
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- model_name: nemotron-super
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litellm_params:
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model: deepinfra/nvidia/Llama-3.3-Nemotron-Super-49B-v1.5
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api_key: os.environ/DEEPINFRA_API_KEY
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# Nemotron Nano 9B — dirt cheap for simple tasks ($0.04 in / $0.16 out per M)
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- model_name: nemotron-nano
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litellm_params:
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model: deepinfra/nvidia/NVIDIA-Nemotron-Nano-9B-v2
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api_key: os.environ/DEEPINFRA_API_KEY
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# ═══════════════════════════════════════════════
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# TIER 4: Other DeepInfra models
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# ═══════════════════════════════════════════════
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- model_name: deepseek-r1
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litellm_params:
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model: deepinfra/deepseek-ai/DeepSeek-R1
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api_key: os.environ/DEEPINFRA_API_KEY
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- model_name: devstral
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litellm_params:
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model: deepinfra/mistralai/Devstral-Small-2505
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api_key: os.environ/DEEPINFRA_API_KEY
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# ═══════════════════════════════════════════════
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# TIER 5: GLM models (cheapest first)
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# ═══════════════════════════════════════════════
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# GLM-4.6 via DeepInfra ($0.60 in / $1.90 out per M)
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- model_name: glm-4.6
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litellm_params:
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model: deepinfra/zai-org/GLM-4.6
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api_key: os.environ/DEEPINFRA_API_KEY
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# GLM-4.7 via DeepInfra ($0.40 in / $1.75 out per M)
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- model_name: glm-4.7
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litellm_params:
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model: deepinfra/zai-org/GLM-4.7
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api_key: os.environ/DEEPINFRA_API_KEY
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# GLM-4.7 fallback via SiliconFlow
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- model_name: glm-4.7
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litellm_params:
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model: openai/THUDM/GLM-4-32B-0414
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api_base: https://api.siliconflow.com/v1
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api_key: os.environ/SILICONFLOW_API_KEY
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# GLM-5 via DeepInfra ($0.80 in / $2.56 out per M)
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- model_name: glm-5
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litellm_params:
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model: deepinfra/zai-org/GLM-5
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api_key: os.environ/DEEPINFRA_API_KEY
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# ═══════════════════════════════════════════════
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# TIER 6: Kimi K2 (cheapest first)
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# ═══════════════════════════════════════════════
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# Kimi K2 via DeepInfra ($0.50 in / $2.00 out per M)
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- model_name: kimi-k2
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litellm_params:
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model: deepinfra/moonshotai/Kimi-K2-Instruct-0905
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api_key: os.environ/DEEPINFRA_API_KEY
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# Kimi K2 fallback via SiliconFlow ($0.58 in / $2.29 out per M)
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- model_name: kimi-k2
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litellm_params:
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model: openai/moonshotai/Kimi-K2-Instruct-0905
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api_base: https://api.siliconflow.com/v1
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api_key: os.environ/SILICONFLOW_API_KEY
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# ═══════════════════════════════════════════════
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# TIER 7: SiliconFlow (Qwen)
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# ═══════════════════════════════════════════════
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# Qwen3 Coder 480B MoE via SiliconFlow ($1.14 in / $2.28 out per M)
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- model_name: qwen3-coder
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litellm_params:
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model: openai/Qwen/Qwen3-Coder-480B-A35B-Instruct
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api_base: https://api.siliconflow.com/v1
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api_key: os.environ/SILICONFLOW_API_KEY
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# Qwen3 Coder 30B — cheaper alternative for simpler tasks
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- model_name: qwen3-coder-30b
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litellm_params:
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model: openai/Qwen/Qwen3-Coder-30B-A3B-Instruct
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api_base: https://api.siliconflow.com/v1
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api_key: os.environ/SILICONFLOW_API_KEY
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# ═══════════════════════════════════════════════
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# TIER 8: OpenRouter (most expensive, widest selection)
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# ═══════════════════════════════════════════════
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# Kimi K2.5 — DeepInfra is cheapest ($0.45 in / $2.25 out per M)
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- model_name: kimi-k2.5
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litellm_params:
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model: deepinfra/moonshotai/Kimi-K2.5
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api_key: os.environ/DEEPINFRA_API_KEY
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# Kimi K2.5 fallback via OpenRouter
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- model_name: kimi-k2.5
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litellm_params:
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model: openrouter/moonshotai/kimi-k2.5
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api_key: os.environ/OPENROUTER_API_KEY
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- model_name: minimax-m2.5
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litellm_params:
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model: openrouter/minimax/minimax-m2.5
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api_key: os.environ/OPENROUTER_API_KEY
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- model_name: gpt-4.1-mini
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litellm_params:
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model: openrouter/openai/gpt-4.1-mini
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api_key: os.environ/OPENROUTER_API_KEY
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- model_name: gemini-3-flash-preview
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litellm_params:
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model: openrouter/google/gemini-3-flash-preview
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api_key: os.environ/OPENROUTER_API_KEY
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- model_name: trinity-large-preview
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litellm_params:
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model: openrouter/arcee-ai/trinity-large-preview
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api_key: os.environ/OPENROUTER_API_KEY
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# --- OpenRouter premium models ---
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- model_name: gemini-2.5-pro
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litellm_params:
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model: openrouter/google/gemini-2.5-pro-preview
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api_key: os.environ/OPENROUTER_API_KEY
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- model_name: claude-sonnet
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litellm_params:
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model: openrouter/anthropic/claude-sonnet-4
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api_key: os.environ/OPENROUTER_API_KEY
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- model_name: gpt-4.1
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litellm_params:
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model: openrouter/openai/gpt-4.1
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api_key: os.environ/OPENROUTER_API_KEY
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# DeepSeek V3.2 last-resort fallback via OpenRouter
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- model_name: deepseek-v3.2
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litellm_params:
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model: openrouter/deepseek/deepseek-chat-v3-0324
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api_key: os.environ/OPENROUTER_API_KEY
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general_settings:
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master_key: os.environ/LITELLM_MASTER_KEY
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# ── Model group fallbacks (when model misbehaves mid-stream) ──
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fallbacks:
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- deepseek-v3.2: [gpt-oss, kimi-k2]
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- gpt-oss: [deepseek-v3.2, nemotron-super]
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- kimi-k2: [deepseek-v3.2, gpt-oss]
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- kimi-k2.5: [deepseek-v3.2, gpt-oss]
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- glm-4.7: [deepseek-v3.2, gpt-oss]
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- glm-5: [deepseek-v3.2, gpt-oss]
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litellm_settings:
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drop_params: true
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set_verbose: false
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num_retries: 2
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request_timeout: 600
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# ── Response caching via Valkey (reuses SearXNG's instance) ──
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cache: true
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cache_params:
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type: redis
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host: valkey
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port: 6379
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ttl: 3600
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# ── Budget limit: $3/day to prevent surprise bills ──
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# max_budget: 3.0
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# budget_duration: "1d"
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# new-api Channel Configuration
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After first start, access the new-api web UI at `http://<server>:4000` to configure channels.
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Default admin credentials: `root` / `123456` — **change immediately**.
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## API Token for Open WebUI
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Create an API token in new-api's token management. Use this token as `OPENWEBUI_API_KEY` in `.env`.
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## Channels to Create
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Configure each channel via **Channels > Add Channel** in the web UI.
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### 1. DeepInfra (Priority 1)
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| Field | Value |
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| Name | DeepInfra |
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| Type | OpenAI |
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| Base URL | `https://api.deepinfra.com/v1/openai` |
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| Key | `$DEEPINFRA_API_KEY` |
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| Priority | 1 |
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| Models | See model mapping below |
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### 2. SiliconFlow (Priority 2)
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| Field | Value |
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|---|---|
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| Name | SiliconFlow |
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| Type | OpenAI |
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| Base URL | `https://api.siliconflow.com/v1` |
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| Key | `$SILICONFLOW_API_KEY` |
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| Priority | 2 |
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| Models | See model mapping below |
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### 3. OpenRouter (Priority 3)
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| Field | Value |
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| Name | OpenRouter |
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| Type | OpenAI |
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| Base URL | `https://openrouter.ai/api/v1` |
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| Key | `$OPENROUTER_API_KEY` |
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| Priority | 3 |
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| Models | See model mapping below |
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### 4. Groq (Priority 1)
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| Field | Value |
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| Name | Groq |
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| Type | OpenAI |
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| Base URL | `https://api.groq.com/openai/v1` |
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| Key | `$GROQ_API_KEY` |
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| Priority | 1 |
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| Models | `llama-3.3-70b` |
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### 5. Cerebras (Priority 1)
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| Field | Value |
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|---|---|
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| Name | Cerebras |
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| Type | OpenAI |
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| Base URL | `https://api.cerebras.ai/v1` |
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| Key | `$CEREBRAS_API_KEY` |
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| Priority | 1 |
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| Models | `llama-3.3-70b-cerebras` |
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## Model Mapping per Channel
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new-api uses model aliasing: the "model name" is what clients see, the "actual model" is what's sent to the provider.
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### DeepInfra Models
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| Client Model Name | Actual Provider Model |
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|---|---|
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| `deepseek-v3.2` | `deepseek-ai/DeepSeek-V3.2` |
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| `deepseek-r1` | `deepseek-ai/DeepSeek-R1` |
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| `gpt-oss` | `openai/gpt-oss-120b` |
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| `gpt-oss-20b` | `openai/gpt-oss-20b` |
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| `nemotron-super` | `nvidia/Llama-3.3-Nemotron-Super-49B-v1.5` |
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| `nemotron-nano` | `nvidia/NVIDIA-Nemotron-Nano-9B-v2` |
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| `devstral` | `mistralai/Devstral-Small-2505` |
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| `glm-4.6` | `zai-org/GLM-4.6` |
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| `glm-4.7` | `zai-org/GLM-4.7` |
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| `glm-5` | `zai-org/GLM-5` |
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| `kimi-k2` | `moonshotai/Kimi-K2-Instruct-0905` |
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| `kimi-k2.5` | `moonshotai/Kimi-K2.5` |
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| `deepseek-v3-free` | `deepseek-ai/DeepSeek-V3` |
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### SiliconFlow Models
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| Client Model Name | Actual Provider Model |
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|---|---|
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| `deepseek-v3.2` | `deepseek-ai/DeepSeek-V3.2` |
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|
||||||
| `glm-4.7` | `THUDM/GLM-4-32B-0414` |
|
|
||||||
| `kimi-k2` | `moonshotai/Kimi-K2-Instruct-0905` |
|
|
||||||
| `qwen3-coder` | `Qwen/Qwen3-Coder-480B-A35B-Instruct` |
|
|
||||||
| `qwen3-coder-30b` | `Qwen/Qwen3-Coder-30B-A3B-Instruct` |
|
|
||||||
|
|
||||||
### OpenRouter Models
|
|
||||||
|
|
||||||
| Client Model Name | Actual Provider Model |
|
|
||||||
|---|---|
|
|
||||||
| `deepseek-v3.2` | `deepseek/deepseek-chat-v3-0324` |
|
|
||||||
| `deepseek-v3-free` | `deepseek/deepseek-chat-v3-0324:free` |
|
|
||||||
| `kimi-k2.5` | `moonshotai/kimi-k2.5` |
|
|
||||||
| `minimax-m2.5` | `minimax/minimax-m2.5` |
|
|
||||||
| `gpt-4.1-mini` | `openai/gpt-4.1-mini` |
|
|
||||||
| `gpt-4.1` | `openai/gpt-4.1` |
|
|
||||||
| `gemini-3-flash-preview` | `google/gemini-3-flash-preview` |
|
|
||||||
| `gemini-2.5-pro` | `google/gemini-2.5-pro-preview` |
|
|
||||||
| `claude-sonnet` | `anthropic/claude-sonnet-4` |
|
|
||||||
| `trinity-large-preview` | `arcee-ai/trinity-large-preview` |
|
|
||||||
|
|
||||||
### Groq Models
|
|
||||||
|
|
||||||
| Client Model Name | Actual Provider Model |
|
|
||||||
|---|---|
|
|
||||||
| `llama-3.3-70b` | `llama-3.3-70b-versatile` |
|
|
||||||
|
|
||||||
### Cerebras Models
|
|
||||||
|
|
||||||
| Client Model Name | Actual Provider Model |
|
|
||||||
|---|---|
|
|
||||||
| `llama-3.3-70b-cerebras` | `llama-3.3-70b` |
|
|
||||||
|
|
||||||
## Fallback Behavior
|
|
||||||
|
|
||||||
new-api handles fallbacks via priority levels:
|
|
||||||
- When a model exists on multiple channels, the highest priority (lowest number) channel is tried first
|
|
||||||
- If it fails, it automatically falls back to the next priority level
|
|
||||||
|
|
||||||
For example, `deepseek-v3.2` exists on:
|
|
||||||
1. DeepInfra (priority 1) — tried first
|
|
||||||
2. SiliconFlow (priority 2) — fallback
|
|
||||||
3. OpenRouter (priority 3) — last resort
|
|
||||||
|
|
||||||
## Grafana Setup
|
|
||||||
|
|
||||||
After first start, access Grafana at `http://<server>:3001`:
|
|
||||||
1. Login with `admin` / `$GRAFANA_ADMIN_PASSWORD`
|
|
||||||
2. Add data source: **Prometheus** with URL `http://victoriametrics:8428`
|
|
||||||
3. Import dashboards:
|
|
||||||
- Node Exporter Full: dashboard ID `1860`
|
|
||||||
- Redis: dashboard ID `763`
|
|
||||||
|
|
@ -1,218 +0,0 @@
|
||||||
#!/usr/bin/env bash
|
|
||||||
# Configures new-api channels and API token via the admin API.
|
|
||||||
# Run once after first boot: ./new-api/init-channels.sh
|
|
||||||
#
|
|
||||||
# Requires these env vars (or .env file in project root):
|
|
||||||
# NEW_API_PASSWORD - admin password
|
|
||||||
# DEEPINFRA_API_KEY
|
|
||||||
# SILICONFLOW_API_KEY
|
|
||||||
# OPENROUTER_API_KEY
|
|
||||||
# GROQ_API_KEY
|
|
||||||
# CEREBRAS_API_KEY
|
|
||||||
#
|
|
||||||
# Optional:
|
|
||||||
# NEW_API_USERNAME - admin username (default: root)
|
|
||||||
# NEW_API_BASE - API base URL (default: http://localhost:4000)
|
|
||||||
|
|
||||||
set -euo pipefail
|
|
||||||
|
|
||||||
SCRIPT_DIR="$(cd "$(dirname "$0")" && pwd)"
|
|
||||||
ENV_FILE="${SCRIPT_DIR}/../.env"
|
|
||||||
|
|
||||||
# Load .env if present
|
|
||||||
if [[ -f "$ENV_FILE" ]]; then
|
|
||||||
set -a
|
|
||||||
# shellcheck disable=SC1090
|
|
||||||
source "$ENV_FILE"
|
|
||||||
set +a
|
|
||||||
fi
|
|
||||||
|
|
||||||
API_BASE="${NEW_API_BASE:-http://localhost:4000}"
|
|
||||||
USERNAME="${NEW_API_USERNAME:-root}"
|
|
||||||
PASSWORD="${NEW_API_PASSWORD:?Set NEW_API_PASSWORD to the admin password}"
|
|
||||||
COOKIE_JAR=$(mktemp)
|
|
||||||
USER_ID=""
|
|
||||||
trap 'rm -f "$COOKIE_JAR"' EXIT
|
|
||||||
|
|
||||||
# ── Login and get user ID ───────────────────────────────
|
|
||||||
login() {
|
|
||||||
echo "Logging in as ${USERNAME}..."
|
|
||||||
local resp
|
|
||||||
resp=$(curl -s -c "$COOKIE_JAR" "${API_BASE}/api/user/login" \
|
|
||||||
-H "Content-Type: application/json" \
|
|
||||||
-d "$(python3 -c "
|
|
||||||
import json, sys
|
|
||||||
print(json.dumps({'username': sys.argv[1], 'password': sys.argv[2]}))
|
|
||||||
" "$USERNAME" "$PASSWORD")")
|
|
||||||
|
|
||||||
local success
|
|
||||||
success=$(echo "$resp" | python3 -c "import sys,json; print(json.load(sys.stdin).get('success', False))")
|
|
||||||
if [[ "$success" != "True" ]]; then
|
|
||||||
echo "ERROR: Login failed: ${resp}"
|
|
||||||
exit 1
|
|
||||||
fi
|
|
||||||
|
|
||||||
USER_ID=$(echo "$resp" | python3 -c "import sys,json; print(json.load(sys.stdin)['data']['id'])")
|
|
||||||
echo " Logged in (user ID: ${USER_ID})."
|
|
||||||
}
|
|
||||||
|
|
||||||
# ── API call helper (cookie + New-Api-User header) ─────
|
|
||||||
api_call() {
|
|
||||||
local endpoint="$1"
|
|
||||||
shift
|
|
||||||
curl -s -b "$COOKIE_JAR" \
|
|
||||||
-H "New-Api-User: ${USER_ID}" \
|
|
||||||
-H "Content-Type: application/json" \
|
|
||||||
"${API_BASE}${endpoint}" "$@"
|
|
||||||
}
|
|
||||||
|
|
||||||
# ── Create channel ──────────────────────────────────────
|
|
||||||
create_channel() {
|
|
||||||
local name="$1" type="$2" key="$3" base_url="$4" priority="$5" models="$6" model_mapping="$7"
|
|
||||||
|
|
||||||
echo "Creating channel: ${name} (priority ${priority})..."
|
|
||||||
|
|
||||||
local payload
|
|
||||||
payload=$(python3 -c "
|
|
||||||
import json, sys
|
|
||||||
print(json.dumps({
|
|
||||||
'type': int(sys.argv[1]),
|
|
||||||
'name': sys.argv[2],
|
|
||||||
'key': sys.argv[3],
|
|
||||||
'base_url': sys.argv[4],
|
|
||||||
'models': sys.argv[5],
|
|
||||||
'model_mapping': sys.argv[6],
|
|
||||||
'priority': int(sys.argv[7]),
|
|
||||||
'status': 1,
|
|
||||||
'group': 'default',
|
|
||||||
'weight': 1,
|
|
||||||
'auto_ban': 1
|
|
||||||
}))
|
|
||||||
" "$type" "$name" "$key" "$base_url" "$models" "$model_mapping" "$priority")
|
|
||||||
|
|
||||||
local resp success
|
|
||||||
resp=$(api_call "/api/channel/" -d "$payload")
|
|
||||||
|
|
||||||
success=$(echo "$resp" | python3 -c "import sys,json; print(json.load(sys.stdin).get('success', False))")
|
|
||||||
if [[ "$success" == "True" ]]; then
|
|
||||||
echo " OK"
|
|
||||||
else
|
|
||||||
echo " FAILED: ${resp}" | head -c 500
|
|
||||||
echo
|
|
||||||
fi
|
|
||||||
}
|
|
||||||
|
|
||||||
# ── Wait for new-api ────────────────────────────────────
|
|
||||||
echo "Waiting for new-api at ${API_BASE}..."
|
|
||||||
for i in $(seq 1 30); do
|
|
||||||
if curl -sf "${API_BASE}/" > /dev/null 2>&1; then
|
|
||||||
echo "new-api is ready."
|
|
||||||
break
|
|
||||||
fi
|
|
||||||
if [[ "$i" == "30" ]]; then
|
|
||||||
echo "ERROR: new-api did not become ready in time."
|
|
||||||
exit 1
|
|
||||||
fi
|
|
||||||
sleep 2
|
|
||||||
done
|
|
||||||
|
|
||||||
# ── Login ───────────────────────────────────────────────
|
|
||||||
login
|
|
||||||
|
|
||||||
# ── Generate system access token for future use ─────────
|
|
||||||
echo ""
|
|
||||||
echo "Generating system access token..."
|
|
||||||
ACCESS_TOKEN_RESP=$(api_call "/api/user/token")
|
|
||||||
ACCESS_TOKEN=$(echo "$ACCESS_TOKEN_RESP" | python3 -c "
|
|
||||||
import sys, json
|
|
||||||
data = json.load(sys.stdin)
|
|
||||||
if data.get('success'):
|
|
||||||
print(data.get('data', ''))
|
|
||||||
else:
|
|
||||||
print('')
|
|
||||||
" 2>/dev/null || echo "")
|
|
||||||
|
|
||||||
if [[ -n "$ACCESS_TOKEN" ]]; then
|
|
||||||
echo " Access token: ${ACCESS_TOKEN}"
|
|
||||||
echo " Save as NEW_API_ACCESS_TOKEN in .env for future API use."
|
|
||||||
echo " Usage: -H 'Authorization: Bearer ${ACCESS_TOKEN}' -H 'New-Api-User: ${USER_ID}'"
|
|
||||||
else
|
|
||||||
echo " Could not generate access token (non-critical, using session)."
|
|
||||||
fi
|
|
||||||
|
|
||||||
# ── Channels ────────────────────────────────────────────
|
|
||||||
|
|
||||||
create_channel "DeepInfra" 1 \
|
|
||||||
"${DEEPINFRA_API_KEY:?}" \
|
|
||||||
"https://api.deepinfra.com/v1/openai" \
|
|
||||||
1 \
|
|
||||||
"deepseek-v3.2,deepseek-r1,gpt-oss,gpt-oss-20b,nemotron-super,nemotron-nano,devstral,glm-4.6,glm-4.7,glm-5,kimi-k2,kimi-k2.5" \
|
|
||||||
'{"deepseek-v3.2":"deepseek-ai/DeepSeek-V3.2","deepseek-r1":"deepseek-ai/DeepSeek-R1","gpt-oss":"openai/gpt-oss-120b","gpt-oss-20b":"openai/gpt-oss-20b","nemotron-super":"nvidia/Llama-3.3-Nemotron-Super-49B-v1.5","nemotron-nano":"nvidia/NVIDIA-Nemotron-Nano-9B-v2","devstral":"mistralai/Devstral-Small-2505","glm-4.6":"zai-org/GLM-4.6","glm-4.7":"zai-org/GLM-4.7","glm-5":"zai-org/GLM-5","kimi-k2":"moonshotai/Kimi-K2-Instruct-0905","kimi-k2.5":"moonshotai/Kimi-K2.5"}'
|
|
||||||
|
|
||||||
create_channel "SiliconFlow" 1 \
|
|
||||||
"${SILICONFLOW_API_KEY:?}" \
|
|
||||||
"https://api.siliconflow.com/v1" \
|
|
||||||
2 \
|
|
||||||
"deepseek-v3.2,glm-4.7,kimi-k2,qwen3-coder,qwen3-coder-30b" \
|
|
||||||
'{"deepseek-v3.2":"deepseek-ai/DeepSeek-V3.2","glm-4.7":"THUDM/GLM-4-32B-0414","kimi-k2":"moonshotai/Kimi-K2-Instruct-0905","qwen3-coder":"Qwen/Qwen3-Coder-480B-A35B-Instruct","qwen3-coder-30b":"Qwen/Qwen3-Coder-30B-A3B-Instruct"}'
|
|
||||||
|
|
||||||
create_channel "OpenRouter" 1 \
|
|
||||||
"${OPENROUTER_API_KEY:?}" \
|
|
||||||
"https://openrouter.ai/api/v1" \
|
|
||||||
3 \
|
|
||||||
"deepseek-v3.2,deepseek-v3-free,kimi-k2.5,minimax-m2.5,gpt-4.1-mini,gpt-4.1,gemini-3-flash-preview,gemini-2.5-pro,claude-sonnet,trinity-large-preview" \
|
|
||||||
'{"deepseek-v3.2":"deepseek/deepseek-chat-v3-0324","deepseek-v3-free":"deepseek/deepseek-chat-v3-0324:free","kimi-k2.5":"moonshotai/kimi-k2.5","minimax-m2.5":"minimax/minimax-m2.5","gpt-4.1-mini":"openai/gpt-4.1-mini","gpt-4.1":"openai/gpt-4.1","gemini-3-flash-preview":"google/gemini-3-flash-preview","gemini-2.5-pro":"google/gemini-2.5-pro-preview","claude-sonnet":"anthropic/claude-sonnet-4","trinity-large-preview":"arcee-ai/trinity-large-preview"}'
|
|
||||||
|
|
||||||
create_channel "Groq" 1 \
|
|
||||||
"${GROQ_API_KEY:?}" \
|
|
||||||
"https://api.groq.com/openai/v1" \
|
|
||||||
1 \
|
|
||||||
"llama-3.3-70b" \
|
|
||||||
'{"llama-3.3-70b":"llama-3.3-70b-versatile"}'
|
|
||||||
|
|
||||||
create_channel "Cerebras" 1 \
|
|
||||||
"${CEREBRAS_API_KEY:?}" \
|
|
||||||
"https://api.cerebras.ai/v1" \
|
|
||||||
1 \
|
|
||||||
"llama-3.3-70b-cerebras" \
|
|
||||||
'{"llama-3.3-70b-cerebras":"llama-3.3-70b"}'
|
|
||||||
|
|
||||||
# ── Create API token for Open WebUI ─────────────────────
|
|
||||||
echo ""
|
|
||||||
echo "Creating API token for Open WebUI..."
|
|
||||||
TOKEN_RESP=$(api_call "/api/token/" -d "$(python3 -c "
|
|
||||||
import json
|
|
||||||
print(json.dumps({
|
|
||||||
'name': 'open-webui',
|
|
||||||
'remain_quota': 0,
|
|
||||||
'unlimited_quota': True
|
|
||||||
}))
|
|
||||||
")")
|
|
||||||
|
|
||||||
TOKEN_KEY=$(echo "$TOKEN_RESP" | python3 -c "
|
|
||||||
import sys, json
|
|
||||||
data = json.load(sys.stdin)
|
|
||||||
if data.get('success'):
|
|
||||||
print(data['data']['key'])
|
|
||||||
else:
|
|
||||||
print('FAILED: ' + data.get('message', 'unknown error'))
|
|
||||||
" 2>/dev/null || echo "FAILED: could not parse response")
|
|
||||||
|
|
||||||
echo ""
|
|
||||||
echo "══════════════════════════════════════"
|
|
||||||
echo "Setup complete!"
|
|
||||||
echo ""
|
|
||||||
if [[ "$TOKEN_KEY" != FAILED* ]]; then
|
|
||||||
echo "Open WebUI API key: ${TOKEN_KEY}"
|
|
||||||
echo "Set OPENWEBUI_API_KEY=${TOKEN_KEY} in your .env"
|
|
||||||
echo ""
|
|
||||||
echo "Test:"
|
|
||||||
echo " curl ${API_BASE}/v1/chat/completions \\"
|
|
||||||
echo " -H 'Authorization: Bearer ${TOKEN_KEY}' \\"
|
|
||||||
echo " -H 'Content-Type: application/json' \\"
|
|
||||||
echo " -d '{\"model\":\"deepseek-v3.2\",\"messages\":[{\"role\":\"user\",\"content\":\"hi\"}]}'"
|
|
||||||
else
|
|
||||||
echo "Token creation: ${TOKEN_KEY}"
|
|
||||||
echo "Create a token manually in the new-api UI."
|
|
||||||
fi
|
|
||||||
echo "══════════════════════════════════════"
|
|
||||||
Loading…
Reference in a new issue