mirror of https://github.com/whit3rabbit/anyllm-proxy.git synced 2026-09-23 00:00:51 +00:00

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whit3rabbitandClaude Sonnet 4.6 545bdbbbd3 feat: add bedrock native passthrough, generic passthrough, provider docs, and managed backend fixes

Adds bedrock_native.rs (Converse/InvokeModel with SigV4) and
generic_passthrough.rs catch-all for Translate mode. Adds comprehensive
provider reference docs (docs/providers/, docs/ENDPOINTS.md). Fixes
managed backend admin UI (BackendForm, ManagedBackendsSection) and
admin route/model handler issues. Adds automated model pricing update
workflow (scripts/update_pricing.py, .github/workflows/update-pricing.yml).

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

2026-04-08 16:36:16 -05:00

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Predibase

Fine-tuned model serving platform specializing in efficient deployment of LoRA adapters on top of open-source base models.

LiteLLM prefix: predibase/
Status: Stub — routes through OpenAI-compatible client
Docs: https://docs.predibase.com

Authentication

Variable	Required	Description
`PREDIBASE_API_KEY`	Yes	API key from app.predibase.com

Quick Start

Single-Backend (env vars)

BACKEND=predibase PREDIBASE_API_KEY=your-key cargo run -p anyllm_proxy
# Docker:
docker run -e BACKEND=predibase -e PREDIBASE_API_KEY=your-key -e PROXY_OPEN_RELAY=true -p 3000:3000 followthewhit3rabbit/anyllm-proxy

LiteLLM YAML Config

model_list:
  - model_name: llama-3-8b
    litellm_params:
      model: predibase/llama-3-1-8b-instruct
      api_key: "env:PREDIBASE_API_KEY"

Usage Examples

Anthropic Messages API

curl http://localhost:3000/v1/messages \
  -H "x-api-key: $PROXY_API_KEYS" \
  -H "Content-Type: application/json" \
  -d '{"model": "llama-3-1-8b-instruct", "max_tokens": 1024, "messages": [{"role": "user", "content": "Hello"}]}'

OpenAI Chat Completions API

curl http://localhost:3000/v1/chat/completions \
  -H "Authorization: Bearer $PROXY_API_KEYS" \
  -H "Content-Type: application/json" \
  -d '{"model": "llama-3-1-8b-instruct", "messages": [{"role": "user", "content": "Hello"}]}'

Capabilities

Feature	Supported
Chat Completions	✓
Streaming	✓
Tool Use	—
Embeddings	—
Vision	—
Batch	—

Notable Models

Model ID	Context	Notes
`llama-3-1-8b-instruct`	128k	Llama 3.1 8B base
`mistral-7b-instruct-v0-3`	32k	Mistral 7B v0.3 base

Notes

Predibase's primary use case is serving custom LoRA adapters trained on the platform. To target a fine-tuned adapter, append the adapter name to the model ID using the format base-model/adapter-name as documented at https://docs.predibase.com/user-guide/inference/fine-tuned-models. The models listed above are base models available without a custom adapter. Tool use is not supported.

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