mirror of https://github.com/whit3rabbit/anyllm-proxy.git synced 2026-09-22 16:00:51 +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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llamafile

Single-file executable that bundles a model and a local inference server.

LiteLLM prefix: llamafile/ Status: Stub — routes through OpenAI-compatible client Docs: https://github.com/Mozilla-Ocho/llamafile

Authentication

Variable	Required	Description
(none)	—	No authentication required

Quick Start

Single-Backend (env vars)

BACKEND=llamafile PROXY_OPEN_RELAY=true cargo run -p anyllm_proxy
# or Docker:
docker run -e BACKEND=llamafile -e PROXY_OPEN_RELAY=true -p 3000:3000 followthewhit3rabbit/anyllm-proxy

LiteLLM YAML Config

model_list:
  - model_name: local-model
    litellm_params:
      model: llamafile/local-model
      api_base: "http://localhost:8080"

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": "local-model", "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": "local-model", "messages": [{"role": "user", "content": "Hello"}]}'

Capabilities

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

Notes

Download the .llamafile for the model you want, make it executable, and run it:

wget https://huggingface.co/Mozilla/Meta-Llama-3.1-8B-Instruct-llamafile/resolve/main/Meta-Llama-3.1-8B-Instruct.Q6_K.llamafile
chmod +x Meta-Llama-3.1-8B-Instruct.Q6_K.llamafile
./Meta-Llama-3.1-8B-Instruct.Q6_K.llamafile --server --port 8080

The server starts on port 8080 by default and exposes an OpenAI-compatible /v1/chat/completions endpoint. The model name used in requests is ignored by llamafile; any non-empty string works.

Tool use and embeddings are not supported by the llamafile server implementation.

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