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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>
1.9 KiB
1.9 KiB
Galadriel
On-chain verifiable AI inference, providing cryptographic proof of model execution.
LiteLLM prefix: galadriel/
Status: Stub — routes through OpenAI-compatible client
Docs: https://docs.galadriel.com
Authentication
| Variable | Required | Description |
|---|---|---|
GALADRIEL_API_KEY |
Yes | API key from the Galadriel developer console |
Quick Start
Single-Backend (env vars)
BACKEND=galadriel GALADRIEL_API_KEY=your-key cargo run -p anyllm_proxy
# Docker:
docker run -e BACKEND=galadriel -e GALADRIEL_API_KEY=your-key -e PROXY_OPEN_RELAY=true -p 3000:3000 followthewhit3rabbit/anyllm-proxy
LiteLLM YAML Config
model_list:
- model_name: llama3.1-70b
litellm_params:
model: galadriel/llama3.1-70b
api_key: "env:GALADRIEL_API_KEY"
Usage Examples
Anthropic Messages API
curl http://localhost:3000/v1/messages \
-H "Content-Type: application/json" \
-H "x-api-key: $PROXY_API_KEYS" \
-d '{"model": "llama3.1-70b", "max_tokens": 1024, "messages": [{"role": "user", "content": "Hello"}]}'
OpenAI Chat Completions API
curl http://localhost:3000/v1/chat/completions \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $PROXY_API_KEYS" \
-d '{"model": "llama3.1-70b", "messages": [{"role": "user", "content": "Hello"}]}'
Capabilities
| Feature | Supported |
|---|---|
| Chat Completions | ✓ |
| Streaming | ✓ |
| Tool Use | — |
| Embeddings | — |
| Vision | — |
| Batch | — |
Notable Models
| Model ID | Notes |
|---|---|
llama3.1-70b |
Meta Llama 3.1 70B, verified inference |
llama3.1-8b |
Meta Llama 3.1 8B, verified inference |
Notes
Galadriel produces verifiable proofs of AI inference, useful for applications that require auditability of model outputs. Tool use and embeddings are not supported.