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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>
1.8 KiB
1.8 KiB
Gradient AI
Fine-tuning and inference platform for open-weight models.
LiteLLM prefix: gradient_ai/
Status: Stub — routes through OpenAI-compatible client
Docs: https://docs.gradient.ai
Authentication
| Variable | Required | Description |
|---|---|---|
GRADIENT_ACCESS_TOKEN |
Yes | Access token from gradient.ai |
Quick Start
Single-Backend (env vars)
BACKEND=gradient_ai GRADIENT_ACCESS_TOKEN=your-token cargo run -p anyllm_proxy
# Docker:
docker run -e BACKEND=gradient_ai -e GRADIENT_ACCESS_TOKEN=your-token -e PROXY_OPEN_RELAY=true -p 3000:3000 followthewhit3rabbit/anyllm-proxy
LiteLLM YAML Config
model_list:
- model_name: llama3-gradient
litellm_params:
model: gradient_ai/llama3-8b-instruct
api_key: "env:GRADIENT_ACCESS_TOKEN"
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": "llama3-8b-instruct", "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": "llama3-8b-instruct", "messages": [{"role": "user", "content": "Hello"}]}'
Capabilities
| Feature | Supported |
|---|---|
| Chat Completions | ✓ |
| Streaming | ✓ |
| Tool Use | — |
| Embeddings | ✓ |
| Vision | — |
| Batch | — |
Notes
Gradient AI supports both hosted inference and model fine-tuning. Obtain an access token at gradient.ai. Tool use is not supported. Available models include fine-tuned variants alongside base open-weight models; check the Gradient console for your deployed model IDs.