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feat(provider): add Eden AI as an OpenAI-compatible provider
Adds Eden AI (https://www.edenai.co/) as a JSON-configured provider in litellm/llms/openai_like/providers.json, the matching LlmProviders enum entry, the .env.example documentation block, and unit + live tests under tests/test_litellm/llms/openai_like/. Eden AI is an aggregator exposing 100+ underlying models from OpenAI, Anthropic, Google, Mistral and others through a single OpenAI-shape chat-completions endpoint. It is a clean drop-in: standard request body, standard `choices[0].message` response, OpenAI-shape `usage`, standard SSE streaming, and standard `tool_calls`. No Python adapter is needed. Files: - litellm/llms/openai_like/providers.json: register `edenai` (base URL https://api.edenai.run/v3, env var EDENAI_API_KEY, optional EDENAI_API_BASE override, max_completion_tokens -> max_tokens param mapping) - litellm/types/utils.py: LlmProviders.EDENAI = "edenai" - litellm/constants.py: edenai added to LITELLM_CHAT_PROVIDERS, openai_compatible_providers, and the base URL added to openai_compatible_endpoints (mirroring Helicone PR #17663) - provider_endpoints_support.json: edenai entry under "providers" so the check_provider_folders_documented.py CI gate sees the new openai_like provider as documented; chat_completions and messages are true (the openai_like loader's default surface plus LiteLLM's internal Anthropic-format -> OpenAI translation); responses, embeddings, image_generations, audio_transcriptions, audio_speech, moderations, batches, rerank are false (Eden AI's API supports them but LiteLLM-side handlers under litellm/llms/edenai/ ship in follow-up PRs and will flip those flags as they land) - README.md: row in the Supported Providers table; chat / messages ticked, matching what is wired through the openai_like loader today - .env.example: document EDENAI_API_KEY and EDENAI_API_BASE next to the existing provider blocks - tests/test_litellm/llms/openai_like/test_edenai.py: mocked tests for enum membership, JSON config shape, get_llm_provider routing, EDENAI_API_BASE override, Router config, mocked completion; plus a live integration test guarded by `pytest.skipif(not os.environ.get('EDENAI_API_KEY'))` that calls api.edenai.run/v3 end-to-end and validates the response shape Endpoints wired through this PR: /chat/completions only (via the openai_like loader's default surface). /messages is also routed via LiteLLM's internal Anthropic-format translation; /responses is NOT (would require explicit `supported_endpoints` opt-in in the JSON config). Provider-specific handlers under litellm/llms/edenai/ for /responses, /embeddings, /image/generations, /audio/* and /moderations ship in follow-up PRs. Companion docs PR: BerriAI/litellm-docs adds the docs/providers/edenai.md page that the README and provider_endpoints_support.json link to. Per CONTRIBUTING.md: - scope is isolated (one provider, no drive-by changes) - adds 1 mocked test in tests/test_litellm/ (hard requirement) plus a live integration test guarded by EDENAI_API_KEY presence - passes make lint and make test-unit - CLA: https://cla-assistant.io/BerriAI/litellm Pattern matches Helicone (#17663) and AIHubMix (#24294) — closest JSON-configured aggregator analogs.
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@ -24,6 +24,9 @@ INFISICAL_TOKEN = ""
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NOVITA_API_KEY = ""
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# INFINITY
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INFINITY_API_KEY = ""
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# Eden AI
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EDENAI_API_KEY = ""
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EDENAI_API_BASE = "https://api.edenai.run/v3"
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# Development Configs
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LITELLM_MASTER_KEY = "sk-1234"
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@ -298,6 +298,7 @@ curl -X POST 'http://0.0.0.0:4000/v1/chat/completions' \
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| [Deepgram (`deepgram`)](https://docs.litellm.ai/docs/providers/deepgram) | ✅ | ✅ | ✅ | | | ✅ | | | | |
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| [DeepInfra (`deepinfra`)](https://docs.litellm.ai/docs/providers/deepinfra) | ✅ | ✅ | ✅ | | | | | | | |
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| [Deepseek (`deepseek`)](https://docs.litellm.ai/docs/providers/deepseek) | ✅ | ✅ | ✅ | | | | | | | |
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| [Eden AI (`edenai`)](https://docs.litellm.ai/docs/providers/edenai) | ✅ | ✅ | | | | | | | | |
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| [ElevenLabs (`elevenlabs`)](https://docs.litellm.ai/docs/providers/elevenlabs) | ✅ | ✅ | ✅ | | | ✅ | ✅ | | | |
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| [Empower (`empower`)](https://docs.litellm.ai/docs/providers/empower) | ✅ | ✅ | ✅ | | | | | | | |
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| [Fal AI (`fal_ai`)](https://docs.litellm.ai/docs/providers/fal_ai) | ✅ | ✅ | ✅ | | ✅ | | | | | |
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@ -552,6 +552,7 @@ LITELLM_CHAT_PROVIDERS = [
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"huggingface",
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"together_ai",
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"datarobot",
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"edenai",
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"helicone",
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"openrouter",
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"cometapi",
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@ -780,6 +781,7 @@ openai_compatible_endpoints: List = [
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"https://api.lambda.ai/v1",
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"https://api.hyperbolic.xyz/v1",
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"https://ai-gateway.helicone.ai/",
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"https://api.edenai.run/v3",
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"https://ai-gateway.vercel.sh/v1",
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"https://api.inference.wandb.ai/v1",
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"https://api.clarifai.com/v2/ext/openai/v1",
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@ -819,6 +821,7 @@ openai_compatible_providers: List = [
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"novita",
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"meta_llama",
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"publicai", # PublicAI - JSON-configured provider
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"edenai", # Eden AI - JSON-configured meta-gateway provider
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"synthetic", # Synthetic - JSON-configured provider
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"apertis", # Apertis - JSON-configured provider
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"nano-gpt", # Nano-GPT - JSON-configured provider
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@ -114,5 +114,13 @@
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"param_mappings": {
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"max_completion_tokens": "max_tokens"
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}
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},
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"edenai": {
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"base_url": "https://api.edenai.run/v3",
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"api_key_env": "EDENAI_API_KEY",
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"api_base_env": "EDENAI_API_BASE",
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"param_mappings": {
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"max_completion_tokens": "max_tokens"
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}
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}
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}
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@ -3333,6 +3333,7 @@ class LlmProviders(str, Enum):
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LITELLM_AGENT = "litellm_agent"
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CURSOR = "cursor"
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BEDROCK_MANTLE = "bedrock_mantle"
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EDENAI = "edenai"
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# Create a set of all provider values for quick lookup
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@ -831,6 +831,22 @@
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"search": true
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}
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},
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"edenai": {
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"display_name": "Eden AI (`edenai`)",
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"url": "https://docs.litellm.ai/docs/providers/edenai",
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"endpoints": {
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"chat_completions": true,
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"messages": true,
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"responses": false,
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"embeddings": false,
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"image_generations": false,
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"audio_transcriptions": false,
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"audio_speech": false,
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"moderations": false,
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"batches": false,
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"rerank": false
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}
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},
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"elevenlabs": {
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"display_name": "ElevenLabs (`elevenlabs`)",
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"url": "https://docs.litellm.ai/docs/providers/elevenlabs",
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174
tests/test_litellm/llms/openai_like/test_edenai.py
Normal file
174
tests/test_litellm/llms/openai_like/test_edenai.py
Normal file
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@ -0,0 +1,174 @@
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"""
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Tests for Eden AI provider configuration and integration.
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Eden AI (https://www.edenai.co/) is an OpenAI-compatible aggregator that
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exposes 100+ underlying models from OpenAI, Anthropic, Google, Mistral and
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others through a single chat-completions endpoint.
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"""
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import os
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import pytest
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import litellm
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class TestEdenAIProviderConfig:
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"""Test Eden AI provider configuration"""
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def test_edenai_in_provider_list(self):
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"""Test that edenai is in the provider list"""
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from litellm import LlmProviders
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assert hasattr(LlmProviders, "EDENAI")
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assert LlmProviders.EDENAI.value == "edenai"
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assert "edenai" in litellm.provider_list
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def test_edenai_json_config_exists(self):
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"""Test that edenai is configured in providers.json"""
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from litellm.llms.openai_like.json_loader import JSONProviderRegistry
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assert JSONProviderRegistry.exists("edenai")
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edenai = JSONProviderRegistry.get("edenai")
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assert edenai is not None
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assert edenai.base_url == "https://api.edenai.run/v3"
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assert edenai.api_key_env == "EDENAI_API_KEY"
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assert edenai.api_base_env == "EDENAI_API_BASE"
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assert edenai.param_mappings.get("max_completion_tokens") == "max_tokens"
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def test_edenai_provider_resolution(self):
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"""Test that provider resolution finds edenai for prefixed model ids"""
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from litellm.litellm_core_utils.get_llm_provider_logic import get_llm_provider
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model, provider, api_key, api_base = get_llm_provider(
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model="edenai/openai/gpt-4o-mini",
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custom_llm_provider=None,
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api_base=None,
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api_key=None,
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)
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# Eden AI's model ids are themselves prefixed (e.g. openai/gpt-4o-mini),
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# so the model returned is everything after the leading "edenai/".
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assert model == "openai/gpt-4o-mini"
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assert provider == "edenai"
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assert api_base == "https://api.edenai.run/v3"
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def test_edenai_api_base_env_override(self, monkeypatch):
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"""Test that EDENAI_API_BASE overrides the default base URL"""
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from litellm.litellm_core_utils.get_llm_provider_logic import get_llm_provider
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monkeypatch.setenv("EDENAI_API_BASE", "https://custom-edenai.example.com/v3")
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_, provider, _, api_base = get_llm_provider(
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model="edenai/openai/gpt-4o-mini",
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custom_llm_provider=None,
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api_base=None,
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api_key=None,
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)
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assert provider == "edenai"
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assert api_base == "https://custom-edenai.example.com/v3"
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def test_edenai_router_config(self):
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"""Test that edenai can be used in Router configuration"""
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from litellm import Router
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router = Router(
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model_list=[
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{
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"model_name": "edenai-gpt-4o-mini",
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"litellm_params": {
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"model": "edenai/openai/gpt-4o-mini",
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"api_key": "test-key",
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},
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}
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]
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)
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assert len(router.model_list) == 1
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assert router.model_list[0]["model_name"] == "edenai-gpt-4o-mini"
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class TestEdenAICompletionMocked:
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"""Mocked completion tests — no real API calls."""
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def test_edenai_completion_mocked(self):
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"""Test that a mocked completion through the edenai/ prefix routes
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correctly and returns the stub content unchanged."""
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response = litellm.completion(
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model="edenai/openai/gpt-4o-mini",
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messages=[{"role": "user", "content": "Say PING and nothing else"}],
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api_key="test-key",
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mock_response="PING",
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)
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assert response is not None
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assert hasattr(response, "choices")
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assert len(response.choices) > 0
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assert response.choices[0].message.content == "PING"
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class TestEdenAILiveIntegration:
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"""Live integration tests against the real Eden AI API.
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Skipped automatically when EDENAI_API_KEY is not set, so CI without the
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secret stays green. When the key is present (local dev, or a dedicated
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integration runner) these validate that each endpoint flagged `true` in
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provider_endpoints_support.json actually routes a request through to
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api.edenai.run/v3 end-to-end. Endpoints flagged `false` (`/responses`,
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`/embeddings`, `/image/generations`, `/audio/*`, `/moderations`,
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`/batches`, `/rerank`) intentionally have no live test here; their
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handlers ship in follow-up PRs and the tests come with them.
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"""
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@pytest.mark.skipif(
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not os.environ.get("EDENAI_API_KEY"), reason="EDENAI_API_KEY not set"
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)
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def test_edenai_live_chat_completions(self):
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"""`/v1/chat/completions` via litellm.completion() — the openai_like
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loader's primary surface."""
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response = litellm.completion(
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model="edenai/openai/gpt-4o-mini",
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messages=[
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{
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"role": "user",
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"content": "Reply with 'PING' and nothing else.",
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}
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],
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max_tokens=8,
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)
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assert response is not None
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assert response.choices[0].message.content
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assert response.usage is not None
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assert response.usage.total_tokens > 0
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@pytest.mark.skipif(
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not os.environ.get("EDENAI_API_KEY"), reason="EDENAI_API_KEY not set"
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)
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@pytest.mark.asyncio
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async def test_edenai_live_anthropic_messages(self):
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"""`/v1/messages` (Anthropic-format) via litellm.anthropic_messages().
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LiteLLM translates the Anthropic-shape request to OpenAI shape
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internally and routes through Eden AI's openai-compatible endpoint;
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the response is translated back to Anthropic shape before being
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returned to the caller."""
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response = await litellm.anthropic_messages(
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model="edenai/anthropic/claude-opus-4-6",
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messages=[
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{
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"role": "user",
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"content": "Reply with 'MSG' and nothing else.",
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}
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],
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max_tokens=8,
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)
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assert response is not None
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# anthropic_messages returns a dict (Anthropic-shape response)
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assert response.get("type") == "message"
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assert response.get("role") == "assistant"
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content = response.get("content", [])
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assert content and content[0].get("type") == "text"
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assert content[0].get("text")
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usage = response.get("usage", {})
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assert usage.get("total_tokens", 0) > 0
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