feat: add Avian as an LLM provider

core/quivr_core/llm/llm_endpoint.py

@@ -291,6 +291,16 @@ def from_config(cls, config: LLMEndpointConfig = LLMEndpointConfig()):
                     max_tokens=config.max_output_tokens,
                     temperature=config.temperature,
                 )
+            elif config.supplier == DefaultModelSuppliers.AVIAN:
+                _llm = ChatOpenAI(
+                    model=config.model,
+                    api_key=SecretStr(config.llm_api_key)
+                    if config.llm_api_key
+                    else None,
+                    base_url=config.llm_base_url or "https://api.avian.io/v1",
+                    max_completion_tokens=config.max_output_tokens,
+                    temperature=config.temperature,
+                )
 
             else:
                 _llm = ChatOpenAI(

core/quivr_core/rag/entities/config.py

@@ -75,6 +75,7 @@ class DefaultModelSuppliers(str, Enum):
     MISTRAL = "mistral"
     GROQ = "groq"
     GEMINI = "gemini"
+    AVIAN = "avian"
 
 
 class LLMConfig(QuivrBaseConfig):
@@ -275,6 +276,24 @@ class LLMModelConfig:
                 tokenizer_hub="Quivr/gemini-tokenizer",
             ),
         },
+        DefaultModelSuppliers.AVIAN: {
+            "deepseek/deepseek-v3.2": LLMConfig(
+                max_context_tokens=164000,
+                max_output_tokens=65000,
+            ),
+            "moonshotai/kimi-k2.5": LLMConfig(
+                max_context_tokens=131000,
+                max_output_tokens=8192,
+            ),
+            "z-ai/glm-5": LLMConfig(
+                max_context_tokens=131000,
+                max_output_tokens=16384,
+            ),
+            "minimax/minimax-m2.5": LLMConfig(
+                max_context_tokens=1000000,
+                max_output_tokens=1000000,
+            ),
+        },
     }
 
     @classmethod

core/tests/test_llm_endpoint.py

@@ -3,7 +3,7 @@
 import pytest
 from langchain_core.language_models import FakeListChatModel
 from pydantic import ValidationError
-from quivr_core.rag.entities.config import LLMEndpointConfig
+from quivr_core.rag.entities.config import DefaultModelSuppliers, LLMEndpointConfig
 from quivr_core.llm import LLMEndpoint
 
 
@@ -46,3 +46,21 @@ def test_llm_endpoint_constructor():
     )
 
     assert not llm_endpoint.supports_func_calling()
+
+
+@pytest.mark.base
+def test_llm_endpoint_avian():
+    from langchain_openai import ChatOpenAI
+
+    config = LLMEndpointConfig(
+        supplier=DefaultModelSuppliers.AVIAN,
+        model="deepseek/deepseek-v3.2",
+        llm_api_key="test",
+    )
+    llm = LLMEndpoint.from_config(config)
+
+    assert llm.supports_func_calling()
+    assert isinstance(llm._llm, ChatOpenAI)
+    assert llm._llm.openai_api_base == "https://api.avian.io/v1"
+    assert config.max_output_tokens == 65000
+    assert config.max_context_tokens <= 164000