Fix issue 2216: Pass custom endpoint to LiteLLM for Ollama provider

Co-Authored-By: Joe Moura <joao@crewai.com>

src/crewai/agent.py

@@ -111,15 +111,20 @@ class Agent(BaseAgent):
         default=None,
         description="Embedder configuration for the agent.",
     )
+    endpoint: Optional[str] = Field(
+        default=None,
+        description="Custom endpoint URL for the LLM API.",
+    )
 
     @model_validator(mode="after")
     def post_init_setup(self):
         self._set_knowledge()
         self.agent_ops_agent_name = self.role
 
-        self.llm = create_llm(self.llm)
+        # Pass endpoint to create_llm if it exists
+        self.llm = create_llm(self.llm, endpoint=self.endpoint)
         if self.function_calling_llm and not isinstance(self.function_calling_llm, LLM):
-            self.function_calling_llm = create_llm(self.function_calling_llm)
+            self.function_calling_llm = create_llm(self.function_calling_llm, endpoint=self.endpoint)
 
         if not self.agent_executor:
             self._setup_agent_executor()

src/crewai/utilities/llm_utils.py

@@ -7,6 +7,7 @@ from crewai.llm import LLM
 
 def create_llm(
     llm_value: Union[str, LLM, Any, None] = None,
+    endpoint: Optional[str] = None,
 ) -> Optional[LLM]:
     """
     Creates or returns an LLM instance based on the given llm_value.
@@ -17,6 +18,8 @@ def create_llm(
             - LLM: Already instantiated LLM, returned as-is.
             - Any: Attempt to extract known attributes like model_name, temperature, etc.
             - None: Use environment-based or fallback default model.
+        endpoint (str | None):
+            - Optional endpoint URL for the LLM API.
 
     Returns:
         An LLM instance if successful, or None if something fails.
@@ -29,7 +32,11 @@ def create_llm(
     # 2) If llm_value is a string (model name)
     if isinstance(llm_value, str):
         try:
-            created_llm = LLM(model=llm_value)
+            # If endpoint is provided and model is Ollama, use it as api_base
+            if endpoint and "ollama" in llm_value.lower():
+                created_llm = LLM(model=llm_value, api_base=endpoint)
+            else:
+                created_llm = LLM(model=llm_value)
             return created_llm
         except Exception as e:
             print(f"Failed to instantiate LLM with model='{llm_value}': {e}")
@@ -37,7 +44,7 @@ def create_llm(
 
     # 3) If llm_value is None, parse environment variables or use default
     if llm_value is None:
-        return _llm_via_environment_or_fallback()
+        return _llm_via_environment_or_fallback(endpoint=endpoint)
 
     # 4) Otherwise, attempt to extract relevant attributes from an unknown object
     try:
@@ -55,6 +62,10 @@ def create_llm(
         base_url: Optional[str] = getattr(llm_value, "base_url", None)
         api_base: Optional[str] = getattr(llm_value, "api_base", None)
 
+        # If endpoint is provided and model is Ollama, use it as api_base
+        if endpoint and "ollama" in str(model).lower():
+            api_base = endpoint
+
         created_llm = LLM(
             model=model,
             temperature=temperature,
@@ -71,9 +82,13 @@ def create_llm(
         return None
 
 
-def _llm_via_environment_or_fallback() -> Optional[LLM]:
+def _llm_via_environment_or_fallback(endpoint: Optional[str] = None) -> Optional[LLM]:
     """
     Helper function: if llm_value is None, we load environment variables or fallback default model.
+    
+    Args:
+        endpoint (str | None):
+            - Optional endpoint URL for the LLM API.
     """
     model_name = (
         os.environ.get("OPENAI_MODEL_NAME")
@@ -172,6 +187,10 @@ def _llm_via_environment_or_fallback() -> Optional[LLM]:
     # Remove None values
     llm_params = {k: v for k, v in llm_params.items() if v is not None}
 
+    # If endpoint is provided and model is Ollama, use it as api_base
+    if endpoint and "ollama" in model_name.lower():
+        llm_params["api_base"] = endpoint
+
     # Try creating the LLM
     try:
         new_llm = LLM(**llm_params)