feat: add variable to control instructor mode

cognee/infrastructure/llm/config.py

@@ -38,6 +38,7 @@ class LLMConfig(BaseSettings):
     """
 
     structured_output_framework: str = "instructor"
+    llm_instructor_mode: Optional[str] = None
     llm_provider: str = "openai"
     llm_model: str = "openai/gpt-5-mini"
     llm_endpoint: str = ""
@@ -181,6 +182,7 @@ class LLMConfig(BaseSettings):
               instance.
         """
         return {
+            "llm_instructor_mode": self.llm_instructor_mode,
             "provider": self.llm_provider,
             "model": self.llm_model,
             "endpoint": self.llm_endpoint,

cognee/infrastructure/llm/structured_output_framework/litellm_instructor/llm/anthropic/adapter.py

@@ -28,13 +28,19 @@ class AnthropicAdapter(LLMInterface):
 
     name = "Anthropic"
     model: str
+    default_instructor_mode = "anthropic_tools"
 
     def __init__(self, max_completion_tokens: int, model: str = None):
         import anthropic
 
+        config_instructor_mode = get_llm_config().llm_instructor_mode
+        instructor_mode = (
+            config_instructor_mode if config_instructor_mode else self.default_instructor_mode
+        )
+
         self.aclient = instructor.patch(
             create=anthropic.AsyncAnthropic(api_key=get_llm_config().llm_api_key).messages.create,
-            mode=instructor.Mode.ANTHROPIC_TOOLS,
+            mode=instructor.Mode(instructor_mode),
         )
 
         self.model = model

cognee/infrastructure/llm/structured_output_framework/litellm_instructor/llm/gemini/adapter.py

@@ -41,6 +41,7 @@ class GeminiAdapter(LLMInterface):
     name: str
     model: str
     api_key: str
+    default_instructor_mode = "json_mode"
 
     def __init__(
         self,
@@ -63,7 +64,16 @@ class GeminiAdapter(LLMInterface):
         self.fallback_api_key = fallback_api_key
         self.fallback_endpoint = fallback_endpoint
 
-        self.aclient = instructor.from_litellm(litellm.acompletion, mode=instructor.Mode.JSON)
+        from cognee.infrastructure.llm.config import get_llm_config
+
+        config_instructor_mode = get_llm_config().llm_instructor_mode
+        instructor_mode = (
+            config_instructor_mode if config_instructor_mode else self.default_instructor_mode
+        )
+
+        self.aclient = instructor.from_litellm(
+            litellm.acompletion, mode=instructor.Mode(instructor_mode)
+        )
 
     @retry(
         stop=stop_after_delay(128),

cognee/infrastructure/llm/structured_output_framework/litellm_instructor/llm/generic_llm_api/adapter.py

@@ -41,6 +41,7 @@ class GenericAPIAdapter(LLMInterface):
     name: str
     model: str
     api_key: str
+    default_instructor_mode = "json_mode"
 
     def __init__(
         self,
@@ -63,7 +64,16 @@ class GenericAPIAdapter(LLMInterface):
         self.fallback_api_key = fallback_api_key
         self.fallback_endpoint = fallback_endpoint
 
-        self.aclient = instructor.from_litellm(litellm.acompletion, mode=instructor.Mode.JSON)
+        from cognee.infrastructure.llm.config import get_llm_config
+
+        config_instructor_mode = get_llm_config().llm_instructor_mode
+        instructor_mode = (
+            config_instructor_mode if config_instructor_mode else self.default_instructor_mode
+        )
+
+        self.aclient = instructor.from_litellm(
+            litellm.acompletion, mode=instructor.Mode(instructor_mode)
+        )
 
     @retry(
         stop=stop_after_delay(128),

cognee/infrastructure/llm/structured_output_framework/litellm_instructor/llm/mistral/adapter.py

@@ -37,6 +37,7 @@ class MistralAdapter(LLMInterface):
     model: str
     api_key: str
     max_completion_tokens: int
+    default_instructor_mode = "mistral_tools"
 
     def __init__(self, api_key: str, model: str, max_completion_tokens: int, endpoint: str = None):
         from mistralai import Mistral
@@ -44,9 +45,14 @@ class MistralAdapter(LLMInterface):
         self.model = model
         self.max_completion_tokens = max_completion_tokens
 
+        config_instructor_mode = get_llm_config().llm_instructor_mode
+        instructor_mode = (
+            config_instructor_mode if config_instructor_mode else self.default_instructor_mode
+        )
+
         self.aclient = instructor.from_litellm(
             litellm.acompletion,
-            mode=instructor.Mode.MISTRAL_TOOLS,
+            mode=instructor.Mode(instructor_mode),
             api_key=get_llm_config().llm_api_key,
         )
 

cognee/infrastructure/llm/structured_output_framework/litellm_instructor/llm/ollama/adapter.py

@@ -42,6 +42,8 @@ class OllamaAPIAdapter(LLMInterface):
     - aclient
     """
 
+    default_instructor_mode = "json_mode"
+
     def __init__(
         self, endpoint: str, api_key: str, model: str, name: str, max_completion_tokens: int
     ):
@@ -51,8 +53,16 @@ class OllamaAPIAdapter(LLMInterface):
         self.endpoint = endpoint
         self.max_completion_tokens = max_completion_tokens
 
+        from cognee.infrastructure.llm.config import get_llm_config
+
+        config_instructor_mode = get_llm_config().llm_instructor_mode
+        instructor_mode = (
+            config_instructor_mode if config_instructor_mode else self.default_instructor_mode
+        )
+
         self.aclient = instructor.from_openai(
-            OpenAI(base_url=self.endpoint, api_key=self.api_key), mode=instructor.Mode.JSON
+            OpenAI(base_url=self.endpoint, api_key=self.api_key),
+            mode=instructor.Mode(instructor_mode),
         )
 
     @retry(

cognee/infrastructure/llm/structured_output_framework/litellm_instructor/llm/openai/adapter.py

@@ -56,6 +56,7 @@ class OpenAIAdapter(LLMInterface):
     model: str
     api_key: str
     api_version: str
+    default_instructor_mode = "json_schema_mode"
 
     MAX_RETRIES = 5
 
@@ -74,14 +75,20 @@ class OpenAIAdapter(LLMInterface):
         fallback_api_key: str = None,
         fallback_endpoint: str = None,
     ):
+        from cognee.infrastructure.llm.config import get_llm_config
+
+        config_instructor_mode = get_llm_config().llm_instructor_mode
+        instructor_mode = (
+            config_instructor_mode if config_instructor_mode else self.default_instructor_mode
+        )
         # TODO: With gpt5 series models OpenAI expects JSON_SCHEMA as a mode for structured outputs.
         #       Make sure all new gpt models will work with this mode as well.
         if "gpt-5" in model:
             self.aclient = instructor.from_litellm(
-                litellm.acompletion, mode=instructor.Mode.JSON_SCHEMA
+                litellm.acompletion, mode=instructor.Mode(instructor_mode)
             )
             self.client = instructor.from_litellm(
-                litellm.completion, mode=instructor.Mode.JSON_SCHEMA
+                litellm.completion, mode=instructor.Mode(instructor_mode)
             )
         else:
             self.aclient = instructor.from_litellm(litellm.acompletion)