UN-3276 support for user defined llm in hocon file with class key

neuro_san/internals/run_context/langchain/core/langchain_run_context.py

@@ -23,9 +23,8 @@
 from logging import Logger
 from logging import getLogger
 
-from openai import APIError
-from anthropic import BadRequestError
-from anthropic import AuthenticationError
+import openai
+import anthropic
 
 from pydantic_core import ValidationError
 
@@ -495,7 +494,7 @@ async def ainvoke(self, agent_executor: AgentExecutor, inputs: Dict[str, Any], i
         while return_dict is None and retries > 0:
             try:
                 return_dict: Dict[str, Any] = await agent_executor.ainvoke(inputs, invoke_config)
-            except (APIError, BadRequestError, AuthenticationError, ChatGoogleGenerativeAIError) as api_error:
+            except (openai.APIError, anthropic.APIError, ChatGoogleGenerativeAIError) as api_error:
                 message: str = ApiKeyErrorCheck.check_for_api_key_exception(api_error)
                 if message is not None:
                     raise ValueError(message) from api_error
@@ -509,6 +508,11 @@ async def ainvoke(self, agent_executor: AgentExecutor, inputs: Dict[str, Any], i
                 retries = retries - 1
                 exception = key_error
                 backtrace = traceback.format_exc()
+            except TypeError as type_error:
+                self.logger.warning("retrying from TypeError")
+                retries = retries - 1
+                exception = type_error
+                backtrace = traceback.format_exc()
             except ValueError as value_error:
                 response = str(value_error)
                 find_string = "An output parsing error occurred. " + \

neuro_san/internals/run_context/langchain/llms/default_llm_factory.py

@@ -33,6 +33,8 @@
 from neuro_san.internals.run_context.langchain.llms.langchain_llm_factory import LangChainLlmFactory
 from neuro_san.internals.run_context.langchain.llms.llm_info_restorer import LlmInfoRestorer
 from neuro_san.internals.run_context.langchain.llms.standard_langchain_llm_factory import StandardLangChainLlmFactory
+from neuro_san.internals.run_context.langchain.llms.user_specified_langchain_llm_factory import \
+    UserSpecifiedLangChainLlmFactory
 from neuro_san.internals.run_context.langchain.util.api_key_error_check import ApiKeyErrorCheck
 
 
@@ -75,6 +77,8 @@ def __init__(self, config: Optional[Dict[str, Any]] = None):
         self.llm_factories: List[LangChainLlmFactory] = [
             StandardLangChainLlmFactory()
         ]
+        self.llm_class: str = None
+
         if config:
             self.llm_info_file: str = config.get("agent_llm_info_file")
         else:
@@ -176,6 +180,14 @@ def create_full_llm_config(self, config: Dict[str, Any]) -> Dict[str, Any]:
         :param config: The llm_config from the user
         :return: The fully specified config with defaults filled in.
         """
+
+        self.llm_class = config.get("class")
+        if self.llm_class:
+            # If config has "class", it is a user-specified llm so return config as is,
+            # and replace "StandardLangChainLlmFactory" with "UserSpecifiedLangChainLlmFactory".
+            self.llm_factories[0] = UserSpecifiedLangChainLlmFactory()
+            return config
+
         default_config: Dict[str, Any] = self.llm_infos.get("default_config")
         use_config = self.overlayer.overlay(default_config, config)
 

neuro_san/internals/run_context/langchain/llms/user_specified_langchain_llm_factory.py

@@ -0,0 +1,86 @@
+
+# Copyright (C) 2023-2025 Cognizant Digital Business, Evolutionary AI.
+# All Rights Reserved.
+# Issued under the Academic Public License.
+#
+# You can be released from the terms, and requirements of the Academic Public
+# License by purchasing a commercial license.
+# Purchase of a commercial license is mandatory for any use of the
+# neuro-san SDK Software in commercial settings.
+#
+# END COPYRIGHT
+
+from typing import Any
+from typing import Dict
+from typing import List
+
+from langchain_anthropic.chat_models import ChatAnthropic
+from langchain_google_genai.chat_models import ChatGoogleGenerativeAI
+from langchain_ollama import ChatOllama
+from langchain_nvidia_ai_endpoints import ChatNVIDIA
+from langchain_core.callbacks.base import BaseCallbackHandler
+from langchain_core.language_models.base import BaseLanguageModel
+from langchain_openai.chat_models.azure import AzureChatOpenAI
+from langchain_openai.chat_models.base import ChatOpenAI
+
+from neuro_san.internals.run_context.langchain.llms.langchain_llm_factory import LangChainLlmFactory
+
+
+class UserSpecifiedLangChainLlmFactory(LangChainLlmFactory):
+    """
+    A factory for constructing LLMs based on user-specified configurations provided under the "llm_config"
+    section of the agent network HOCON file.
+
+    The specific LLM class to instantiate is determined by the "class" field in "llm_config", and all
+    other keys in the config are passed as arguments to that class's constructor.
+    """
+
+    def create_base_chat_model(self, config: Dict[str, Any],
+                               callbacks: List[BaseCallbackHandler] = None) -> BaseLanguageModel:
+        """
+        Create a BaseLanguageModel from the user-specified llm config.
+        :param config: The user-specified llm config
+        :param callbacks: A list of BaseCallbackHandlers to add to the chat model.
+        :return: A BaseLanguageModel (can be Chat or LLM)
+                Can raise a ValueError if the config's class or model_name value is
+                unknown to this method.
+        """
+        # Construct the LLM
+        llm: BaseLanguageModel = None
+        chat_class: str = config.get("class")
+        if chat_class is not None:
+            chat_class = chat_class.lower()
+
+        # Take "class" out of config and add "callback".
+        config.pop("class")
+        config["callbacks"] = callbacks
+
+        # Unpack config in the user-specified class
+        if chat_class == "openai":
+            llm = ChatOpenAI(**config)
+        elif chat_class == "azure-openai":
+            llm = AzureChatOpenAI(**config)
+        elif chat_class == "anthropic":
+            llm = ChatAnthropic(**config)
+        elif chat_class == "ollama":
+            llm = ChatOllama(**config)
+        elif chat_class == "nvidia":
+            llm = ChatNVIDIA(**config)
+        elif chat_class == "gemini":
+            llm = ChatGoogleGenerativeAI(**config)
+        else:
+            valid_class_map = {
+                "openai": "ChatOpenAI",
+                "azure-openai": "AzureChatOpenAI",
+                "anthropic": "ChatAnthropic",
+                "ollama": "ChatOllama",
+                "nvidia": "ChatNVIDIA",
+                "gemini": "ChatGoogleGenerativeAI",
+            }
+            available = "\n".join(f"  - '{key}': {val}" for key, val in valid_class_map.items())
+            raise ValueError(
+                f"Unrecognized model class '{chat_class}'.\n"
+                f"Valid class values and their corresponding implementations are:\n{available}"
+            )
+
+        return llm

neuro_san/internals/run_context/langchain/util/api_key_error_check.py

@@ -22,12 +22,10 @@
 
     # Azure OpenAI requires several parameters; all can be set via environment variables
     # except "deployment_name", which must be provided explicitly.
-    "AZURE_OPENAI_API_KEY": ["Error code: 401", "invalid subscription key", "wrong API endpoint", "Connection error"],
-    "AZURE_OPENAI_ENDPOINT": ["validation error", "base_url", "azure_endpoint", "AZURE_OPENAI_ENDPOINT",
-                              "Connection error"],
-    "OPENAI_API_VERSION": ["validation error", "api_version", "OPENAI_API_VERSION", "Error code: 404",
-                           "Resource not found"],
-    "deployment_name": ["Error code: 404", "Resource not found", "API deployment for this resource does not exist"],
+    "AZURE_OPENAI_API_KEY": ["invalid subscription key", "wrong API endpoint"],
+    "AZURE_OPENAI_ENDPOINT": ["base_url", "azure_endpoint", "AZURE_OPENAI_ENDPOINT"],
+    "OPENAI_API_VERSION": ["api_version", "OPENAI_API_VERSION"],
+    "deployment_name": ["API deployment for this resource does not exist"],
 }
 
 

neuro_san/registries/google_serper.hocon

@@ -35,10 +35,10 @@
         {
             "name": "searcher",
             "instructions": "Use your tool to respond to the inquiry.",
-             "function": {
+            "function": {
                 # The description acts as an initial prompt.
                 "description": "Assist user with answer from internet."
-             }
+            }
             "tools": ["search_tool"]
         },
         {