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feat: Add llms to support the latest Open Source SOTA models (#497)

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* fix: update README and configuration guide for new model support and reasoning capabilities

* fix: format code for consistency in agent and node files

* fix: update test cases for environment variable handling in llm configuration

* fix: refactor message chunk conversion functions for improved clarity and maintainability

* refactor: remove enable_thinking parameter from LLM configuration functions

* chore: update agent-LLM mapping for consistency

* chore: update LLM configuration handling for improved clarity

* test: add unit tests for Dashscope message chunk conversion and LLM configuration

* test: add unit tests for message chunk conversion in Dashscope

* test: add unit tests for message chunk conversion in Dashscope

* chore: remove unused imports from test_dashscope.py

---------

Co-authored-by: Willem Jiang <willem.jiang@gmail.com>
This commit is contained in:
CHANGXUBO
2025-08-13 22:29:22 +08:00
committed by GitHub
parent ea17e82514
commit d65b8f8fcc
6 changed files with 684 additions and 9 deletions
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19
src/llms/llm.py
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@@ -13,6 +13,7 @@ from typing import get_args
from src.config import load_yaml_config
from src.config.agents import LLMType
from src.llms.providers.dashscope import ChatDashscope
# Cache for LLM instances
_llm_cache: dict[LLMType, BaseChatModel] = {}
@@ -29,6 +30,7 @@ def _get_llm_type_config_keys() -> dict[str, str]:
"reasoning": "REASONING_MODEL",
"basic": "BASIC_MODEL",
"vision": "VISION_MODEL",
"code": "CODE_MODEL",
}
@@ -72,9 +74,6 @@ def _create_llm_use_conf(llm_type: LLMType, conf: Dict[str, Any]) -> BaseChatMod
if "max_retries" not in merged_conf:
merged_conf["max_retries"] = 3
if llm_type == "reasoning":
merged_conf["api_base"] = merged_conf.pop("base_url", None)
# Handle SSL verification settings
verify_ssl = merged_conf.pop("verify_ssl", True)
@@ -87,15 +86,23 @@ def _create_llm_use_conf(llm_type: LLMType, conf: Dict[str, Any]) -> BaseChatMod
if "azure_endpoint" in merged_conf or os.getenv("AZURE_OPENAI_ENDPOINT"):
return AzureChatOpenAI(**merged_conf)
# Check if base_url is dashscope endpoint
if "base_url" in merged_conf and "dashscope." in merged_conf["base_url"]:
if llm_type == "reasoning":
merged_conf["extra_body"] = {"enable_thinking": True}
else:
merged_conf["extra_body"] = {"enable_thinking": False}
return ChatDashscope(**merged_conf)
if llm_type == "reasoning":
merged_conf["api_base"] = merged_conf.pop("base_url", None)
return ChatDeepSeek(**merged_conf)
else:
return ChatOpenAI(**merged_conf)
def get_llm_by_type(
llm_type: LLMType,
) -> BaseChatModel:
def get_llm_by_type(llm_type: LLMType) -> BaseChatModel:
"""
Get LLM instance by type. Returns cached instance if available.
"""