[fel] Improve the code of ecological plug-ins and introduce third-party packages

framework/fel/python/plugins/fel_langchain_tools/langchain_tools.py

@@ -5,21 +5,10 @@
 # ======================================================================================================================
 import json
 from urllib.parse import quote_plus
-import psycopg2
-from langchain.agents import AgentExecutor
 
-from langchain_community.utilities.sql_database import SQLDatabase
-from langchain_community.agent_toolkits import create_sql_agent
-from langchain_community.tools.sql_database.tool import (
-    InfoSQLDatabaseTool,
-    ListSQLDatabaseTool,
-    QuerySQLCheckerTool,
-    QuerySQLDataBaseTool,
-)
-from langchain_core.tools import BaseTool
-from langchain_openai import ChatOpenAI, OpenAI
-from langchain_community.utilities.requests import TextRequestsWrapper
+from langchain.agents import AgentExecutor
 from langchain_community.agent_toolkits import JsonToolkit, create_json_agent
+from langchain_community.agent_toolkits import create_sql_agent
 from langchain_community.tools.json.tool import JsonSpec
 from langchain_community.tools.requests.tool import (
     RequestsDeleteTool,
@@ -28,6 +17,17 @@
     RequestsPostTool,
     RequestsPutTool,
 )
+from langchain_community.tools.sql_database.tool import (
+    InfoSQLDatabaseTool,
+    ListSQLDatabaseTool,
+    QuerySQLCheckerTool,
+    QuerySQLDataBaseTool,
+)
+from langchain_community.utilities.requests import TextRequestsWrapper
+from langchain_community.utilities.sql_database import SQLDatabase
+from langchain_core.tools import BaseTool
+from langchain_openai import ChatOpenAI
+
 from .langchain_registers import register_function_tools, register_api_tools
 
 

framework/fel/python/plugins/fel_llama_index_tools/llama_rag_basic_toolkit.py

@@ -3,30 +3,27 @@
 # This file is a part of the ModelEngine Project.
 # Licensed under the MIT License. See License.txt in the project root for license information.
 # ======================================================================================================================
-import functools
 import os
 import traceback
 from enum import Enum, unique
-from inspect import signature
 from typing import List, Callable, Any, Tuple
 
 from fitframework import fit_logger
 from fitframework.core.repo.fitable_register import register_fitable
-from llama_index.core import PromptTemplate
 from llama_index.core.base.base_selector import SingleSelection
 from llama_index.core.postprocessor import SimilarityPostprocessor, SentenceEmbeddingOptimizer, LLMRerank, \
     LongContextReorder, FixedRecencyPostprocessor
 from llama_index.core.postprocessor.types import BaseNodePostprocessor
-from llama_index.core.prompts import PromptType
+from llama_index.core.prompts import PromptType, PromptTemplate
 from llama_index.core.prompts.default_prompts import DEFAULT_CHOICE_SELECT_PROMPT_TMPL
 from llama_index.core.selectors import LLMSingleSelector, LLMMultiSelector
 from llama_index.core.selectors.prompts import DEFAULT_SINGLE_SELECT_PROMPT_TMPL, DEFAULT_MULTI_SELECT_PROMPT_TMPL
 from llama_index.embeddings.openai import OpenAIEmbedding
-from llama_index.legacy.llms import OpenAILike
+from llama_index.llms.openai import OpenAI
 
 from .callable_registers import register_callable_tool
-from .types.document import Document
 from .node_utils import document_to_query_node, query_node_to_document
+from .types.document import Document
 
 os.environ["no_proxy"] = "*"
 
@@ -80,7 +77,7 @@ def llm_rerank(nodes: List[Document], query_str: str, **kwargs) -> List[Document
     choice_batch_size = int(kwargs.get("choice_batch_size") or 10)
     top_n = int(kwargs.get("top_n") or 10)
 
-    llm = OpenAILike(model=model_name, api_base=api_base, api_key=api_key, max_tokens=4096)
+    llm = OpenAI(model=model_name, api_base=api_base, api_key=api_key, max_tokens=4096)
     choice_select_prompt = PromptTemplate(prompt, prompt_type=PromptType.CHOICE_SELECT)
     llm_rerank_obj = LLMRerank(llm=llm, choice_select_prompt=choice_select_prompt, choice_batch_size=choice_batch_size,
                                top_n=top_n)
@@ -110,7 +107,7 @@ def llm_choice_selector(choice: List[str], query_str: str, **kwargs) -> List[Sin
     if mode.lower() not in [m.value for m in SelectorMode]:
         raise ValueError(f"Invalid mode {mode}.")
 
-    llm = OpenAILike(model=model_name, api_base=api_base, api_key=api_key, max_tokens=4096)
+    llm = OpenAI(model=model_name, api_base=api_base, api_key=api_key, max_tokens=4096)
     if mode.lower() == SelectorMode.SINGLE.value:
         selector_prompt = prompt or DEFAULT_SINGLE_SELECT_PROMPT_TMPL
         selector = LLMSingleSelector.from_defaults(llm=llm, prompt_template_str=selector_prompt)

framework/fel/python/plugins/fel_llama_index_tools/node_utils.py

@@ -5,7 +5,7 @@
 # ======================================================================================================================
 from llama_index.core.multi_modal_llms.generic_utils import encode_image
 from llama_index.core.schema import ImageNode, TextNode, NodeWithScore
-from llama_index.core import Document as LDocument
+from llama_index.core.schema import Document as LDocument
 
 from .types.document import Document
 from .types.media import Media

framework/fel/python/plugins/fel_llamaindex_network_tools/llamaindex_network_tool.py

@@ -5,7 +5,7 @@
 # ======================================================================================================================
 
 import time
-from typing import List, Any, Optional, Callable, Union, Tuple
+from typing import List, Any, Callable, Tuple
 
 from .callable_registers import register_callable_tool
 

framework/fel/python/requirements.txt

@@ -1,4 +1,7 @@
 pydantic==2.6.3
 psutil==6.1.1
 httpx==0.28.1
-pandas==2.1.3
+pandas==2.1.3
+llama-index==0.12.46
+langchain-core==0.3.68
+langchain_community==0.3.27