fmt

src/langchain_lab/core/audio.py

@@ -6,8 +6,5 @@
 def openai_speech_to_text(audio_file_path):
     client = OpenAI(base_url=os.environ["OPENAI_API_BASE"], api_key=os.environ["OPENAI_API_KEY"])
     audio_file = open(audio_file_path, "rb")
-    transcription = client.audio.transcriptions.create(
-        model="whisper-1",
-        file=audio_file
-    )
+    transcription = client.audio.transcriptions.create(model="whisper-1", file=audio_file)
     print(transcription.text)

src/langchain_lab/core/embedding.py

@@ -21,7 +21,6 @@
 from langchain_community.embeddings import HuggingFaceEmbeddings, OpenAIEmbeddings
 from langchain_community.vectorstores import FAISS
 
-
 from langchain_lab import logger
 
 

src/langchain_lab/core/llm.py

@@ -21,7 +21,6 @@
 from langchain.chat_models.base import BaseChatModel
 from langchain.schema import LLMResult
 from langchain_openai import ChatOpenAI
-
 from openai import OpenAI
 
 from langchain_lab import logger

src/langchain_lab/scenarios/agents/__init__.py

@@ -1,4 +1,7 @@
 from langchain_lab.core.agents import agent_register
+from langchain_lab.scenarios.agents.langgraph_agent.langgraph_demo_agent import (
+    LangGraphDemoAgent,
+)
 from langchain_lab.scenarios.agents.translation_agent.translation_english2chinese import (
     TranslationEnglish2Chinese,
 )
@@ -8,3 +11,4 @@
 
 agent_register(WikipediaAgent())
 agent_register(TranslationEnglish2Chinese())
+agent_register(LangGraphDemoAgent())

src/langchain_lab/scenarios/agents/langgraph_agent/langgraph_demo_agent.py

@@ -0,0 +1,10 @@
+from typing import Any, Dict
+
+from langchain_lab.core.agents import LabAgent
+
+
+class LangGraphDemoAgent(LabAgent):
+    description = "这是一个演示 LangGraph 的 Agent"
+
+    def agent_invoke(self, inputs: Dict[str, Any]) -> Dict[str, Any]:
+        return {"input": inputs, "output": "hello world"}