Update src/app/main_agent.py

src/app/main_agent.py

@@ -1,50 +1,49 @@
- from langchain_core.messages import BaseMessage, AIMessage
- from langchain_core.runnables import RunnableLambda, Runnable
- from langchain_community.llms import Ollama
- from langchain.tools import Tool
- from langgraph.graph import MessageGraph
- import re
-
- llm = Ollama(model="gemma3", temperature=0.0) # llama3.1
-
- def create_agent(accent_tool_obj) -> tuple[Runnable, Runnable]:
-     accent_tool = Tool(
-         name="AccentAnalyzer",
-         func=accent_tool_obj.analyze,
-         description="Analyze a public MP4 video URL and determine the English accent with transcription."
-     )
-
-     def analyze_node(messages: list[BaseMessage]) -> AIMessage:
-         last_input = messages[-1].content
-         match = re.search(r'https?://\S+', last_input)
-         if match:
-             url = match.group()
-             result = accent_tool.func(url)
-         else:
-             result = "No valid video URL found in your message."
-         return AIMessage(content=result)
-
-     graph = MessageGraph()
-     graph.add_node("analyze_accent", RunnableLambda(analyze_node))
-     graph.set_entry_point("analyze_accent")
-     graph.set_finish_point("analyze_accent")
-     analysis_agent = graph.compile()
-
-     # Follow-up agent that uses transcript and responds to questions
-     def follow_up_node(messages: list[BaseMessage]) -> AIMessage:
-         user_question = messages[-1].content
-         transcript = accent_tool_obj.last_transcript or ""
-         prompt = f"""You are given this transcript of a video:
+from langchain_core.messages import BaseMessage, AIMessage
+from langchain_core.runnables import RunnableLambda, Runnable
+from langchain_community.llms import Ollama
+from langchain.tools import Tool
+from langgraph.graph import MessageGraph
+import re
+
+llm = Ollama(model="gemma3", temperature=0.0) # llama3.1
+
+def create_agent(accent_tool_obj) -> tuple[Runnable, Runnable]:
+    accent_tool = Tool(
+        name="AccentAnalyzer",
+        func=accent_tool_obj.analyze,
+        description="Analyze a public MP4 video URL and determine the English accent with transcription."
+    )
+
+    def analyze_node(messages: list[BaseMessage]) -> AIMessage:
+        last_input = messages[-1].content
+        match = re.search(r'https?://\S+', last_input)
+        if match:
+            url = match.group()
+            result = accent_tool.func(url)
+        else:
+            result = "No valid video URL found in your message."
+        return AIMessage(content=result)
+
+    graph = MessageGraph()
+    graph.add_node("analyze_accent", RunnableLambda(analyze_node))
+    graph.set_entry_point("analyze_accent")
+    graph.set_finish_point("analyze_accent")
+    analysis_agent = graph.compile()
+
+    # Follow-up agent that uses transcript and responds to questions
+    def follow_up_node(messages: list[BaseMessage]) -> AIMessage:
+        user_question = messages[-1].content
+        transcript = accent_tool_obj.last_transcript or ""
+        prompt = f"""You are given this transcript of a video:
 
          \"\"\"{transcript}\"\"\"
 
          Now respond to the user's follow-up question: {user_question}
          """
-         response = llm.invoke(prompt)
-         return AIMessage(content=response)
+        response = llm.invoke(prompt)
+        return AIMessage(content=response)
 
-     follow_up_agent = RunnableLambda(follow_up_node)
-
-     return analysis_agent, follow_up_agent
+    follow_up_agent = RunnableLambda(follow_up_node)
 
+    return analysis_agent, follow_up_agent