Update tools.py

tools.py

@@ -22,6 +22,7 @@ from langchain_community.tools.wikipedia.tool import WikipediaQueryRun
 from langchain_google_community import SpeechToTextLoader
 from langchain_community.tools import YouTubeSearchTool
 from youtube_transcript_api import YouTubeTranscriptApi
+from langchain_community.document_loaders.blob_loaders.youtube_audio import YoutubeAudioLoader
 from langchain_community.tools.file_management.read import ReadFileTool
 from langchain.chains.summarize import load_summarize_chain
 from langchain.prompts import PromptTemplate
@@ -122,7 +123,7 @@ def search_and_extract(query: str) -> list[dict]:
 
 
 @tool
-def aggregate_information(results: list[str], query: str) -> str:
+def aggregate_information(query: str, results: list[str]) -> str:
     """
     Processes a list of unstructured text chunks (e.g., search results) and produces a concise, query-specific summary.
 
@@ -144,9 +145,9 @@ def aggregate_information(results: list[str], query: str) -> str:
     # Convert to LangChain Document objects
     docs = [Document(page_content=chunk) for chunk in results]
 
-    llm = ChatOpenAI(model="gpt-4o-mini", temperature=0.2)
+    llm = ChatOpenAI(model="gpt-4o-mini", temperature=0)
 
-    # Map Prompt — Summarize each document in light of the query
+    # 🔍 Map Prompt — Summarize each document in light of the query
     map_prompt = PromptTemplate.from_template(
         "You are analyzing a search result in the context of the question: '{query}'.\n\n"
         "Search result:\n{text}\n\n"
@@ -158,13 +159,12 @@ def aggregate_information(results: list[str], query: str) -> str:
         "Relevant Summary:"
     )
 
-    # Combine Prompt — Aggregate the summaries to one final answer
+    # 🧠 Combine Prompt — Aggregate the summaries to one final answer
     combine_prompt = PromptTemplate.from_template(
-        "You are aggregating information to answer the following question: '{query}'.\n\n"
+        "You are aggregating information to provide context to answer the following question: '{query}'.\n\n"
         "Here are the summaries from filtered search results:\n{text}\n\n"
-        "Using the most relevant points, write a clear, concise, and complete answer to the original query.\n"
-        "If there's conflicting information, mention it briefly. Otherwise, focus on consensus.\n\n"
-        "Final Answer:"
+        "Use the provided summaries to construct a context that directly supports the query without answering it.\n"
+        "Context:"
     )
 
     chain = load_summarize_chain(