Tavily integration

ra_aid/agent_utils.py

@@ -161,7 +161,7 @@ def run_research_agent(
     return run_agent_with_retry(agent, prompt, run_config)
 
 def run_web_research_agent(
-    base_task_or_query: str,
+    query: str,
     model,
     *,
     expert_enabled: bool = False,
@@ -174,7 +174,7 @@ def run_web_research_agent(
     """Run a web research agent with the given configuration.
     
     Args:
-        base_task_or_query: The main task or query for web research
+        query: The mainquery for web research
         model: The LLM model to use
         expert_enabled: Whether expert mode is enabled
         hil: Whether human-in-the-loop mode is enabled
@@ -218,7 +218,7 @@ def run_web_research_agent(
     
     # Build prompt
     prompt = WEB_RESEARCH_PROMPT.format(
-        base_task=base_task_or_query,
+        web_research_query=query,
         expert_section=expert_section,
         human_section=human_section,
         key_facts=key_facts,

ra_aid/tool_configs.py

@@ -117,7 +117,8 @@ def get_web_research_tools(expert_enabled: bool = True) -> list:
         list: List of tools configured for web research
     """
     tools = [
-        web_search_tavily
+        web_search_tavily,
+        emit_research_notes
     ]
 
     if expert_enabled:

ra_aid/tools/agent.py

@@ -111,10 +111,12 @@ def request_web_research(query: str) -> ResearchResult:
     
     success = True
     reason = None
+    web_research_notes = []
     
     try:
         # Run web research agent
         from ..agent_utils import run_web_research_agent
+        original_research_notes = _global_memory.get('research_notes', [])
         result = run_web_research_agent(
             query,
             model,
@@ -123,6 +125,7 @@ def request_web_research(query: str) -> ResearchResult:
             console_message=query,
             config=config
         )
+        web_research_notes = _global_memory.get('research_notes', [])
     except AgentInterrupt:
         print()
         response = ask_human.invoke({"question": "Why did you interrupt me?"})
@@ -135,6 +138,7 @@ def request_web_research(query: str) -> ResearchResult:
         success = False
         reason = f"error: {str(e)}"
     finally:
+        _global_memory['research_notes'] = original_research_notes
         # Get completion message if available
         completion_message = _global_memory.get('completion_message', 'Task was completed successfully.' if success else None)
         
@@ -151,9 +155,7 @@ def request_web_research(query: str) -> ResearchResult:
     return {
         "work_log": work_log,
         "completion_message": completion_message,
-        "key_facts": get_memory_value("key_facts"),
-        "related_files": get_related_files(),
-        "research_notes": get_memory_value("research_notes"),
+        "web_research_notes": web_research_notes,
         "key_snippets": get_memory_value("key_snippets"),
         "success": success,
         "reason": reason

ra_aid/tools/read_file.py

@@ -5,6 +5,7 @@ from typing import Dict, Optional, Tuple
 from langchain_core.tools import tool
 from rich.console import Console
 from rich.panel import Panel
+from rich.markdown import Markdown
 from ra_aid.text.processing import truncate_output
 
 console = Console()

ra_aid/tools/web_search_tavily.py

@@ -2,6 +2,11 @@ import os
 from typing import Dict
 from tavily import TavilyClient
 from langchain_core.tools import tool
+from rich.console import Console
+from rich.panel import Panel
+from rich.markdown import Markdown
+
+console = Console()
 
 @tool
 def web_search_tavily(query: str) -> Dict:
@@ -15,5 +20,6 @@ def web_search_tavily(query: str) -> Dict:
         Dict containing search results from Tavily
     """
     client = TavilyClient(api_key=os.environ["TAVILY_API_KEY"])
+    console.print(Panel(Markdown(query), title="🔍 Searching Tavily", border_style="bright_blue"))
     search_result = client.search(query=query)
     return search_result