agent_action: Prompt-lab work item started
agent_action: Pinned repository checkout verified
agent_action: I'll research the repository structure first to understand what we're working with.
agent_action: Read /home/user/worktrees/attempt-9a635b55-4bb4-44ce-9dcd-67638deae344-cap-0
command: find /home/user/worktrees/attempt-9a635b55-4bb4-44ce-9dcd-67638deae344-cap-0 -maxdepth 2 -type f \( -name "README*" -o -name "package.json" -o -name "requirements.txt" -o -name "pyproject.toml" -o -name "Dockerfile*" -o -name ".env*" \) | head -20
agent_action: Read README.md
agent_action: Glob **/package.json
agent_action: Glob **/pyproject.toml
agent_action: Glob **/requirements.txt
command: find /home/user/worktrees/attempt-9a635b55-4bb4-44ce-9dcd-67638deae344-cap-0 -type f \( -name "*.json" -o -name "*.toml" -o -name "requirements*.txt" \) | head -20
command: ls -la /home/user/worktrees/attempt-9a635b55-4bb4-44ce-9dcd-67638deae344-cap-0/
agent_action: Read requirements.client.txt
agent_action: Read requirements.server.txt
command: ls -la /home/user/worktrees/attempt-9a635b55-4bb4-44ce-9dcd-67638deae344-cap-0/server/
agent_action: Read server/main.py
agent_action: Read server/config.py
command: ls -la /home/user/worktrees/attempt-9a635b55-4bb4-44ce-9dcd-67638deae344-cap-0/server/modules/
agent_action: Read server/modules/vectorstore.py
agent_action: Read server/modules/llm.py
agent_action: Read server/modules/auth.py
command: ls -la /home/user/worktrees/attempt-9a635b55-4bb4-44ce-9dcd-67638deae344-cap-0/client/
agent_action: Read Dockerfile.server
agent_action: Read Dockerfile.client
agent_action: Read client/main.py
agent_action: Read client/api_client.py
command: ls -la /home/user/worktrees/attempt-9a635b55-4bb4-44ce-9dcd-67638deae344-cap-0/server/tests/
agent_action: Read server/tests/test_hybrid_search.py
command: ls -la /home/user/worktrees/attempt-9a635b55-4bb4-44ce-9dcd-67638deae344-cap-0/server/db/
agent_action: Read compose.yaml
agent_action: Let me verify the key integration file and load web research tools.
agent_action: Read server/modules/llm.py
agent_action: Now let me consult the documentation of the leading managed web-search providers fo...
search: Tavily search API LangChain integration RAG agents documentation 2026
search: Exa API vs Tavily vs Brave search API for LLM RAG grounding pricing 2026
agent_action: Let me consult the actual provider documentation pages directly.
url: https://docs.tavily.com/documentation/api-reference/endpoint/search
url: https://docs.exa.ai/reference/getting-started
agent_action: I have enough on Tavily; let me confirm Exa's specifics and check Brave's LLM Conte...
url: https://exa.ai/docs/reference/getting-started
url: https://api-dashboard.search.brave.com/app/documentation/llm-context/get-started
agent_action: ## Recommendation: Tavily **The provider I'd choose: Tavily Search API.** ### Why i...
result: Selected unknown