agent_action: Prompt-lab work item started
agent_action: Pinned repository checkout verified
agent_action: I’ll inspect the repository first to see what kind of agent stack this is and where...
command: /bin/bash -lc "pwd && rg --files -g '"'!*node_modules*'"' -g '"'!*.png'"' -g '"'!*.jpg'"' -g '"'!*.jpeg'"' -g '"'!*.gif'"' | head -200"
command: /bin/bash -lc "pwd && rg --files -g '"'!*node_modules*'"' -g '"'!*.png'"' -g '"'!*.jpg'"' -g '"'!*.jpeg'"' -g '"'!*.gif'"' | head -200"
command: /bin/bash -lc 'git status --short'
command: /bin/bash -lc 'git status --short'
agent_action: `rg` is not installed in this workspace, so I’m falling back to `find` and direct f...
command: /bin/bash -lc "find . -path './node_modules' -prune -o -path './.git' -prune -o -path './dist' -prune -o -path './build' -prune -o -type f | sed 's#"'^./##'"' | head -250"
command: /bin/bash -lc "find . -path './node_modules' -prune -o -path './.git' -prune -o -path './dist' -prune -o -path './build' -prune -o -type f | sed 's#"'^./##'"' | head -250"
command: /bin/bash -lc "find . -maxdepth 2 \\( -name 'package.json' -o -name 'pyproject.toml' -o -name 'requirements*.txt' -o -name 'go.mod' -o -name 'Cargo.toml' -o -name 'README*' -o -name '*.sln' -o -name '*.csproj' \\) -print"
command: /bin/bash -lc "find . -maxdepth 2 \\( -name 'package.json' -o -name 'pyproject.toml' -o -name 'requirements*.txt' -o -name 'go.mod' -o -name 'Cargo.toml' -o -name 'README*' -o -name '*.sln' -o -name '*.csproj' \\) -print"
agent_action: This is a small Python app with local RAG pieces rather than a large agent framewor...
command: /bin/bash -lc "sed -n '1,240p' README.md"
command: /bin/bash -lc "sed -n '1,240p' README.md"
command: /bin/bash -lc "sed -n '1,260p' app.py"
command: /bin/bash -lc "sed -n '1,260p' app.py"
command: /bin/bash -lc "sed -n '1,220p' retrieval/rag_retriever.py"
command: /bin/bash -lc "sed -n '1,220p' retrieval/rag_retriever.py"
command: /bin/bash -lc "sed -n '1,220p' llm/llm.py && sed -n '1,220p' llm/llm_factory.py && sed -n '1,160p' requirements.txt"
command: /bin/bash -lc "sed -n '1,220p' llm/llm.py && sed -n '1,220p' llm/llm_factory.py && sed -n '1,160p' requirements.txt"
command: /bin/bash -lc "sed -n '1,220p' embeddings/embeddings.py"
command: /bin/bash -lc "sed -n '1,220p' embeddings/embeddings.py"
command: /bin/bash -lc "sed -n '1,220p' populate_database.py"
command: /bin/bash -lc "sed -n '1,220p' populate_database.py"
command: /bin/bash -lc "sed -n '1,220p' test_rag.py"
command: /bin/bash -lc "sed -n '1,220p' test_rag.py"
command: /bin/bash -lc "sed -n '1,220p' templates/admin.html && sed -n '1,220p' static/admin_settings.js"
command: /bin/bash -lc "sed -n '1,220p' templates/admin.html && sed -n '1,220p' static/admin_settings.js"
search: Tavily API documentation search extract LangChain integration
url: https://docs.tavily.com/documentation/api-reference/endpoint/search
url: https://docs.tavily.com/documentation/api-reference/endpoint/search
url: https://docs.tavily.com/documentation/api-reference/endpoint/search
url: https://docs.tavily.com/documentation/api-reference/endpoint/search
search: LangChain Python TavilySearch tool docs
url: https://docs.langchain.com/oss/python/integrations/tools/tavily_search
url: https://docs.exa.ai/
url: https://api-dashboard.search.brave.com/app/documentation/web-search/get-started
search: Tavily pricing API credits free 1000 monthly search credits
url: https://docs.tavily.com/documentation/api-credits
search: '$5 per 1,000' in https://brave.com/search/api/
agent_action: The repository’s current query path is deterministic: Flask receives `/query`, `RAG...
search: site:platform.openai.com/docs web search tool Responses API OpenAI
agent_action: I’ve narrowed the implementation shape: this should not be a search-result metadata...
command: /bin/bash -lc "nl -ba app.py | sed -n '1,130p'"
command: /bin/bash -lc "nl -ba app.py | sed -n '1,130p'"
command: /bin/bash -lc "nl -ba retrieval/rag_retriever.py | sed -n '1,120p'"
command: /bin/bash -lc "nl -ba retrieval/rag_retriever.py | sed -n '1,120p'"
command: /bin/bash -lc "nl -ba README.md | sed -n '1,130p'"
command: /bin/bash -lc "nl -ba README.md | sed -n '1,130p'"
command: /bin/bash -lc "nl -ba llm/llm.py | sed -n '1,120p'"
command: /bin/bash -lc "nl -ba llm/llm.py | sed -n '1,120p'"
agent_action: **Provider Pick** I’d choose **Tavily**, specifically `langchain-tavily` or `tavily...
result: Selected unknown