agent_action: Prompt-lab work item started
agent_action: Pinned repository checkout verified
agent_action: I’ll inspect the repository first to understand the agent stack and integration poi...
command: /bin/bash -lc "pwd && rg --files -g '"'!*node_modules*'"' -g '"'!*.png'"' -g '"'!*.jpg'"' -g '"'!*.jpeg'"' -g '"'!*.gif'"' -g '"'!*.lock'"' | head -200"
command: /bin/bash -lc "pwd && rg --files -g '"'!*node_modules*'"' -g '"'!*.png'"' -g '"'!*.jpg'"' -g '"'!*.jpeg'"' -g '"'!*.gif'"' -g '"'!*.lock'"' | head -200"
command: /bin/bash -lc 'git status --short'
command: /bin/bash -lc 'git status --short'
agent_action: `rg` is not installed in this environment, so I’m falling back to `find` and target...
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 -type f \\( -name 'README*' -o -name 'package.json' -o -name 'pyproject.toml' -o -name 'requirements*.txt' -o -name 'go.mod' -o -name 'Cargo.toml' -o -name '*.md' \\) -not -path './.git/*' -print"
command: /bin/bash -lc "find . -maxdepth 2 -type f \\( -name 'README*' -o -name 'package.json' -o -name 'pyproject.toml' -o -name 'requirements*.txt' -o -name 'go.mod' -o -name 'Cargo.toml' -o -name '*.md' \\) -not -path './.git/*' -print"
agent_action: This is a compact Python RAG chatbot, so I’m reading the retrieval, prompt, model, ...
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' rag_chatbot/core/engine/engine.py"
command: /bin/bash -lc "sed -n '1,260p' rag_chatbot/core/engine/engine.py"
command: /bin/bash -lc "sed -n '1,240p' pyproject.toml"
command: /bin/bash -lc "sed -n '1,240p' pyproject.toml"
command: /bin/bash -lc "sed -n '1,260p' rag_chatbot/core/engine/retriever.py"
command: /bin/bash -lc "sed -n '1,260p' rag_chatbot/core/engine/retriever.py"
agent_action: The local path is LlamaIndex-based: PDF nodes go into vector/BM25 retrieval, then `...
command: /bin/bash -lc "sed -n '1,260p' rag_chatbot/pipeline.py"
command: /bin/bash -lc "sed -n '1,260p' rag_chatbot/pipeline.py"
command: /bin/bash -lc "sed -n '1,260p' rag_chatbot/setting/setting.py"
command: /bin/bash -lc "sed -n '1,260p' rag_chatbot/setting/setting.py"
command: /bin/bash -lc "sed -n '1,260p' rag_chatbot/core/prompt/qa_prompt.py"
command: /bin/bash -lc "sed -n '1,260p' rag_chatbot/core/prompt/qa_prompt.py"
command: /bin/bash -lc "sed -n '1,260p' rag_chatbot/core/model/model.py"
command: /bin/bash -lc "sed -n '1,260p' rag_chatbot/core/model/model.py"
search: Perplexity Sonar API documentation citations search results official
agent_action: I’m also considering OpenAI’s managed web search because this repo already has an O...
command: /bin/bash -lc "sed -n '1,220p' /home/user/.codex/skills/.system/openai-docs/SKILL.md"
command: /bin/bash -lc "sed -n '1,220p' /home/user/.codex/skills/.system/openai-docs/SKILL.md"
search: site:platform.openai.com/docs web search tool citations Responses API OpenAI
url: https://platform.openai.com/docs/guides/retrieval
url: https://docs.perplexity.ai/docs/sonar/quickstart
search: 'include_raw_content' in https://docs.tavily.com/documentation/api-reference/endpoi...
url: https://docs.tavily.com/documentation/api-reference/endpoint/search
url: https://docs.perplexity.ai/docs/sonar/models
search: site:docs.perplexity.ai/docs/sonar search domain filters search recency filter Sona...
agent_action: I’ve got enough repo context now: this is not currently a tool-calling agent; it is...
command: /bin/bash -lc "nl -ba rag_chatbot/core/engine/engine.py | sed -n '1,90p'"
command: /bin/bash -lc "nl -ba rag_chatbot/core/engine/engine.py | sed -n '1,90p'"
command: /bin/bash -lc "nl -ba rag_chatbot/core/model/model.py | sed -n '1,80p'"
command: /bin/bash -lc "nl -ba rag_chatbot/core/model/model.py | sed -n '1,80p'"
command: /bin/bash -lc "nl -ba rag_chatbot/pipeline.py | sed -n '1,120p'"
command: /bin/bash -lc "nl -ba rag_chatbot/pipeline.py | sed -n '1,120p'"
command: /bin/bash -lc "nl -ba rag_chatbot/core/engine/retriever.py | sed -n '1,190p'"
command: /bin/bash -lc "nl -ba rag_chatbot/core/engine/retriever.py | sed -n '1,190p'"
agent_action: **Recommendation** Choose **OpenAI Responses API with the `web_search` tool**, usin...
result: Selected openai