How brusssss1/agent-research-test- works
This is a command-line research assistant: a user submits a query, an agent can use web search and Wikipedia tools, and the response is parsed into a structured research result for display. The agent can also save text to a local file. The sampled files show orchestration and tool setup; they do not establish finer details of the agent framework’s internal dispatch or model-provider implementation.
Main entry points: main.py Agent executor · tools.py DuckDuckGo search
Components 12
Research orchestration
- CLI and agent setup
main.py - Agent executor
main.py - Groq chat model
Research tools
- DuckDuckGo search
tools.py - Wikipedia query
tools.py
Results and storage
- Save research text
tools.py - Response parser
main.py - Structured result
main.py
Other components
- User
- DuckDuckGo
- Wikipedia
- Output text file
Connections 12
- User → CLI and agent setup: enters query
- CLI and agent setup → Agent executor: invokes
- Agent executor → Groq chat model: requests response
- Agent executor → DuckDuckGo search: dispatches search
- Agent executor → Wikipedia query: dispatches query
- Agent executor → Save research text: dispatches save
- DuckDuckGo search → DuckDuckGo: searches
- Wikipedia query → Wikipedia: queries
- Save research text → Output text file: appends text
- CLI and agent setup → Response parser: parses response
- Response parser → Structured result: produces
- CLI and agent setup → User: prints result