| # ============================================================================ | |
| # node_01_familiarization.py — Phase 1 (PLACEHOLDER) | |
| # ============================================================================ | |
| # | |
| # PURPOSE (Braun & Clarke 2006) | |
| # ----------------------------- | |
| # "Transcribing data, reading and re-reading the data, noting down | |
| # initial ideas." | |
| # | |
| # Phase 1 is fundamentally a human activity — immersion in the data. | |
| # LLM-assisted versions of this phase typically produce a summary memo | |
| # capturing first impressions of the corpus as a whole, to prime the | |
| # coding phase that follows. | |
| # | |
| # STATUS | |
| # ------ | |
| # PLACEHOLDER. When built, this node will call the LLM with the full | |
| # corpus (or a representative sample) and ask for a brief familiarization | |
| # memo — what kinds of data are present, what stands out, what initial | |
| # impressions the analyst should carry into coding. | |
| # ============================================================================ | |
| def phase1_familiarization_node(state): | |
| iteration = state.get("iteration", 0) | |
| return { | |
| "phase1_familiarization": { | |
| "status": "placeholder", | |
| "note": ( | |
| "Phase 1 (Familiarization) is not yet implemented. When " | |
| "built, this node will generate a familiarization memo " | |
| "summarizing initial impressions of the corpus." | |
| ), | |
| }, | |
| "steps": [{ | |
| "step": iteration, | |
| "node": "phase1_familiarization", | |
| "action": "placeholder", | |
| "detail": "Phase 1 not yet implemented", | |
| }], | |
| } | |