Five endpoints under /api/narrative/*:
- GET /story/<sim_id> — full story so far
- GET /story/<sim_id>/round/<num> — single round
- POST /translate — translate a round on demand
- GET /characters/<sim_id> — roster with emotional state
- POST /characters/<sim_id>/init — bootstrap from OASIS profiles
Blueprint registered alongside existing graph/simulation/report
blueprints following the established pattern. Smoke-tested via Flask
test client.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
translate_round() ties together:
- reading the round's actions from actions.jsonl
- generating prose via the LLM
- updating per-character emotional state
- persisting the beat, characters, and file offset
Full test suite now at 19/19 passing across action mapper, character
engine, story store, and translator.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Module-level call_llm() wrapper (patchable by tests) drives
PROSE_PROMPT_TEMPLATE rendering with character summaries, actions,
previous beats, and user-selected tone. Prompt tuned for punchy,
cinematic, dialogue-heavy voice.
Tests: 5/5 passing.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Reads one round's worth of agent actions from the OASIS log file,
tracking file offset so callers can resume across translation calls.
Handles missing files, malformed JSON lines, and non-target rounds
gracefully.
Tests: 3/3 passing.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Character profiles now track a six-dimension emotional state (anger,
fear, joy, sadness, trust, surprise) that evolves based on actions
taken. Initial deltas for all 13 OASIS actions chosen as a balanced
baseline (see module docstring for tuning guidance).
Tests: 5/5 passing.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Three JSON files per simulation under narrative/ subdir:
- story_beats.json: chronological story passages
- translator_state.json: per-platform file offsets
- characters.json: extended character profiles
Tests: 4/4 passing.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
New narrative package with action_mapper module that maps the 13 OASIS
action types (CREATE_POST, LIKE_POST, REPOST, etc.) to narrative verbs
and interpretations used when generating story prose.
Tests: 4/4 passing.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Background threads (graph building, simulation prep, report generation,
profile generation) now inherit the requesting user's locale preference.
Previously these fell back to 'zh' because Flask request context was
unavailable in spawned threads.
Ensure poster_type stays PascalCase English and stance stays English enum
values regardless of language setting. Only natural language fields follow
the user's language preference.
The language instruction was causing LLM to change entity/relation naming
conventions. Now explicitly enforce PascalCase/UPPER_SNAKE_CASE for technical
identifiers while only applying language preference to description fields.
- Implemented `_get_report_id_for_simulation` to find the most recent report ID associated with a simulation ID by scanning the reports directory.
- Updated `get_simulation_history` to include the retrieved report ID in the response, enhancing the simulation data returned to the client.
- Updated simulation history retrieval to read project details directly from the Simulation file.
- Improved simulation configuration handling by reading simulation requirements from JSON.
- Added project file listing to the simulation history, displaying up to three associated files.
- Refined card layout in HistoryDatabase.vue to accommodate new file display features and improved responsiveness.
- Decreased the maximum tool calls per section from 8 to 5.
- Reduced the maximum iterations in the ReACT loop from 8 to 5, streamlining the report generation process.
- Reduced maximum tool calls per chat from 5 to 2 for improved efficiency.
- Simplified system prompt to focus on concise responses and report content.
- Implemented report content retrieval with length limitation to prevent context overflow.
- Adjusted tool call execution to limit to one call per iteration, enhancing clarity in responses.
- Updated user message prompts to encourage concise answers based on retrieved data.
- Increased the maximum tool calls per section from 4 to 8, enhancing the agent's capabilities.
- Raised the maximum reflection rounds from 2 to 3 to allow for deeper analysis.
- Adjusted the maximum tool calls per chat from 3 to 5 for improved interaction.
- Expanded the maximum agents for interviews from 5 to 20, facilitating more comprehensive data gathering.
- Increased the maximum iterations for ReACT loops from 5 to 8 and from 3 to 5 in different contexts, optimizing the report generation process.
- Updated the `to_text` method in the `PanoramaResult` class to provide complete outputs for current facts, historical facts, and involved entities, improving data visibility.
- Modified the `to_text` method in the `AgentInterview` class to display the full agent bio without truncation.
- Adjusted the `ZepToolsService` class to retrieve all related entity details and facts without limiting the output, ensuring comprehensive data representation.
- Renamed log_section_complete to log_section_content to better reflect its purpose, and added is_subsection parameter for improved logging of subsection content.
- Introduced log_section_full_complete method to log the completion of entire sections, including all subsections, enhancing tracking of report generation status.
- Adjusted maximum tool call limits for sections and chats to optimize performance during report generation.
- Updated system prompts and user prompts in the ReportAgent class to clarify the report's focus on future predictions rather than current analysis.
- Enhanced the Step3Simulation and Step4Report components for improved user experience, including UI updates and better handling of report generation states.
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