Step 02/03 UX:
- Remove duplicate simulation params (total_hours, minutes_per_round) from Fase B form
- Add following_probability + recsys_type to step 03 config panel instead
- Step 03 now read-only by default with Edit / Save toolbar toggle
- Add common.edit and log.configSaved i18n keys to all 4 locales
Backend - Azure OpenAI fix (run_parallel_simulation.py):
- create_model() now detects Azure URLs (cognitiveservices.azure.com / openai.azure.com)
and uses ModelPlatformType.AZURE with AzureOpenAIModel, passing api_version and
azure_deployment_name explicitly — fixes 404 "Resource not found" from camel-ai
Backend - offline report interviews (simulation_runner.py):
- interview_agents_batch() falls back to _offline_batch_interview() when OASIS env is
closed (simulation finished), reading posts from SQLite DB instead of failing with
"No successful interviews / check OASIS environment status"
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Implements Tasks 8 and 9 of F2-A+B: async agent creation from entity UUID
and async per-agent profile regeneration, both with atomic profile file writes.
Refactors generate_profile_from_entity to accept extra_instructions instead
of requiring user_id (renamed internal logic to _generate_single_profile).
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Implements SimulationManager.clone_simulation() and the corresponding
Flask route. The clone copies reddit_profiles.json, twitter_profiles.csv
and agent_profiles.json from the source simulation; does not copy
simulation_config.json; sets status=PROFILES_READY and records
parent_simulation_id. All 3 tests in test_simulation_clone.py pass.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Implements atomic agent profile editing with manually_edited flag.
Blocks edits when simulation is running or completed.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Extract parse_azure_url from graphiti_backend into utils/llm_client so all
services (oasis_profile_generator, simulation_config_generator, graphiti_backend,
LLMClient) strip the /chat/completions suffix and api-version before passing
base_url to the OpenAI SDK, fixing 404 errors when the full Azure endpoint URL
is set in LLM_BASE_URL.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Revert default limits back to 10 edges and 12 entities (10 specific + 2
fallback), matching Zep Cloud's maximum. Expose ONTOLOGY_MAX_ENTITY_TYPES
and ONTOLOGY_MAX_EDGE_TYPES in Config so operators can override without
touching code. Prompts now inject the live values at request time.
Also replace Chinese comments in .env.example with English equivalents.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- ontology_generator: increase entity limit to 20 (18 specific + 2 fallback),
edge types to 20 (12-20 requested); bump max_tokens to 8192
- ontology_generator: fallback type names (Person/Organization) now resolved
via i18n so Catalan gets Persona/Organització
- locales: add ontologyFallback* keys to en/zh/es/ca
- graph_builder: pass entity/edge attributes to non-Zep set_ontology (were discarded)
- graphiti_backend: _make_model builds real Pydantic fields per attribute
- graphiti_backend: _build_extraction_instructions includes per-entity attribute
hints so the LLM knows which fields to extract
- graphiti_backend: add_batch retries up to 3x on "node not found" race condition
with exponential backoff (2s, 4s) before propagating the error
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Translate all Chinese comments, docstrings, log messages, error messages,
and LLM prompt text to English across the entire backend codebase.
Locale translation files (locales/*.json) are unchanged.
Co-Authored-By: Claude Sonnet 4.6 <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.
- 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.
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