MASForensic

BattleTag/MASForensic

Fork 0

Commit Graph

Author	SHA1	Message	Date
BattleTag	81ade8f7ac	feat(refit): complete S1-S6 — case abstraction, grounding, log-odds, plugins, coref, multi-source Consolidates the long-running refit work (DESIGN.md as authoritative spec) into a single baseline commit. Six stages landed together: S1 Case + EvidenceSource abstraction; tools parameterised by source_id (case.py, main.py multi-source bootstrap, .bin extension support) S2 Grounding gateway in add_phenomenon: verified_facts cite real ToolInvocation ids; substring / normalised match enforced; agent + task scope checked. Phenomenon.description split into verified_facts (grounded) + interpretation (free text). [invocation: inv-xxx] prefix on every wrapped tool result so the LLM can cite. S3 Confidence as additive log-odds: edge_type → log10(LR) calibration table; commutative updates; supported / refuted thresholds derived from log_odds; hypothesis × evidence matrix view. S4 iOS plugin: unzip_archive + parse_plist / sqlite_tables / sqlite_query / parse_ios_keychain / read_idevice_info; IOSArtifactAgent; SOURCE_TYPE_AGENTS routing. S5 Cross-source entity resolution: typed identifiers on Entity, observe_identity gateway, auto coref hypothesis with shared / conflicting strong/weak LR edges, reversible same_as edges, actor_clusters() view. S6 Android partition probe + AndroidArtifactAgent; MediaAgent with OCR fallback; orchestrator Phase 1 iterates every analysable source; platform-aware get_triage_agent_type; ReportAgent renders actor clusters + per-source breakdown. 142 unit tests / 1 skipped — full coverage of the new gateway, log-odds math, coref hypothesis fall-out, and orchestrator multi-source dispatch. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>	2026-05-21 02:12:10 -10:00
BattleTag	0a966d8476	feat: switch LLM client to OpenAI SDK for DeepSeek compatibility The previous LLMClient used raw httpx + Claude Messages API (/v1/messages, x-api-key, Anthropic SSE event types). Incompatible with DeepSeek. Rewrite LLMClient.__init__/chat/close to use openai.AsyncOpenAI: - /v1/chat/completions endpoint, OpenAI message format - Bearer auth, native SDK error types - Stream chunks via async for + chunk.choices[0].delta.content Tool calling protocol (ReAct text-based tags) and all surrounding helpers (_apply_progressive_decay, _fold_old_messages, _partition_tool_calls, tool_call_loop, etc.) are unchanged — endpoint-agnostic by design. New optional config params surfaced to config.yaml.agent: - reasoning_effort: "high" \| "medium" \| "low" — DeepSeek/o1-style depth - thinking_enabled: bool — DeepSeek extra_body.thinking switch main.py and regenerate_report.py pass these through to LLMClient. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>	2026-05-12 17:13:54 +08:00
BattleTag	097d2ce472	Initial commit Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>	2026-05-09 17:36:26 +08:00

Author

SHA1

Message

Date

BattleTag

81ade8f7ac

feat(refit): complete S1-S6 — case abstraction, grounding, log-odds, plugins, coref, multi-source

Consolidates the long-running refit work (DESIGN.md as authoritative spec)
into a single baseline commit. Six stages landed together:

  S1  Case + EvidenceSource abstraction; tools parameterised by source_id
      (case.py, main.py multi-source bootstrap, .bin extension support)
  S2  Grounding gateway in add_phenomenon: verified_facts cite real
      ToolInvocation ids; substring / normalised match enforced; agent +
      task scope checked. Phenomenon.description split into verified_facts
      (grounded) + interpretation (free text). [invocation: inv-xxx]
      prefix on every wrapped tool result so the LLM can cite.
  S3  Confidence as additive log-odds: edge_type → log10(LR) calibration
      table; commutative updates; supported / refuted thresholds derived
      from log_odds; hypothesis × evidence matrix view.
  S4  iOS plugin: unzip_archive + parse_plist / sqlite_tables /
      sqlite_query / parse_ios_keychain / read_idevice_info;
      IOSArtifactAgent; SOURCE_TYPE_AGENTS routing.
  S5  Cross-source entity resolution: typed identifiers on Entity,
      observe_identity gateway, auto coref hypothesis with shared /
      conflicting strong/weak LR edges, reversible same_as edges,
      actor_clusters() view.
  S6  Android partition probe + AndroidArtifactAgent; MediaAgent with
      OCR fallback; orchestrator Phase 1 iterates every analysable
      source; platform-aware get_triage_agent_type; ReportAgent renders
      actor clusters + per-source breakdown.

142 unit tests / 1 skipped — full coverage of the new gateway, log-odds
math, coref hypothesis fall-out, and orchestrator multi-source dispatch.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

2026-05-21 02:12:10 -10:00

BattleTag

0a966d8476

feat: switch LLM client to OpenAI SDK for DeepSeek compatibility

The previous LLMClient used raw httpx + Claude Messages API (/v1/messages,
x-api-key, Anthropic SSE event types). Incompatible with DeepSeek.

Rewrite LLMClient.__init__/chat/close to use openai.AsyncOpenAI:
- /v1/chat/completions endpoint, OpenAI message format
- Bearer auth, native SDK error types
- Stream chunks via async for + chunk.choices[0].delta.content

Tool calling protocol (ReAct text-based tags) and all surrounding helpers
(_apply_progressive_decay, _fold_old_messages, _partition_tool_calls,
tool_call_loop, etc.) are unchanged — endpoint-agnostic by design.

New optional config params surfaced to config.yaml.agent:
- reasoning_effort: "high" | "medium" | "low" — DeepSeek/o1-style depth
- thinking_enabled: bool — DeepSeek extra_body.thinking switch

main.py and regenerate_report.py pass these through to LLMClient.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

2026-05-12 17:13:54 +08:00

BattleTag

097d2ce472

Initial commit

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

2026-05-09 17:36:26 +08:00

3 Commits