Phase 0 Prep: Cache restructure, Vision investigation, HF integration plan

Changes:
- Unified export location to _cache/ folder (all environments)
- Cleaned up obsolete exports/ files
- PLAN.md: Comprehensive HF vision integration plan with Phase 0 API validation
- CHANGELOG: Documented Stage 5 investigation findings (0% accuracy root cause)
- README: Updated project status and workflow documentation

Key findings:
- Vision tool hardcoded to Gemini→Claude, ignores UI LLM selection
- HF Inference API vision support needs validation before implementation
- Added decision gates and backup strategies to PLAN.md

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>

.gitignore

@@ -30,6 +30,9 @@ Thumbs.db
 # Input documents (PDFs not allowed in HF Spaces)
 input/*.pdf
 
+# Runtime cache (not in git, served via app download)
+_cache/
+
 # Testing
 .pytest_cache/
 .coverage

CHANGELOG.md

@@ -1 +1,204 @@
 # Session Changelog
+
+## [2026-01-06] [Plan Revision] [COMPLETED] HuggingFace Vision Integration Plan - Corrected Architecture
+
+**Problem:** Initial plan had critical gaps that would waste implementation time:
+
+- Missing Phase 0 API validation (could implement non-functional approach)
+- Included fallback logic during testing (defeats isolation purpose)
+- Wrong model selection order (large → small, should be small → large)
+- No smoke tests before GAIA (would debug complex questions with broken integration)
+- Premature cost optimization
+
+**Solution - Plan Corrections Applied:**
+
+1. **Added Phase 0: API Validation (CRITICAL)**
+   - Test HF Inference API with vision models BEFORE implementation
+   - Model order: Phi-3.5 (3.8B) → Llama-3.2 (11B) → Qwen2-VL (72B)
+   - Decision gate: Only proceed if ≥1 model works, otherwise pivot to backup options
+   - Time saved: Prevents 2-3 hours implementing non-functional code
+
+2. **Removed Fallback Logic from Testing**
+   - Each provider fails independently with clear error message
+   - NO fallback chains (HF → Gemini → Claude) during testing
+   - Philosophy: Build capability knowledge, don't hide problems
+   - Log exact failure reasons for debugging
+
+3. **Added Smoke Tests (Phase 2)**
+   - 4 tests before GAIA: description, OCR, counting, single GAIA question
+   - Decision gate: ≥3/4 must pass before full evaluation
+   - Prevents debugging chess positions when basic integration broken
+
+4. **Added Decision Gates**
+   - Gate 1 (Phase 0): API validation → GO/NO-GO
+   - Gate 2 (Phase 2): Smoke tests → GO/NO-GO
+   - Gate 3 (Phase 3): GAIA accuracy ≥20% → Continue or iterate
+
+5. **Added Backup Strategy Documentation**
+   - Option C: HF Spaces deployment (custom endpoint)
+   - Option D: Local transformers library (no API)
+   - Option E: Hybrid (HF text + Gemini/Claude vision)
+
+6. **Separate Results Per Provider**
+   - Export format: `gaia_results_hf_TIMESTAMP.json` (HF only)
+   - Build capability matrix: which provider for which tasks
+   - No combined/fallback results during testing
+
+**Modified Files:**
+
+- **PLAN.md** (~200 lines restructured)
+  - Phase 0: API Validation (NEW)
+  - Phase 1: Implementation (revised - no fallbacks)
+  - Phase 2: Smoke Tests (NEW)
+  - Phase 3: GAIA Evaluation (revised)
+  - Phase 4: Media Processing (YouTube, audio)
+  - Phase 5: Groq Integration (future)
+  - Phase 6: Final Verification
+  - Added: Backup Strategy Options section
+  - Added: Decision Gates Summary section
+  - Updated: Files to Modify (10 files total)
+  - Updated: Success Criteria (per-phase)
+
+**Key Changes Summary:**
+
+| Before | After |
+|--------|-------|
+| Jump to implementation | Phase 0: Validate API first |
+| Fallback chains | No fallbacks, fail independently |
+| Large models first (Qwen2-VL) | Small models first (Phi-3.5) |
+| Direct to GAIA | Smoke tests → GAIA |
+| No backup plan | 3 backup options documented |
+| Single success criteria | Per-phase criteria + decision gates |
+
+**Benefits:**
+
+- ✅ Prevents wasted implementation time on non-functional approach
+- ✅ Clear debugging with isolated provider failures
+- ✅ Faster iteration with small models
+- ✅ Risk mitigation with decision gates
+- ✅ Backup options if HF API doesn't support vision
+
+**Next Steps:** Proceed to Phase 0 (API validation) when implementation starts
+
+---
+
+## [2026-01-06] [Stage 5 Investigation] [COMPLETED] Vision Tool Ignores UI LLM Selection - Root Cause of 0% Accuracy
+
+**Problem:** Stage 5 claimed 25% accuracy (5/20 correct) but actual results show 0% accuracy (0/20 correct). User selected HuggingFace in UI but vision questions still failing.
+
+**Investigation Findings:**
+
+**Ground Truth Analysis (output/gaia_results_20260105_203102.json):**
+
+- Actual score: 0% (0/20 correct) - complete failure
+- Stage 5 dev record claimed: 25% (5/20 correct) - false success claim
+- Regression from baseline 10% → 0%
+
+**Failure Pattern Breakdown:**
+
+1. **Vision tool failures:** 40% of questions (8/20)
+   - Error: "Vision analysis failed - Gemini and Claude both failed"
+   - Questions: Chess position, YouTube videos, audio file parsing
+2. **Calculator threading error:** 5% of questions (1/20)
+   - Error: "ValueError: signal only works in main thread of the main interpreter"
+   - Root cause: `signal.alarm()` doesn't work in Gradio async context
+3. **Wrong answers:** 55% of questions (11/20)
+   - Tools work, but answer synthesis produces incorrect factoids
+   - Example: Mercedes Sosa albums - submitted "4", correct "3"
+
+**Root Cause - Vision Tool Bug:**
+
+**Critical bug in `src/tools/vision.py:303-339`:**
+
+- Vision tool HARDCODED to always try Gemini → Claude fallback
+- Never checks `os.getenv("LLM_PROVIDER")` setting
+- Ignores UI LLM selection completely
+- Other tools (planning, tool selection, synthesis) correctly respect UI selection
+
+**Code Evidence:**
+
+```python
+def analyze_image(image_path: str, question: Optional[str] = None) -> Dict:
+    # MISSING: No check for os.getenv("LLM_PROVIDER")
+
+    # HARDCODED: Always try Gemini first
+    if settings.google_api_key:
+        return analyze_image_gemini(image_path, question)
+
+    # HARDCODED: Always fallback to Claude
+    if settings.anthropic_api_key:
+        return analyze_image_claude(image_path, question)
+```
+
+**Impact:**
+
+- When user selects "HuggingFace" in UI:
+  - ✅ Planning uses HuggingFace
+  - ✅ Tool selection uses HuggingFace
+  - ❌ Vision still calls Gemini/Claude (ignores selection)
+  - Result: 40% of questions auto-fail due to Gemini/Claude quota exhaustion
+
+**Additional Issue:**
+
+- HuggingFace Inference API free tier doesn't support multimodal vision analysis
+- Even if bug fixed, HF can't handle vision questions
+
+**Modified Files:**
+
+- **NONE** (investigation only - no code changes yet)
+
+**Next Steps Identified:**
+
+1. Fix vision tool to respect `LLM_PROVIDER` setting
+2. Add proper error handling when HF selected for vision questions
+3. Fix calculator threading issue (`signal.alarm()` in async context)
+4. Improve answer synthesis prompts
+5. Add verification protocol: MUST verify claims with actual JSON output
+
+**Current Baseline:** 0% (need to fix regressions before optimizing)
+**Target:** 30% minimum (6/20 questions)
+
+---
+
+## [2026-01-05] [Runtime Cache Folder] [COMPLETED] Eliminate exports/ Redundancy
+
+**Problem:**
+
+- Environment-dependent paths: `~/Downloads` (local) vs `./exports` (HF Spaces)
+- `exports/` folder name confusing - looked like user-facing folder
+- Files visible in HF UI when committed to git
+- User couldn't locate where files were saved
+
+**Solution:**
+
+- Single `_cache/` folder for all environments (local, HF Spaces)
+- Name clearly indicates internal runtime storage (not user-accessible via file browser)
+- Files served via app download button, not HF Spaces UI
+- Added to .gitignore to keep runtime files out of git
+
+**Modified Files:**
+
+- **app.py** (~10 lines modified)
+  - Removed environment detection logic (`if os.getenv("SPACE_ID")`)
+  - Changed: `exports/` → `_cache/`
+  - Updated docstring: "All environments: Saves to ./_cache/gaia_results_TIMESTAMP.json"
+  - Updated comment: "Save to _cache/ folder (internal runtime storage, not accessible via HF UI)"
+
+- **.gitignore** (~3 lines added)
+  - Added `_cache/` to ignore list
+  - Added comment explaining runtime cache behavior
+
+**Benefits:**
+
+- ✅ Single location for all environments (no environment detection)
+- ✅ Clear naming indicates internal storage (not user-facing)
+- ✅ Files accessible via download button
+- ✅ Not visible in HF Spaces file browser
+- ✅ Not committed to git
+
+**File Lifecycle on HF Spaces:**
+
+- Files persist on server between runs (accumulate in `_cache/`)
+- Wiped clean on redeploy (container rebuild)
+- Standard container behavior: runtime storage is temporary
+- No manual cleanup needed (redeploy handles it)

PLAN.md

@@ -1,27 +1,499 @@
-# Implementation Plan
+# Implementation Plan - LLM Selection Routing & HuggingFace Vision Support
 
-**Date:** [YYYY-MM-DD]
-**Status:** Planning | In Progress | Completed
+**Date:** 2026-01-06
+**Status:** Planning
+
+## Objective
+
+Fix LLM selection routing so UI provider selection propagates to ALL tools (planning, tool selection, synthesis, AND vision). Enable vision capability using HuggingFace multimodal models.
+
+## Current Problems
+
+1. **Vision tool ignores UI selection** - Hardcoded Gemini → Claude fallback
+2. **No HuggingFace vision support** - HF Inference API integration missing multimodal capability
+3. **Inconsistent routing** - Planning/tool selection respect UI, vision doesn't
+
+## Solution Architecture
+
+### Part 1: Fix LLM Selection Routing
+
+**Goal:** When user selects "HuggingFace" in UI, ALL agent components use HuggingFace LLM
+
+**Changes needed:**
+
+1. **Vision tool (src/tools/vision.py):**
+   - Add `analyze_image_hf()` function for HuggingFace multimodal models
+   - Modify `analyze_image()` to check `os.getenv("LLM_PROVIDER")`
+   - Route to correct provider: `gemini`, `huggingface`, `groq`, `claude`
+   - Respect `ENABLE_LLM_FALLBACK` setting
+
+2. **Ensure consistency:**
+   - Planning: ✅ Already respects `LLM_PROVIDER`
+   - Tool selection: ✅ Already respects `LLM_PROVIDER`
+   - Synthesis: ✅ Already respects `LLM_PROVIDER`
+   - Vision: ❌ **NEEDS FIX** - Add routing logic
+
+### Part 2: HuggingFace Vision Capability
+
+**Two approaches identified:**
+
+#### Option A: Direct Multimodal LLM (Preferred)
+
+**Approach:** Use HuggingFace multimodal models that support vision + text
+
+**Candidate models:**
+
+1. **Qwen/Qwen2-VL-72B-Instruct** (Recommended)
+   - 72B parameters, vision-language model
+   - Supports: images, video, text
+   - API: HuggingFace Inference API (paid tier)
+   - Format: Base64 image + text prompt
+
+2. **meta-llama/Llama-3.2-90B-Vision-Instruct**
+   - 90B parameters, multimodal
+   - Supports: images + text
+   - API: HuggingFace Inference API
+
+3. **microsoft/Phi-3.5-vision-instruct**
+   - Smaller model (3.8B), efficient
+   - Supports: images + text
+   - Good for testing/debugging
+
+**Implementation:**
+
+- Use `InferenceClient.chat_completion()` with image content
+- Send base64-encoded images in messages array
+- Similar to Claude vision integration pattern
+
+**Pros:**
+
+- ✅ Native vision understanding
+- ✅ Single API call (no preprocessing)
+- ✅ Better accuracy for visual reasoning
+- ✅ Consistent with current architecture
+
+**Cons:**
+
+- ❌ Requires HuggingFace paid tier (but user confirmed they have this)
+- ❌ Need to verify which models work with Inference API
+
+#### Option B: Image-to-Text Preprocessing
+
+**Approach:** Convert images to text descriptions using separate tool, then feed to text-only LLM
+
+**Tools available:**
+
+1. **BLIP-2** (Salesforce/blip2-opt-2.7b)
+   - Image captioning model
+   - Converts image → text description
+
+2. **LLaVA** (llava-hf/llava-1.5-7b-hf)
+   - Vision-language assistant
+   - Image → detailed text
+
+3. **OpenCV + OCR** (pytesseract)
+   - Extract text from images
+   - Good for documents/screenshots
+
+**Implementation:**
+
+- Load image → Run BLIP-2/LLaVA → Get text description
+- Pass text description to HuggingFace text-only LLM
+- Two-step process: vision → text → reasoning
+
+**Pros:**
+
+- ✅ Works with any text-only LLM
+- ✅ Cheaper (can use smaller vision models)
+- ✅ Fallback option if multimodal API unavailable
+
+**Cons:**
+
+- ❌ Two API calls (slower)
+- ❌ Information loss in image → text conversion
+- ❌ Poor for complex visual reasoning (chess positions, video analysis)
+- ❌ Extra dependency management
+
+## Recommended Approach
+
+**Use Option A: Direct Multimodal LLM (Qwen2-VL-72B-Instruct)**
+
+**Reasoning:**
+
+1. User has HuggingFace paid tier access (confirmed)
+2. GAIA questions require complex visual reasoning (chess positions, video analysis)
+3. Simpler architecture - consistent with existing pattern
+4. Better accuracy for benchmark performance
+5. Focus on HF testing first, Groq later
+
+**Fallback:** Keep Option B as backup if multimodal API doesn't work
+
+## Implementation Steps
+
+### Phase 0: API Validation (CRITICAL - DO THIS FIRST)
+
+**Goal:** Validate HuggingFace Inference API supports vision BEFORE implementation
+
+**Decision Gate 1:** Only proceed to Phase 1 if at least one model works
+
+#### Step 0.1: Test HF Inference API with Vision Models
+
+- [ ] Test **Phi-3.5-vision-instruct** (3.8B) - Smallest, fastest iteration
+- [ ] Test **Llama-3.2-11B-Vision-Instruct** - Medium model
+- [ ] Test **Qwen2-VL-72B-Instruct** - Largest, only if needed
+- [ ] Simple test: Load apple image, ask "What is this?"
+- [ ] Verify API accepts vision input (base64, URL, or file path)
+- [ ] Document response format and error patterns
+
+#### Step 0.2: Test Image Format Support
+
+- [ ] Base64 encoding in messages
+- [ ] Direct URL support
+- [ ] Local file path support
+- [ ] Document which format(s) work
+
+#### Step 0.3: Document API Behavior
+
+- [ ] Response structure (JSON schema)
+- [ ] Error patterns (quota, rate limit, invalid input)
+- [ ] Rate limits and quotas
+- [ ] Model selection recommendation
+
+#### Step 0.4: Decision Gate - GO/NO-GO
+
+- [ ] **GO:** At least 1 model works → Proceed to Phase 1
+- [ ] **NO-GO:** 0 models work → Pivot to backup options:
+  - **Option C:** HF Spaces deployment (custom endpoint)
+  - **Option D:** Local transformers library (no API)
+  - **Option E:** Hybrid (HF text + Gemini/Claude vision only)
 
 ---
 
-## Objective
-[Clear goal statement]
+### Phase 1: HuggingFace Vision Implementation (Only if Phase 0 passes)
+
+**Goal:** Implement `analyze_image_hf()` using validated API pattern
+
+#### Step 1.1: Implement `analyze_image_hf()` in vision.py
+
+- [ ] Add function signature matching existing pattern
+- [ ] Use validated model from Phase 0 (start with smallest working model)
+- [ ] Format image using validated format from Phase 0
+- [ ] Add retry logic with exponential backoff
+- [ ] Handle API errors with clear error messages
+- [ ] **NO fallback logic** - fail loudly for debugging
+
+#### Step 1.2: Fix Vision Tool Routing (NO FALLBACKS)
+
+- [ ] Modify `analyze_image()` to check `os.getenv("LLM_PROVIDER")`
+- [ ] Add routing logic (each provider fails independently):
+
+  ```python
+  if provider == "huggingface":
+      return analyze_image_hf(image_path, question)  # Fail if error
+  elif provider == "gemini":
+      return analyze_image_gemini(image_path, question)  # Fail if error
+  elif provider == "claude":
+      return analyze_image_claude(image_path, question)  # Fail if error
+  # NO fallback chains during testing - defeats isolation purpose
+  ```
+
+- [ ] Log exact failure reason for debugging
+- [ ] Add placeholder for `groq` (future Phase 4)
+
+#### Step 1.3: Update Configuration
+
+- [ ] Add `HF_VISION_MODEL` to .env (use smallest working model from Phase 0)
+- [ ] Update `src/config/settings.py` with vision model setting
+- [ ] Document model options (Phi-3.5, Llama-3.2, Qwen2-VL)
 
 ---
 
-## Steps
-1. [Step 1]
-2. [Step 2]
+### Phase 2: Smoke Tests (Before GAIA Evaluation)
+
+**Goal:** Validate basic vision works before complex GAIA questions
+
+**Decision Gate 2:** Only proceed to Phase 3 if ≥3/4 smoke tests pass
+
+#### Step 2.1: Simple Image Description Test
+
+- [ ] Test image: Photo of apple
+- [ ] Question: "Describe this image"
+- [ ] Expected: Basic object recognition works
+- [ ] Export: `output/smoke_test_description.json`
+
+#### Step 2.2: OCR Test
+
+- [ ] Test image: Image with text "Hello World"
+- [ ] Question: "What text do you see?"
+- [ ] Expected: Text extraction works
+- [ ] Export: `output/smoke_test_ocr.json`
+
+#### Step 2.3: Counting Test
+
+- [ ] Test image: Image with 3 distinct objects
+- [ ] Question: "How many objects are visible?"
+- [ ] Expected: Visual reasoning works
+- [ ] Export: `output/smoke_test_counting.json`
+
+#### Step 2.4: Single GAIA Question Test
+
+- [ ] Select easiest GAIA vision question
+- [ ] Run with HuggingFace provider
+- [ ] Verify end-to-end integration works
+- [ ] Export: `output/smoke_test_gaia_single.json`
+
+#### Step 2.5: Decision Gate - GO/NO-GO
+
+- [ ] **GO:** ≥3/4 smoke tests pass → Proceed to Phase 3
+- [ ] **NO-GO:** <3/4 pass → Debug before GAIA evaluation
 
 ---
 
-## Files to Modify
-- file1.py
-- file2.md
+### Phase 3: GAIA Evaluation (Only if Smoke Tests Pass)
+
+**Goal:** Test HuggingFace vision on full GAIA benchmark
+
+#### Step 3.1: Run Full GAIA Evaluation (HuggingFace Only)
+
+- [ ] Set `LLM_PROVIDER=huggingface` in UI
+- [ ] Run all 20 questions
+- [ ] Export: `output/gaia_results_hf_TIMESTAMP.json` (HF only, no mixing)
+- [ ] Log which questions use vision tool vs other tools
+
+#### Step 3.2: Analyze Results
+
+- [ ] Calculate accuracy: X/20 correct
+- [ ] Break down by question type:
+  - Vision questions: X/8 correct
+  - Non-vision questions: X/12 correct
+- [ ] Identify failure patterns (vision errors, wrong answers, tool selection errors)
+- [ ] Compare to 0% baseline
+
+#### Step 3.3: Build Capability Matrix
+
+- [ ] Document per-provider results:
+
+| Provider | Vision Questions | Accuracy | Notes |
+|----------|-----------------|----------|-------|
+| HuggingFace (Phi-3.5) | 8/8 attempted | X% | [observations] |
+| Gemini (baseline) | 8/8 attempted | Y% | [comparison] |
+
+#### Step 3.4: Decision Gate - Optimization Decision
+
+- [ ] **If accuracy ≥20%:** Good enough, proceed to Phase 4 (media processing)
+- [ ] **If accuracy <20%:** Analyze failures, try larger HF model (Llama-3.2 or Qwen2-VL)
+- [ ] **If accuracy <5%:** Re-evaluate approach, consider backup options
+
+---
+
+### Phase 4: Media Processing Gaps (After Vision Works)
+
+**Goal:** Add YouTube and audio support
+
+#### Step 4.1: YouTube Video Support
+
+- [ ] Add YouTube transcript extraction tool
+- [ ] Use `youtube-transcript-api` library
+- [ ] Extract dialogue/captions as text
+- [ ] Pass transcript to LLM for question answering
+- [ ] Test on GAIA YouTube questions (bird species, Stargate quote)
+- [ ] Export: `output/gaia_results_hf_with_youtube.json`
+
+#### Step 4.2: Audio File Support
+
+- [ ] Add audio transcription tool
+- [ ] Use OpenAI Whisper or HuggingFace audio models
+- [ ] Transcribe audio → text
+- [ ] Pass transcript to LLM
+- [ ] Test on GAIA audio question (Strawberry pie.mp3)
+- [ ] Export: `output/gaia_results_hf_with_audio.json`
 
 ---
 
+### Phase 5: Groq Vision Integration (Future)
+
+**Goal:** Add free tier fallback option
+
+#### Step 5.1: Add Groq Vision Support
+
+- [ ] Implement `analyze_image_groq()` using Llama-3.2-90B-Vision
+- [ ] Add to vision tool routing (independent, no fallback)
+- [ ] Test with Groq free tier (30 req/min)
+- [ ] Export: `output/gaia_results_groq_TIMESTAMP.json`
+- [ ] Compare accuracy: HF vs Groq
+
+---
+
+### Phase 6: Final Verification
+
+**Goal:** Document final results and verify all tests pass
+
+#### Step 6.1: Final GAIA Evaluation (All Media Types)
+
+- [ ] Run all 20 questions with HuggingFace
+- [ ] Verify: images, videos, audio all work
+- [ ] Export: `output/gaia_results_final_TIMESTAMP.json`
+- [ ] Document final accuracy vs 0% baseline
+
+#### Step 6.2: Regression Testing
+
+- [ ] Run all 99 tests
+- [ ] Verify no regressions introduced
+- [ ] Fix any broken tests
+
+#### Step 6.3: Documentation
+
+- [ ] Update CHANGELOG.md with final results
+- [ ] Update README.md with HF vision support
+- [ ] Document model selection strategy
+
+## Files to Modify
+
+### Phase 0-1: Core Vision Integration
+
+1. **src/tools/vision.py** (~150 lines added/modified)
+   - Add `analyze_image_hf()` function (Phase 1)
+   - Modify `analyze_image()` routing logic - NO FALLBACKS (Phase 1)
+   - Add retry logic with exponential backoff
+   - Clear error messages for debugging
+
+2. **.env** (~3 lines added)
+   - Add `HF_VISION_MODEL=microsoft/Phi-3.5-vision-instruct` (start small)
+   - Document alternatives: Llama-3.2-11B-Vision, Qwen2-VL-72B
+
+3. **src/config/settings.py** (~5 lines)
+   - Add `hf_vision_model` setting
+   - Load from environment variable
+
+### Phase 2-3: Testing Infrastructure
+
+1. **test/test_vision_smoke.py** (NEW - ~100 lines)
+   - Smoke test suite: description, OCR, counting, single GAIA
+   - Export individual test results
+
+2. **app.py** (optional - ~10 lines)
+   - Update export filenames to include provider: `gaia_results_hf_TIMESTAMP.json`
+   - Separate results per provider for capability matrix
+
+### Phase 4: Media Processing
+
+1. **src/tools/youtube.py** (NEW - ~80 lines)
+   - YouTube transcript extraction
+   - Use `youtube-transcript-api`
+
+2. **src/tools/audio.py** (NEW - ~80 lines)
+   - Audio transcription (Whisper or HF audio models)
+   - Convert audio → text
+
+3. **src/tools/__init__.py** (~10 lines)
+   - Register new tools: youtube_transcript, audio_transcribe
+
+4. **requirements.txt** (~3 lines)
+   - Add `youtube-transcript-api`
+   - Add `openai-whisper` or HF audio model library
+
+### Phase 6: Documentation
+
+1. **README.md** (~30 lines modified)
+    - Document HF vision support
+    - List model options and selection strategy
+    - Update architecture diagram with media processing tools
+
 ## Success Criteria
-- [ ] Criterion 1
-- [ ] Criterion 2
+
+### Phase 0: API Validation
+
+- [ ] At least 1 HF vision model works with Inference API
+- [ ] Image format documented (base64/URL/file)
+- [ ] Response format documented
+
+### Phase 1: Implementation
+
+- [ ] `analyze_image_hf()` function implemented
+- [ ] Vision tool routing respects `LLM_PROVIDER` (NO FALLBACKS)
+- [ ] Clear error messages when provider fails
+
+### Phase 2: Smoke Tests
+
+- [ ] ≥3/4 smoke tests pass
+- [ ] Basic vision capabilities validated
+
+### Phase 3: GAIA Evaluation
+
+- [ ] UI LLM selection propagates to vision tool
+- [ ] HuggingFace-only results exported: `output/gaia_results_hf_TIMESTAMP.json`
+- [ ] Accuracy measured and compared to 0% baseline
+- [ ] Capability matrix built (per-provider comparison)
+
+### Phase 4-6: Full Coverage
+
+- [ ] YouTube video questions work (transcript extraction)
+- [ ] Audio questions work (transcription)
+- [ ] All 99 tests still passing
+- [ ] Final accuracy ≥20% (minimum acceptable)
+
+## Backup Strategy Options
+
+If Phase 0 reveals HF Inference API doesn't support vision:
+
+### Option C: HuggingFace Spaces Deployment
+
+- Deploy custom vision model to HF Spaces
+- Use Inference Endpoints (paid tier)
+- More control, higher cost
+
+### Option D: Local Transformers Library
+
+- Use `transformers` library directly (no API)
+- Load model locally: `AutoModelForVision2Seq`
+- Slower, requires GPU, but guaranteed to work
+
+### Option E: Hybrid Architecture
+
+- Keep HuggingFace for text-only LLM
+- Use Gemini/Claude for vision only
+- Compromise: HF testing focus, but vision delegates to working providers
+
+## Decision Gates Summary
+
+**Gate 1 (Phase 0):** Does HF API support vision?
+
+- **GO:** ≥1 model works → Phase 1
+- **NO-GO:** 0 models work → Pivot to Option C/D/E
+
+**Gate 2 (Phase 2):** Do smoke tests pass?
+
+- **GO:** ≥3/4 pass → Phase 3
+- **NO-GO:** <3/4 pass → Debug before GAIA
+
+**Gate 3 (Phase 3):** Is accuracy acceptable?
+
+- **GO:** ≥20% → Phase 4 (media processing)
+- **ITERATE:** <20% → Try larger model or analyze failures
+- **PIVOT:** <5% → Re-evaluate approach
+
+## Phase 0 Research Questions (Answer These First)
+
+1. **Does HF Inference API support vision models?**
+   - Test Phi-3.5-vision-instruct with simple image
+   - Test Llama-3.2-11B-Vision-Instruct
+   - Test Qwen2-VL-72B-Instruct
+
+2. **What's the image input format?**
+   - Base64 encoding in messages?
+   - Direct URL support?
+   - File path support?
+
+3. **What's the response structure?**
+   - JSON schema format
+   - Error patterns
+   - Rate limits and quotas
+
+## Next Actions
+
+**Phase 0 starts with:**
+
+1. Research HF Inference API documentation for vision support
+2. Test simple vision API call with Phi-3.5-vision-instruct
+3. Document working pattern or confirm API doesn't support vision
+4. Decision gate: GO to Phase 1 or pivot to backup options

README.md

@@ -396,19 +396,71 @@ When /update-dev runs:
 4. Empties PLAN.md, TODO.md, CHANGELOG.md back to templates
 5. Marks dev record status as ✅ Resolved
 
-### AI Context Loading
-
-**When new AI session starts:**
-
-- Read CHANGELOG.md for current session context
-  - CHANGELOG contains problem-tagged changes from ongoing work
-  - Structured by `### [PROBLEM: ...]` headers
-  - Source of truth for what changed during active session
-- Read last 2-3 dev records for historical context
-  - Dev records sorted by date: newest `dev_YYMMDD_##_title.md` files first
-  - Provides context from previous sessions
-- Read README.md for project structure
-- Read CLAUDE.md for coding standards
-- Check PLAN.md/TODO.md for active work (if any)
-
-**Context Priority:** CHANGELOG (current session) + Latest dev records (historical) = Complete context
+### AI Context Loading Protocol
+
+**MANDATORY - Execute in exact order. NO delegating to sub-agents for initial context.**
+
+**Phase 1: Current State (What's happening NOW)**
+
+1. **Read workspace files:**
+   - `CHANGELOG.md` - Active session changes (reverse chronological, newest first)
+   - `PLAN.md` - Current implementation plan (if exists)
+   - `TODO.md` - Active task tracking (if exists)
+
+2. **Read actual outputs (CRITICAL - verify claims, don't trust summaries):**
+   - Latest files in `output/` folder (sorted by timestamp, newest first)
+   - For GAIA projects: Read latest `output/gaia_results_*.json` completely
+     - Check `metadata.score_percent` and `metadata.correct_count`
+     - Read ALL `results[].submitted_answer` to understand failure patterns
+     - Identify error categories (vision failures, tool errors, wrong answers)
+   - For test projects: Read latest test output logs
+   - **Purpose:** Ground truth of what ACTUALLY happened, not what was claimed
+
+**Phase 2: Recent History (What was done recently)**
+
+3. **Read last 3 dev records from `dev/` folder:**
+   - Sort by filename (newest `dev_YYMMDD_##_title.md` first)
+   - Read: Problem Description, Key Decisions, Outcome, Changelog
+   - **Cross-verify:** Compare dev record claims with actual output files
+   - **Red flag:** If dev record says "25% accuracy" but latest JSON shows "0%", prioritize JSON truth
+
+**Phase 3: Project Structure (How it works)**
+
+4. **Read README.md sections in order:**
+   - Section 1: Overview (purpose, objectives)
+   - Section 2: Architecture (tech stack, components, diagrams)
+   - Section 3: Specification (current state, workflows, requirements)
+   - Section 4: Workflow (this protocol)
+
+5. **Read CLAUDE.md:**
+   - Project-specific coding standards
+   - Usually empty (inherits from global ~/.claude/CLAUDE.md)
+
+**Phase 4: Code Structure (Critical files)**
+
+6. **Identify critical files from README.md Architecture section:**
+   - Note main entry points (e.g., `app.py`)
+   - Note core logic files (e.g., `src/agent/graph.py`, `src/agent/llm_client.py`)
+   - Note tool implementations (e.g., `src/tools/*.py`)
+   - **DO NOT read these yet** - only note their locations for later reference
+
+**Verification Checklist (Before claiming "I have context"):**
+
+- [ ] I personally read CHANGELOG.md, PLAN.md, TODO.md (not delegated)
+- [ ] I personally read latest output files (JSON results, test logs, etc.)
+- [ ] I know the ACTUAL current accuracy/status from output files
+- [ ] I read last 3 dev records and cross-verified claims with output data
+- [ ] I read README.md sections 1-4 completely
+- [ ] I can answer: "What is the current status and why?"
+- [ ] I can answer: "What were the last 3 major changes and their outcomes?"
+- [ ] I can answer: "What specific problems exist based on latest outputs?"
+
+**Anti-Patterns (NEVER do these):**
+
+- ❌ Delegate initial context loading to Explore/Task agents
+- ❌ Trust dev record claims without verifying against output files
+- ❌ Skip reading actual output data (JSON results, logs, test outputs)
+- ❌ Claim "I have context" after only reading summaries
+- ❌ Read code files before understanding current state from outputs
+
+**Context Priority:** Latest Outputs (ground truth) > CHANGELOG (active work) > Dev Records (history) > README (structure)

TODO.md

@@ -1,18 +0,0 @@
-# TODO List
-
-**Session Date:** [YYYY-MM-DD]
-**Dev Record:** [link to dev/dev_YYMMDD_##_concise_title.md]
-
----
-
-## Active Tasks
-
-- [ ] [Task 1]
-- [ ] [Task 2]
-- [ ] [Task 3]
-
----
-
-## Completed Tasks
-
-- [x] [Completed task 1]

app.py

@@ -52,8 +52,8 @@ def export_results_to_json(
 ) -> str:
     """Export evaluation results to JSON file for easy processing.
 
-    - Local: Saves to ~/Downloads/gaia_results_TIMESTAMP.json
-    - HF Spaces: Saves to ./exports/gaia_results_TIMESTAMP.json
+    - All environments: Saves to ./_cache/gaia_results_TIMESTAMP.json
+    - Gradio serves file from _cache/ folder via gr.File component
     - Format: Clean JSON with full error messages, no truncation
     - Single source: Both UI and JSON use identical results_log data
 
@@ -68,16 +68,10 @@ def export_results_to_json(
     timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
     filename = f"gaia_results_{timestamp}.json"
 
-    # Detect environment: HF Spaces or local
-    if os.getenv("SPACE_ID"):
-        # HF Spaces: save to local exports directory for Gradio to serve
-        export_dir = os.path.join(os.getcwd(), "exports")
-        os.makedirs(export_dir, exist_ok=True)
-        filepath = os.path.join(export_dir, filename)
-    else:
-        # Local: save to Downloads folder
-        downloads_dir = os.path.expanduser("~/Downloads")
-        filepath = os.path.join(downloads_dir, filename)
+    # Save to _cache/ folder (internal runtime storage, not accessible via HF UI)
+    cache_dir = os.path.join(os.getcwd(), "_cache")
+    os.makedirs(cache_dir, exist_ok=True)
+    filepath = os.path.join(cache_dir, filename)
 
     # Build JSON structure
     metadata = {
@@ -110,7 +104,9 @@ def export_results_to_json(
 
         # Add correctness if available
         if result.get("Correct?"):
-            result_dict["correct"] = True if result.get("Correct?") == "✅ Yes" else False
+            result_dict["correct"] = (
+                True if result.get("Correct?") == "✅ Yes" else False
+            )
 
         # Add ground truth answer if available
         if result.get("Ground Truth Answer"):
@@ -295,7 +291,10 @@ def process_single_question(agent, item, index, total):
 
 
 def run_and_submit_all(
-    llm_provider: str, enable_fallback: bool, question_limit: int = 0, profile: gr.OAuthProfile | None = None
+    llm_provider: str,
+    enable_fallback: bool,
+    question_limit: int = 0,
+    profile: gr.OAuthProfile | None = None,
 ):
     """
     Fetches all questions, runs the BasicAgent on them, submits all answers,
@@ -355,7 +354,11 @@ def run_and_submit_all(
             return "Fetched questions list is empty or invalid format.", None, ""
 
         # Apply question limit if configured (from UI or .env)
-        limit = int(question_limit) if question_limit > 0 else int(os.getenv("DEBUG_QUESTION_LIMIT", "0"))
+        limit = (
+            int(question_limit)
+            if question_limit > 0
+            else int(os.getenv("DEBUG_QUESTION_LIMIT", "0"))
+        )
         if limit > 0:
             questions_data = questions_data[:limit]
             logger.warning(f"DEBUG MODE: Limited to first {limit} questions")
@@ -405,7 +408,9 @@ def run_and_submit_all(
             result = future.result()
 
             # Compare with ground truth if available
-            is_correct = ground_truth.compare_answer(result["task_id"], result["answer"])
+            is_correct = ground_truth.compare_answer(
+                result["task_id"], result["answer"]
+            )
 
             # Get ground truth answer and metadata (fetch once)
             gt_answer = ground_truth.get_answer(result["task_id"])
@@ -653,7 +658,11 @@ with gr.Blocks() as demo:
 
             run_button.click(
                 fn=run_and_submit_all,
-                inputs=[eval_llm_provider_dropdown, eval_enable_fallback_checkbox, eval_question_limit],
+                inputs=[
+                    eval_llm_provider_dropdown,
+                    eval_enable_fallback_checkbox,
+                    eval_question_limit,
+                ],
                 outputs=[status_output, results_table, export_output],
             )
 

dev/dev_260104_17_json_export_system.md

@@ -38,20 +38,20 @@
 - ❌ Hard to parse programmatically
 - ❌ Not suitable for error logs with technical details
 
-### **Decision 2: Environment-Aware Export Paths**
+### **Decision 2: Unified Output Folder**
 
 **Why chosen:**
 
-- ✅ Local development: Save to `~/Downloads` (user's familiar location)
-- ✅ HF Spaces: Save to `./exports` (accessible by Gradio file server)
-- ✅ Detect environment via `SPACE_ID` environment variable
-- ✅ Automatic directory creation if missing
+- ✅ All environments: Save to `./output/` (consistent location)
+- ✅ Gradio serves from any folder via `gr.File(type="filepath")`
+- ✅ No environment detection needed
+- ✅ Matches project structure expectations
 
 **Trade-offs:**
 
-- **Pro:** Works seamlessly in both environments without configuration
-- **Pro:** Users know where to find files based on context
-- **Con:** Slight complexity in path logic (acceptable for portability)
+- **Pro:** Single code path for local and HF Spaces
+- **Pro:** No confusion about file locations
+- **Pro:** Simpler code, easier maintenance
 
 ### **Decision 3: gr.File Download Button over Textbox Display**
 

exports/gaia_results_20260104_005516.md

@@ -1,35 +0,0 @@
-# GAIA Agent Evaluation Results
-
-**Generated:** 2026-01-04 00:55:16
-
-## Submission Status
-
-Submission Successful!
-User: mangoobee
-Overall Score: 0.0% (0/20 correct)
-Message: Score calculated successfully: 0/20 total questions answered correctly (20 valid tasks attempted). Score did not improve previous record, leaderboard not updated.
-
-## Questions and Answers
-
-| Task ID | Question | Submitted Answer |
-|---------|----------|------------------|
-| 8e867cd7-cff9-4e6c-867a-ff5ddc2550be | How many studio albums were published by Mercedes Sosa between 2000 and 2009 (included)? You can ... | ERROR: No evidence collected. Details: Planning error: Exception: Planning failed with all LLMs. ... |
-| a1e91b78-d3d8-4675-bb8d-62741b4b68a6 | In the video https://www.youtube.com/watch?v=L1vXCYZAYYM, what is the highest number of bird spec... | ERROR: No evidence collected. Details: Planning error: Exception: Planning failed with all LLMs. ... |
-| 2d83110e-a098-4ebb-9987-066c06fa42d0 | .rewsna eht sa "tfel" drow eht fo etisoppo eht etirw ,ecnetnes siht dnatsrednu uoy fI | ERROR: No evidence collected. Details: Planning error: Exception: Planning failed with all LLMs. ... |
-| cca530fc-4052-43b2-b130-b30968d8aa44 | Review the chess position provided in the image. It is black's turn. Provide the correct next mov... | ERROR: No evidence collected. Details: Planning error: Exception: Planning failed with all LLMs. ... |
-| 4fc2f1ae-8625-45b5-ab34-ad4433bc21f8 | Who nominated the only Featured Article on English Wikipedia about a dinosaur that was promoted i... | ERROR: No evidence collected. Details: Planning error: Exception: Planning failed with all LLMs. ... |
-| 6f37996b-2ac7-44b0-8e68-6d28256631b4 | Given this table defining * on the set S = {a, b, c, d, e}  \|*\|a\|b\|c\|d\|e\| \|---\|---\|---\... | ERROR: No evidence collected. Details: Planning error: Exception: Planning failed with all LLMs. ... |
-| 9d191bce-651d-4746-be2d-7ef8ecadb9c2 | Examine the video at https://www.youtube.com/watch?v=1htKBjuUWec.  What does Teal'c say in respon... | ERROR: No evidence collected. Details: Planning error: Exception: Planning failed with all LLMs. ... |
-| cabe07ed-9eca-40ea-8ead-410ef5e83f91 | What is the surname of the equine veterinarian mentioned in 1.E Exercises from the chemistry mate... | ERROR: No evidence collected. Details: Planning error: Exception: Planning failed with all LLMs. ... |
-| 3cef3a44-215e-4aed-8e3b-b1e3f08063b7 | I'm making a grocery list for my mom, but she's a professor of botany and she's a real stickler w... | ERROR: No evidence collected. Details: Planning error: Exception: Planning failed with all LLMs. ... |
-| 99c9cc74-fdc8-46c6-8f8d-3ce2d3bfeea3 | Hi, I'm making a pie but I could use some help with my shopping list. I have everything I need fo... | ERROR: No evidence collected. Details: Planning error: Exception: Planning failed with all LLMs. ... |
-| 305ac316-eef6-4446-960a-92d80d542f82 | Who did the actor who played Ray in the Polish-language version of Everybody Loves Raymond play i... | ERROR: No evidence collected. Details: Planning error: Exception: Planning failed with all LLMs. ... |
-| f918266a-b3e0-4914-865d-4faa564f1aef | What is the final numeric output from the attached Python code? | ERROR: No evidence collected. Details: Planning error: Exception: Planning failed with all LLMs. ... |
-| 3f57289b-8c60-48be-bd80-01f8099ca449 | How many at bats did the Yankee with the most walks in the 1977 regular season have that same sea... | ERROR: No evidence collected. Details: Planning error: Exception: Planning failed with all LLMs. ... |
-| 1f975693-876d-457b-a649-393859e79bf3 | Hi, I was out sick from my classes on Friday, so I'm trying to figure out what I need to study fo... | ERROR: No evidence collected. Details: Planning error: Exception: Planning failed with all LLMs. ... |
-| 840bfca7-4f7b-481a-8794-c560c340185d | On June 6, 2023, an article by Carolyn Collins Petersen was published in Universe Today. This art... | ERROR: No evidence collected. Details: Planning error: Exception: Planning failed with all LLMs. ... |
-| bda648d7-d618-4883-88f4-3466eabd860e | Where were the Vietnamese specimens described by Kuznetzov in Nedoshivina's 2010 paper eventually... | ERROR: No evidence collected. Details: Planning error: Exception: Planning failed with all LLMs. ... |
-| cf106601-ab4f-4af9-b045-5295fe67b37d | What country had the least number of athletes at the 1928 Summer Olympics? If there's a tie for a... | ERROR: No evidence collected. Details: Planning error: Exception: Planning failed with all LLMs. ... |
-| a0c07678-e491-4bbc-8f0b-07405144218f | Who are the pitchers with the number before and after Taishō Tamai's number as of July 2023? Give... | ERROR: No evidence collected. Details: Planning error: Exception: Planning failed with all LLMs. ... |
-| 7bd855d8-463d-4ed5-93ca-5fe35145f733 | The attached Excel file contains the sales of menu items for a local fast-food chain. What were t... | ERROR: No evidence collected. Details: Planning error: Exception: Planning failed with all LLMs. ... |
-| 5a0c1adf-205e-4841-a666-7c3ef95def9d | What is the first name of the only Malko Competition recipient from the 20th Century (after 1977)... | ERROR: No evidence collected. Details: Planning error: Exception: Planning failed with all LLMs. ... |

exports/gaia_results_20260104_005610.md

@@ -1,35 +0,0 @@
-# GAIA Agent Evaluation Results
-
-**Generated:** 2026-01-04 00:56:10
-
-## Submission Status
-
-Submission Successful!
-User: mangoobee
-Overall Score: 0.0% (0/20 correct)
-Message: Score calculated successfully: 0/20 total questions answered correctly (20 valid tasks attempted). Score did not improve previous record, leaderboard not updated.
-
-## Questions and Answers
-
-| Task ID | Question | Submitted Answer |
-|---------|----------|------------------|
-| 8e867cd7-cff9-4e6c-867a-ff5ddc2550be | How many studio albums were published by Mercedes Sosa between 2000 and 2009 (included)? You can ... | ERROR: No evidence collected. Details: Planning error: Exception: Planning failed with all LLMs. ... |
-| a1e91b78-d3d8-4675-bb8d-62741b4b68a6 | In the video https://www.youtube.com/watch?v=L1vXCYZAYYM, what is the highest number of bird spec... | ERROR: No evidence collected. Details: Planning error: Exception: Planning failed with all LLMs. ... |
-| 2d83110e-a098-4ebb-9987-066c06fa42d0 | .rewsna eht sa "tfel" drow eht fo etisoppo eht etirw ,ecnetnes siht dnatsrednu uoy fI | ERROR: No evidence collected. Details: Planning error: Exception: Planning failed with all LLMs. ... |
-| cca530fc-4052-43b2-b130-b30968d8aa44 | Review the chess position provided in the image. It is black's turn. Provide the correct next mov... | ERROR: No evidence collected. Details: Planning error: Exception: Planning failed with all LLMs. ... |
-| 4fc2f1ae-8625-45b5-ab34-ad4433bc21f8 | Who nominated the only Featured Article on English Wikipedia about a dinosaur that was promoted i... | ERROR: No evidence collected. Details: Planning error: Exception: Planning failed with all LLMs. ... |
-| 6f37996b-2ac7-44b0-8e68-6d28256631b4 | Given this table defining * on the set S = {a, b, c, d, e}  \|*\|a\|b\|c\|d\|e\| \|---\|---\|---\... | ERROR: No evidence collected. Details: Planning error: Exception: Planning failed with all LLMs. ... |
-| 9d191bce-651d-4746-be2d-7ef8ecadb9c2 | Examine the video at https://www.youtube.com/watch?v=1htKBjuUWec.  What does Teal'c say in respon... | ERROR: No evidence collected. Details: Planning error: Exception: Planning failed with all LLMs. ... |
-| cabe07ed-9eca-40ea-8ead-410ef5e83f91 | What is the surname of the equine veterinarian mentioned in 1.E Exercises from the chemistry mate... | ERROR: No evidence collected. Details: Planning error: Exception: Planning failed with all LLMs. ... |
-| 3cef3a44-215e-4aed-8e3b-b1e3f08063b7 | I'm making a grocery list for my mom, but she's a professor of botany and she's a real stickler w... | ERROR: No evidence collected. Details: Planning error: Exception: Planning failed with all LLMs. ... |
-| 99c9cc74-fdc8-46c6-8f8d-3ce2d3bfeea3 | Hi, I'm making a pie but I could use some help with my shopping list. I have everything I need fo... | ERROR: No evidence collected. Details: Planning error: Exception: Planning failed with all LLMs. ... |
-| 305ac316-eef6-4446-960a-92d80d542f82 | Who did the actor who played Ray in the Polish-language version of Everybody Loves Raymond play i... | ERROR: No evidence collected. Details: Planning error: Exception: Planning failed with all LLMs. ... |
-| f918266a-b3e0-4914-865d-4faa564f1aef | What is the final numeric output from the attached Python code? | ERROR: No evidence collected. Details: Planning error: Exception: Planning failed with all LLMs. ... |
-| 3f57289b-8c60-48be-bd80-01f8099ca449 | How many at bats did the Yankee with the most walks in the 1977 regular season have that same sea... | ERROR: No evidence collected. Details: Planning error: Exception: Planning failed with all LLMs. ... |
-| 1f975693-876d-457b-a649-393859e79bf3 | Hi, I was out sick from my classes on Friday, so I'm trying to figure out what I need to study fo... | ERROR: No evidence collected. Details: Planning error: Exception: Planning failed with all LLMs. ... |
-| 840bfca7-4f7b-481a-8794-c560c340185d | On June 6, 2023, an article by Carolyn Collins Petersen was published in Universe Today. This art... | ERROR: No evidence collected. Details: Planning error: Exception: Planning failed with all LLMs. ... |
-| bda648d7-d618-4883-88f4-3466eabd860e | Where were the Vietnamese specimens described by Kuznetzov in Nedoshivina's 2010 paper eventually... | ERROR: No evidence collected. Details: Planning error: Exception: Planning failed with all LLMs. ... |
-| cf106601-ab4f-4af9-b045-5295fe67b37d | What country had the least number of athletes at the 1928 Summer Olympics? If there's a tie for a... | ERROR: No evidence collected. Details: Planning error: Exception: Planning failed with all LLMs. ... |
-| a0c07678-e491-4bbc-8f0b-07405144218f | Who are the pitchers with the number before and after Taishō Tamai's number as of July 2023? Give... | ERROR: No evidence collected. Details: Planning error: Exception: Planning failed with all LLMs. ... |
-| 7bd855d8-463d-4ed5-93ca-5fe35145f733 | The attached Excel file contains the sales of menu items for a local fast-food chain. What were t... | ERROR: No evidence collected. Details: Planning error: Exception: Planning failed with all LLMs. ... |
-| 5a0c1adf-205e-4841-a666-7c3ef95def9d | What is the first name of the only Malko Competition recipient from the 20th Century (after 1977)... | ERROR: No evidence collected. Details: Planning error: Exception: Planning failed with all LLMs. ... |

exports/gaia_results_20260104_214534.json

@@ -1,33 +0,0 @@
-{
-  "metadata": {
-    "generated": "2026-01-04 21:45:34",
-    "timestamp": "20260104_214534",
-    "total_questions": 3,
-    "execution_time_seconds": 14.57,
-    "execution_time_formatted": "0m 14s",
-    "score_percent": 5.0,
-    "correct_count": 1,
-    "total_attempted": 3
-  },
-  "submission_status": "Submission Successful!\nUser: mangoobee\nOverall Score: 5.0% (1/3 correct)\nMessage: Score calculated successfully: 1/20 total questions answered correctly (3 valid tasks attempted). Score did not improve previous record, leaderboard not updated.",
-  "results": [
-    {
-      "task_id": "8e867cd7-cff9-4e6c-867a-ff5ddc2550be",
-      "question": "How many studio albums were published by Mercedes Sosa between 2000 and 2009 (included)? You can use the latest 2022 version of english wikipedia.",
-      "submitted_answer": "Unable to answer",
-      "correct": null
-    },
-    {
-      "task_id": "a1e91b78-d3d8-4675-bb8d-62741b4b68a6",
-      "question": "In the video https://www.youtube.com/watch?v=L1vXCYZAYYM, what is the highest number of bird species to be on camera simultaneously?",
-      "submitted_answer": "ERROR: No evidence collected. Details: Tool vision failed: Exception: Vision analysis failed - Gemini and Claude both failed",
-      "correct": null
-    },
-    {
-      "task_id": "2d83110e-a098-4ebb-9987-066c06fa42d0",
-      "question": ".rewsna eht sa \"tfel\" drow eht fo etisoppo eht etirw ,ecnetnes siht dnatsrednu uoy fI",
-      "submitted_answer": "right",
-      "correct": null
-    }
-  ]
-}

exports/gaia_results_20260104_220404.json

@@ -1,33 +0,0 @@
-{
-  "metadata": {
-    "generated": "2026-01-04 22:04:04",
-    "timestamp": "20260104_220404",
-    "total_questions": 3,
-    "execution_time_seconds": 21.65,
-    "execution_time_formatted": "0m 21s",
-    "score_percent": 0.0,
-    "correct_count": 0,
-    "total_attempted": 3
-  },
-  "submission_status": "Submission Successful!\nUser: mangoobee\nOverall Score: 0.0% (0/3 correct)\nMessage: Score calculated successfully: 0/20 total questions answered correctly (3 valid tasks attempted). Score did not improve previous record, leaderboard not updated.",
-  "results": [
-    {
-      "task_id": "8e867cd7-cff9-4e6c-867a-ff5ddc2550be",
-      "question": "How many studio albums were published by Mercedes Sosa between 2000 and 2009 (included)? You can use the latest 2022 version of english wikipedia.",
-      "submitted_answer": "Unable to answer",
-      "correct": false
-    },
-    {
-      "task_id": "a1e91b78-d3d8-4675-bb8d-62741b4b68a6",
-      "question": "In the video https://www.youtube.com/watch?v=L1vXCYZAYYM, what is the highest number of bird species to be on camera simultaneously?",
-      "submitted_answer": "ERROR: No evidence collected. Details: Tool vision failed: Exception: Vision analysis failed - Gemini and Claude both failed",
-      "correct": false
-    },
-    {
-      "task_id": "2d83110e-a098-4ebb-9987-066c06fa42d0",
-      "question": ".rewsna eht sa \"tfel\" drow eht fo etisoppo eht etirw ,ecnetnes siht dnatsrednu uoy fI",
-      "submitted_answer": "満足感",
-      "correct": false
-    }
-  ]
-}

exports/gaia_results_20260104_220718.json

@@ -1,33 +0,0 @@
-{
-  "metadata": {
-    "generated": "2026-01-04 22:07:18",
-    "timestamp": "20260104_220718",
-    "total_questions": 3,
-    "execution_time_seconds": 19.42,
-    "execution_time_formatted": "0m 19s",
-    "score_percent": 5.0,
-    "correct_count": 1,
-    "total_attempted": 3
-  },
-  "submission_status": "Submission Successful!\nUser: mangoobee\nOverall Score: 5.0% (1/3 correct)\nMessage: Score calculated successfully: 1/20 total questions answered correctly (3 valid tasks attempted). Score did not improve previous record, leaderboard not updated.",
-  "results": [
-    {
-      "task_id": "8e867cd7-cff9-4e6c-867a-ff5ddc2550be",
-      "question": "How many studio albums were published by Mercedes Sosa between 2000 and 2009 (included)? You can use the latest 2022 version of english wikipedia.",
-      "submitted_answer": "3",
-      "correct": true
-    },
-    {
-      "task_id": "a1e91b78-d3d8-4675-bb8d-62741b4b68a6",
-      "question": "In the video https://www.youtube.com/watch?v=L1vXCYZAYYM, what is the highest number of bird species to be on camera simultaneously?",
-      "submitted_answer": "ERROR: No evidence collected. Details: Tool vision failed: Exception: Vision analysis failed - Gemini and Claude both failed",
-      "correct": false
-    },
-    {
-      "task_id": "2d83110e-a098-4ebb-9987-066c06fa42d0",
-      "question": ".rewsna eht sa \"tfel\" drow eht fo etisoppo eht etirw ,ecnetnes siht dnatsrednu uoy fI",
-      "submitted_answer": "Unable to answer",
-      "correct": false
-    }
-  ]
-}

exports/gaia_results_20260105_153616.json

@@ -1,85 +0,0 @@
-{
-  "metadata": {
-    "generated": "2026-01-05 15:36:16",
-    "timestamp": "20260105_153616",
-    "total_questions": 5,
-    "execution_time_seconds": 51.51,
-    "execution_time_formatted": "0m 51s",
-    "score_percent": 0.0,
-    "correct_count": 0,
-    "total_attempted": 5
-  },
-  "submission_status": "Submission Successful!\nUser: mangoobee\nOverall Score: 0.0% (0/5 correct)\nMessage: Score calculated successfully: 0/20 total questions answered correctly (5 valid tasks attempted). Score did not improve previous record, leaderboard not updated.",
-  "results": [
-    {
-      "task_id": "2d83110e-a098-4ebb-9987-066c06fa42d0",
-      "question": ".rewsna eht sa \"tfel\" drow eht fo etisoppo eht etirw ,ecnetnes siht dnatsrednu uoy fI",
-      "submitted_answer": "ERROR: No evidence collected. Details: Tool selection returned no tools - using fallback keyword matching; Tool calculator failed: SyntaxError: Invalid expression syntax: invalid syntax (<unknown>, line 1)",
-      "correct": false,
-      "ground_truth_answer": "Right",
-      "annotator_metadata": {
-        "Steps": "1. Read the instructions in reverse",
-        "Number of steps": "1",
-        "How long did this take?": "1 minute",
-        "Tools": "1. A word reversal tool / script",
-        "Number of tools": "0"
-      }
-    },
-    {
-      "task_id": "cca530fc-4052-43b2-b130-b30968d8aa44",
-      "question": "Review the chess position provided in the image. It is black's turn. Provide the correct next move for black which guarantees a win. Please provide your response in algebraic notation.",
-      "submitted_answer": "ERROR: No evidence collected. Details: Tool vision failed: Exception: Vision analysis failed - Gemini and Claude both failed",
-      "correct": false,
-      "ground_truth_answer": "Rd5",
-      "annotator_metadata": {
-        "Steps": "Step 1: Evaluate the position of the pieces in the chess position\nStep 2: Report the best move available for black: \"Rd5\"",
-        "Number of steps": "2",
-        "How long did this take?": "10 minutes",
-        "Tools": "1. Image recognition tools",
-        "Number of tools": "1"
-      }
-    },
-    {
-      "task_id": "a1e91b78-d3d8-4675-bb8d-62741b4b68a6",
-      "question": "In the video https://www.youtube.com/watch?v=L1vXCYZAYYM, what is the highest number of bird species to be on camera simultaneously?",
-      "submitted_answer": "Unable to answer",
-      "correct": false,
-      "ground_truth_answer": "3",
-      "annotator_metadata": {
-        "Steps": "1. Navigate to the YouTube link.\n2. Watch the video to see the highest number of bird species.\n3. Note the number.",
-        "Number of steps": "3",
-        "How long did this take?": "3 minutes",
-        "Tools": "1. Web browser\n2. Video parsing",
-        "Number of tools": "2"
-      }
-    },
-    {
-      "task_id": "8e867cd7-cff9-4e6c-867a-ff5ddc2550be",
-      "question": "How many studio albums were published by Mercedes Sosa between 2000 and 2009 (included)? You can use the latest 2022 version of english wikipedia.",
-      "submitted_answer": "",
-      "correct": false,
-      "ground_truth_answer": "3",
-      "annotator_metadata": {
-        "Steps": "1. I did a search for Mercedes Sosa\n2. I went to the Wikipedia page for her\n3. I scrolled down to \"Studio albums\"\n4. I counted the ones between 2000 and 2009",
-        "Number of steps": "4",
-        "How long did this take?": "5 minutes",
-        "Tools": "1. web browser\n2. google search",
-        "Number of tools": "2"
-      }
-    },
-    {
-      "task_id": "4fc2f1ae-8625-45b5-ab34-ad4433bc21f8",
-      "question": "Who nominated the only Featured Article on English Wikipedia about a dinosaur that was promoted in November 2016?",
-      "submitted_answer": "",
-      "correct": false,
-      "ground_truth_answer": "FunkMonk",
-      "annotator_metadata": {
-        "Steps": "1. Search \"Wikipedia featured articles promoted in november 2016\"\n2. Click through to the appropriate page and find the person who nominated Giganotosaurus.",
-        "Number of steps": "2",
-        "How long did this take?": "5 minutes",
-        "Tools": "1. web browser\n2. search engine",
-        "Number of tools": "2"
-      }
-    }
-  ]
-}

exports/gaia_results_20260104_064016.json → output/gaia_results_20260105_203102.json

@@ -1,110 +1,295 @@
 {
   "metadata": {
-    "generated": "2026-01-04 06:40:16",
-    "timestamp": "20260104_064016",
-    "total_questions": 20
+    "generated": "2026-01-05 20:31:02",
+    "timestamp": "20260105_203102",
+    "total_questions": 20,
+    "execution_time_seconds": 55.54,
+    "execution_time_formatted": "0m 55s",
+    "score_percent": 0.0,
+    "correct_count": 0,
+    "total_attempted": 20
   },
-  "submission_status": "Submission Successful!\nUser: mangoobee\nOverall Score: 5.0% (1/20 correct)\nMessage: Score calculated successfully: 1/20 total questions answered correctly (20 valid tasks attempted). Score did not improve previous record, leaderboard not updated.",
+  "submission_status": "Submission Successful!\nUser: mangoobee\nOverall Score: 0.0% (0/20 correct)\nMessage: Score calculated successfully: 0/20 total questions answered correctly (20 valid tasks attempted). Score did not improve previous record, leaderboard not updated.",
   "results": [
     {
-      "task_id": "8e867cd7-cff9-4e6c-867a-ff5ddc2550be",
-      "question": "How many studio albums were published by Mercedes Sosa between 2000 and 2009 (included)? You can use the latest 2022 version of english wikipedia.",
-      "submitted_answer": "Unable to answer"
+      "task_id": "cca530fc-4052-43b2-b130-b30968d8aa44",
+      "question": "Review the chess position provided in the image. It is black's turn. Provide the correct next move for black which guarantees a win. Please provide your response in algebraic notation.",
+      "submitted_answer": "ERROR: No evidence collected. Details: Tool vision failed: Exception: Vision analysis failed - Gemini and Claude both failed",
+      "correct": false,
+      "ground_truth_answer": "Rd5",
+      "annotator_metadata": {
+        "Steps": "Step 1: Evaluate the position of the pieces in the chess position\nStep 2: Report the best move available for black: \"Rd5\"",
+        "Number of steps": "2",
+        "How long did this take?": "10 minutes",
+        "Tools": "1. Image recognition tools",
+        "Number of tools": "1"
+      }
     },
     {
       "task_id": "a1e91b78-d3d8-4675-bb8d-62741b4b68a6",
       "question": "In the video https://www.youtube.com/watch?v=L1vXCYZAYYM, what is the highest number of bird species to be on camera simultaneously?",
-      "submitted_answer": "ERROR: No evidence collected. Details: Tool vision failed: Exception: Vision analysis failed - Gemini and Claude both failed"
-    },
-    {
-      "task_id": "2d83110e-a098-4ebb-9987-066c06fa42d0",
-      "question": ".rewsna eht sa \"tfel\" drow eht fo etisoppo eht etirw ,ecnetnes siht dnatsrednu uoy fI",
-      "submitted_answer": "Unable to answer"
+      "submitted_answer": "ERROR: No evidence collected. Details: Tool vision failed: Exception: Vision analysis failed - Gemini and Claude both failed",
+      "correct": false,
+      "ground_truth_answer": "3",
+      "annotator_metadata": {
+        "Steps": "1. Navigate to the YouTube link.\n2. Watch the video to see the highest number of bird species.\n3. Note the number.",
+        "Number of steps": "3",
+        "How long did this take?": "3 minutes",
+        "Tools": "1. Web browser\n2. Video parsing",
+        "Number of tools": "2"
+      }
     },
     {
-      "task_id": "cca530fc-4052-43b2-b130-b30968d8aa44",
-      "question": "Review the chess position provided in the image. It is black's turn. Provide the correct next move for black which guarantees a win. Please provide your response in algebraic notation.",
-      "submitted_answer": "ERROR: No evidence collected. Details: Tool vision failed: Exception: Vision analysis failed - Gemini and Claude both failed"
+      "task_id": "8e867cd7-cff9-4e6c-867a-ff5ddc2550be",
+      "question": "How many studio albums were published by Mercedes Sosa between 2000 and 2009 (included)? You can use the latest 2022 version of english wikipedia.",
+      "submitted_answer": "4",
+      "correct": false,
+      "ground_truth_answer": "3",
+      "annotator_metadata": {
+        "Steps": "1. I did a search for Mercedes Sosa\n2. I went to the Wikipedia page for her\n3. I scrolled down to \"Studio albums\"\n4. I counted the ones between 2000 and 2009",
+        "Number of steps": "4",
+        "How long did this take?": "5 minutes",
+        "Tools": "1. web browser\n2. google search",
+        "Number of tools": "2"
+      }
     },
     {
       "task_id": "4fc2f1ae-8625-45b5-ab34-ad4433bc21f8",
       "question": "Who nominated the only Featured Article on English Wikipedia about a dinosaur that was promoted in November 2016?",
-      "submitted_answer": "<think>\nOkay, let's tackle this question. The user is asking who nominated the only Featured Article on English Wikipedia about a dinosaur that was promoted in November 2016.\n\nFirst, I need to look through the provided evidence to find any mention of a dinosaur-related article promoted in November 2016. The evidence includes several web search results from Wikipedia pages related to November 2016 featured articles.\n\nLooking at the first result from \"Wikipedia:Today's featured article/November 2016\", the snippet mentions various topics like a RAAF officer, General Patton, a video game, and a Star Trek film. There's no mention of a dinosaur here.\n\nThe second result from \"Wikipedia:Today's featured article/recent TFAs/November 2016\" lists entries for November dates in 2016. The entries include \"Mughal-e-Azam\", \"Star Trek: First Contact\", \"Warlugulong\", \"Banksia canei\", \"SMS Lützow\", and \"Scotland national football team\". None of these seem to be about a dinosaur. Warlugulong is an art piece, and Banksia canei is a plant. SMS Lützow is a"
-    },
-    {
-      "task_id": "6f37996b-2ac7-44b0-8e68-6d28256631b4",
-      "question": "Given this table defining * on the set S = {a, b, c, d, e}\n\n|*|a|b|c|d|e|\n|---|---|---|---|---|---|\n|a|a|b|c|b|d|\n|b|b|c|a|e|c|\n|c|c|a|b|b|a|\n|d|b|e|b|e|d|\n|e|d|b|a|d|c|\n\nprovide the subset of S involved in any possible counter-examples that prove * is not commutative. Provide your answer as a comma separated list of the elements in the set in alphabetical order.",
-      "submitted_answer": "b, d, e"
+      "submitted_answer": "Unable to answer",
+      "correct": false,
+      "ground_truth_answer": "FunkMonk",
+      "annotator_metadata": {
+        "Steps": "1. Search \"Wikipedia featured articles promoted in november 2016\"\n2. Click through to the appropriate page and find the person who nominated Giganotosaurus.",
+        "Number of steps": "2",
+        "How long did this take?": "5 minutes",
+        "Tools": "1. web browser\n2. search engine",
+        "Number of tools": "2"
+      }
     },
     {
       "task_id": "9d191bce-651d-4746-be2d-7ef8ecadb9c2",
       "question": "Examine the video at https://www.youtube.com/watch?v=1htKBjuUWec.\n\nWhat does Teal'c say in response to the question \"Isn't that hot?\"",
-      "submitted_answer": "ERROR: No evidence collected. Details: Tool vision failed: Exception: Vision analysis failed - Gemini and Claude both failed"
+      "submitted_answer": "ERROR: No evidence collected. Details: Tool vision failed: Exception: Vision analysis failed - Gemini and Claude both failed",
+      "correct": false,
+      "ground_truth_answer": "Extremely",
+      "annotator_metadata": {
+        "Steps": "1. Follow the link\n2. Watch the clip until the question \"Isn't that hot\" is asked\n3. Take note of the reply.",
+        "Number of steps": "3",
+        "How long did this take?": "2 minutes",
+        "Tools": "1. Web browser\n2. Video processing software\n3. Audio processing software",
+        "Number of tools": "1"
+      }
     },
     {
-      "task_id": "cabe07ed-9eca-40ea-8ead-410ef5e83f91",
-      "question": "What is the surname of the equine veterinarian mentioned in 1.E Exercises from the chemistry materials licensed by Marisa Alviar-Agnew & Henry Agnew under the CK-12 license in LibreText's Introductory Chemistry materials as compiled 08/21/2023?",
-      "submitted_answer": "Unable to answer"
+      "task_id": "2d83110e-a098-4ebb-9987-066c06fa42d0",
+      "question": ".rewsna eht sa \"tfel\" drow eht fo etisoppo eht etirw ,ecnetnes siht dnatsrednu uoy fI",
+      "submitted_answer": "ERROR: No evidence collected. Details: Tool calculator failed: ValueError: signal only works in main thread of the main interpreter",
+      "correct": false,
+      "ground_truth_answer": "Right",
+      "annotator_metadata": {
+        "Steps": "1. Read the instructions in reverse",
+        "Number of steps": "1",
+        "How long did this take?": "1 minute",
+        "Tools": "1. A word reversal tool / script",
+        "Number of tools": "0"
+      }
+    },
+    {
+      "task_id": "99c9cc74-fdc8-46c6-8f8d-3ce2d3bfeea3",
+      "question": "Hi, I'm making a pie but I could use some help with my shopping list. I have everything I need for the crust, but I'm not sure about the filling. I got the recipe from my friend Aditi, but she left it as a voice memo and the speaker on my phone is buzzing so I can't quite make out what she's saying. Could you please listen to the recipe and list all of the ingredients that my friend described? I only want the ingredients for the filling, as I have everything I need to make my favorite pie crust. I've attached the recipe as Strawberry pie.mp3.\n\nIn your response, please only list the ingredients, not any measurements. So if the recipe calls for \"a pinch of salt\" or \"two cups of ripe strawberries\" the ingredients on the list would be \"salt\" and \"ripe strawberries\".\n\nPlease format your response as a comma separated list of ingredients. Also, please alphabetize the ingredients.",
+      "submitted_answer": "ERROR: No evidence collected. Details: Tool parse_file failed: ValueError: Unsupported file type: .mp3. Supported: .pdf, .xlsx, .xls, .docx, .txt, .csv",
+      "correct": false,
+      "ground_truth_answer": "cornstarch, freshly squeezed lemon juice, granulated sugar, pure vanilla extract, ripe strawberries",
+      "annotator_metadata": {
+        "Steps": "Step 1: Load the file supplied to me by my user.\nStep 2: Using speech-to-text tools, convert the audio file to plain text and store it for the candidate word list:\n\n\"In a saucepan, combine ripe strawberries, granulated sugar, freshly squeezed lemon juice, and cornstarch. Cook the mixture over medium heat, stirring constantly, until it thickens to a smooth consistency. Remove from heat and stir in a dash of pure vanilla extract. Allow the strawberry pie filling to cool before using it as a delicious and fruity filling for your pie crust.\"\n\nStep 3: Evaluate the candidate word list and process it, stripping each ingredient encountered to a provisional response list:\n\nripe strawberries\ngranulated sugar\nfreshly squeezed lemon juice\ncornstarch\npure vanilla extract\n\nStep 4: Alphabetize the list of ingredients as requested by my user to create a finalized response:\n\ncornstarch\nfreshly squeezed lemon juice\ngranulated sugar\npure vanilla extract\nripe strawberries\n\nStep 5: Report the correct response to my user:\n\n\"cornstarch\nfreshly squeezed lemon juice\ngranulated sugar\npure vanilla extract\nripe strawberries\"",
+        "Number of steps": "5",
+        "How long did this take?": "3 minutes",
+        "Tools": "1. A file interface\n2. A speech-to-text tool",
+        "Number of tools": "2"
+      }
     },
     {
       "task_id": "3cef3a44-215e-4aed-8e3b-b1e3f08063b7",
       "question": "I'm making a grocery list for my mom, but she's a professor of botany and she's a real stickler when it comes to categorizing things. I need to add different foods to different categories on the grocery list, but if I make a mistake, she won't buy anything inserted in the wrong category. Here's the list I have so far:\n\nmilk, eggs, flour, whole bean coffee, Oreos, sweet potatoes, fresh basil, plums, green beans, rice, corn, bell pepper, whole allspice, acorns, broccoli, celery, zucchini, lettuce, peanuts\n\nI need to make headings for the fruits and vegetables. Could you please create a list of just the vegetables from my list? If you could do that, then I can figure out how to categorize the rest of the list into the appropriate categories. But remember that my mom is a real stickler, so make sure that no botanical fruits end up on the vegetable list, or she won't get them when she's at the store. Please alphabetize the list of vegetables, and place each item in a comma separated list.",
-      "submitted_answer": "acorns, bell pepper, broccoli, celery, green beans, lettuce, zucchini"
+      "submitted_answer": "acorns, bell pepper, broccoli, celery, green beans, lettuce, zucchini",
+      "correct": false,
+      "ground_truth_answer": "broccoli, celery, fresh basil, lettuce, sweet potatoes",
+      "annotator_metadata": {
+        "Steps": "Step 1: Evaluate the list provided by my user, eliminating objects which are neither fruits nor vegetables:\nsweet potatoes, fresh basil, plums, green beans, rice, corn, bell pepper, whole allspice, acorns, broccoli, celery, zucchini, lettuce, peanuts\nStep 2: Remove all items from the list which are botanical fruits, leaving a list of vegetables:\nsweet potatoes, fresh basil, broccoli, celery, lettuce\nStep 3: Alphabetize the remaining list as requested by my user:\nbroccoli, celery, fresh basil, lettuce, sweet potatoes\nStep 4: Provide the correct response in the requested format:\n\"broccoli\ncelery\nfresh basil\nlettuce\nsweet potatoes\"",
+        "Number of steps": "4",
+        "How long did this take?": "5 minutes",
+        "Tools": "No tools required",
+        "Number of tools": "0"
+      }
     },
     {
-      "task_id": "99c9cc74-fdc8-46c6-8f8d-3ce2d3bfeea3",
-      "question": "Hi, I'm making a pie but I could use some help with my shopping list. I have everything I need for the crust, but I'm not sure about the filling. I got the recipe from my friend Aditi, but she left it as a voice memo and the speaker on my phone is buzzing so I can't quite make out what she's saying. Could you please listen to the recipe and list all of the ingredients that my friend described? I only want the ingredients for the filling, as I have everything I need to make my favorite pie crust. I've attached the recipe as Strawberry pie.mp3.\n\nIn your response, please only list the ingredients, not any measurements. So if the recipe calls for \"a pinch of salt\" or \"two cups of ripe strawberries\" the ingredients on the list would be \"salt\" and \"ripe strawberries\".\n\nPlease format your response as a comma separated list of ingredients. Also, please alphabetize the ingredients.",
-      "submitted_answer": "ERROR: No evidence collected. Details: Tool vision failed: Exception: Vision analysis failed - Gemini and Claude both failed"
+      "task_id": "6f37996b-2ac7-44b0-8e68-6d28256631b4",
+      "question": "Given this table defining * on the set S = {a, b, c, d, e}\n\n|*|a|b|c|d|e|\n|---|---|---|---|---|---|\n|a|a|b|c|b|d|\n|b|b|c|a|e|c|\n|c|c|a|b|b|a|\n|d|b|e|b|e|d|\n|e|d|b|a|d|c|\n\nprovide the subset of S involved in any possible counter-examples that prove * is not commutative. Provide your answer as a comma separated list of the elements in the set in alphabetical order.",
+      "submitted_answer": "ERROR: No evidence collected. Details: Tool parse_file failed: FileNotFoundError: Text file not found: path_to_the_table_file.csv",
+      "correct": false,
+      "ground_truth_answer": "b, e",
+      "annotator_metadata": {
+        "Steps": "1. Compile the markdown.\n2. Look at the table across the diagonal to see if any portions are not symmetrical.\n3. See that b * e != e * b, but all others are symmetrical.",
+        "Number of steps": "3",
+        "How long did this take?": "5 minutes",
+        "Tools": "1. Markdown",
+        "Number of tools": "1"
+      }
     },
     {
       "task_id": "305ac316-eef6-4446-960a-92d80d542f82",
       "question": "Who did the actor who played Ray in the Polish-language version of Everybody Loves Raymond play in Magda M.? Give only the first name.",
-      "submitted_answer": "<think>\nOkay, let's tackle this question. The user is asking who the actor who played Ray in the Polish-language version of \"Everybody Loves Raymond\" played in \"Magda M.,\" and they want just the first name.\n\nFirst, I need to look through the provided evidence to find the actor's name. The key part here is identifying the Polish dubbing actor for Ray. Let's check the evidence snippets.\n\nLooking at Evidence 1, the web search results. The first result mentions Peter Boyle as Frank Barone in the sitcom, but that's the original US version. The second result from Screen Rant says Ray Romano plays Ray Barone. The third result from Yahoo also mentions Ray Romano as Ray Barone. The fourth result is an Instagram post titled \"Polish Dubbing Cast Everybody Loves Raymond Ray\" but the snippet doesn't mention the actor's name. The fifth result is a YouTube video about Ray Romano, but that's the original actor.\n\nWait, the user is asking about the Polish-language version. The original actor is Ray Romano, but in Polish dubbing, a different actor would voice him. However, none of the evidence snippets explicitly state the name of the Polish actor who dubbed Ray Romano. The fourth result's"
+      "submitted_answer": "Bartłomiej",
+      "correct": false,
+      "ground_truth_answer": "Wojciech",
+      "annotator_metadata": {
+        "Steps": "1. Search \"Polish-language version of Everybody Loves Raymond\" and pull up the Wiki page for Wszyscy kochają Romana.\n2. See that Bartłomiej Kasprzykowski is marked as playing Ray and go to his Wiki page.\n3. See that he is stated to have played Wojciech Płaska in Magda M.",
+        "Number of steps": "3",
+        "How long did this take?": "5 minutes",
+        "Tools": "None",
+        "Number of tools": "0"
+      }
+    },
+    {
+      "task_id": "cabe07ed-9eca-40ea-8ead-410ef5e83f91",
+      "question": "What is the surname of the equine veterinarian mentioned in 1.E Exercises from the chemistry materials licensed by Marisa Alviar-Agnew & Henry Agnew under the CK-12 license in LibreText's Introductory Chemistry materials as compiled 08/21/2023?",
+      "submitted_answer": "Unable to answer",
+      "correct": false,
+      "ground_truth_answer": "Louvrier",
+      "annotator_metadata": {
+        "Steps": "1. Search for \"1.E Exercises LibreText Introductory Chemistry\"\n2. Read to see the horse doctor mentioned.",
+        "Number of steps": "2",
+        "How long did this take?": "5 minutes",
+        "Tools": "1. Web browser\n2. Search engine",
+        "Number of tools": "2"
+      }
     },
     {
       "task_id": "f918266a-b3e0-4914-865d-4faa564f1aef",
       "question": "What is the final numeric output from the attached Python code?",
-      "submitted_answer": "ERROR: No evidence collected. Details: Tool parse_file failed: ValueError: Unsupported file type: . Supported: .pdf, .xlsx, .xls, .docx, .txt, .csv"
+      "submitted_answer": "ERROR: No evidence collected. Details: Tool parse_file failed: ValueError: Unsupported file type: . Supported: .pdf, .xlsx, .xls, .docx, .txt, .csv",
+      "correct": false,
+      "ground_truth_answer": "0",
+      "annotator_metadata": {
+        "Steps": "1. Run the attached Python code",
+        "Number of steps": "1",
+        "How long did this take?": "30 seconds",
+        "Tools": "1. Python",
+        "Number of tools": "1"
+      }
     },
     {
       "task_id": "3f57289b-8c60-48be-bd80-01f8099ca449",
       "question": "How many at bats did the Yankee with the most walks in the 1977 regular season have that same season?",
-      "submitted_answer": "<think>\nOkay, let's see. The user is asking about the number of at-bats for the Yankee player who had the most walks in the 1977 regular season. \n\nFirst, I need to figure out who that player is. The evidence provided includes a few sources. The first one is the Wikipedia page for the 1977 Yankees season, but the snippet doesn't mention walks. The third result is from ESPN's MLB Pitching Leaders, but that's about pitchers' walks, not hitters. The fourth result is from MLB.com's 1977 Yankees stats. Let me check that snippet.\n\nLooking at the snippet from MLB.com, there's a table with player stats. The first entry is Graig Nettles with 158 games and 589 at-bats. Then Chris Chambliss has 157 games and 600 at-bats. The walks (BB) for Nettles are 37, and for Chambliss it's 17. Wait, that can't be right. Wait, maybe I'm misreading. Let me check again. The columns are labeled BB (walks) and SO (strikeouts). For Graig Nettles"
+      "submitted_answer": "589",
+      "correct": false,
+      "ground_truth_answer": "519",
+      "annotator_metadata": {
+        "Steps": "1. Search \"yankee stats\" to find their MLB stats page.\n2. Set the data to the 1977 regular season.\n3. Sort to find the most walks.\n4. See how many at bats the player had.",
+        "Number of steps": "4",
+        "How long did this take?": "5 minutes",
+        "Tools": "1. web browser\n2. search engine",
+        "Number of tools": "2"
+      }
     },
     {
       "task_id": "1f975693-876d-457b-a649-393859e79bf3",
       "question": "Hi, I was out sick from my classes on Friday, so I'm trying to figure out what I need to study for my Calculus mid-term next week. My friend from class sent me an audio recording of Professor Willowbrook giving out the recommended reading for the test, but my headphones are broken :(\n\nCould you please listen to the recording for me and tell me the page numbers I'm supposed to go over? I've attached a file called Homework.mp3 that has the recording. Please provide just the page numbers as a comma-delimited list. And please provide the list in ascending order.",
-      "submitted_answer": "Unable to answer"
+      "submitted_answer": "ERROR: No evidence collected. Details: Tool parse_file failed: ValueError: Unsupported file type: .mp3. Supported: .pdf, .xlsx, .xls, .docx, .txt, .csv",
+      "correct": false,
+      "ground_truth_answer": "132, 133, 134, 197, 245",
+      "annotator_metadata": {
+        "Steps": "Step 1: Load the file supplied by my user.\nStep 2: Using audio processing tools, convert the text of the audio file to speech:\n\n\"Before you all go, I want to remind you that the midterm is next week. Here's a little hint; you should be familiar with the differential equations on page 245, problems that are very similar to problems 32, 33, and 44 from that page might be on the test. And also some of you might want to brush up on the last page in the integration section, page 197. I know some of you struggled on last week's quiz. I foresee problem 22 from page 197 being on your midterm. Oh, and don't forget to brush up on the section on related rates, on pages 132, 133, and 134.\"\n\nStep 3: Evaluate the converted audio, recording each instance of page numbers: 245, 197, 197, 132, 133, 134\nStep 4: Sort the page numbers in ascending order, omitting duplicates, and store this list as the correct answer to my user's request: 132, 133, 134, 197, 245\nStep 5: Report the correct response to my user: \"132, 133, 134, 197, 245\"",
+        "Number of steps": "5",
+        "How long did this take?": "2 minutes",
+        "Tools": "1. A file interface\n2. A speech-to-text audio processing tool",
+        "Number of tools": "2"
+      }
+    },
+    {
+      "task_id": "7bd855d8-463d-4ed5-93ca-5fe35145f733",
+      "question": "The attached Excel file contains the sales of menu items for a local fast-food chain. What were the total sales that the chain made from food (not including drinks)? Express your answer in USD with two decimal places.",
+      "submitted_answer": "ERROR: No evidence collected. Details: Tool parse_file failed: ValueError: Unsupported file type: . Supported: .pdf, .xlsx, .xls, .docx, .txt, .csv",
+      "correct": false,
+      "ground_truth_answer": "89706.00",
+      "annotator_metadata": {
+        "Steps": "1. Open the attached file.\n2. Read the columns representing different menu items. Note that they all appear to be food except for the “soda” column.\n3. Write a function to sum the relevant columns.\n4. Ensure the answer follows the specified formatting.",
+        "Number of steps": "4",
+        "How long did this take?": "5 minutes",
+        "Tools": "1. Excel\n2. Calculator",
+        "Number of tools": "2"
+      }
     },
     {
       "task_id": "840bfca7-4f7b-481a-8794-c560c340185d",
       "question": "On June 6, 2023, an article by Carolyn Collins Petersen was published in Universe Today. This article mentions a team that produced a paper about their observations, linked at the bottom of the article. Find this paper. Under what NASA award number was the work performed by R. G. Arendt supported by?",
-      "submitted_answer": "Unable to answer"
+      "submitted_answer": "Unable to answer",
+      "correct": false,
+      "ground_truth_answer": "80GSFC21M0002",
+      "annotator_metadata": {
+        "Steps": "1. Google \"June 6, 2023 Carolyn Collins Petersen Universe Today\"\n2. Find the relevant link to the scientific paper and follow that link\n3. Open the PDF. \n4. Search for NASA award number",
+        "Number of steps": "4",
+        "How long did this take?": "5 minutes",
+        "Tools": "1. Web browser\n2. Search engine\n3. Access to academic journal websites",
+        "Number of tools": "2"
+      }
     },
     {
       "task_id": "bda648d7-d618-4883-88f4-3466eabd860e",
       "question": "Where were the Vietnamese specimens described by Kuznetzov in Nedoshivina's 2010 paper eventually deposited? Just give me the city name without abbreviations.",
-      "submitted_answer": "<think>\nOkay, let's tackle this question. The user is asking where the Vietnamese specimens described by Kuznetzov in Nedoshivina's 2010 paper were eventually deposited. They want just the city name without abbreviations.\n\nFirst, I need to look through the provided evidence to find any mention of deposition locations. Let's go through each of the web search results.\n\nEvidence 1's snippet talks about specimens collected at Mê Linh biological station in North Vietnam, Vinh Phuc Province. But it doesn't mention where they were deposited. The other entries in Evidence 1's results mention Sapa, Lao Cai Province, but that's about museum specimens from Vietnam in general, not specifically Kuznetzov's. The third result mentions the Field Museum of Natural History, Australian National Wildlife Collection, etc., but again, not specific to Kuznetzov's specimens. The fourth result is about central Vietnam specimens being different but doesn't mention deposition. The last result is about Nedoshivina's Google Scholar profile, which doesn't help here.\n\nLooking back, the first result's snippet mentions Mê Linh biological station where specimens were collected. However, the question is about where they were deposited, not where"
+      "submitted_answer": "Unable to answer",
+      "correct": false,
+      "ground_truth_answer": "Saint Petersburg",
+      "annotator_metadata": {
+        "Steps": "1. Search \"Kuznetzov Nedoshivina 2010\"\n2. Find the 2010 paper \"A catalogue of type specimens of the Tortricidae described by V. I. Kuznetzov from Vietnam and deposited in the Zoological Institute, St. Petersburg\"",
+        "Number of steps": "2",
+        "How long did this take?": "5 minutes",
+        "Tools": "1. search engine",
+        "Number of tools": "1"
+      }
     },
     {
       "task_id": "cf106601-ab4f-4af9-b045-5295fe67b37d",
       "question": "What country had the least number of athletes at the 1928 Summer Olympics? If there's a tie for a number of athletes, return the first in alphabetical order. Give the IOC country code as your answer.",
-      "submitted_answer": "CUB"
+      "submitted_answer": "CUB, MON",
+      "correct": false,
+      "ground_truth_answer": "CUB",
+      "annotator_metadata": {
+        "Steps": "1. Look up the 1928 Summer Olympics on Wikipedia\n2. Look at a table of athletes from countries.\n3. See that two countries had 1 and 2 athletes, so disregard those and choose the Cuba as CUB.",
+        "Number of steps": "3",
+        "How long did this take?": "5 minutes",
+        "Tools": "None",
+        "Number of tools": "0"
+      }
     },
     {
       "task_id": "a0c07678-e491-4bbc-8f0b-07405144218f",
       "question": "Who are the pitchers with the number before and after Taishō Tamai's number as of July 2023? Give them to me in the form Pitcher Before, Pitcher After, use their last names only, in Roman characters.",
-      "submitted_answer": "<think>\nOkay, let's see. The user is asking for the pitchers with the numbers immediately before and after Taishō Tamai's number as of July 2023, using their last names in Roman characters.\n\nFirst, I need to find out what number Taishō Tamai wears. Looking at the evidence provided, the fifth result from the web search shows a 2023 Hokkaido Nippon-Ham Fighters Individual Pitching list. The entry for Tamai, Taisho is listed with the number 50. So his number is 50.\n\nNext, I need to check the numbers before and after 50. The same list in the fifth result shows Tanaka, Eito with number 2, Tanaka, Seigi with 47, and Tateno, Kazuaki with 4. Wait, that doesn't seem to be in order. Maybe the list isn't sorted by numbers. Let me check again. The snippet shows \"Tamai, Taisho, 50 ; Tanaka, Eito, 2 ; Tanaka, Seigi, 47 ; Tateno, Kazuaki, 4\". Hmm, that's not a sequential list. Maybe"
-    },
-    {
-      "task_id": "7bd855d8-463d-4ed5-93ca-5fe35145f733",
-      "question": "The attached Excel file contains the sales of menu items for a local fast-food chain. What were the total sales that the chain made from food (not including drinks)? Express your answer in USD with two decimal places.",
-      "submitted_answer": "ERROR: No evidence collected. Details: Tool parse_file failed: ValueError: Unsupported file type: . Supported: .pdf, .xlsx, .xls, .docx, .txt, .csv"
+      "submitted_answer": "Unable to answer",
+      "correct": false,
+      "ground_truth_answer": "Yoshida, Uehara",
+      "annotator_metadata": {
+        "Steps": "1. Look up Taishō Tamai on Wikipedia\n2. See the pitcher with the number 18 (before) is Kōsei Yoshida and number 20 (after) is Kenta Uehara",
+        "Number of steps": "2",
+        "How long did this take?": "5 minutes",
+        "Tools": "1. Wikipedia",
+        "Number of tools": "1"
+      }
     },
     {
       "task_id": "5a0c1adf-205e-4841-a666-7c3ef95def9d",
       "question": "What is the first name of the only Malko Competition recipient from the 20th Century (after 1977) whose nationality on record is a country that no longer exists?",
-      "submitted_answer": "Unable to answer"
+      "submitted_answer": "Jan",
+      "correct": false,
+      "ground_truth_answer": "Claus",
+      "annotator_metadata": {
+        "Steps": "1. Look at the Malko Competition page on Wikipedia\n2. Scan the winners to see that the 1983 winner, Claus Peter Flor is stated to be from East Germany.",
+        "Number of steps": "2",
+        "How long did this take?": "5-10 minutes",
+        "Tools": "None",
+        "Number of tools": "0"
+      }
     }
   ]
 }