Stage 5: Performance optimization - retry logic, Groq integration, improved prompts

- Added exponential backoff retry logic (3 attempts, 1s/2s/4s delays)
- Integrated Groq as 4th free LLM tier (Llama 3.1 70B)
- Improved tool selection prompts with few-shot examples
- Added graceful vision question skip logic
- Relaxed calculator validation (graceful errors)
- Improved TOOLS schema descriptions
- All 99 tests passing

🤖 Generated with Claude Code

Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>

CHANGELOG.md

@@ -2,143 +2,103 @@
 
 **Session Date:** 2026-01-04
 
-**Dev Records:**
-
-- dev/dev_260102_15_stage4_mvp_real_integration.md (recovered)
-- dev/dev_260103_16_huggingface_llm_integration.md (cleaned up)
-- dev/dev_260104_17_json_export_system.md (created)
-
 ## Changes Made
 
-### Modified Files
-
-- **src/agent/llm_client.py** (~150 lines added)
-  - Added `create_hf_client()` - Initialize HuggingFace InferenceClient with HF_TOKEN
-  - Added `plan_question_hf(question, available_tools, file_paths)` - Planning with Qwen 2.5 72B
-  - Added `select_tools_hf(question, plan, available_tools)` - Function calling with OpenAI-compatible tools format
-  - Added `synthesize_answer_hf(question, evidence)` - Answer synthesis from evidence
-  - Updated `plan_question()` - Added HuggingFace as middle fallback tier (Gemini → HF → Claude)
-  - Updated `select_tools_with_function_calling()` - Added HuggingFace as middle fallback tier
-  - Updated `synthesize_answer()` - Added HuggingFace as middle fallback tier
-  - Added CONFIG constant: `HF_MODEL = "Qwen/Qwen2.5-72B-Instruct"`
-  - Added import: `from huggingface_hub import InferenceClient`
-
-- **src/agent/graph.py**
-  - Updated `validate_environment()` - Added HF_TOKEN to API key validation check
-  - Updated startup logging - Shows ⚠️ WARNING if HF_TOKEN missing
-
-- **app.py**
-  - Updated `check_api_keys()` - Added HF_TOKEN status display in Test & Debug tab
-  - UI now shows: "HF_TOKEN (HuggingFace): ✓ SET" or "✗ MISSING"
-  - Added `export_results_to_json(results_log, submission_status)` - Export evaluation results as JSON
-    - Local: Saves to ~/Downloads/gaia_results_TIMESTAMP.json
-    - HF Spaces: Saves to ./exports/gaia_results_TIMESTAMP.json (fixes cloud deployment issue)
-    - JSON format: No special char escaping issues, full error messages, easy code processing
-    - Pretty formatted with indent=2, ensure_ascii=False for readability
-  - Updated `run_and_submit_all()` - ALL return paths now export results
-  - Added gr.File download button - Users can directly download results (better UX than textbox)
-  - Updated run_button click handler - Now outputs 3 values (status, table, export_path)
-
-- **src/tools/__init__.py** (Fixed earlier in session)
-  - Fixed TOOLS schema bug - Changed parameters from list to dict format
-  - Updated all tool definitions to include type/description for each parameter
-  - Added `"required_params"` field to specify required parameters
-  - Fixed Gemini function calling compatibility
-
-### Created Files
-
-- **dev/dev_260103_16_huggingface_integration.md**
-  - Comprehensive dev log documenting Stage 4 completion and HuggingFace integration
-  - Documents 3-tier fallback architecture (Gemini → HuggingFace → Claude)
-  - Includes key decisions, learnings, and test results
+### [PROBLEM: LLM Quota Exhaustion - Retry Logic]
 
-### No Files Deleted
+**Modified Files:**
 
-## Implementation Summary
+- **src/agent/llm_client.py** (~60 lines added/modified)
+  - Added `import time` and `Callable` to imports
+  - Added `retry_with_backoff()` function (lines 52-96)
+    - Exponential backoff: 1s, 2s, 4s for quota/rate limit errors
+    - Detects 429, quota, rate limit, too many requests errors
+    - Max 3 retry attempts per LLM provider
+  - Updated `plan_question()` - Wrapped all 3 provider calls (Gemini, HF, Claude) with retry_with_backoff
+  - Updated `select_tools_with_function_calling()` - Wrapped all 3 provider calls with retry_with_backoff
+  - Updated `synthesize_answer()` - Wrapped all 3 provider calls with retry_with_backoff
 
-**Stage 4: MVP - Real Integration + HuggingFace Free LLM Fallback**
+### [PROBLEM: LLM Quota Exhaustion - Groq Integration]
 
-**Goal:** Fix LLM availability issues by adding completely free alternative when Gemini quota exhausted and Claude credits depleted.
+**Modified Files:**
 
-**Problem Identified:**
-- Gemini 2.0 Flash quota exceeded (1,500 requests/day free tier limit exhausted)
-- Claude Sonnet 4.5 credit balance too low (paid tier, user's balance depleted)
-- Agent falling back to keyword-based tool selection (Stage 4 fallback mechanism)
+- **requirements.txt** (~1 line added)
+  - Added `groq>=0.4.0` - Groq API client (Llama 3.1 70B, free tier: 30 req/min)
 
-**Solution Implemented:**
-- Added HuggingFace Inference API (Qwen 2.5 72B Instruct) as free middle tier
-- 3-tier fallback chain: Gemini (free, daily quota) → HuggingFace (free, rate limited) → Claude (paid) → Keyword matching
-- All LLM functions updated: planning, tool selection with function calling, answer synthesis
+- **src/agent/llm_client.py** (~250 lines added/modified)
+  - Added `from groq import Groq` import
+  - Added `GROQ_MODEL = "llama-3.1-70b-versatile"` to CONFIG
+  - Added `create_groq_client()` function (lines 138-145)
+  - Added `plan_question_groq()` function (lines 339-398) - Planning with Groq
+  - Added `select_tools_groq()` function (lines 670-743) - Tool selection with Groq function calling
+  - Added `synthesize_answer_groq()` function (lines 977-1032) - Answer synthesis with Groq
+  - Updated `plan_question()` - New fallback chain: Gemini → HF → **Groq** → Claude (4-tier)
+  - Updated `select_tools_with_function_calling()` - New fallback chain: Gemini → HF → **Groq** → Claude (4-tier)
+  - Updated `synthesize_answer()` - New fallback chain: Gemini → HF → **Groq** → Claude (4-tier)
 
-**Completed (8/10 Stage 4 tasks):**
+### [PROBLEM: Tool Selection Accuracy - Few-Shot Examples]
 
-1. ✅ **Comprehensive Debug Logging** - All nodes log inputs, LLM details, tool execution, state transitions
-2. ✅ **Improved Error Messages** - answer_node shows specific failure reasons and suggestions
-3. ✅ **API Key Validation** - Agent startup checks GOOGLE_API_KEY, HF_TOKEN, ANTHROPIC_API_KEY, TAVILY_API_KEY
-4. ✅ **Tool Execution Error Handling** - execute_node validates tool_calls, handles exceptions gracefully
-5. ✅ **Fallback Tool Execution** - Keyword matching when LLM function calling fails
-6. ✅ **LLM Exception Handling** - 3-tier fallback with comprehensive error capture
-7. ✅ **Diagnostics Display** - Test & Debug tab shows API status, plan, tools, evidence, errors, answer
-8. ✅ **Documentation** - Dev log created (dev_260103_16_huggingface_integration.md)
+**Modified Files:**
 
-**Completed (10/10 tasks):**
+- **src/agent/llm_client.py** (~40 lines modified)
+  - Updated `select_tools_claude()` prompt - Added few-shot examples (web_search, calculator, vision, parse_file)
+  - Updated `select_tools_gemini()` prompt - Added few-shot examples with parameter extraction guidance
+  - Updated `select_tools_hf()` prompt - Added few-shot examples matching tool schemas
+  - Updated `select_tools_groq()` prompt - Added few-shot examples for improved accuracy
+  - Changed prompt tone from "agent" to "expert" for better LLM performance
+  - Added explicit instruction: "Use exact parameter names from tool schemas"
 
-- ✅ Tool name consistency fix (commit d94eeec)
-- ✅ Deploy to HF Space and run GAIA validation
+### [PROBLEM: Vision Tool Failures - Graceful Skip]
 
-**GAIA Validation Results:**
+**Modified Files:**
 
-- **Score:** 10.0% (2/20 correct)
-- **Improvement:** 0/20 → 2/20 (MVP validated!)
-- **Status:** Agent operational
+- **src/agent/graph.py** (~30 lines added)
+  - Added `is_vision_question()` helper function (lines 37-50)
+    - Detects vision keywords: image, video, youtube, photo, picture, watch, screenshot, visual
+  - Updated `execute_node()` - Graceful vision error handling (lines 322-326)
+    - Detects vision tool failures with quota errors
+    - Provides specific error message: "Vision analysis failed: LLM quota exhausted"
+  - Updated `execute_node()` - Graceful execution error handling (lines 329-334)
+    - Detects vision questions with quota errors during tool selection
+    - Avoids generic crash, provides context-aware error message
 
-**Stage 4 COMPLETE** ✅
+### [PROBLEM: Calculator Tool Crashes - Relaxed Validation]
 
-## Notes
+**Modified Files:**
 
-**Test Results:**
-
-All tests passing with 3-tier fallback architecture:
-```bash
-uv run pytest test/ -q
-======================== 99 passed, 11 warnings in 51.99s ========================
-```
-
-**Key Technical Achievements:**
+- **src/tools/calculator.py** (~30 lines modified)
+  - Updated `safe_eval()` - Relaxed empty expression validation (lines 258-287)
+    - Changed from raising ValueError to returning error dict: {"success": False, "error": "..."}
+    - Handles empty expressions gracefully (no crash)
+    - Handles whitespace-only expressions gracefully
+    - Handles oversized expressions gracefully (returns partial expression in error)
+    - All validation errors now non-fatal - agent can continue with other tools
 
-1. **3-Tier Fallback Architecture:**
-   - Tier 1: Gemini 2.0 Flash (free, 1,500 req/day)
-   - Tier 2: HuggingFace Qwen 2.5 72B (free, rate limited) - NEW
-   - Tier 3: Claude Sonnet 4.5 (paid, credits)
-   - Tier 4: Keyword matching (deterministic fallback)
+### [PROBLEM: Tool Selection Accuracy - Improved Tool Descriptions]
 
-2. **Function Calling Compatibility:**
-   - Gemini: `genai.protos.Tool` with `function_declarations`
-   - HuggingFace: OpenAI-compatible tools array format
-   - Claude: Anthropic native tools format
-   - Single source of truth in `src/tools/__init__.py` with provider-specific transformations
+**Modified Files:**
 
-3. **TOOLS Schema Bug Fix:**
-   - Changed parameters from list `["query"]` to dict `{"query": {"type": "string", ...}}`
-   - Fixed Gemini function calling `'list' object has no attribute 'items'` error
-   - All LLM providers now compatible with unified schema
+- **src/tools/__init__.py** (~20 lines modified)
+  - Updated `web_search` description - More specific: "factual information, current events, Wikipedia, statistics, people, companies". Added when-to-use guidance.
+  - Updated `parse_file` description - More specific: mentions "the file", "uploaded document", "attachment" triggers. Explains what it reads.
+  - Updated `calculator` description - Lists supported operations: arithmetic, algebra, trig, logarithms. Lists functions: sqrt, sin, cos, log, abs.
+  - Updated `vision` description - More specific actions: describe content, identify objects, read text. Added triggers: images, photos, videos, YouTube.
+  - All descriptions now action-oriented with explicit "Use when..." guidance for better LLM tool selection
 
-**Known Issues (Resolved):**
+### [PROBLEM: Calculator Tool Crashes - Test Updates]
 
-- ✅ Gemini quota exceeded → HuggingFace fallback works
-- ✅ Claude credit balance low → HuggingFace fallback works
-- ✅ TOOLS schema mismatch → Fixed with dict format
+**Modified Files:**
 
-**Next Steps:**
+- **test/test_calculator.py** (~15 lines modified)
+  - Updated `test_empty_expression()` - Changed from expecting ValueError to checking error dict
+  - Updated `test_too_long_expression()` - Changed from expecting ValueError to checking error dict
+  - Tests now verify: result["success"] == False, error message present, result is None
 
-1. **User:** Set up HF_TOKEN in HuggingFace Space environment variables (in progress)
-2. **Update README:** Add API key setup instructions for all 4 providers
-3. **Deploy:** Test with real GAIA validation questions
-4. **Target:** Achieve 5/20 GAIA questions answered correctly (up from 0/20)
+**Test Results:**
+- ✅ All 99 tests passing (0 failures)
+- ✅ No regressions introduced by Stage 5 changes
+- ✅ Test suite run time: ~2min 40sec
 
-**Architectural Improvements Made:**
+### Created Files
 
-- **Free-first strategy:** Maximize free tier usage before burning paid credits
-- **Diverse quota models:** Daily limits (Gemini) + rate limits (HF) provide better resilience
-- **Function calling standardization:** Single source of truth with provider-specific transformations
-- **Early validation:** Check all API keys at agent startup, not at first use
+### Deleted Files

dev/dev_260102_15_stage4_mvp_real_integration.md

@@ -10,6 +10,7 @@
 **Context:** After Stage 3 core logic implementation, agent was deployed to HuggingFace Spaces for real GAIA testing. Result: 0/20 questions correct with all answers = "Unable to answer: No evidence collected".
 
 **Root Causes:**
+
 1. **Silent LLM Failures:** Function calling errors swallowed, no diagnostic visibility
 2. **Tool Execution Broken:** Evidence collection failing but continuing silently
 3. **No Error Visibility:** User sees "Unable to answer" with zero debug info
@@ -24,12 +25,14 @@
 ### **Decision 1: Comprehensive Debug Logging Over Silent Failures**
 
 **Why chosen:**
+
 - ✅ Visibility into where integration breaks (LLM? Tools? Network?)
 - ✅ Each node logs inputs, outputs, errors with full context
 - ✅ State transitions tracked for debugging flow issues
 - ✅ Production-ready logging infrastructure for future stages
 
 **Implementation:**
+
 - Added detailed logging in `plan_node`, `execute_node`, `answer_node`
 - Log LLM provider used, tool calls made, evidence collected
 - Full error stack traces with context
@@ -42,22 +45,26 @@
 **New:** `"ERROR: No evidence. Errors: Gemini 429 quota exceeded, Claude 400 credit low, Tavily timeout"`
 
 **Why chosen:**
+
 - ✅ Users understand WHY it failed (API key missing? Quota? Network?)
 - ✅ Developers can fix root cause without re-running
 - ✅ Gradio UI shows diagnostics instead of hiding failures
 
 **Trade-offs:**
+
 - **Pro:** Debugging 10x faster with actionable feedback
 - **Con:** Longer error messages (acceptable for MVP)
 
 ### **Decision 3: API Key Validation at Startup Over First-Use Failures**
 
 **Why chosen:**
+
 - ✅ Fail fast with clear message listing missing keys
 - ✅ Prevents wasting time on runs that will fail anyway
 - ✅ Non-blocking warnings (continues anyway for partial API availability)
 
 **Implementation:**
+
 ```python
 def validate_environment() -> List[str]:
     """Check API keys at startup."""
@@ -75,17 +82,20 @@ def validate_environment() -> List[str]:
 ### **Decision 4: Graceful LLM Fallback Chain Over Single Provider Dependency**
 
 **Final Architecture:**
+
 1. **Gemini 2.0 Flash** (free, 1,500 req/day) - Primary
 2. **HuggingFace Qwen 2.5 72B** (free, rate limited) - Middle tier (added later)
 3. **Claude Sonnet 4.5** (paid, credits) - Expensive fallback
 4. **Keyword matching** (deterministic) - Last resort
 
 **Why 3-tier free-first:**
+
 - ✅ Maximizes free tier usage before burning paid credits
 - ✅ Different quota models (daily vs rate-limited) provide resilience
 - ✅ Guarantees agent never completely fails (keyword fallback)
 
 **Trade-offs:**
+
 - **Pro:** 4 layers of resilience, cost-optimized
 - **Con:** Slightly higher latency on fallback traversal (acceptable)
 
@@ -94,6 +104,7 @@ def validate_environment() -> List[str]:
 **Problem:** If LLM function calling returns empty tool_calls, execution would continue silently
 
 **Solution:**
+
 ```python
 tool_calls = select_tools_with_function_calling(...)
 
@@ -104,6 +115,7 @@ if not tool_calls:
 ```
 
 **Why chosen:**
+
 - ✅ MVP priority: Get SOMETHING working even if LLM fails
 - ✅ Keyword matching better than no tools at all
 - ✅ Temporary hack acceptable for MVP validation
@@ -113,12 +125,14 @@ if not tool_calls:
 ### **Decision 6: Gradio Diagnostics Display Over Answer-Only UI**
 
 **Why chosen:**
+
 - ✅ Users see plan, tools selected, evidence, errors in real-time
 - ✅ Debugging possible without checking logs
 - ✅ Test & Debug tab shows API key status
 - ✅ Transparency builds user trust
 
 **Implementation:**
+
 - `format_diagnostics()` function formats state for display
 - Test & Debug tab shows: API keys, plan, tools, evidence, errors, final answer
 
@@ -131,6 +145,7 @@ if not tool_calls:
 **Impact:** Gemini function calling completely broken - `'list' object has no attribute 'items'` error.
 
 **Fix:** Updated all tool definitions to proper schema:
+
 ```python
 "parameters": {
     "query": {
@@ -156,6 +171,7 @@ Successfully achieved MVP: Agent operational with real API integration, 10% GAIA
 **Deliverables:**
 
 ### 1. src/agent/graph.py (~100 lines added/modified)
+
 - Added `validate_environment()` - API key validation at startup
 - Updated `plan_node` - Comprehensive logging, error context
 - Updated `execute_node` - Fallback tool selection when LLM fails
@@ -163,6 +179,7 @@ Successfully achieved MVP: Agent operational with real API integration, 10% GAIA
 - Added state inspection logging throughout execution flow
 
 ### 2. src/agent/llm_client.py (~200 lines added - includes HF integration)
+
 - Improved exception handling with specific error types
 - Distinguished: API key missing, rate limit, network error, API error
 - Added `create_hf_client()` - HuggingFace InferenceClient initialization
@@ -171,6 +188,7 @@ Successfully achieved MVP: Agent operational with real API integration, 10% GAIA
 - Log which provider failed and why
 
 ### 3. app.py (~100 lines added/modified)
+
 - Added `format_diagnostics()` - Format agent state for display
 - Updated Test & Debug tab - Shows API key status, plan, tools, evidence, errors
 - Added `check_api_keys()` - Display all API key statuses (GOOGLE, HF, ANTHROPIC, TAVILY, EXA)
@@ -178,12 +196,14 @@ Successfully achieved MVP: Agent operational with real API integration, 10% GAIA
 - Added export functionality (later enhanced to JSON in dev_260104_17)
 
 ### 4. src/tools/__init__.py
+
 - Fixed TOOLS schema bug - Changed parameters from list to dict format
 - Added type/description for each parameter
 - Added `"required_params"` field
 - Fixed Gemini function calling compatibility
 
 **GAIA Validation Results:**
+
 - **Score:** 10.0% (2/20 correct)
 - **Improvement:** 0/20 → 2/20 (MVP validated!)
 - **Success Cases:**
@@ -191,6 +211,7 @@ Successfully achieved MVP: Agent operational with real API integration, 10% GAIA
   - Question 5: Wikipedia search → "FunkMonk" ✅
 
 **Test Results:**
+
 ```bash
 uv run pytest test/ -q
 99 passed, 11 warnings in 51.99s ✅
@@ -203,11 +224,13 @@ uv run pytest test/ -q
 ### **Pattern: Free-First Fallback Architecture**
 
 **What worked well:**
+
 - Prioritizing free tiers (Gemini → HuggingFace) before paid tier (Claude) maximizes cost efficiency
 - Multiple free alternatives with different quota models (daily vs rate-limited) provide better resilience than single free tier
 - Keyword fallback ensures agent never completely fails even when all LLMs unavailable
 
 **Reusable pattern:**
+
 ```python
 def unified_llm_function(...):
     """3-tier fallback with comprehensive error capture."""
@@ -242,11 +265,13 @@ def unified_llm_function(...):
 ### **Pattern: Environment Validation at Startup**
 
 **What worked well:**
+
 - Validating all API keys at agent initialization (not at first use) provides immediate feedback
 - Clear warnings listing missing keys help users diagnose setup issues
 - Non-blocking warnings (continue anyway) allow testing with partial configuration
 
 **Implementation:**
+
 ```python
 def validate_environment() -> List[str]:
     """Check API keys at startup, return list of missing keys."""
@@ -283,17 +308,20 @@ def validate_environment() -> List[str]:
 ### **Critical Issues Discovered for Stage 5:**
 
 **P0 - Critical: LLM Quota Exhaustion (15/20 failed - 75%)**
+
 - Gemini: 429 quota exceeded (daily limit)
 - HuggingFace: 402 payment required (novita free limit)
 - Claude: 400 credit balance too low
 - **Impact:** 75% of failures not due to logic, but infrastructure
 
 **P1 - High: Vision Tool Failures (3/20 failed)**
+
 - All image/video questions auto-fail
 - "Vision analysis failed - Gemini and Claude both failed"
 - Vision depends on quota-limited multimodal LLMs
 
 **P1 - High: Tool Selection Errors (2/20 failed)**
+
 - Fallback to keyword matching in some cases
 - Calculator tool validation too strict (empty expression errors)
 
@@ -342,6 +370,7 @@ def validate_environment() -> List[str]:
 ### Test Results
 
 All tests passing with new fallback architecture:
+
 ```bash
 uv run pytest test/ -q
 ======================== 99 passed, 11 warnings in 51.99s ========================
@@ -360,6 +389,7 @@ uv run pytest test/ -q
 **Final Status:** MVP validated with 10% GAIA score
 
 **What Worked:**
+
 - ✅ Real API integration operational (Gemini, HuggingFace, Claude, Tavily)
 - ✅ Evidence collection working (not empty anymore)
 - ✅ Diagnostic visibility enables debugging
@@ -367,11 +397,13 @@ uv run pytest test/ -q
 - ✅ Agent functional and deployed to production
 
 **Critical Issues for Stage 5:**
+
 1. **LLM Quota Management** (P0) - 75% of failures due to quota exhaustion
 2. **Vision Tool Failures** (P1) - All image questions auto-fail
 3. **Tool Selection Accuracy** (P1) - Keyword fallback too simplistic
 
 **Ready for Stage 5:** Performance Optimization
+
 - **Target:** 10% → 25% accuracy (5/20 questions)
 - **Priority:** Fix quota management, improve tool selection, fix vision tool
 - **Infrastructure:** Debugging tools ready, JSON export system in place

dev/dev_260104_17_json_export_system.md

@@ -24,6 +24,7 @@
 ### **Decision 1: JSON Export over Markdown Table**
 
 **Why chosen:**
+
 - ✅ No special character escaping required
 - ✅ Full error messages preserved (no truncation)
 - ✅ Easy programmatic processing for Stage 5 analysis
@@ -31,6 +32,7 @@
 - ✅ Universal format for both human and machine reading
 
 **Rejected alternative: Fixed markdown table**
+
 - ❌ Still requires escaping pipes, quotes, newlines
 - ❌ Still needs truncation to maintain readable width
 - ❌ Hard to parse programmatically
@@ -39,12 +41,14 @@
 ### **Decision 2: Environment-Aware Export Paths**
 
 **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
 
 **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)
@@ -52,6 +56,7 @@
 ### **Decision 3: gr.File Download Button over Textbox Display**
 
 **Why chosen:**
+
 - ✅ Better UX - direct download instead of copy-paste
 - ✅ Preserves formatting (JSON indentation, Unicode characters)
 - ✅ Gradio natively handles file serving in HF Spaces
@@ -81,6 +86,7 @@ Successfully implemented production-ready JSON export system for GAIA evaluation
    - Updated button click handler to output 3 values: `(status, table, export_path)`
 
 **Test Results:**
+
 - ✅ All tests passing (99/99)
 - ✅ JSON export verified with real GAIA validation results
 - ✅ File: `output/gaia_results_20260104_011001.json` (20 questions, full error details)
@@ -92,6 +98,7 @@ Successfully implemented production-ready JSON export system for GAIA evaluation
 ### **Pattern: Data Format Selection Based on Use Case**
 
 **What worked well:**
+
 - Choosing JSON for machine-readable debugging data over human-readable presentation formats
 - Environment-aware paths avoid deployment issues between local and cloud
 - File download UI pattern better than inline text display for large data

output/gaia_results_20260104_011001.json

@@ -0,0 +1,110 @@
+{
+  "metadata": {
+    "generated": "2026-01-04 01:10:01",
+    "timestamp": "20260104_011001",
+    "total_questions": 20
+  },
+  "submission_status": "Submission Successful!\nUser: mangoobee\nOverall Score: 10.0% (2/20 correct)\nMessage: Score calculated successfully: 2/20 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": "5"
+    },
+    {
+      "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"
+    },
+    {
+      "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"
+    },
+    {
+      "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": "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": "FunkMonk"
+    },
+    {
+      "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 selection returned no tools - using fallback keyword matching; Tool calculator failed: ValueError: Expression must be a non-empty string"
+    },
+    {
+      "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"
+    },
+    {
+      "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": "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"
+    },
+    {
+      "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: Planning error: Exception: Planning failed with all LLMs. Gemini: 429 You exceeded your current quota, please check your plan and billing details. For more information on this error, head to: https://ai.google.dev/gemini-api/docs/rate-limits. To monitor your current usage, head to: https://ai.dev/usage?tab=rate-limit. \n* Quota exceeded for metric: generativelanguage.googleapis.com/generate_content_free_tier_requests, limit: 0, model: gemini-2.0-flash-exp\n* Quota exceeded for metric: generativelanguage.googleapis.com/generate_content_free_tier_requests, limit: 0, model: gemini-2.0-flash-exp\n* Quota exceeded for metric: generativelanguage.googleapis.com/generate_content_free_tier_input_token_count, limit: 0, model: gemini-2.0-flash-exp\nPlease retry in 12.260562268s. [links {\n  description: \"Learn more about Gemini API quotas\"\n  url: \"https://ai.google.dev/gemini-api/docs/rate-limits\"\n}\n, violations {\n  quota_metric: \"generativelanguage.googleapis.com/generate_content_free_tier_requests\"\n  quota_id: \"GenerateRequestsPerDayPerProjectPerModel-FreeTier\"\n  quota_dimensions {\n    key: \"model\"\n    value: \"gemini-2.0-flash-exp\"\n  }\n  quota_dimensions {\n    key: \"location\"\n    value: \"global\"\n  }\n}\nviolations {\n  quota_metric: \"generativelanguage.googleapis.com/generate_content_free_tier_requests\"\n  quota_id: \"GenerateRequestsPerMinutePerProjectPerModel-FreeTier\"\n  quota_dimensions {\n    key: \"model\"\n    value: \"gemini-2.0-flash-exp\"\n  }\n  quota_dimensions {\n    key: \"location\"\n    value: \"global\"\n  }\n}\nviolations {\n  quota_metric: \"generativelanguage.googleapis.com/generate_content_free_tier_input_token_count\"\n  quota_id: \"GenerateContentInputTokensPerModelPerMinute-FreeTier\"\n  quota_dimensions {\n    key: \"model\"\n    value: \"gemini-2.0-flash-exp\"\n  }\n  quota_dimensions {\n    key: \"location\"\n    value: \"global\"\n  }\n}\n, retry_delay {\n  seconds: 12\n}\n], HF: Client error '402 Payment Required' for url 'https://router.huggingface.co/v1/chat/completions' (Request ID: Root=1-6959afcb-0ebda39f3785ed635bbffaf4;71a477c0-3e17-48e4-aedd-67cfd0eba3b0)\nFor more information check: https://developer.mozilla.org/en-US/docs/Web/HTTP/Status/402\n\nYou have reached the free monthly usage limit for novita. Subscribe to PRO to get 20x more included usage, or add pre-paid credits to your account., Claude: Error code: 400 - {'type': 'error', 'error': {'type': 'invalid_request_error', 'message': 'Your credit balance is too low to access the Anthropic API. Please go to Plans & Billing to upgrade or purchase credits.'}, 'request_id': 'req_011CWmNEE1hiTCxakFhjKstL'}; Execution error: Exception: Tool selection failed with all LLMs. Gemini: 429 You exceeded your current quota, please check your plan and billing details. For more information on this error, head to: https://ai.google.dev/gemini-api/docs/rate-limits. To monitor your current usage, head to: https://ai.dev/usage?tab=rate-limit. \n* Quota exceeded for metric: generativelanguage.googleapis.com/generate_content_free_tier_input_token_count, limit: 0, model: gemini-2.0-flash-exp\n* Quota exceeded for metric: generativelanguage.googleapis.com/generate_content_free_tier_requests, limit: 0, model: gemini-2.0-flash-exp\n* Quota exceeded for metric: generativelanguage.googleapis.com/generate_content_free_tier_requests, limit: 0, model: gemini-2.0-flash-exp\nPlease retry in 12.075520346s. [links {\n  description: \"Learn more about Gemini API quotas\"\n  url: \"https://ai.google.dev/gemini-api/docs/rate-limits\"\n}\n, violations {\n  quota_metric: \"generativelanguage.googleapis.com/generate_content_free_tier_input_token_count\"\n  quota_id: \"GenerateContentInputTokensPerModelPerMinute-FreeTier\"\n  quota_dimensions {\n    key: \"model\"\n    value: \"gemini-2.0-flash-exp\"\n  }\n  quota_dimensions {\n    key: \"location\"\n    value: \"global\"\n  }\n}\nviolations {\n  quota_metric: \"generativelanguage.googleapis.com/generate_content_free_tier_requests\"\n  quota_id: \"GenerateRequestsPerMinutePerProjectPerModel-FreeTier\"\n  quota_dimensions {\n    key: \"model\"\n    value: \"gemini-2.0-flash-exp\"\n  }\n  quota_dimensions {\n    key: \"location\"\n    value: \"global\"\n  }\n}\nviolations {\n  quota_metric: \"generativelanguage.googleapis.com/generate_content_free_tier_requests\"\n  quota_id: \"GenerateRequestsPerDayPerProjectPerModel-FreeTier\"\n  quota_dimensions {\n    key: \"model\"\n    value: \"gemini-2.0-flash-exp\"\n  }\n  quota_dimensions {\n    key: \"location\"\n    value: \"global\"\n  }\n}\n, retry_delay {\n  seconds: 12\n}\n], HF: Client error '402 Payment Required' for url 'https://router.huggingface.co/v1/chat/completions' (Request ID: Root=1-6959afcb-6f6a5e0e1e8807f95daafccd;b0a40509-e136-4fa7-ad71-7923ead8447f)\nFor more information check: https://developer.mozilla.org/en-US/docs/Web/HTTP/Status/402\n\nYou have reached the free monthly usage limit for novita. Subscribe to PRO to get 20x more included usage, or add pre-paid credits to your account., Claude: Error code: 400 - {'type': 'error', 'error': {'type': 'invalid_request_error', 'message': 'Your credit balance is too low to access the Anthropic API. Please go to Plans & Billing to upgrade or purchase credits.'}, 'request_id': 'req_011CWmNEEm6iMQx7zbzJy3dw'}"
+    },
+    {
+      "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": "ERROR: No evidence collected. Details: Planning error: Exception: Planning failed with all LLMs. Gemini: 429 You exceeded your current quota, please check your plan and billing details. For more information on this error, head to: https://ai.google.dev/gemini-api/docs/rate-limits. To monitor your current usage, head to: https://ai.dev/usage?tab=rate-limit. \n* Quota exceeded for metric: generativelanguage.googleapis.com/generate_content_free_tier_input_token_count, limit: 0, model: gemini-2.0-flash-exp\n* Quota exceeded for metric: generativelanguage.googleapis.com/generate_content_free_tier_requests, limit: 0, model: gemini-2.0-flash-exp\n* Quota exceeded for metric: generativelanguage.googleapis.com/generate_content_free_tier_requests, limit: 0, model: gemini-2.0-flash-exp\nPlease retry in 11.278160968s. [links {\n  description: \"Learn more about Gemini API quotas\"\n  url: \"https://ai.google.dev/gemini-api/docs/rate-limits\"\n}\n, violations {\n  quota_metric: \"generativelanguage.googleapis.com/generate_content_free_tier_input_token_count\"\n  quota_id: \"GenerateContentInputTokensPerModelPerMinute-FreeTier\"\n  quota_dimensions {\n    key: \"model\"\n    value: \"gemini-2.0-flash-exp\"\n  }\n  quota_dimensions {\n    key: \"location\"\n    value: \"global\"\n  }\n}\nviolations {\n  quota_metric: \"generativelanguage.googleapis.com/generate_content_free_tier_requests\"\n  quota_id: \"GenerateRequestsPerMinutePerProjectPerModel-FreeTier\"\n  quota_dimensions {\n    key: \"model\"\n    value: \"gemini-2.0-flash-exp\"\n  }\n  quota_dimensions {\n    key: \"location\"\n    value: \"global\"\n  }\n}\nviolations {\n  quota_metric: \"generativelanguage.googleapis.com/generate_content_free_tier_requests\"\n  quota_id: \"GenerateRequestsPerDayPerProjectPerModel-FreeTier\"\n  quota_dimensions {\n    key: \"model\"\n    value: \"gemini-2.0-flash-exp\"\n  }\n  quota_dimensions {\n    key: \"location\"\n    value: \"global\"\n  }\n}\n, retry_delay {\n  seconds: 11\n}\n], HF: Client error '402 Payment Required' for url 'https://router.huggingface.co/v1/chat/completions' (Request ID: Root=1-6959afcc-3ef2237d004be5466af168e0;77ed17a7-4d55-4075-b583-3dc2cd142e4c)\nFor more information check: https://developer.mozilla.org/en-US/docs/Web/HTTP/Status/402\n\nYou have reached the free monthly usage limit for novita. Subscribe to PRO to get 20x more included usage, or add pre-paid credits to your account., Claude: Error code: 400 - {'type': 'error', 'error': {'type': 'invalid_request_error', 'message': 'Your credit balance is too low to access the Anthropic API. Please go to Plans & Billing to upgrade or purchase credits.'}, 'request_id': 'req_011CWmNEJ9zKGwcQAg5Sj6XR'}; Execution error: Exception: Tool selection failed with all LLMs. Gemini: 429 You exceeded your current quota, please check your plan and billing details. For more information on this error, head to: https://ai.google.dev/gemini-api/docs/rate-limits. To monitor your current usage, head to: https://ai.dev/usage?tab=rate-limit. \n* Quota exceeded for metric: generativelanguage.googleapis.com/generate_content_free_tier_input_token_count, limit: 0, model: gemini-2.0-flash-exp\n* Quota exceeded for metric: generativelanguage.googleapis.com/generate_content_free_tier_requests, limit: 0, model: gemini-2.0-flash-exp\n* Quota exceeded for metric: generativelanguage.googleapis.com/generate_content_free_tier_requests, limit: 0, model: gemini-2.0-flash-exp\nPlease retry in 11.089695796s. [links {\n  description: \"Learn more about Gemini API quotas\"\n  url: \"https://ai.google.dev/gemini-api/docs/rate-limits\"\n}\n, violations {\n  quota_metric: \"generativelanguage.googleapis.com/generate_content_free_tier_input_token_count\"\n  quota_id: \"GenerateContentInputTokensPerModelPerMinute-FreeTier\"\n  quota_dimensions {\n    key: \"model\"\n    value: \"gemini-2.0-flash-exp\"\n  }\n  quota_dimensions {\n    key: \"location\"\n    value: \"global\"\n  }\n}\nviolations {\n  quota_metric: \"generativelanguage.googleapis.com/generate_content_free_tier_requests\"\n  quota_id: \"GenerateRequestsPerMinutePerProjectPerModel-FreeTier\"\n  quota_dimensions {\n    key: \"model\"\n    value: \"gemini-2.0-flash-exp\"\n  }\n  quota_dimensions {\n    key: \"location\"\n    value: \"global\"\n  }\n}\nviolations {\n  quota_metric: \"generativelanguage.googleapis.com/generate_content_free_tier_requests\"\n  quota_id: \"GenerateRequestsPerDayPerProjectPerModel-FreeTier\"\n  quota_dimensions {\n    key: \"model\"\n    value: \"gemini-2.0-flash-exp\"\n  }\n  quota_dimensions {\n    key: \"location\"\n    value: \"global\"\n  }\n}\n, retry_delay {\n  seconds: 11\n}\n], HF: Client error '402 Payment Required' for url 'https://router.huggingface.co/v1/chat/completions' (Request ID: Root=1-6959afcc-426b813c44ac777029e19f09;229eb0c8-cfc0-477e-acba-760f16748664)\nFor more information check: https://developer.mozilla.org/en-US/docs/Web/HTTP/Status/402\n\nYou have reached the free monthly usage limit for novita. Subscribe to PRO to get 20x more included usage, or add pre-paid credits to your account., Claude: Error code: 400 - {'type': 'error', 'error': {'type': 'invalid_request_error', 'message': 'Your credit balance is too low to access the Anthropic API. Please go to Plans & Billing to upgrade or purchase credits.'}, 'request_id': 'req_011CWmNEJvNpZZ4d351AXX9T'}"
+    },
+    {
+      "task_id": "f918266a-b3e0-4914-865d-4faa564f1aef",
+      "question": "What is the final numeric output from the attached Python code?",
+      "submitted_answer": "ERROR: Answer synthesis failed - Exception: Answer synthesis failed with all LLMs. Gemini: 429 You exceeded your current quota, please check your plan and billing details. For more information on this error, head to: https://ai.google.dev/gemini-api/docs/rate-limits. To monitor your current usage, head to: https://ai.dev/usage?tab=rate-limit. \n* Quota exceeded for metric: generativelanguage.googleapis.com/generate_content_free_tier_requests, limit: 0, model: gemini-2.0-flash-exp\n* Quota exceeded for metric: generativelanguage.googleapis.com/generate_content_free_tier_requests, limit: 0, model: gemini-2.0-flash-exp\n* Quota exceeded for metric: generativelanguage.googleapis.com/generate_content_free_tier_input_token_count, limit: 0, model: gemini-2.0-flash-exp\nPlease retry in 10.530596622s. [links {\n  description: \"Learn more about Gemini API quotas\"\n  url: \"https://ai.google.dev/gemini-api/docs/rate-limits\"\n}\n, violations {\n  quota_metric: \"generativelanguage.googleapis.com/generate_content_free_tier_requests\"\n  quota_id: \"GenerateRequestsPerDayPerProjectPerModel-FreeTier\"\n  quota_dimensions {\n    key: \"model\"\n    value: \"gemini-2.0-flash-exp\"\n  }\n  quota_dimensions {\n    key: \"location\"\n    value: \"global\"\n  }\n}\nviolations {\n  quota_metric: \"generativelanguage.googleapis.com/generate_content_free_tier_requests\"\n  quota_id: \"GenerateRequestsPerMinutePerProjectPerModel-FreeTier\"\n  quota_dimensions {\n    key: \"model\"\n    value: \"gemini-2.0-flash-exp\"\n  }\n  quota_dimensions {\n    key: \"location\"\n    value: \"global\"\n  }\n}\nviolations {\n  quota_metric: \"generativelanguage.googleapis.com/generate_content_free_tier_input_token_count\"\n  quota_id: \"GenerateContentInputTokensPerModelPerMinute-FreeTier\"\n  quota_dimensions {\n    key: \"model\"\n    value: \"gemini-2.0-flash-exp\"\n  }\n  quota_dimensions {\n    key: \"location\"\n    value: \"global\"\n  }\n}\n, retry_delay {\n  seconds: 10\n}\n], HF: Client error '402 Payment Required' for url 'https://router.huggingface.co/v1/chat/completions' (Request ID: Root=1-6959afcd-1933b44b3b34f43f065b4b08;d07e4465-2cb3-4101-899e-66a6dba83880)\nFor more information check: https://developer.mozilla.org/en-US/docs/Web/HTTP/Status/402\n\nYou have reached the free monthly usage limit for novita. Subscribe to PRO to get 20x more included usage, or add pre-paid credits to your account., Claude: Error code: 400 - {'type': 'error', 'error': {'type': 'invalid_request_error', 'message': 'Your credit balance is too low to access the Anthropic API. Please go to Plans & Billing to upgrade or purchase credits.'}, 'request_id': 'req_011CWmNEMLUkDkNeWqdxW2NK'}"
+    },
+    {
+      "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": "ERROR: Answer synthesis failed - Exception: Answer synthesis failed with all LLMs. Gemini: 429 You exceeded your current quota, please check your plan and billing details. For more information on this error, head to: https://ai.google.dev/gemini-api/docs/rate-limits. To monitor your current usage, head to: https://ai.dev/usage?tab=rate-limit. \n* Quota exceeded for metric: generativelanguage.googleapis.com/generate_content_free_tier_requests, limit: 0, model: gemini-2.0-flash-exp\n* Quota exceeded for metric: generativelanguage.googleapis.com/generate_content_free_tier_requests, limit: 0, model: gemini-2.0-flash-exp\n* Quota exceeded for metric: generativelanguage.googleapis.com/generate_content_free_tier_input_token_count, limit: 0, model: gemini-2.0-flash-exp\nPlease retry in 9.923153297s. [links {\n  description: \"Learn more about Gemini API quotas\"\n  url: \"https://ai.google.dev/gemini-api/docs/rate-limits\"\n}\n, violations {\n  quota_metric: \"generativelanguage.googleapis.com/generate_content_free_tier_requests\"\n  quota_id: \"GenerateRequestsPerDayPerProjectPerModel-FreeTier\"\n  quota_dimensions {\n    key: \"model\"\n    value: \"gemini-2.0-flash-exp\"\n  }\n  quota_dimensions {\n    key: \"location\"\n    value: \"global\"\n  }\n}\nviolations {\n  quota_metric: \"generativelanguage.googleapis.com/generate_content_free_tier_requests\"\n  quota_id: \"GenerateRequestsPerMinutePerProjectPerModel-FreeTier\"\n  quota_dimensions {\n    key: \"model\"\n    value: \"gemini-2.0-flash-exp\"\n  }\n  quota_dimensions {\n    key: \"location\"\n    value: \"global\"\n  }\n}\nviolations {\n  quota_metric: \"generativelanguage.googleapis.com/generate_content_free_tier_input_token_count\"\n  quota_id: \"GenerateContentInputTokensPerModelPerMinute-FreeTier\"\n  quota_dimensions {\n    key: \"model\"\n    value: \"gemini-2.0-flash-exp\"\n  }\n  quota_dimensions {\n    key: \"location\"\n    value: \"global\"\n  }\n}\n, retry_delay {\n  seconds: 9\n}\n], HF: Client error '402 Payment Required' for url 'https://router.huggingface.co/v1/chat/completions' (Request ID: Root=1-6959afce-135196d1362d0a66447ba8cf;67616613-6ad2-4f0e-ae74-d88ee5d1f877)\nFor more information check: https://developer.mozilla.org/en-US/docs/Web/HTTP/Status/402\n\nYou have reached the free monthly usage limit for novita. Subscribe to PRO to get 20x more included usage, or add pre-paid credits to your account., Claude: Error code: 400 - {'type': 'error', 'error': {'type': 'invalid_request_error', 'message': 'Your credit balance is too low to access the Anthropic API. Please go to Plans & Billing to upgrade or purchase credits.'}, 'request_id': 'req_011CWmNEPyUuTQJLARRBib1d'}"
+    },
+    {
+      "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": "ERROR: No evidence collected. Details: Planning error: Exception: Planning failed with all LLMs. Gemini: 429 You exceeded your current quota, please check your plan and billing details. For more information on this error, head to: https://ai.google.dev/gemini-api/docs/rate-limits. To monitor your current usage, head to: https://ai.dev/usage?tab=rate-limit. \n* Quota exceeded for metric: generativelanguage.googleapis.com/generate_content_free_tier_input_token_count, limit: 0, model: gemini-2.0-flash-exp\n* Quota exceeded for metric: generativelanguage.googleapis.com/generate_content_free_tier_requests, limit: 0, model: gemini-2.0-flash-exp\n* Quota exceeded for metric: generativelanguage.googleapis.com/generate_content_free_tier_requests, limit: 0, model: gemini-2.0-flash-exp\nPlease retry in 9.710374487s. [links {\n  description: \"Learn more about Gemini API quotas\"\n  url: \"https://ai.google.dev/gemini-api/docs/rate-limits\"\n}\n, violations {\n  quota_metric: \"generativelanguage.googleapis.com/generate_content_free_tier_input_token_count\"\n  quota_id: \"GenerateContentInputTokensPerModelPerMinute-FreeTier\"\n  quota_dimensions {\n    key: \"model\"\n    value: \"gemini-2.0-flash-exp\"\n  }\n  quota_dimensions {\n    key: \"location\"\n    value: \"global\"\n  }\n}\nviolations {\n  quota_metric: \"generativelanguage.googleapis.com/generate_content_free_tier_requests\"\n  quota_id: \"GenerateRequestsPerMinutePerProjectPerModel-FreeTier\"\n  quota_dimensions {\n    key: \"model\"\n    value: \"gemini-2.0-flash-exp\"\n  }\n  quota_dimensions {\n    key: \"location\"\n    value: \"global\"\n  }\n}\nviolations {\n  quota_metric: \"generativelanguage.googleapis.com/generate_content_free_tier_requests\"\n  quota_id: \"GenerateRequestsPerDayPerProjectPerModel-FreeTier\"\n  quota_dimensions {\n    key: \"model\"\n    value: \"gemini-2.0-flash-exp\"\n  }\n  quota_dimensions {\n    key: \"location\"\n    value: \"global\"\n  }\n}\n, retry_delay {\n  seconds: 9\n}\n], HF: Client error '402 Payment Required' for url 'https://router.huggingface.co/v1/chat/completions' (Request ID: Root=1-6959afce-1edf0bc76b216b89360f819d;e3cbcb26-7956-4d7a-9c7d-411a6c464d3f)\nFor more information check: https://developer.mozilla.org/en-US/docs/Web/HTTP/Status/402\n\nYou have reached the free monthly usage limit for novita. Subscribe to PRO to get 20x more included usage, or add pre-paid credits to your account., Claude: Error code: 400 - {'type': 'error', 'error': {'type': 'invalid_request_error', 'message': 'Your credit balance is too low to access the Anthropic API. Please go to Plans & Billing to upgrade or purchase credits.'}, 'request_id': 'req_011CWmNEQp5pvv9CD9k7p4sG'}; Execution error: Exception: Tool selection failed with all LLMs. Gemini: 429 You exceeded your current quota, please check your plan and billing details. For more information on this error, head to: https://ai.google.dev/gemini-api/docs/rate-limits. To monitor your current usage, head to: https://ai.dev/usage?tab=rate-limit. \n* Quota exceeded for metric: generativelanguage.googleapis.com/generate_content_free_tier_input_token_count, limit: 0, model: gemini-2.0-flash-exp\n* Quota exceeded for metric: generativelanguage.googleapis.com/generate_content_free_tier_requests, limit: 0, model: gemini-2.0-flash-exp\n* Quota exceeded for metric: generativelanguage.googleapis.com/generate_content_free_tier_requests, limit: 0, model: gemini-2.0-flash-exp\nPlease retry in 9.5500296s. [links {\n  description: \"Learn more about Gemini API quotas\"\n  url: \"https://ai.google.dev/gemini-api/docs/rate-limits\"\n}\n, violations {\n  quota_metric: \"generativelanguage.googleapis.com/generate_content_free_tier_input_token_count\"\n  quota_id: \"GenerateContentInputTokensPerModelPerMinute-FreeTier\"\n  quota_dimensions {\n    key: \"model\"\n    value: \"gemini-2.0-flash-exp\"\n  }\n  quota_dimensions {\n    key: \"location\"\n    value: \"global\"\n  }\n}\nviolations {\n  quota_metric: \"generativelanguage.googleapis.com/generate_content_free_tier_requests\"\n  quota_id: \"GenerateRequestsPerMinutePerProjectPerModel-FreeTier\"\n  quota_dimensions {\n    key: \"model\"\n    value: \"gemini-2.0-flash-exp\"\n  }\n  quota_dimensions {\n    key: \"location\"\n    value: \"global\"\n  }\n}\nviolations {\n  quota_metric: \"generativelanguage.googleapis.com/generate_content_free_tier_requests\"\n  quota_id: \"GenerateRequestsPerDayPerProjectPerModel-FreeTier\"\n  quota_dimensions {\n    key: \"model\"\n    value: \"gemini-2.0-flash-exp\"\n  }\n  quota_dimensions {\n    key: \"location\"\n    value: \"global\"\n  }\n}\n, retry_delay {\n  seconds: 9\n}\n], HF: Client error '402 Payment Required' for url 'https://router.huggingface.co/v1/chat/completions' (Request ID: Root=1-6959afce-728a1eeb5ed5337a5ca10fd0;b87e8fe8-e3e9-415e-a720-28b6f5d12010)\nFor more information check: https://developer.mozilla.org/en-US/docs/Web/HTTP/Status/402\n\nYou have reached the free monthly usage limit for novita. Subscribe to PRO to get 20x more included usage, or add pre-paid credits to your account., Claude: Error code: 400 - {'type': 'error', 'error': {'type': 'invalid_request_error', 'message': 'Your credit balance is too low to access the Anthropic API. Please go to Plans & Billing to upgrade or purchase credits.'}, 'request_id': 'req_011CWmNERbTzqBfuMHa7xnaJ'}"
+    },
+    {
+      "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": "ERROR: Answer synthesis failed - Exception: Answer synthesis failed with all LLMs. Gemini: 429 You exceeded your current quota, please check your plan and billing details. For more information on this error, head to: https://ai.google.dev/gemini-api/docs/rate-limits. To monitor your current usage, head to: https://ai.dev/usage?tab=rate-limit. \n* Quota exceeded for metric: generativelanguage.googleapis.com/generate_content_free_tier_requests, limit: 0, model: gemini-2.0-flash-exp\n* Quota exceeded for metric: generativelanguage.googleapis.com/generate_content_free_tier_requests, limit: 0, model: gemini-2.0-flash-exp\n* Quota exceeded for metric: generativelanguage.googleapis.com/generate_content_free_tier_input_token_count, limit: 0, model: gemini-2.0-flash-exp\nPlease retry in 8.209649658s. [links {\n  description: \"Learn more about Gemini API quotas\"\n  url: \"https://ai.google.dev/gemini-api/docs/rate-limits\"\n}\n, violations {\n  quota_metric: \"generativelanguage.googleapis.com/generate_content_free_tier_requests\"\n  quota_id: \"GenerateRequestsPerDayPerProjectPerModel-FreeTier\"\n  quota_dimensions {\n    key: \"model\"\n    value: \"gemini-2.0-flash-exp\"\n  }\n  quota_dimensions {\n    key: \"location\"\n    value: \"global\"\n  }\n}\nviolations {\n  quota_metric: \"generativelanguage.googleapis.com/generate_content_free_tier_requests\"\n  quota_id: \"GenerateRequestsPerMinutePerProjectPerModel-FreeTier\"\n  quota_dimensions {\n    key: \"model\"\n    value: \"gemini-2.0-flash-exp\"\n  }\n  quota_dimensions {\n    key: \"location\"\n    value: \"global\"\n  }\n}\nviolations {\n  quota_metric: \"generativelanguage.googleapis.com/generate_content_free_tier_input_token_count\"\n  quota_id: \"GenerateContentInputTokensPerModelPerMinute-FreeTier\"\n  quota_dimensions {\n    key: \"model\"\n    value: \"gemini-2.0-flash-exp\"\n  }\n  quota_dimensions {\n    key: \"location\"\n    value: \"global\"\n  }\n}\n, retry_delay {\n  seconds: 8\n}\n], HF: Client error '402 Payment Required' for url 'https://router.huggingface.co/v1/chat/completions' (Request ID: Root=1-6959afcf-673e8fef593bbd614ae1938b;1cf7e171-cba7-4a2e-9423-01b64b573770)\nFor more information check: https://developer.mozilla.org/en-US/docs/Web/HTTP/Status/402\n\nYou have reached the free monthly usage limit for novita. Subscribe to PRO to get 20x more included usage, or add pre-paid credits to your account., Claude: Error code: 400 - {'type': 'error', 'error': {'type': 'invalid_request_error', 'message': 'Your credit balance is too low to access the Anthropic API. Please go to Plans & Billing to upgrade or purchase credits.'}, 'request_id': 'req_011CWmNEXF3Te5sTxuQ7X5hn'}"
+    },
+    {
+      "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": "ERROR: Answer synthesis failed - Exception: Answer synthesis failed with all LLMs. Gemini: 429 You exceeded your current quota, please check your plan and billing details. For more information on this error, head to: https://ai.google.dev/gemini-api/docs/rate-limits. To monitor your current usage, head to: https://ai.dev/usage?tab=rate-limit. \n* Quota exceeded for metric: generativelanguage.googleapis.com/generate_content_free_tier_input_token_count, limit: 0, model: gemini-2.0-flash-exp\n* Quota exceeded for metric: generativelanguage.googleapis.com/generate_content_free_tier_requests, limit: 0, model: gemini-2.0-flash-exp\n* Quota exceeded for metric: generativelanguage.googleapis.com/generate_content_free_tier_requests, limit: 0, model: gemini-2.0-flash-exp\nPlease retry in 6.27633531s. [links {\n  description: \"Learn more about Gemini API quotas\"\n  url: \"https://ai.google.dev/gemini-api/docs/rate-limits\"\n}\n, violations {\n  quota_metric: \"generativelanguage.googleapis.com/generate_content_free_tier_input_token_count\"\n  quota_id: \"GenerateContentInputTokensPerModelPerMinute-FreeTier\"\n  quota_dimensions {\n    key: \"model\"\n    value: \"gemini-2.0-flash-exp\"\n  }\n  quota_dimensions {\n    key: \"location\"\n    value: \"global\"\n  }\n}\nviolations {\n  quota_metric: \"generativelanguage.googleapis.com/generate_content_free_tier_requests\"\n  quota_id: \"GenerateRequestsPerMinutePerProjectPerModel-FreeTier\"\n  quota_dimensions {\n    key: \"model\"\n    value: \"gemini-2.0-flash-exp\"\n  }\n  quota_dimensions {\n    key: \"location\"\n    value: \"global\"\n  }\n}\nviolations {\n  quota_metric: \"generativelanguage.googleapis.com/generate_content_free_tier_requests\"\n  quota_id: \"GenerateRequestsPerDayPerProjectPerModel-FreeTier\"\n  quota_dimensions {\n    key: \"model\"\n    value: \"gemini-2.0-flash-exp\"\n  }\n  quota_dimensions {\n    key: \"location\"\n    value: \"global\"\n  }\n}\n, retry_delay {\n  seconds: 6\n}\n], HF: Client error '402 Payment Required' for url 'https://router.huggingface.co/v1/chat/completions' (Request ID: Root=1-6959afd1-57204e0f3392f4dd033a9319;98304f21-8c15-463a-82a6-fe7eeacb9157)\nFor more information check: https://developer.mozilla.org/en-US/docs/Web/HTTP/Status/402\n\nYou have reached the free monthly usage limit for novita. Subscribe to PRO to get 20x more included usage, or add pre-paid credits to your account., Claude: Error code: 400 - {'type': 'error', 'error': {'type': 'invalid_request_error', 'message': 'Your credit balance is too low to access the Anthropic API. Please go to Plans & Billing to upgrade or purchase credits.'}, 'request_id': 'req_011CWmNEfeJyHp7Jw1D9sTpS'}"
+    },
+    {
+      "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": "ERROR: No evidence collected. Details: Planning error: Exception: Planning failed with all LLMs. Gemini: 429 You exceeded your current quota, please check your plan and billing details. For more information on this error, head to: https://ai.google.dev/gemini-api/docs/rate-limits. To monitor your current usage, head to: https://ai.dev/usage?tab=rate-limit. \n* Quota exceeded for metric: generativelanguage.googleapis.com/generate_content_free_tier_requests, limit: 0, model: gemini-2.0-flash-exp\n* Quota exceeded for metric: generativelanguage.googleapis.com/generate_content_free_tier_requests, limit: 0, model: gemini-2.0-flash-exp\n* Quota exceeded for metric: generativelanguage.googleapis.com/generate_content_free_tier_input_token_count, limit: 0, model: gemini-2.0-flash-exp\nPlease retry in 5.987771258s. [links {\n  description: \"Learn more about Gemini API quotas\"\n  url: \"https://ai.google.dev/gemini-api/docs/rate-limits\"\n}\n, violations {\n  quota_metric: \"generativelanguage.googleapis.com/generate_content_free_tier_requests\"\n  quota_id: \"GenerateRequestsPerDayPerProjectPerModel-FreeTier\"\n  quota_dimensions {\n    key: \"model\"\n    value: \"gemini-2.0-flash-exp\"\n  }\n  quota_dimensions {\n    key: \"location\"\n    value: \"global\"\n  }\n}\nviolations {\n  quota_metric: \"generativelanguage.googleapis.com/generate_content_free_tier_requests\"\n  quota_id: \"GenerateRequestsPerMinutePerProjectPerModel-FreeTier\"\n  quota_dimensions {\n    key: \"model\"\n    value: \"gemini-2.0-flash-exp\"\n  }\n  quota_dimensions {\n    key: \"location\"\n    value: \"global\"\n  }\n}\nviolations {\n  quota_metric: \"generativelanguage.googleapis.com/generate_content_free_tier_input_token_count\"\n  quota_id: \"GenerateContentInputTokensPerModelPerMinute-FreeTier\"\n  quota_dimensions {\n    key: \"model\"\n    value: \"gemini-2.0-flash-exp\"\n  }\n  quota_dimensions {\n    key: \"location\"\n    value: \"global\"\n  }\n}\n, retry_delay {\n  seconds: 5\n}\n], HF: Client error '402 Payment Required' for url 'https://router.huggingface.co/v1/chat/completions' (Request ID: Root=1-6959afd2-407132ca1d9ad96c3c287d55;9d0b5220-be1c-4c8d-b6e0-2fb49184710d)\nFor more information check: https://developer.mozilla.org/en-US/docs/Web/HTTP/Status/402\n\nYou have reached the free monthly usage limit for novita. Subscribe to PRO to get 20x more included usage, or add pre-paid credits to your account., Claude: Error code: 400 - {'type': 'error', 'error': {'type': 'invalid_request_error', 'message': 'Your credit balance is too low to access the Anthropic API. Please go to Plans & Billing to upgrade or purchase credits.'}, 'request_id': 'req_011CWmNEgn2Lg9QEcgE4naaK'}; Execution error: Exception: Tool selection failed with all LLMs. Gemini: 429 You exceeded your current quota, please check your plan and billing details. For more information on this error, head to: https://ai.google.dev/gemini-api/docs/rate-limits. To monitor your current usage, head to: https://ai.dev/usage?tab=rate-limit. \n* Quota exceeded for metric: generativelanguage.googleapis.com/generate_content_free_tier_requests, limit: 0, model: gemini-2.0-flash-exp\n* Quota exceeded for metric: generativelanguage.googleapis.com/generate_content_free_tier_requests, limit: 0, model: gemini-2.0-flash-exp\n* Quota exceeded for metric: generativelanguage.googleapis.com/generate_content_free_tier_input_token_count, limit: 0, model: gemini-2.0-flash-exp\nPlease retry in 5.811263591s. [links {\n  description: \"Learn more about Gemini API quotas\"\n  url: \"https://ai.google.dev/gemini-api/docs/rate-limits\"\n}\n, violations {\n  quota_metric: \"generativelanguage.googleapis.com/generate_content_free_tier_requests\"\n  quota_id: \"GenerateRequestsPerDayPerProjectPerModel-FreeTier\"\n  quota_dimensions {\n    key: \"model\"\n    value: \"gemini-2.0-flash-exp\"\n  }\n  quota_dimensions {\n    key: \"location\"\n    value: \"global\"\n  }\n}\nviolations {\n  quota_metric: \"generativelanguage.googleapis.com/generate_content_free_tier_requests\"\n  quota_id: \"GenerateRequestsPerMinutePerProjectPerModel-FreeTier\"\n  quota_dimensions {\n    key: \"model\"\n    value: \"gemini-2.0-flash-exp\"\n  }\n  quota_dimensions {\n    key: \"location\"\n    value: \"global\"\n  }\n}\nviolations {\n  quota_metric: \"generativelanguage.googleapis.com/generate_content_free_tier_input_token_count\"\n  quota_id: \"GenerateContentInputTokensPerModelPerMinute-FreeTier\"\n  quota_dimensions {\n    key: \"model\"\n    value: \"gemini-2.0-flash-exp\"\n  }\n  quota_dimensions {\n    key: \"location\"\n    value: \"global\"\n  }\n}\n, retry_delay {\n  seconds: 5\n}\n], HF: Client error '402 Payment Required' for url 'https://router.huggingface.co/v1/chat/completions' (Request ID: Root=1-6959afd2-486fe1c16fc378e4677d73c6;57383797-ec4f-4a2d-8638-edca39c03263)\nFor more information check: https://developer.mozilla.org/en-US/docs/Web/HTTP/Status/402\n\nYou have reached the free monthly usage limit for novita. Subscribe to PRO to get 20x more included usage, or add pre-paid credits to your account., Claude: Error code: 400 - {'type': 'error', 'error': {'type': 'invalid_request_error', 'message': 'Your credit balance is too low to access the Anthropic API. Please go to Plans & Billing to upgrade or purchase credits.'}, 'request_id': 'req_011CWmNEhathU1tbmAiDfbSv'}"
+    },
+    {
+      "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": "ERROR: Answer synthesis failed - Exception: Answer synthesis failed with all LLMs. Gemini: 429 You exceeded your current quota, please check your plan and billing details. For more information on this error, head to: https://ai.google.dev/gemini-api/docs/rate-limits. To monitor your current usage, head to: https://ai.dev/usage?tab=rate-limit. \n* Quota exceeded for metric: generativelanguage.googleapis.com/generate_content_free_tier_requests, limit: 0, model: gemini-2.0-flash-exp\n* Quota exceeded for metric: generativelanguage.googleapis.com/generate_content_free_tier_requests, limit: 0, model: gemini-2.0-flash-exp\n* Quota exceeded for metric: generativelanguage.googleapis.com/generate_content_free_tier_input_token_count, limit: 0, model: gemini-2.0-flash-exp\nPlease retry in 3.6593123s. [links {\n  description: \"Learn more about Gemini API quotas\"\n  url: \"https://ai.google.dev/gemini-api/docs/rate-limits\"\n}\n, violations {\n  quota_metric: \"generativelanguage.googleapis.com/generate_content_free_tier_requests\"\n  quota_id: \"GenerateRequestsPerDayPerProjectPerModel-FreeTier\"\n  quota_dimensions {\n    key: \"model\"\n    value: \"gemini-2.0-flash-exp\"\n  }\n  quota_dimensions {\n    key: \"location\"\n    value: \"global\"\n  }\n}\nviolations {\n  quota_metric: \"generativelanguage.googleapis.com/generate_content_free_tier_requests\"\n  quota_id: \"GenerateRequestsPerMinutePerProjectPerModel-FreeTier\"\n  quota_dimensions {\n    key: \"model\"\n    value: \"gemini-2.0-flash-exp\"\n  }\n  quota_dimensions {\n    key: \"location\"\n    value: \"global\"\n  }\n}\nviolations {\n  quota_metric: \"generativelanguage.googleapis.com/generate_content_free_tier_input_token_count\"\n  quota_id: \"GenerateContentInputTokensPerModelPerMinute-FreeTier\"\n  quota_dimensions {\n    key: \"model\"\n    value: \"gemini-2.0-flash-exp\"\n  }\n  quota_dimensions {\n    key: \"location\"\n    value: \"global\"\n  }\n}\n, retry_delay {\n  seconds: 3\n}\n], HF: Client error '402 Payment Required' for url 'https://router.huggingface.co/v1/chat/completions' (Request ID: Root=1-6959afd4-057c9e456a5f63df302884f1;f679c5b5-97c2-41b5-862b-f30fab2cecab)\nFor more information check: https://developer.mozilla.org/en-US/docs/Web/HTTP/Status/402\n\nYou have reached the free monthly usage limit for novita. Subscribe to PRO to get 20x more included usage, or add pre-paid credits to your account., Claude: Error code: 400 - {'type': 'error', 'error': {'type': 'invalid_request_error', 'message': 'Your credit balance is too low to access the Anthropic API. Please go to Plans & Billing to upgrade or purchase credits.'}, 'request_id': 'req_011CWmNErhaG5fPNTEmUnY2v'}"
+    },
+    {
+      "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: Planning error: Exception: Planning failed with all LLMs. Gemini: 429 You exceeded your current quota, please check your plan and billing details. For more information on this error, head to: https://ai.google.dev/gemini-api/docs/rate-limits. To monitor your current usage, head to: https://ai.dev/usage?tab=rate-limit. \n* Quota exceeded for metric: generativelanguage.googleapis.com/generate_content_free_tier_requests, limit: 0, model: gemini-2.0-flash-exp\n* Quota exceeded for metric: generativelanguage.googleapis.com/generate_content_free_tier_requests, limit: 0, model: gemini-2.0-flash-exp\n* Quota exceeded for metric: generativelanguage.googleapis.com/generate_content_free_tier_input_token_count, limit: 0, model: gemini-2.0-flash-exp\nPlease retry in 3.490976864s. [links {\n  description: \"Learn more about Gemini API quotas\"\n  url: \"https://ai.google.dev/gemini-api/docs/rate-limits\"\n}\n, violations {\n  quota_metric: \"generativelanguage.googleapis.com/generate_content_free_tier_requests\"\n  quota_id: \"GenerateRequestsPerDayPerProjectPerModel-FreeTier\"\n  quota_dimensions {\n    key: \"model\"\n    value: \"gemini-2.0-flash-exp\"\n  }\n  quota_dimensions {\n    key: \"location\"\n    value: \"global\"\n  }\n}\nviolations {\n  quota_metric: \"generativelanguage.googleapis.com/generate_content_free_tier_requests\"\n  quota_id: \"GenerateRequestsPerMinutePerProjectPerModel-FreeTier\"\n  quota_dimensions {\n    key: \"model\"\n    value: \"gemini-2.0-flash-exp\"\n  }\n  quota_dimensions {\n    key: \"location\"\n    value: \"global\"\n  }\n}\nviolations {\n  quota_metric: \"generativelanguage.googleapis.com/generate_content_free_tier_input_token_count\"\n  quota_id: \"GenerateContentInputTokensPerModelPerMinute-FreeTier\"\n  quota_dimensions {\n    key: \"model\"\n    value: \"gemini-2.0-flash-exp\"\n  }\n  quota_dimensions {\n    key: \"location\"\n    value: \"global\"\n  }\n}\n, retry_delay {\n  seconds: 3\n}\n], HF: Client error '402 Payment Required' for url 'https://router.huggingface.co/v1/chat/completions' (Request ID: Root=1-6959afd4-6f89987051f61884058a053b;8578d871-7617-4fa3-9a51-86b4d6afcc89)\nFor more information check: https://developer.mozilla.org/en-US/docs/Web/HTTP/Status/402\n\nYou have reached the free monthly usage limit for novita. Subscribe to PRO to get 20x more included usage, or add pre-paid credits to your account., Claude: Error code: 400 - {'type': 'error', 'error': {'type': 'invalid_request_error', 'message': 'Your credit balance is too low to access the Anthropic API. Please go to Plans & Billing to upgrade or purchase credits.'}, 'request_id': 'req_011CWmNEsRV2oRD9LPHJTMBF'}; Execution error: Exception: Tool selection failed with all LLMs. Gemini: 429 You exceeded your current quota, please check your plan and billing details. For more information on this error, head to: https://ai.google.dev/gemini-api/docs/rate-limits. To monitor your current usage, head to: https://ai.dev/usage?tab=rate-limit. \n* Quota exceeded for metric: generativelanguage.googleapis.com/generate_content_free_tier_input_token_count, limit: 0, model: gemini-2.0-flash-exp\n* Quota exceeded for metric: generativelanguage.googleapis.com/generate_content_free_tier_requests, limit: 0, model: gemini-2.0-flash-exp\n* Quota exceeded for metric: generativelanguage.googleapis.com/generate_content_free_tier_requests, limit: 0, model: gemini-2.0-flash-exp\nPlease retry in 3.338385606s. [links {\n  description: \"Learn more about Gemini API quotas\"\n  url: \"https://ai.google.dev/gemini-api/docs/rate-limits\"\n}\n, violations {\n  quota_metric: \"generativelanguage.googleapis.com/generate_content_free_tier_input_token_count\"\n  quota_id: \"GenerateContentInputTokensPerModelPerMinute-FreeTier\"\n  quota_dimensions {\n    key: \"model\"\n    value: \"gemini-2.0-flash-exp\"\n  }\n  quota_dimensions {\n    key: \"location\"\n    value: \"global\"\n  }\n}\nviolations {\n  quota_metric: \"generativelanguage.googleapis.com/generate_content_free_tier_requests\"\n  quota_id: \"GenerateRequestsPerMinutePerProjectPerModel-FreeTier\"\n  quota_dimensions {\n    key: \"model\"\n    value: \"gemini-2.0-flash-exp\"\n  }\n  quota_dimensions {\n    key: \"location\"\n    value: \"global\"\n  }\n}\nviolations {\n  quota_metric: \"generativelanguage.googleapis.com/generate_content_free_tier_requests\"\n  quota_id: \"GenerateRequestsPerDayPerProjectPerModel-FreeTier\"\n  quota_dimensions {\n    key: \"model\"\n    value: \"gemini-2.0-flash-exp\"\n  }\n  quota_dimensions {\n    key: \"location\"\n    value: \"global\"\n  }\n}\n, retry_delay {\n  seconds: 3\n}\n], HF: Client error '402 Payment Required' for url 'https://router.huggingface.co/v1/chat/completions' (Request ID: Root=1-6959afd4-04822a1e48a801ac7e65b9af;59d83f54-7a75-449a-8c02-628300e94309)\nFor more information check: https://developer.mozilla.org/en-US/docs/Web/HTTP/Status/402\n\nYou have reached the free monthly usage limit for novita. Subscribe to PRO to get 20x more included usage, or add pre-paid credits to your account., Claude: Error code: 400 - {'type': 'error', 'error': {'type': 'invalid_request_error', 'message': 'Your credit balance is too low to access the Anthropic API. Please go to Plans & Billing to upgrade or purchase credits.'}, 'request_id': 'req_011CWmNEt7ADkKf4gRxn1Yo8'}"
+    },
+    {
+      "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": "ERROR: Answer synthesis failed - Exception: Answer synthesis failed with all LLMs. Gemini: 429 You exceeded your current quota, please check your plan and billing details. For more information on this error, head to: https://ai.google.dev/gemini-api/docs/rate-limits. To monitor your current usage, head to: https://ai.dev/usage?tab=rate-limit. \n* Quota exceeded for metric: generativelanguage.googleapis.com/generate_content_free_tier_requests, limit: 0, model: gemini-2.0-flash-exp\n* Quota exceeded for metric: generativelanguage.googleapis.com/generate_content_free_tier_requests, limit: 0, model: gemini-2.0-flash-exp\n* Quota exceeded for metric: generativelanguage.googleapis.com/generate_content_free_tier_input_token_count, limit: 0, model: gemini-2.0-flash-exp\nPlease retry in 1.151799375s. [links {\n  description: \"Learn more about Gemini API quotas\"\n  url: \"https://ai.google.dev/gemini-api/docs/rate-limits\"\n}\n, violations {\n  quota_metric: \"generativelanguage.googleapis.com/generate_content_free_tier_requests\"\n  quota_id: \"GenerateRequestsPerDayPerProjectPerModel-FreeTier\"\n  quota_dimensions {\n    key: \"model\"\n    value: \"gemini-2.0-flash-exp\"\n  }\n  quota_dimensions {\n    key: \"location\"\n    value: \"global\"\n  }\n}\nviolations {\n  quota_metric: \"generativelanguage.googleapis.com/generate_content_free_tier_requests\"\n  quota_id: \"GenerateRequestsPerMinutePerProjectPerModel-FreeTier\"\n  quota_dimensions {\n    key: \"model\"\n    value: \"gemini-2.0-flash-exp\"\n  }\n  quota_dimensions {\n    key: \"location\"\n    value: \"global\"\n  }\n}\nviolations {\n  quota_metric: \"generativelanguage.googleapis.com/generate_content_free_tier_input_token_count\"\n  quota_id: \"GenerateContentInputTokensPerModelPerMinute-FreeTier\"\n  quota_dimensions {\n    key: \"model\"\n    value: \"gemini-2.0-flash-exp\"\n  }\n  quota_dimensions {\n    key: \"location\"\n    value: \"global\"\n  }\n}\n, retry_delay {\n  seconds: 1\n}\n], HF: Client error '402 Payment Required' for url 'https://router.huggingface.co/v1/chat/completions' (Request ID: Root=1-6959afd6-6c2ba73f3d1cb79f3845ee60;03cb8610-4d47-4365-b4b5-c0c59f7b60f2)\nFor more information check: https://developer.mozilla.org/en-US/docs/Web/HTTP/Status/402\n\nYou have reached the free monthly usage limit for novita. Subscribe to PRO to get 20x more included usage, or add pre-paid credits to your account., Claude: Error code: 400 - {'type': 'error', 'error': {'type': 'invalid_request_error', 'message': 'Your credit balance is too low to access the Anthropic API. Please go to Plans & Billing to upgrade or purchase credits.'}, 'request_id': 'req_011CWmNF3SjPhVkdSicuM1NF'}"
+    }
+  ]
+}

pyproject.toml

@@ -31,6 +31,7 @@ dependencies = [
     "gradio[oauth]>=5.0.0",
     "pandas>=2.2.0",
     "tenacity>=9.1.2",
+    "groq>=1.0.0",
 ]
 
 [tool.uv]

requirements.txt

@@ -18,6 +18,7 @@ anthropic>=0.39.0
 # Free baseline alternatives
 google-generativeai>=0.8.0  # Gemini 2.0 Flash (current SDK used in code)
 huggingface-hub>=0.26.0     # For HF Inference API (Qwen, Llama)
+groq>=0.4.0                 # Groq API (Llama 3.1 70B - free tier, 30 req/min)
 
 # ============================================================================
 # Tool Dependencies (Level 5 - Component Selection)

src/agent/graph.py

@@ -30,6 +30,25 @@ from src.agent.llm_client import (
 # ============================================================================
 logger = logging.getLogger(__name__)
 
+# ============================================================================
+# Helper Functions
+# ============================================================================
+
+def is_vision_question(question: str) -> bool:
+    """
+    Detect if question requires vision analysis tool.
+
+    Vision questions typically contain keywords about visual content like images, videos, or YouTube links.
+
+    Args:
+        question: GAIA question text
+
+    Returns:
+        True if question likely requires vision tool, False otherwise
+    """
+    vision_keywords = ["image", "video", "youtube", "photo", "picture", "watch", "screenshot", "visual"]
+    return any(keyword in question.lower() for keyword in vision_keywords)
+
 # ============================================================================
 # Agent State Definition
 # ============================================================================
@@ -299,14 +318,25 @@ def execute_node(state: AgentState) -> AgentState:
                         "status": "failed",
                     }
                 )
-                state["errors"].append(f"Tool {tool_name} failed: {type(tool_error).__name__}: {str(tool_error)}")
+
+                # Provide specific error message for vision tool failures
+                if tool_name == "vision" and ("quota" in str(tool_error).lower() or "429" in str(tool_error)):
+                    state["errors"].append(f"Vision analysis failed: LLM quota exhausted. Vision requires multimodal LLM (Gemini/Claude).")
+                else:
+                    state["errors"].append(f"Tool {tool_name} failed: {type(tool_error).__name__}: {str(tool_error)}")
 
         logger.info(f"[execute_node] Summary: {len(tool_results)} tool(s) executed, {len(evidence)} evidence items collected")
         logger.debug(f"[execute_node] Evidence: {evidence}")
 
     except Exception as e:
         logger.error(f"[execute_node] ✗ Execution failed: {type(e).__name__}: {str(e)}", exc_info=True)
-        state["errors"].append(f"Execution error: {type(e).__name__}: {str(e)}")
+
+        # Graceful handling for vision questions when LLMs unavailable
+        if is_vision_question(state["question"]) and ("quota" in str(e).lower() or "429" in str(e)):
+            logger.warning(f"[execute_node] Vision question detected with quota error - providing graceful skip")
+            state["errors"].append("Vision analysis unavailable (LLM quota exhausted). Vision questions require multimodal LLMs.")
+        else:
+            state["errors"].append(f"Execution error: {type(e).__name__}: {str(e)}")
 
         # Try fallback if we don't have any tool_calls yet
         if not tool_calls:

src/agent/llm_client.py

@@ -16,10 +16,12 @@ Pattern: Matches Stage 2 tools (Gemini primary, Claude fallback)
 
 import os
 import logging
-from typing import List, Dict, Optional, Any
+import time
+from typing import List, Dict, Optional, Any, Callable
 from anthropic import Anthropic
 import google.generativeai as genai
 from huggingface_hub import InferenceClient
+from groq import Groq
 
 # ============================================================================
 # CONFIG
@@ -35,6 +37,10 @@ GEMINI_MODEL = "gemini-2.0-flash-exp"
 HF_MODEL = "Qwen/Qwen2.5-72B-Instruct"  # Excellent for function calling and reasoning
 # Alternatives: "meta-llama/Llama-3.1-70B-Instruct", "NousResearch/Hermes-3-Llama-3.1-70B"
 
+# Groq Configuration
+GROQ_MODEL = "llama-3.1-70b-versatile"  # Free tier: 30 req/min, fast inference
+# Alternatives: "llama-3.1-8b-instant", "mixtral-8x7b-32768"
+
 # Shared Configuration
 TEMPERATURE = 0  # Deterministic for factoid answers
 MAX_TOKENS = 4096
@@ -44,6 +50,56 @@ MAX_TOKENS = 4096
 # ============================================================================
 logger = logging.getLogger(__name__)
 
+# ============================================================================
+# Retry Logic with Exponential Backoff
+# ============================================================================
+
+def retry_with_backoff(func: Callable, max_retries: int = 3) -> Any:
+    """
+    Retry function with exponential backoff on quota errors.
+
+    Handles:
+    - 429 rate limit errors
+    - Quota exceeded errors
+    - Respects retry_after header if present
+
+    Args:
+        func: Function to retry (should be a lambda or callable with no args)
+        max_retries: Maximum number of retry attempts (default: 3)
+
+    Returns:
+        Result of successful function call
+
+    Raises:
+        Exception: If all retries exhausted or non-quota error encountered
+    """
+    for attempt in range(max_retries):
+        try:
+            return func()
+        except Exception as e:
+            error_str = str(e).lower()
+
+            # Check if this is a quota/rate limit error
+            is_quota_error = (
+                "429" in str(e) or
+                "quota" in error_str or
+                "rate limit" in error_str or
+                "too many requests" in error_str
+            )
+
+            if is_quota_error and attempt < max_retries - 1:
+                # Exponential backoff: 1s, 2s, 4s
+                wait_time = 2 ** attempt
+                logger.warning(
+                    f"Quota/rate limit error (attempt {attempt + 1}/{max_retries}): {e}. "
+                    f"Retrying in {wait_time}s..."
+                )
+                time.sleep(wait_time)
+                continue
+
+            # If not a quota error, or last attempt, raise immediately
+            raise
+
 # ============================================================================
 # Client Initialization
 # ============================================================================
@@ -79,6 +135,16 @@ def create_hf_client() -> InferenceClient:
     return InferenceClient(model=HF_MODEL, token=hf_token)
 
 
+def create_groq_client() -> Groq:
+    """Initialize Groq client with API key from environment."""
+    api_key = os.getenv("GROQ_API_KEY")
+    if not api_key:
+        raise ValueError("GROQ_API_KEY environment variable not set")
+
+    logger.info(f"Initializing Groq client with model: {GROQ_MODEL}")
+    return Groq(api_key=api_key)
+
+
 # ============================================================================
 # Planning Functions - Claude Implementation
 # ============================================================================
@@ -266,6 +332,72 @@ Create an execution plan to answer this question. Format as numbered steps."""
     return plan
 
 
+# ============================================================================
+# Planning Functions - Groq Implementation
+# ============================================================================
+
+def plan_question_groq(
+    question: str,
+    available_tools: Dict[str, Dict],
+    file_paths: Optional[List[str]] = None
+) -> str:
+    """Analyze question and generate execution plan using Groq."""
+    client = create_groq_client()
+
+    # Format tool information
+    tool_descriptions = []
+    for name, info in available_tools.items():
+        tool_descriptions.append(
+            f"- {name}: {info['description']} (Category: {info['category']})"
+        )
+    tools_text = "\n".join(tool_descriptions)
+
+    # File context
+    file_context = ""
+    if file_paths:
+        file_context = f"\n\nAvailable files:\n" + "\n".join([f"- {fp}" for fp in file_paths])
+
+    # System message for Llama 3.1 (supports system/user format)
+    system_prompt = """You are a planning agent for answering complex questions.
+
+Your task is to analyze the question and create a step-by-step execution plan.
+
+Consider:
+1. What information is needed to answer the question?
+2. Which tools can provide that information?
+3. In what order should tools be executed?
+4. What parameters need to be extracted from the question?
+
+Generate a concise plan with numbered steps."""
+
+    user_prompt = f"""Question: {question}{file_context}
+
+Available tools:
+{tools_text}
+
+Create an execution plan to answer this question. Format as numbered steps."""
+
+    logger.info(f"[plan_question_groq] Calling Groq ({GROQ_MODEL}) for planning")
+
+    # Groq uses OpenAI-compatible API
+    messages = [
+        {"role": "system", "content": system_prompt},
+        {"role": "user", "content": user_prompt}
+    ]
+
+    response = client.chat.completions.create(
+        model=GROQ_MODEL,
+        messages=messages,
+        max_tokens=MAX_TOKENS,
+        temperature=TEMPERATURE
+    )
+
+    plan = response.choices[0].message.content
+    logger.info(f"[plan_question_groq] Generated plan ({len(plan)} chars)")
+
+    return plan
+
+
 # ============================================================================
 # Unified Planning Function with Fallback Chain
 # ============================================================================
@@ -278,8 +410,9 @@ def plan_question(
     """
     Analyze question and generate execution plan using LLM.
 
-    Pattern: Try Gemini first (free tier), HuggingFace (free tier), then Claude (paid) if both fail.
-    3-tier fallback ensures availability even with quota limits.
+    Pattern: Try Gemini first (free tier), HuggingFace (free tier), Groq (free tier), then Claude (paid) if all fail.
+    4-tier fallback ensures availability even with quota limits.
+    Each provider call wrapped with retry logic (3 attempts with exponential backoff).
 
     Args:
         question: GAIA question text
@@ -290,18 +423,30 @@ def plan_question(
         Execution plan as structured text
     """
     try:
-        return plan_question_gemini(question, available_tools, file_paths)
+        return retry_with_backoff(
+            lambda: plan_question_gemini(question, available_tools, file_paths)
+        )
     except Exception as gemini_error:
         logger.warning(f"[plan_question] Gemini failed: {gemini_error}, trying HuggingFace fallback")
         try:
-            return plan_question_hf(question, available_tools, file_paths)
+            return retry_with_backoff(
+                lambda: plan_question_hf(question, available_tools, file_paths)
+            )
         except Exception as hf_error:
-            logger.warning(f"[plan_question] HuggingFace failed: {hf_error}, trying Claude fallback")
+            logger.warning(f"[plan_question] HuggingFace failed: {hf_error}, trying Groq fallback")
             try:
-                return plan_question_claude(question, available_tools, file_paths)
-            except Exception as claude_error:
-                logger.error(f"[plan_question] All LLMs failed. Gemini: {gemini_error}, HF: {hf_error}, Claude: {claude_error}")
-                raise Exception(f"Planning failed with all LLMs. Gemini: {gemini_error}, HF: {hf_error}, Claude: {claude_error}")
+                return retry_with_backoff(
+                    lambda: plan_question_groq(question, available_tools, file_paths)
+                )
+            except Exception as groq_error:
+                logger.warning(f"[plan_question] Groq failed: {groq_error}, trying Claude fallback")
+                try:
+                    return retry_with_backoff(
+                        lambda: plan_question_claude(question, available_tools, file_paths)
+                    )
+                except Exception as claude_error:
+                    logger.error(f"[plan_question] All LLMs failed. Gemini: {gemini_error}, HF: {hf_error}, Groq: {groq_error}, Claude: {claude_error}")
+                    raise Exception(f"Planning failed with all LLMs. Gemini: {gemini_error}, HF: {hf_error}, Groq: {groq_error}, Claude: {claude_error}")
 
 
 # ============================================================================
@@ -329,16 +474,22 @@ def select_tools_claude(
             }
         })
 
-    system_prompt = f"""You are a tool selection agent. Based on the question and execution plan, select appropriate tools to use.
+    system_prompt = f"""You are a tool selection expert. Based on the question and execution plan, select appropriate tools with correct parameters.
 
-Execute the plan step by step. Call the necessary tools with correct parameters extracted from the question.
+Few-shot examples:
+- "How many albums did The Beatles release?" → web_search(query="Beatles discography number of albums")
+- "What is 25 * 37 + 100?" → calculator(expression="25 * 37 + 100")
+- "Analyze the image at example.com/pic.jpg" → vision(image_url="example.com/pic.jpg")
+- "What's in the uploaded Excel file?" → parse_file(file_path="<provided_path>")
+
+Execute the plan step by step. Extract correct parameters from the question.
 
 Plan:
 {plan}"""
 
     user_prompt = f"""Question: {question}
 
-Select and call the tools needed to answer this question according to the plan."""
+Select and call the tools needed according to the plan. Use exact parameter names from tool schemas."""
 
     logger.info(f"[select_tools_claude] Calling Claude with function calling for {len(tool_schemas)} tools")
 
@@ -401,16 +552,22 @@ def select_tools_gemini(
             ]
         ))
 
-    prompt = f"""You are a tool selection agent. Based on the question and execution plan, select appropriate tools to use.
+    prompt = f"""You are a tool selection expert. Based on the question and execution plan, select appropriate tools with correct parameters.
+
+Few-shot examples:
+- "How many albums did The Beatles release?" → web_search(query="Beatles discography number of albums")
+- "What is 25 * 37 + 100?" → calculator(expression="25 * 37 + 100")
+- "Analyze the image at example.com/pic.jpg" → vision(image_url="example.com/pic.jpg")
+- "What's in the uploaded Excel file?" → parse_file(file_path="<provided_path>")
 
-Execute the plan step by step. Call the necessary tools with correct parameters extracted from the question.
+Execute the plan step by step. Extract correct parameters from the question.
 
 Plan:
 {plan}
 
 Question: {question}
 
-Select and call the tools needed to answer this question according to the plan."""
+Select and call the tools needed according to the plan. Use exact parameter names from tool schemas."""
 
     logger.info(f"[select_tools_gemini] Calling Gemini with function calling for {len(available_tools)} tools")
 
@@ -476,16 +633,22 @@ def select_tools_hf(
 
         tools.append(tool_schema)
 
-    system_prompt = f"""You are a tool selection agent. Based on the question and execution plan, select appropriate tools to use.
+    system_prompt = f"""You are a tool selection expert. Based on the question and execution plan, select appropriate tools with correct parameters.
 
-Execute the plan step by step. Call the necessary tools with correct parameters extracted from the question.
+Few-shot examples:
+- "How many albums did The Beatles release?" → web_search(query="Beatles discography number of albums")
+- "What is 25 * 37 + 100?" → calculator(expression="25 * 37 + 100")
+- "Analyze the image at example.com/pic.jpg" → vision(image_url="example.com/pic.jpg")
+- "What's in the uploaded Excel file?" → parse_file(file_path="<provided_path>")
+
+Execute the plan step by step. Extract correct parameters from the question.
 
 Plan:
 {plan}"""
 
     user_prompt = f"""Question: {question}
 
-Select and call the tools needed to answer this question according to the plan."""
+Select and call the tools needed according to the plan. Use exact parameter names from tool schemas."""
 
     logger.info(f"[select_tools_hf] Calling HuggingFace with function calling for {len(tools)} tools")
 
@@ -518,6 +681,92 @@ Select and call the tools needed to answer this question according to the plan."
     return tool_calls
 
 
+# ============================================================================
+# Tool Selection - Groq Implementation
+# ============================================================================
+
+def select_tools_groq(
+    question: str,
+    plan: str,
+    available_tools: Dict[str, Dict]
+) -> List[Dict[str, Any]]:
+    """Use Groq with function calling to select tools and extract parameters."""
+    client = create_groq_client()
+
+    # Convert tool registry to OpenAI-compatible tool schema (Groq uses same format)
+    tools = []
+    for name, info in available_tools.items():
+        tool_schema = {
+            "type": "function",
+            "function": {
+                "name": name,
+                "description": info["description"],
+                "parameters": {
+                    "type": "object",
+                    "properties": {},
+                    "required": info.get("required_params", [])
+                }
+            }
+        }
+
+        # Add parameter schemas
+        for param_name, param_info in info.get("parameters", {}).items():
+            tool_schema["function"]["parameters"]["properties"][param_name] = {
+                "type": param_info.get("type", "string"),
+                "description": param_info.get("description", "")
+            }
+
+        tools.append(tool_schema)
+
+    system_prompt = f"""You are a tool selection expert. Based on the question and execution plan, select appropriate tools with correct parameters.
+
+Few-shot examples:
+- "How many albums did The Beatles release?" → web_search(query="Beatles discography number of albums")
+- "What is 25 * 37 + 100?" → calculator(expression="25 * 37 + 100")
+- "Analyze the image at example.com/pic.jpg" → vision(image_url="example.com/pic.jpg")
+- "What's in the uploaded Excel file?" → parse_file(file_path="<provided_path>")
+
+Execute the plan step by step. Extract correct parameters from the question.
+
+Plan:
+{plan}"""
+
+    user_prompt = f"""Question: {question}
+
+Select and call the tools needed according to the plan. Use exact parameter names from tool schemas."""
+
+    logger.info(f"[select_tools_groq] Calling Groq with function calling for {len(tools)} tools")
+
+    messages = [
+        {"role": "system", "content": system_prompt},
+        {"role": "user", "content": user_prompt}
+    ]
+
+    # Groq function calling
+    response = client.chat.completions.create(
+        model=GROQ_MODEL,
+        messages=messages,
+        tools=tools,
+        max_tokens=MAX_TOKENS,
+        temperature=TEMPERATURE
+    )
+
+    # Extract tool calls from response
+    tool_calls = []
+    if hasattr(response.choices[0].message, 'tool_calls') and response.choices[0].message.tool_calls:
+        for tool_call in response.choices[0].message.tool_calls:
+            import json
+            tool_calls.append({
+                "tool": tool_call.function.name,
+                "params": json.loads(tool_call.function.arguments),
+                "id": tool_call.id
+            })
+
+    logger.info(f"[select_tools_groq] Groq selected {len(tool_calls)} tool(s)")
+
+    return tool_calls
+
+
 # ============================================================================
 # Unified Tool Selection with Fallback Chain
 # ============================================================================
@@ -530,8 +779,9 @@ def select_tools_with_function_calling(
     """
     Use LLM function calling to dynamically select tools and extract parameters.
 
-    Pattern: Try Gemini first (free tier), HuggingFace (free tier), then Claude (paid) if both fail.
-    3-tier fallback ensures availability even with quota limits.
+    Pattern: Try Gemini first (free tier), HuggingFace (free tier), Groq (free tier), then Claude (paid) if all fail.
+    4-tier fallback ensures availability even with quota limits.
+    Each provider call wrapped with retry logic (3 attempts with exponential backoff).
 
     Args:
         question: GAIA question text
@@ -542,18 +792,30 @@ def select_tools_with_function_calling(
         List of tool calls with extracted parameters
     """
     try:
-        return select_tools_gemini(question, plan, available_tools)
+        return retry_with_backoff(
+            lambda: select_tools_gemini(question, plan, available_tools)
+        )
     except Exception as gemini_error:
         logger.warning(f"[select_tools] Gemini failed: {gemini_error}, trying HuggingFace fallback")
         try:
-            return select_tools_hf(question, plan, available_tools)
+            return retry_with_backoff(
+                lambda: select_tools_hf(question, plan, available_tools)
+            )
         except Exception as hf_error:
-            logger.warning(f"[select_tools] HuggingFace failed: {hf_error}, trying Claude fallback")
+            logger.warning(f"[select_tools] HuggingFace failed: {hf_error}, trying Groq fallback")
             try:
-                return select_tools_claude(question, plan, available_tools)
-            except Exception as claude_error:
-                logger.error(f"[select_tools] All LLMs failed. Gemini: {gemini_error}, HF: {hf_error}, Claude: {claude_error}")
-                raise Exception(f"Tool selection failed with all LLMs. Gemini: {gemini_error}, HF: {hf_error}, Claude: {claude_error}")
+                return retry_with_backoff(
+                    lambda: select_tools_groq(question, plan, available_tools)
+                )
+            except Exception as groq_error:
+                logger.warning(f"[select_tools] Groq failed: {groq_error}, trying Claude fallback")
+                try:
+                    return retry_with_backoff(
+                        lambda: select_tools_claude(question, plan, available_tools)
+                    )
+                except Exception as claude_error:
+                    logger.error(f"[select_tools] All LLMs failed. Gemini: {gemini_error}, HF: {hf_error}, Groq: {groq_error}, Claude: {claude_error}")
+                    raise Exception(f"Tool selection failed with all LLMs. Gemini: {gemini_error}, HF: {hf_error}, Groq: {groq_error}, Claude: {claude_error}")
 
 
 # ============================================================================
@@ -732,6 +994,68 @@ Extract the factoid answer from the evidence above. Return only the factoid, not
     return answer
 
 
+# ============================================================================
+# Answer Synthesis - Groq Implementation
+# ============================================================================
+
+def synthesize_answer_groq(
+    question: str,
+    evidence: List[str]
+) -> str:
+    """Synthesize factoid answer from evidence using Groq."""
+    client = create_groq_client()
+
+    # Format evidence
+    evidence_text = "\n\n".join([f"Evidence {i+1}:\n{e}" for i, e in enumerate(evidence)])
+
+    system_prompt = """You are an answer synthesis agent for the GAIA benchmark.
+
+Your task is to extract a factoid answer from the provided evidence.
+
+CRITICAL - Answer format requirements:
+1. Answers must be factoids: a number, a few words, or a comma-separated list
+2. Be concise - no explanations, just the answer
+3. If evidence conflicts, evaluate source credibility and recency
+4. If evidence is insufficient, state "Unable to answer"
+
+Examples of good factoid answers:
+- "42"
+- "Paris"
+- "Albert Einstein"
+- "red, blue, green"
+- "1969-07-20"
+
+Examples of bad answers (too verbose):
+- "The answer is 42 because..."
+- "Based on the evidence, it appears that..."
+"""
+
+    user_prompt = f"""Question: {question}
+
+{evidence_text}
+
+Extract the factoid answer from the evidence above. Return only the factoid, nothing else."""
+
+    logger.info(f"[synthesize_answer_groq] Calling Groq for answer synthesis")
+
+    messages = [
+        {"role": "system", "content": system_prompt},
+        {"role": "user", "content": user_prompt}
+    ]
+
+    response = client.chat.completions.create(
+        model=GROQ_MODEL,
+        messages=messages,
+        max_tokens=256,  # Factoid answers are short
+        temperature=TEMPERATURE
+    )
+
+    answer = response.choices[0].message.content.strip()
+    logger.info(f"[synthesize_answer_groq] Generated answer: {answer}")
+
+    return answer
+
+
 # ============================================================================
 # Unified Answer Synthesis with Fallback Chain
 # ============================================================================
@@ -743,8 +1067,9 @@ def synthesize_answer(
     """
     Synthesize factoid answer from collected evidence using LLM.
 
-    Pattern: Try Gemini first (free tier), HuggingFace (free tier), then Claude (paid) if both fail.
-    3-tier fallback ensures availability even with quota limits.
+    Pattern: Try Gemini first (free tier), HuggingFace (free tier), Groq (free tier), then Claude (paid) if all fail.
+    4-tier fallback ensures availability even with quota limits.
+    Each provider call wrapped with retry logic (3 attempts with exponential backoff).
 
     Args:
         question: Original GAIA question
@@ -754,18 +1079,30 @@ def synthesize_answer(
         Factoid answer string
     """
     try:
-        return synthesize_answer_gemini(question, evidence)
+        return retry_with_backoff(
+            lambda: synthesize_answer_gemini(question, evidence)
+        )
     except Exception as gemini_error:
         logger.warning(f"[synthesize_answer] Gemini failed: {gemini_error}, trying HuggingFace fallback")
         try:
-            return synthesize_answer_hf(question, evidence)
+            return retry_with_backoff(
+                lambda: synthesize_answer_hf(question, evidence)
+            )
         except Exception as hf_error:
-            logger.warning(f"[synthesize_answer] HuggingFace failed: {hf_error}, trying Claude fallback")
+            logger.warning(f"[synthesize_answer] HuggingFace failed: {hf_error}, trying Groq fallback")
             try:
-                return synthesize_answer_claude(question, evidence)
-            except Exception as claude_error:
-                logger.error(f"[synthesize_answer] All LLMs failed. Gemini: {gemini_error}, HF: {hf_error}, Claude: {claude_error}")
-                raise Exception(f"Answer synthesis failed with all LLMs. Gemini: {gemini_error}, HF: {hf_error}, Claude: {claude_error}")
+                return retry_with_backoff(
+                    lambda: synthesize_answer_groq(question, evidence)
+                )
+            except Exception as groq_error:
+                logger.warning(f"[synthesize_answer] Groq failed: {groq_error}, trying Claude fallback")
+                try:
+                    return retry_with_backoff(
+                        lambda: synthesize_answer_claude(question, evidence)
+                    )
+                except Exception as claude_error:
+                    logger.error(f"[synthesize_answer] All LLMs failed. Gemini: {gemini_error}, HF: {hf_error}, Groq: {groq_error}, Claude: {claude_error}")
+                    raise Exception(f"Answer synthesis failed with all LLMs. Gemini: {gemini_error}, HF: {hf_error}, Groq: {groq_error}, Claude: {claude_error}")
 
 
 # ============================================================================

src/tools/__init__.py

@@ -21,7 +21,7 @@ from src.tools.vision import analyze_image, analyze_image_gemini, analyze_image_
 TOOLS = {
     "web_search": {
         "function": search,
-        "description": "Search the web using Tavily or Exa APIs with fallback",
+        "description": "Search the web for factual information, current events, Wikipedia articles, statistics, people, companies, and research. Use when question requires external knowledge not in context or files.",
         "parameters": {
             "query": {
                 "description": "Search query string",
@@ -37,7 +37,7 @@ TOOLS = {
     },
     "parse_file": {
         "function": parse_file,
-        "description": "Parse files (PDF, Excel, Word, Text, CSV) and extract content",
+        "description": "Extract and parse content from uploaded files (PDF, Excel, Word, Text, CSV). Use when question references 'the file', 'uploaded document', 'attachment', or specific file formats. Reads file structure and text content.",
         "parameters": {
             "file_path": {
                 "description": "Absolute or relative path to the file to parse",
@@ -49,10 +49,10 @@ TOOLS = {
     },
     "calculator": {
         "function": safe_eval,
-        "description": "Safely evaluate mathematical expressions",
+        "description": "Evaluate mathematical expressions and perform calculations (arithmetic, algebra, trigonometry, logarithms). Supports operators (+, -, *, /, **) and functions (sqrt, sin, cos, log, abs, etc). Use for any numerical computation or formula evaluation.",
         "parameters": {
             "expression": {
-                "description": "Mathematical expression to evaluate (e.g., '2 + 2', 'sqrt(16)')",
+                "description": "Mathematical expression to evaluate (e.g., '2 + 2', 'sqrt(16)', '25 * 37 + 100')",
                 "type": "string"
             }
         },
@@ -61,7 +61,7 @@ TOOLS = {
     },
     "vision": {
         "function": analyze_image,
-        "description": "Analyze images using multimodal LLMs (Gemini/Claude)",
+        "description": "Analyze images or videos using multimodal AI vision models. Describe visual content, identify objects, read text from images, answer questions about photos or screenshots. Use when question mentions images, photos, pictures, videos, YouTube links, or visual content.",
         "parameters": {
             "image_path": {
                 "description": "Path to the image file to analyze",

src/tools/calculator.py

@@ -255,17 +255,36 @@ def safe_eval(expression: str) -> Dict[str, Any]:
 
         >>> safe_eval("import os")  # Raises ValueError
     """
-    # Input validation
+    # Input validation - relaxed to avoid crashes
     if not expression or not isinstance(expression, str):
-        raise ValueError("Expression must be a non-empty string")
+        logger.warning("Calculator received empty or non-string expression - returning graceful error")
+        return {
+            "result": None,
+            "expression": str(expression) if expression else "",
+            "success": False,
+            "error": "Empty expression provided. Calculator requires a mathematical expression string."
+        }
 
     expression = expression.strip()
 
+    # Handle case where expression becomes empty after stripping whitespace
+    if not expression:
+        logger.warning("Calculator expression was only whitespace - returning graceful error")
+        return {
+            "result": None,
+            "expression": "",
+            "success": False,
+            "error": "Expression was only whitespace. Provide a valid mathematical expression."
+        }
+
     if len(expression) > MAX_EXPRESSION_LENGTH:
-        raise ValueError(
-            f"Expression too long ({len(expression)} chars). "
-            f"Maximum: {MAX_EXPRESSION_LENGTH} chars"
-        )
+        logger.warning(f"Expression too long ({len(expression)} chars) - returning graceful error")
+        return {
+            "result": None,
+            "expression": expression[:100] + "...",
+            "success": False,
+            "error": f"Expression too long ({len(expression)} chars). Maximum: {MAX_EXPRESSION_LENGTH} chars"
+        }
 
     logger.info(f"Evaluating expression: {expression}")
 

test/test_calculator.py

@@ -220,16 +220,20 @@ def test_invalid_syntax():
 
 
 def test_empty_expression():
-    """Test empty expression raises error"""
-    with pytest.raises(ValueError, match="non-empty string"):
-        safe_eval("")
+    """Test empty expression returns graceful error dict"""
+    result = safe_eval("")
+    assert result["success"] is False
+    assert "Empty expression" in result["error"]
+    assert result["result"] is None
 
 
 def test_too_long_expression():
-    """Test expression length limit"""
+    """Test expression length limit returns graceful error dict"""
     long_expr = "1 + " * 300 + "1"
-    with pytest.raises(ValueError, match="too long"):
-        safe_eval(long_expr)
+    result = safe_eval(long_expr)
+    assert result["success"] is False
+    assert "too long" in result["error"]
+    assert result["result"] is None
 
 
 def test_huge_exponent():