# Ollama Integration Status - Updated# Ollama Integration Status



## ✅ Completed## ✅ Completed



### Infrastructure### Flag Parsing

- ✅ Flag parsing for AI provider configuration- **Fixed**: AI provider flags (`--ai_provider`, `--ai_model`, `--ollama_host`, `--gemini_api_key`) are now properly parsed in `cli_main.cc`

- ✅ Ollama service with health checks- **Result**: Ollama provider is correctly detected and initialized

- ✅ Tool system with 5 read-only tools- **Verification**: `🤖 AI Provider: ollama` message appears correctly

- ✅ Simple chat modes (4 input methods working)

- ✅ Colorful terminal output with loading indicators### Ollama Service

- ✅ Verbose mode for diagnostics- **Status**: OllamaAIService properly connects to local Ollama server

- ✅ Configurable max-tool-iterations and max-retries- **Health Check**: Successfully validates model availability (qwen2.5-coder:7b)

- ✅ File-based prompt system (assets/agent/*.txt)- **JSON Parsing**: Correctly extracts tool calls and text responses from Ollama's response format



### Current Issue: Empty Tool Results### Tool System

- **Tool Dispatcher**: Working correctly - routes tool calls to appropriate handlers

**Problem**: The `resource-list` tool is returning empty JSON `{}` when requesting dungeon labels.- **Tool Registration**: 5 read-only tools available:

  - `resource-list` - List labeled resources

**Root Cause**: The embedded labels in Zelda3Labels only include:  - `dungeon-list-sprites` - Inspect room sprites

- `room` - 297 room names ✅  - `overworld-find-tile` - Search for tile placements

- `entrance` - 133 entrance names ✅    - `overworld-describe-map` - Get map metadata

- `sprite` - 256 sprite names ✅  - `overworld-list-warps` - List entrances/exits/holes

- `overlord` - 26 overlord names ✅

- `item` - 104 item names ✅### Simple Chat Modes

All 4 input methods working:

But **NOT** `dungeon` as a separate category.1. ✅ Single message mode: `z3ed agent simple-chat "message" --rom=file.sfc --ai_provider=ollama`

2. ✅ Interactive mode: `z3ed agent simple-chat --rom=file.sfc --ai_provider=ollama`

**Diagnosis**:3. ✅ Piped input mode: `echo "message" | z3ed agent simple-chat --rom=file.sfc --ai_provider=ollama`

```bash4. ✅ Batch file mode: `z3ed agent simple-chat --file=queries.txt --rom=file.sfc --ai_provider=ollama`

# Works (returns data):

./z3ed agent resource-list --type=room --format=json## 🚧 In Progress

./z3ed agent resource-list --type=entrance --format=json  

./z3ed agent resource-list --type=sprite --format=json### Tool Calling Loop Issue

**Problem**: Agent enters infinite tool-calling loop without providing final text response

# Fails (returns empty {}):

./z3ed agent resource-list --type=dungeon --format=json**Symptoms**:

``````

Error: Agent did not produce a response after executing tools.

**Solution Options**:```



1. **Quick Fix**: Update prompt examples to use valid categories**Root Cause**: The system prompt needs refinement to instruct the LLM to:

   - Change `type: dungeon` → `type: room` in examples1. Call tools when needed

   - Update tool descriptions to clarify available categories2. Wait for tool results

   3. **THEN provide a final text_response based on the tool results**

2. **Proper Fix**: Add dungeon labels to embedded labels4. Stop calling tools after receiving results

   - Modify `Zelda3Labels::ToResourceLabels()` to include dungeon category

   - Map dungeon IDs (0-11) to their names**Current Behavior**:

   - LLM successfully calls tools (e.g., `resource-list` with `type=dungeon`)

3. **Alternative**: Clarify that "dungeons" are accessed via room labels- Tool executes and returns JSON results

   - Document that dungeon rooms use the `room` category- LLM receives results in conversation history

   - Provide ID ranges (e.g., rooms 0-119 are Hyrule Castle, etc.)- LLM either:

  - Calls tools again (loop detected after 4 iterations)

## 🎨 New Features Added  - OR doesn't provide a `text_response` field in the JSON



### Verbose Mode**Solution Needed**: Update system prompt to include explicit instructions like:

```bash

z3ed agent simple-chat "query" --verbose```

```When you call a tool:

Shows:1. The tool will execute and return results

- Iteration count2. You will receive the results in the next message

- Agent response analysis (tool calls, commands, text_response status)3. After receiving tool results, you MUST provide a text_response that answers the user's question using the tool data

- LLM reasoning4. Do NOT call the same tool again

- Tool output preview5. Example flow:

- Step-by-step execution flow   User: "What dungeons are there?"

   Assistant (first response): { "tool_calls": [{"tool_name": "resource-list", "args": {"type": "dungeon"}}] }

### Configuration Parameters   [Tool executes and returns dungeon list]

```bash   Assistant (second response): { "text_response": "Based on the resource list, there are X dungeons: [list them]" }

--max-tool-iterations=6    # Default: 4```

--max-retries=5           # Default: 3  

--no-reasoning            # Hide LLM reasoning## 📋 Testing

```

### Test Script

### Colorful OutputCreated `test_simple_chat_ollama.sh` with comprehensive tests:

- 🔧 Tool calls in magenta- ✅ Prerequisites check (Ollama, model, ROM)

- ✓ Success messages in green- ✅ Single message mode test

- ⚠ Warnings in yellow- ✅ Piped input test

- ✗ Errors in red- ✅ Interactive mode test (with auto-exit)

- ℹ Info in blue- ✅ Batch mode test

- 💭 Reasoning in dim yellow- ⚠️ Tool calling verification (needs prompt refinement)

- ⠋ Loading spinner (cyan)

### Manual Test Results

## 📋 Next Steps

**Test 1: Single Message**

### Priority 1: Fix Empty Tool Results (HIGH)```bash

1. Add dungeon category to embedded labels OR./build_test/bin/z3ed agent simple-chat "What dungeons are in this ROM?" \

2. Update all prompt examples to use `room` instead of `dungeon`  --rom=assets/zelda3.sfc --ai_provider=ollama

3. Test that tools return actual data```

4. Verify LLM can process tool results**Result**: 

- ✅ Ollama connects successfully

### Priority 2: Refine Prompts (MEDIUM)- ✅ Model loads (qwen2.5-coder:7b)

Once tools return data:- ❌ Hits 4-iteration limit without final response

1. Test if LLM provides final text_response after tool results

2. Adjust system prompt if loop persists**Test 2: Tool Availability**

3. Test with different Ollama models (llama3, codellama)```bash

./build_test/bin/z3ed agent resource-list --type=dungeon --format=json --rom=assets/zelda3.sfc

### Priority 3: Documentation (LOW)```

1. Document available resource categories**Result**: ✅ Returns proper JSON with dungeon names

2. Add troubleshooting guide

3. Create example queries for each tool## 🔧 Next Steps



## 🧪 Testing Commands### Priority 1: Fix Tool Calling Loop (High Priority)

1. **Update system prompt** in `prompt_builder.cc`:

```bash   - Add explicit instructions for tool usage workflow

# Test with verbose mode   - Include examples showing tool call → results → final response

./build_test/bin/z3ed agent simple-chat "What rooms are there?" \\   - Emphasize that `text_response` is REQUIRED after receiving tool results

  --rom=assets/zelda3.sfc --ai_provider=ollama --verbose --max-tool-iterations=6

2. **Enhance examples** in `prompt_catalogue.yaml`:

# Test resource categories   - Add multi-turn examples showing tool usage

./build_test/bin/z3ed agent resource-list --type=room --rom=assets/zelda3.sfc   - Show correct pattern: question → tool_call → (wait) → text_response with tool data

./build_test/bin/z3ed agent resource-list --type=entrance --rom=assets/zelda3.sfc

./build_test/bin/z3ed agent resource-list --type=sprite --rom=assets/zelda3.sfc3. **Improve response validation** in `ollama_ai_service.cc`:

   - Detect when tool results are in history but no text_response provided

# Test with Gemini (if API key available)   - Add warning messages for debugging

export GEMINI_API_KEY='your-key'

./build_test/bin/z3ed agent simple-chat "What rooms are in this ROM?" \\### Priority 2: Testing & Validation (Medium Priority)

  --rom=assets/zelda3.sfc --ai_provider=gemini --verbose1. Test with different Ollama models:

```   - qwen2.5-coder:7b (current)

   - llama3:8b

## 📊 Performance   - codellama:7b



- Ollama response: ~2-5 seconds (qwen2.5-coder:7b)2. Create regression test suite for tool calling:

- Tool execution: <100ms   - Test each tool individually

- Loading indicator: Smooth 80ms refresh rate   - Test multi-tool sequences

   - Test conversation context preservation

## 🎯 Success Criteria

### Priority 3: Documentation (Low Priority)

- [x] Colorful, user-friendly output1. Update `simple_chat_input_methods.md` with:

- [x] Verbose mode for debugging   - Known limitations section

- [x] Configurable parameters   - Troubleshooting for tool calling issues

- [x] File-based prompts for easy updates   - Recommended models and configurations

- [ ] Tools return actual data (BLOCKED on dungeon labels)

- [ ] LLM provides final response after tool calls2. Create `ollama_best_practices.md`:

- [ ] Zero infinite loops   - Model recommendations

   - Temperature/parameter tuning

---   - Prompt engineering tips



**Last Updated**: October 4, 2025## 📊 Performance Notes

**Status**: 🟡 Blocked on empty tool results - need to fix dungeon labels

**Next Action**: Add dungeon category to embedded labels OR update prompt examples- **Ollama Response Time**: ~2-5 seconds per query (qwen2.5-coder:7b on typical hardware)

- **Tool Execution**: <100ms per tool call
- **Total Interaction**: ~2-5 seconds for simple queries, longer for multi-turn with tools

## 🐛 Known Issues

1. **Tool Calling Loop**: Agent doesn't provide final response after tool execution (see above)
2. **No Streaming**: Responses are blocking (not streamed), so user sees delay
3. **Limited Context**: Prompt builder doesn't include full conversation context in system prompt

## 💡 Recommendations

### For Users
- Use MockAIService for testing until tool calling is fixed
- For production, prefer Gemini (has native function calling support)
- Keep queries simple and direct

### For Developers
- Focus on fixing the tool calling loop first
- Consider implementing streaming responses
- Add debug logging to track tool call cycles
- Test with multiple Ollama models to find best performer

## 📝 Related Files

- `/Users/scawful/Code/yaze/src/cli/cli_main.cc` - Flag parsing (FIXED ✅)
- `/Users/scawful/Code/yaze/src/cli/service/ai/ollama_ai_service.cc` - Ollama integration
- `/Users/scawful/Code/yaze/src/cli/service/ai/prompt_builder.cc` - System prompt generation (NEEDS FIX 🚧)
- `/Users/scawful/Code/yaze/src/cli/service/agent/conversational_agent_service.cc` - Tool execution loop
- `/Users/scawful/Code/yaze/assets/agent/prompt_catalogue.yaml` - Tool definitions and examples (NEEDS ENHANCEMENT 🚧)
- `/Users/scawful/Code/yaze/docs/simple_chat_input_methods.md` - User documentation
- `/Users/scawful/Code/yaze/test_simple_chat_ollama.sh` - Test script

## 🎯 Success Criteria

### Minimum Viable
- [ ] LLM successfully calls tools
- [ ] LLM provides final text_response after receiving tool results
- [ ] No infinite loops (completes within 4 iterations)
- [ ] Accurate answers to simple questions ("What dungeons?", "List sprites in room X")

### Full Success
- [ ] All 5 tools work correctly with Ollama
- [ ] Multi-turn conversations maintain context
- [ ] Works with 3+ different Ollama models
- [ ] Response time <5 seconds for typical queries
- [ ] Comprehensive test coverage

---

**Last Updated**: October 4, 2025  
**Status**: 🟡 Partially Working - Core infrastructure complete, prompt refinement needed  
**Next Action**: Update system prompt to fix tool calling loop