CONTEXT_STRUCTURE_FIX_IMPLEMENTATION.md

# Context Structure Fix Implementation

## Summary

Fixed context structure mismatches across all agents to properly use the Context Manager's actual data structure. All agents now correctly access `interaction_contexts`, `user_context`, and `combined_context` instead of non-existent keys like `conversation_history` or `interactions`.

## Changes Made

### 1. Intent Recognition Agent (`src/agents/intent_agent.py`)

**Problem**: Was accessing `context.get('conversation_history', [])` which doesn't exist.

**Fix**: 
- Now uses `combined_context` (preferred) or builds from `interaction_contexts` and `user_context`
- Shows last 2 interaction summaries for context awareness
- Includes user context if available
- Provides informative message when no context is available

**Key Changes**:
```python
# OLD (line 109):
Available Context: {context.get('conversation_history', [])[-2:] if context else []}

# NEW:
# Uses combined_context if available, otherwise builds from interaction_contexts
combined_context = context.get('combined_context', '')
interaction_contexts = context.get('interaction_contexts', [])
user_context = context.get('user_context', '')
```

**Impact**: Intent agent now sees actual conversation history, improving intent recognition accuracy for follow-up questions.

---

### 2. Response Synthesis Agent (`src/agents/synthesis_agent.py`)

**Problem**: Was accessing `context.get('interactions', [])` which doesn't exist.

**Fix**:
- `_build_context_section()` now uses `combined_context` (preferred) or builds from `interaction_contexts`
- Updated `_summarize_interaction_contexts()` to work with Context Manager structure
- Added backward compatibility via `_summarize_interactions()` wrapper
- Updated logging and metadata to use correct keys

**Key Changes**:
```python
# OLD (line 534):
interactions = context.get('interactions', [])

# NEW:
combined_context = context.get('combined_context', '')
interaction_contexts = context.get('interaction_contexts', [])
user_context = context.get('user_context', '')
```

**Impact**: Synthesis agent now uses actual conversation context for generating contextually relevant responses.

---

### 3. Safety Check Agent (`src/agents/safety_agent.py`)

**Problem**: Wasn't using context at all in safety analysis.

**Fix**:
- Enhanced `_build_safety_prompt()` to include context information
- Uses `user_context` and recent `interaction_contexts` for context-aware safety analysis
- Helps safety agent understand conversational context when assessing content appropriateness

**Key Changes**:
```python
# Added context awareness:
user_context = context.get('user_context', '')
interaction_contexts = context.get('interaction_contexts', [])
# Includes context in safety analysis prompt
```

**Impact**: Safety analysis now considers conversation context, improving appropriateness assessment.

---

### 4. Skills Identification Agent (`src/agents/skills_identification_agent.py`)

**Problem**: Wasn't using context in skill identification.

**Fix**:
- Enhanced `_build_market_analysis_prompt()` to accept and use context parameter
- Includes user context and recent interaction contexts in market analysis
- Helps identify skills based on conversation continuity

**Key Changes**:
```python
# Updated method signature:
def _build_market_analysis_prompt(self, user_input: str, context: Dict[str, Any] = None)

# Added context information:
user_context = context.get('user_context', '')
interaction_contexts = context.get('interaction_contexts', [])
```

**Impact**: Skills identification now considers conversation history for better skill relevance.

---

## Context Structure Reference

All agents now correctly use the Context Manager's structure:

```python
context = {
    "session_id": str,
    "user_id": str,
    "user_context": str,  # 500-token user persona summary
    "interaction_contexts": [  # List of interaction summary dicts
        {
            "summary": str,  # 50-token interaction summary
            "timestamp": str
        },
        ...
    ],
    "combined_context": str,  # Pre-formatted: "[User Context]\n...\n[Interaction Context #N]\n..."
    "preferences": dict,
    "active_tasks": list,
    "last_activity": str
}
```

## Implementation Strategy

### Priority Order
1. **Use `combined_context` first** - Pre-formatted by Context Manager, most efficient
2. **Fallback to building from components** - If `combined_context` not available
3. **Handle empty context gracefully** - Informative messages when no context exists

### Context Access Pattern
```python
# Preferred pattern used across all agents:
if context:
    # Option 1: Use pre-formatted combined_context
    combined_context = context.get('combined_context', '')
    if combined_context:
        # Use combined_context directly
        context_info = combined_context
    
    # Option 2: Build from components
    else:
        user_context = context.get('user_context', '')
        interaction_contexts = context.get('interaction_contexts', [])
        # Build context_info from components
```

## Testing Recommendations

### Test Scenarios

1. **First Turn (No Context)**
   - Verify agents handle empty context gracefully
   - Verify informative messages when no context available

2. **Second Turn (1 Interaction)**
   - Verify agents access `interaction_contexts[0]`
   - Verify context appears in prompts

3. **Multiple Turns (3+ Interactions)**
   - Verify agents use last N interaction contexts
   - Verify context accumulates correctly

4. **With User Persona (20+ Interactions)**
   - Verify `user_context` appears in prompts
   - Verify `combined_context` includes user context

### Expected Behavior

| Turn | Intent Agent Sees | Synthesis Agent Sees | Safety Agent Sees | Skills Agent Sees |
|------|------------------|---------------------|-------------------|-------------------|
| 1    | "No previous context" | Empty | No context | No context |
| 2    | Interaction #1 summary | Interaction #1 | Recent context | Recent context |
| 3+   | Last 2 interactions | All/Summarized interactions | Recent context | Recent context |
| 20+  | User context + interactions | User context + interactions | User context | User context |

## Benefits

1. **Intent Recognition**: Now context-aware, better accuracy for follow-up questions
2. **Response Synthesis**: Uses conversation history for more relevant responses
3. **Safety Analysis**: Context-aware appropriateness assessment
4. **Skills Identification**: Considers conversation continuity for better skill matching
5. **Consistency**: All agents use the same context structure
6. **Performance**: Uses pre-formatted `combined_context` when available (more efficient)

## Backward Compatibility

- Synthesis agent includes `_summarize_interactions()` wrapper for backward compatibility
- All changes are additive (enhancements) rather than breaking changes
- Fallback logic handles missing or incomplete context gracefully

## Files Modified

1. `src/agents/intent_agent.py` - Fixed context access in `_build_chain_of_thought_prompt()`
2. `src/agents/synthesis_agent.py` - Fixed `_build_context_section()` and related methods
3. `src/agents/safety_agent.py` - Enhanced `_build_safety_prompt()` with context
4. `src/agents/skills_identification_agent.py` - Enhanced `_build_market_analysis_prompt()` with context

## Verification

✅ No linting errors  
✅ All agents use correct context keys  
✅ Backward compatibility maintained  
✅ Graceful handling of empty context  
✅ Consistent implementation pattern across all agents