# Long-Term Context Memory Fix

## Problem

After 2-3 interactions, the system loses context and gives factually incorrect answers. In the user's example:
- Discussed Sachin Tendulkar (cricket)
- Lost context of sport and gave gaming journalist advice about Tom Bramwell

## Root Cause Analysis

### Issue 1: Limited Context Window
- Only showing **last 3 interactions** in prompts
- With longer conversations, early context gets lost

### Issue 2: Incomplete Context Storage
- **OLD**: Only stored `user_input`, not the response
- Context looked like this:
  ```
  interactions: [
    {"user_input": "Who is Sachin?", "timestamp": "..."},
    {"user_input": "Is he the greatest?", "timestamp": "..."}
  ]
  ```
- **PROBLEM**: LLM doesn't know what was answered before!

### Issue 3: No Response Tracking
- When retrieving context from DB, only user questions were available
- Missing the actual conversation flow (Q&A pairs)

## Solution Implemented

### 1. Increased Context Window (3 → 5 interactions)
```python
# OLD: 
recent_interactions = context.get('interactions', [])[:3]

# NEW:
recent_interactions = context.get('interactions', [])[:5]  # Last 5 interactions
```

### 2. Added Response Storage
```python
# OLD:
new_interaction = {
    "user_input": user_input,
    "timestamp": datetime.now().isoformat()
}

# NEW:
new_interaction = {
    "user_input": user_input,
    "timestamp": datetime.now().isoformat(),
    "response": response  # Store the response text ✓
}
```

### 3. Enhanced Conversation History in Prompts
```python
# OLD format:
"1. User asked: Who is Sachin?\n"

# NEW format:
"Q1: Who is Sachin?
A1: Sachin Ramesh Tendulkar is a legendary Indian cricketer...

Q2: Is he the greatest? 
A2: The question of who is the greatest..."
```

### 4. Updated Orchestrator to Save Responses
```python
# After generating response, update context:
response_text = str(result.get('response', ''))
if response_text:
    self.context_manager._update_context(context, user_input, response_text)
```

## Files Modified

1. **`src/agents/synthesis_agent.py`**:
   - Increased context window from 3 to 5
   - Enhanced conversation history format to include Q&A pairs
   - Added support for displaying responses in prompts

2. **`context_manager.py`**:
   - Updated `_update_context()` to accept `response` parameter
   - Now stores full interaction (user_input + response)

3. **`orchestrator_engine.py`**:
   - Added call to update context with response after processing
   - Ensures responses are saved for future context retrieval

4. **Duplicates in `Research_AI_Assistant/`**: Applied same fixes

## Expected Behavior

### Before Fix:
```
Q1: "Who is Sachin?"
A1: (Cricket info)

Q2: "Is he the greatest?"
A2: (Compares Sachin to Bradman)

Q3: "Define greatness parameters"
A3: ❌ Lost context, gives generic answer

Q4: "Name a cricket journalist"
A4: ❌ Switches to gaming journalist (wrong sport!)
```

### After Fix:
```
Q1: "Who is Sachin?"
A1: (Cricket info) ✓ Saved to context

Q2: "Is he the greatest?"
A2: (Compares Sachin to Bradman) ✓ Saved to context
   Context includes: Q1+A1, Q2+A2

Q3: "Define greatness parameters"
A3: ✓ Knows we're talking about CRICKET greatness
   Context includes: Q1+A1, Q2+A2, Q3+A3

Q4: "Name a cricket journalist"
A4: ✓ Suggests cricket journalists (Harsha Bhogle, etc.)
   Context includes: Q1+A1, Q2+A2, Q3+A3, Q4+A4
```

## Technical Details

### Context Structure Now:
```json
{
  "session_id": "d5e8171f",
  "interactions": [
    {
      "user_input": "Who is Sachin?",
      "timestamp": "2025-10-27T15:39:32",
      "response": "Sachin Ramesh Tendulkar is a legendary Indian cricketer..."
    },
    {
      "user_input": "Is he the greatest?",
      "timestamp": "2025-10-27T15:40:04",
      "response": "The question of who is the greatest cricketer..."
    }
  ]
}
```

### Prompt Format:
```
User Question: Define greatness parameters

Previous conversation:
Q1: Who is Sachin?
A1: Sachin Ramesh Tendulkar is a legendary Indian cricketer...

Q2: Is he the greatest? What about Don Bradman?
A2: The question of who is the greatest cricketer...

Instructions: Provide a comprehensive, helpful response that directly addresses the question. If there's conversation context, use it to answer the current question appropriately.
```

## Testing

To verify the fix:

1. Ask about a specific topic: "Who is Sachin Tendulkar?"
2. Ask 3-4 follow-up questions without mentioning the sport
3. Verify the system still knows you're talking about cricket
4. Check logs for "context has X interactions"

## Impact

- ✅ Better context retention (5 vs 3 interactions)
- ✅ Complete conversation history (Q&A pairs)
- ✅ Reduced factual errors due to context loss
- ✅ More coherent multi-turn conversations
- ✅ Sport/domain awareness maintained across turns