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Guides️💻 Customising Prompts

Customizing Prompts in DocsGPT

Customizing prompts for DocsGPT gives you powerful control over the AI’s behavior and responses. With the new template-based system, you can inject dynamic context through organized namespaces, making prompts flexible and maintainable without hardcoding values.

Quick Start

  1. Navigate to SideBar -> Settings.
  2. In Settings, select the Active Prompt to see various prompt styles.
  3. Click on the edit icon on your chosen prompt to customize it.

Video Demo

prompts

Template-Based Prompt System

DocsGPT now uses Jinja2 templating with four organized namespaces for dynamic variable injection:

Available Namespaces

1. system - System Metadata

Access system-level information:

{{ system.date }}         # Current date (YYYY-MM-DD)
{{ system.time }}         # Current time (HH:MM:SS)
{{ system.timestamp }}    # ISO 8601 timestamp
{{ system.request_id }}   # Unique request identifier
{{ system.user_id }}      # Current user ID

2. source - Retrieved Documents

Access RAG (Retrieval-Augmented Generation) document context:

{{ source.content }}      # Concatenated document content
{{ source.summaries }}    # Alias for content (backward compatible)
{{ source.documents }}    # List of document objects
{{ source.count }}        # Number of retrieved documents

3. passthrough - Request Parameters

Access custom parameters passed in the API request:

{{ passthrough.company }}     # Custom field from request
{{ passthrough.user_name }}   # User-provided data
{{ passthrough.context }}     # Any custom parameter

To use passthrough data, send it in your API request:

{
  "question": "What is the pricing?",
  "passthrough": {
    "company": "Acme Corp",
    "user_name": "Alice",
    "plan_type": "enterprise"
  }
}

4. tools - Pre-fetched Tool Data

Access results from tools that run before the agent (like memory tool):

{{ tools.memory.root }}       # Memory tool directory listing
{{ tools.memory.available }}  # Boolean: is memory available

Example Prompts

Basic Prompt with Documents

You are a helpful AI assistant for DocsGPT.
 
Current date: {{ system.date }}
 
Use the following documents to answer the question:
 
{{ source.content }}
 
Provide accurate, helpful answers with code examples when relevant.

Advanced Prompt with All Namespaces

You are an AI assistant for {{ passthrough.company }}.
 
**System Info:**
- Date: {{ system.date }}
- Request ID: {{ system.request_id }}
 
**User Context:**
- User: {{ passthrough.user_name }}
- Role: {{ passthrough.role }}
 
**Available Documents ({{ source.count }}):**
{{ source.content }}
 
**Memory Context:**
{% if tools.memory.available %}
{{ tools.memory.root }}
{% else %}
No saved context available.
{% endif %}
 
Please provide detailed, accurate answers based on the documents above.

Conditional Logic Example

You are a DocsGPT assistant.
 
{% if source.count > 0 %}
I found {{ source.count }} relevant document(s):
 
{{ source.content }}
 
Base your answer on these documents.
{% else %}
No documents were found. Please answer based on your general knowledge.
{% endif %}

Migration Guide

Legacy Format (Still Supported)

The old {summaries} format continues to work for backward compatibility:

You are a helpful assistant.
 
Documents:
{summaries}

This will automatically substitute {summaries} with document content.

Migrate to the new template syntax for more flexibility:

You are a helpful assistant.
 
Documents:
{{ source.content }}

Migration mapping:

  • {summaries} → {{ source.content }} or {{ source.summaries }}

Best Practices

1. Use Descriptive Context

**Retrieved Documents:**
{{ source.content }}
 
**User Query Context:**
- Company: {{ passthrough.company }}
- Department: {{ passthrough.department }}

2. Handle Missing Data Gracefully

{% if passthrough.user_name %}
Hello {{ passthrough.user_name }}!
{% endif %}

3. Leverage Memory for Continuity

{% if tools.memory.available %}
**Previous Context:**
{{ tools.memory.root }}
{% endif %}
 
**Current Question:**
Please consider the above context when answering.

4. Add Clear Instructions

You are a technical support assistant.
 
**Guidelines:**
1. Always reference the documents below
2. Provide step-by-step instructions
3. Include code examples when relevant
 
**Reference Documents:**
{{ source.content }}

Advanced Features

Looping Over Documents

{% for doc in source.documents %}
**Source {{ loop.index }}:** {{ doc.filename }}
{{ doc.text }}
 
{% endfor %}

Date-Based Behavior

{% if system.date > "2025-01-01" %}
Note: This is information from 2025 or later.
{% endif %}

Custom Formatting

**Request Information**
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
• Request ID: {{ system.request_id }}
• User: {{ passthrough.user_name | default("Guest") }}
• Time: {{ system.time }}
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

Tool Pre-Fetching

Memory Tool Configuration

Enable memory tool pre-fetching to inject saved context into prompts:

# In your tool configuration
{
  "name": "memory",
  "config": {
    "pre_fetch_enabled": true  # Default: true
  }
}

Control pre-fetching globally:

# .env file
ENABLE_TOOL_PREFETCH=true

Or per-request:

{
  "question": "What are the requirements?",
  "disable_tool_prefetch": false
}

Debugging Prompts

View Rendered Prompts in Logs

Set log level to INFO to see the final rendered prompt sent to the LLM:

export LOG_LEVEL=INFO

You’ll see output like:

INFO - Rendered system prompt for agent (length: 1234 chars):
================================================================================
You are a helpful assistant for Acme Corp.

Current date: 2025-10-30
Request ID: req_abc123

Documents:
Technical documentation about...
================================================================================

Template Validation

Test your template syntax before saving:

from application.api.answer.services.prompt_renderer import PromptRenderer
 
renderer = PromptRenderer()
is_valid = renderer.validate_template("Your prompt with {{ variables }}")

Common Use Cases

1. Customer Support Bot

You are a customer support assistant for {{ passthrough.company }}.
 
**Customer:** {{ passthrough.customer_name }}
**Ticket ID:** {{ system.request_id }}
**Date:** {{ system.date }}
 
**Knowledge Base:**
{{ source.content }}
 
**Previous Interactions:**
{{ tools.memory.root }}
 
Please provide helpful, friendly support based on the knowledge base above.

2. Technical Documentation Assistant

You are a technical documentation expert.
 
**Available Documentation ({{ source.count }} documents):**
{{ source.content }}
 
**Requirements:**
- Provide code examples in {{ passthrough.language }}
- Focus on {{ passthrough.framework }} best practices
- Include relevant links when possible

3. Internal Knowledge Base

You are an internal AI assistant for {{ passthrough.department }}.
 
**Employee:** {{ passthrough.employee_name }}
**Access Level:** {{ passthrough.access_level }}
 
**Relevant Documents:**
{{ source.content }}
 
Provide detailed answers appropriate for {{ passthrough.access_level }} access level.

Template Syntax Reference

Variables

{{ variable_name }}              # Output variable
{{ namespace.field }}            # Access nested field
{{ variable | default("N/A") }}  # Default value

Conditionals

{% if condition %}
  Content
{% elif other_condition %}
  Other content
{% else %}
  Default content
{% endif %}

Loops

{% for item in list %}
  {{ item.field }}
{% endfor %}

Comments

{# This is a comment and won't appear in output #}

Security Considerations

  1. Input Sanitization: Passthrough data is automatically sanitized to prevent injection attacks
  2. Type Filtering: Only primitive types (string, int, float, bool, None) are allowed in passthrough
  3. Autoescaping: Jinja2 autoescaping is enabled by default
  4. Size Limits: Consider the token budget when including large documents

Troubleshooting

Problem: Variables Not Rendering

Solution: Ensure you’re using the correct namespace:

❌ {{ company }}
✅ {{ passthrough.company }}

Problem: Empty Output for Tool Data

Solution: Check that tool pre-fetching is enabled and the tool is configured correctly.

Problem: Syntax Errors

Solution: Validate template syntax. Common issues:

❌ {{ variable }     # Missing closing brace
❌ {% if x %         # Missing closing %}
✅ {{ variable }}
✅ {% if x %}...{% endif %}

Problem: Legacy Prompts Not Working

Solution: The system auto-detects template syntax. If your prompt uses {summaries}, it will work in legacy mode. To use new features, add {{ }} syntax.

API Reference

Render Prompt via API

from application.api.answer.services.prompt_renderer import PromptRenderer
 
renderer = PromptRenderer()
rendered = renderer.render_prompt(
    prompt_content="Your template with {{ passthrough.name }}",
    user_id="user_123",
    request_id="req_456",
    passthrough_data={"name": "Alice"},
    docs_together="Document content here",
    tools_data={"memory": {"root": "Files: notes.txt"}}
)

Conclusion

The new template-based prompt system provides powerful flexibility while maintaining backward compatibility. By leveraging namespaces, you can create dynamic, context-aware prompts that adapt to your specific use case.

Key Benefits:

  • ✅ Dynamic variable injection
  • ✅ Organized namespaces
  • ✅ Backward compatible
  • ✅ Security built-in
  • ✅ Easy to debug

Start with simple templates and gradually add complexity as needed. Happy prompting! 🚀

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