agent.py

import datetime
from typing import List, Tuple, Dict, Any

# Constants used in the app
PREFIX = """Current Date: {timestamp}
Purpose: {purpose}
System: You are an advanced AI assistant specialized in data processing and summarization.
"""

COMPRESS_DATA_PROMPT = """You are processing data for summarization and analysis.

Task Context:
- Direction: {direction}
- Knowledge: {knowledge}

Data to Process:
{history}

Instructions:
1. Analyze and summarize the data while preserving key information
2. Maintain original meaning and important details
3. Output should be concise yet comprehensive
4. Format as plain text with clear section headers
5. Include all critical data points and references

Output Format:
[Summary]
- Key points
- Important details
- Relevant references

[Analysis]
- Insights
- Patterns
- Conclusions
"""

COMPRESS_DATA_PROMPT_SMALL = """You are processing data chunks for summarization.

Task Context:
- Direction: {direction}

Current Data Chunk:
{history}

Instructions:
1. Extract key information from this chunk
2. Format as bullet points
3. Keep concise but preserve meaning
4. Focus on most relevant content
5. Include source references if available

Output Format:
- Point 1
- Point 2
- ...
"""

LOG_PROMPT = """=== PROMPT ===
{content}
"""

LOG_RESPONSE = """=== RESPONSE ===
{content}
"""

def run_gpt(
    prompt_template: str,
    stop_tokens: List[str],
    max_tokens: int,
    seed: int,
    **prompt_kwargs: Any
) -> str:
    """Run GPT model with given parameters.
    
    Args:
        prompt_template: Template string for the prompt
        stop_tokens: List of stop sequences
        max_tokens: Maximum tokens to generate
        seed: Random seed
        **prompt_kwargs: Additional formatting arguments
        
    Returns:
        Generated text response
    """
    # This would normally interface with the actual model
    # For now returning a mock implementation
    return "Mock response for testing purposes"

def compress_data(
    c: int,
    instruct: str,
    history: str
) -> List[str]:
    """Compress data into smaller chunks.
    
    Args:
        c: Count of data points
        instruct: Instruction for compression
        history: Data to compress
        
    Returns:
        List of compressed data chunks
    """
    # Mock implementation
    return ["Compressed data chunk 1", "Compressed data chunk 2"]

def compress_data_og(
    c: int,
    instruct: str,
    history: str
) -> str:
    """Original version of data compression.
    
    Args:
        c: Count of data points
        instruct: Instruction for compression
        history: Data to compress
        
    Returns:
        Compressed data as single string
    """
    # Mock implementation
    return "Compressed data output"

def save_memory(
    purpose: str,
    history: str
) -> List[Dict[str, Any]]:
    """Save processed data to memory format.
    
    Args:
        purpose: Purpose of the processing
        history: Data to process
        
    Returns:
        List of memory dictionaries
    """
    # Mock implementation
    return [{
        "keywords": ["sample", "data"],
        "title": "Sample Entry",
        "description": "Sample description",
        "content": "Sample content",
        "url": "https://example.com"
    }]