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#!/bin/bash
# === SYSTEM PROMPT ===
# This script builds a Bengali language model using a multi-agent system with human-in-the-loop (HIL) capabilities.
# Advanced Features:
# - Real-Time Streaming: Displays a colorful, dynamic status dashboard in the terminal.
# - Robust Error Handling: Validates setup, API calls, and file operations with detailed logging.
# - Modern Interface: Uses ANSI colors, progress bars, and a boxed header for a polished look.
# - Loop and Iteration: Monitors execution, retries on failure, and ensures task completion.
# - Code Execution: Executes Python and Node.js code locally for preprocessing and evaluation.
# - Tools: Provides Python and Node.js REPLs for file operations and analysis.
# - Time Travel: Logs actions with timestamps for debugging and auditing.
# - Subgraph Support: Encapsulates tasks (data collection, preprocessing, training, evaluation) as reusable nodes.
# - Memory: Persists state across agent interactions using a key-value store.
# - API Integrations: Uses Together, Cohere, and Gemini APIs (Together as primary for text generation).
# - File Operations: Creates, edits, and validates files with error checking.
# - Output: Saves the model to /storage/BA73-022B/bd/bd-model-genaretions/model.pt.
# === CONFIGURATION ===
PROJECT_DIR="/storage/BA73-022B/bd/bd-model-genaretions" # Updated as per user request
LOG_FILE="$PROJECT_DIR/logs/actions.log"
MEMORY_FILE="$PROJECT_DIR/memory.txt"
REQUESTS_DIR="$PROJECT_DIR/requests"
RESPONSES_DIR="$PROJECT_DIR/responses"
DATA_DIR="$PROJECT_DIR/data"
STATUS_DIR="$PROJECT_DIR/status"
# API Keys
TOGETHER_API_KEY="07f08ca73c50496a3406ff621912254a67370d576822f1921f77eed47e649545"
COHERE_API_KEY="rvpLjkuzZPsoHGeIxqQxttTTIt4IxGUS5FOINU4L"
GEMINI_API_KEY="AIzaSyAQNxQU0WnegEnMfP6LCwkVw-PUtR11qaI"
# === SETUP ===
echo "Initializing project directories..."
for dir in "$PROJECT_DIR" "$DATA_DIR" "$REQUESTS_DIR" "$RESPONSES_DIR" "$PROJECT_DIR/logs" "$STATUS_DIR"; do
mkdir -p "$dir"
if [ $? -ne 0 ]; then
echo -e "\033[1;31mError: Failed to create directory $dir\033[0m"
exit 1
fi
done
touch "$LOG_FILE" "$MEMORY_FILE"
if [ ! -f "$LOG_FILE" ] || [ ! -f "$MEMORY_FILE" ]; then
echo -e "\033[1;31mError: Failed to create log or memory file\033[0m"
exit 1
fi
echo "[$(date)] Starting Bengali language model generation" >> "$LOG_FILE"
# === UTILITY FUNCTIONS ===
# Memory Management
function set_memory {
local key="$1"
local value="$2"
grep -v "^$key=" "$MEMORY_FILE" > "$MEMORY_FILE.tmp" && mv "$MEMORY_FILE.tmp" "$MEMORY_FILE"
echo "$key=$value" >> "$MEMORY_FILE"
}
function get_memory {
local key="$1"
local value=$(grep "^$key=" "$MEMORY_FILE" | cut -d'=' -f2)
echo "${value:-false}"
}
# Logging (Time Travel)
function log_action {
local agent_id="$1"
local action="$2"
echo "[$(date)] [Agent $agent_id] $action" >> "$LOG_FILE"
}
# Status Updates
function set_status {
local agent_id="$1"
local status="$2"
echo "$status" > "$STATUS_DIR/agent$agent_id.status"
}
# === TOOL CALLING FUNCTIONS ===
function run_python {
local code="$1"
log_action "Tool" "Running Python code: $code"
local output=$(python3 -c "$code" 2>> "$LOG_FILE")
local exit_code=$?
if [ $exit_code -ne 0 ]; then
log_action "Tool" "Python execution failed with exit code $exit_code"
return $exit_code
fi
echo "$output"
}
function run_node {
local code="$1"
log_action "Tool" "Running Node.js code: $code"
local output=$(node -e "$code" 2>> "$LOG_FILE")
local exit_code=$?
if [ $exit_code -ne 0 ]; then
log_action "Tool" "Node.js execution failed with exit code $exit_code"
return $exit_code
fi
echo "$output"
}
# === API CALLING FUNCTIONS ===
function call_together_api {
local prompt="$1"
curl -s -m 10 -X POST "https://api.together.ai/v1/completions" \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $TOGETHER_API_KEY" \
-d "{\"prompt\": \"$prompt\", \"model\": \"some_model\", \"max_tokens\": 100}"
}
function call_cohere_api {
local prompt="$1"
curl -s -m 10 -X POST "https://api.cohere.ai/generate" \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $COHERE_API_KEY" \
-d "{\"prompt\": \"$prompt\", \"max_tokens\": 100}"
}
function call_gemini_api {
local prompt="$1"
curl -s -m 10 -X POST "https://api.gemini.ai/v1/completions" \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $GEMINI_API_KEY" \
-d "{\"prompt\": \"$prompt\", \"model\": \"some_model\"}"
}
function generate_text {
local prompt="$1"
local api="$2"
local attempts=3
for ((i=1; i<=attempts; i++)); do
local response text
case "$api" in
together)
response=$(call_together_api "$prompt")
text=$(echo "$response" | jq -r '.choices[0].text' 2>/dev/null)
;;
cohere)
response=$(call_cohere_api "$prompt")
text=$(echo "$response" | jq -r '.generations[0].text' 2>/dev/null)
;;
gemini)
response=$(call_gemini_api "$prompt")
text=$(echo "$response" | jq -r '.choices[0].text' 2>/dev/null)
;;
*)
text="Unknown API"
;;
esac
if [ -n "$text" ] && [ "$text" != "null" ] && [[ ! "$text" =~ "Error" ]]; then
echo "$text"
return 0
fi
log_action "API" "Attempt $i failed for $api API, retrying..."
sleep 2
done
log_action "API" "Failed to generate text with $api after $attempts attempts"
return 1
}
# === HUMAN-IN-THE-LOOP REQUEST FUNCTION ===
function request_human_input {
local agent_id="$1"
local request="$2"
log_action "$agent_id" "Requesting human input: $request"
set_status "$agent_id" "Waiting for human input"
echo "$request" > "$REQUESTS_DIR/agent$agent_id.txt"
while [ ! -f "$RESPONSES_DIR/agent$agent_id.txt" ]; do
sleep 1
done
local response=$(cat "$RESPONSES_DIR/agent$agent_id.txt")
rm "$RESPONSES_DIR/agent$agent_id.txt"
log_action "$agent_id" "Received human response: $response"
set_status "$agent_id" "Processing human input"
echo "$response"
}
# === SUBGRAPH FUNCTIONS ===
function collect_data {
set_status 1 "Generating Bengali text via API"
local prompt="Generate a sample of Bengali text for language model training."
local text=$(generate_text "$prompt" "together")
if [ $? -eq 0 ]; then
set_status 1 "Saving data to file"
echo "$text" > "$DATA_DIR/bengali_text.txt"
if [ $? -ne 0 ]; then
set_status 1 "Error: Failed to save data"
log_action 1 "Failed to write to $DATA_DIR/bengali_text.txt"
return 1
fi
log_action 1 "Data saved to $DATA_DIR/bengali_text.txt"
set_memory "data_collected" "true"
else
set_status 1 "API error"
log_action 1 "Failed to collect data due to API error"
return 1
fi
set_status 1 "Data collection completed"
}
function preprocess_data {
set_status 2 "Waiting for data collection"
while [ "$(get_memory 'data_collected')" != "true" ]; do
sleep 1
done
set_status 2 "Analyzing data"
if [ ! -f "$DATA_DIR/bengali_text.txt" ]; then
set_status 2 "Error: Data file missing"
log_action 2 "Error: No data file found at $DATA_DIR/bengali_text.txt"
return 1
fi
local output=$(run_python "with open('$DATA_DIR/bengali_text.txt', 'r') as f: text = f.read(); print(f'Text length: {len(text)} characters')")
if [ $? -ne 0 ]; then
set_status 2 "Error: Analysis failed"
log_action 2 "Preprocessing analysis failed"
return 1
fi
log_action 2 "Analysis result: $output"
set_status 2 "Awaiting human review"
local response=$(request_human_input 2 "Review the Bengali text in $DATA_DIR/bengali_text.txt (approve/reject/edit)")
case "$response" in
approve)
set_status 2 "Saving preprocessed data"
echo "Data preprocessed" > "$DATA_DIR/preprocessed_text.txt"
log_action 2 "Preprocessing approved, saved to $DATA_DIR/preprocessed_text.txt"
set_memory "data_preprocessed" "true"
;;
edit)
set_status 2 "Editing data"
log_action 2 "Human requested edit; applying transformation"
run_python "with open('$DATA_DIR/bengali_text.txt', 'r') as f: text = f.read(); with open('$DATA_DIR/preprocessed_text.txt', 'w') as f: f.write(text.upper())"
if [ $? -eq 0 ]; then
set_memory "data_preprocessed" "true"
else
set_status 2 "Error: Edit failed"
return 1
fi
;;
*)
set_status 2 "Preprocessing rejected"
log_action 2 "Preprocessing rejected by human"
return 1
;;
esac
}
function train_model {
set_status 3 "Waiting for preprocessing"
while [ "$(get_memory 'data_preprocessed')" != "true" ]; do
sleep 1
done
set_status 3 "Training model"
if [ ! -f "$DATA_DIR/preprocessed_text.txt" ]; then
set_status 3 "Error: Preprocessed data missing"
log_action 3 "Error: No preprocessed data found at $DATA_DIR/preprocessed_text.txt"
return 1
fi
echo "Training Bengali model..."
sleep 2 # Simulate training
echo "Model trained" > "$PROJECT_DIR/model.pt"
if [ $? -ne 0 ]; then
set_status 3 "Error: Failed to save model"
log_action 3 "Failed to save model to $PROJECT_DIR/model.pt"
return 1
fi
log_action 3 "Model saved to $PROJECT_DIR/model.pt"
set_memory "model_trained" "true"
set_status 3 "Training completed"
}
function evaluate_model {
set_status 4 "Waiting for model training"
while [ "$(get_memory 'model_trained')" != "true" ]; do
sleep 1
done
set_status 4 "Evaluating model"
if [ ! -f "$PROJECT_DIR/model.pt" ]; then
set_status 4 "Error: Model file missing"
log_action 4 "Error: No model file found at $PROJECT_DIR/model.pt"
return 1
fi
local output=$(run_python "print('Simulated accuracy: 85%')")
if [ $? -ne 0 ]; then
set_status 4 "Error: Evaluation failed"
log_action 4 "Evaluation failed"
return 1
fi
set_status 4 "Awaiting human review"
local response=$(request_human_input 4 "Review model performance: $output (approve/reject/fix)")
case "$response" in
approve)
log_action 4 "Evaluation approved"
set_memory "evaluation_completed" "true"
;;
fix)
set_status 4 "Fixing model"
log_action 4 "Human requested fix; simulating correction"
echo "Fixed model" > "$PROJECT_DIR/model.pt"
set_memory "evaluation_completed" "true"
;;
*)
set_status 4 "Evaluation rejected"
log_action 4 "Evaluation rejected by human"
return 1
;;
esac
set_status 4 "Evaluation completed"
}
# === AGENT FUNCTIONS ===
function agent1 {
set_status 1 "Starting data collection"
until collect_data; do
set_status 1 "Retrying data collection"
log_action 1 "Retrying data collection after failure"
sleep 2
done
set_status 1 "Data collection completed"
set_memory "agent1_completed" "true"
}
function agent2 {
set_status 2 "Starting preprocessing"
until preprocess_data; do
set_status 2 "Retrying preprocessing"
log_action 2 "Retrying preprocessing after failure"
sleep 2
done
set_status 2 "Preprocessing completed"
set_memory "agent2_completed" "true"
}
function agent3 {
set_status 3 "Starting training"
until train_model; do
set_status 3 "Retrying training"
log_action 3 "Retrying training after failure"
sleep 2
done
set_status 3 "Training completed"
set_memory "agent3_completed" "true"
}
function agent4 {
set_status 4 "Starting evaluation"
until evaluate_model; do
set_status 4 "Retrying evaluation"
log_action 4 "Retrying evaluation after failure"
sleep 2
done
set_status 4 "Evaluation completed"
set_memory "agent4_completed" "true"
}
# === STATUS DISPLAY ===
function display_status {
echo -e "\033[1;34mββββββββββββββββββββββββ STATUS DASHBOARD βββββββββββββββββββββββ\033[0m"
echo -e "\033[1;34mβ Bengali Language Model Generation - $(date +%H:%M:%S) β\033[0m"
echo -e "\033[1;34mβββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ\033[0m"
local completed=0
for agent in 1 2 3 4; do
local status="Not started"
if [ -f "$STATUS_DIR/agent$agent.status" ]; then
status=$(cat "$STATUS_DIR/agent$agent.status")
fi
if [ "$(get_memory "agent${agent}_completed")" == "true" ]; then
status="Completed"
((completed++))
fi
case $agent in
1) color="\033[1;32m" ;; # Green
2) color="\033[1;33m" ;; # Yellow
3) color="\033[1;34m" ;; # Blue
4) color="\033[1;35m" ;; # Magenta
esac
echo -e "${color}Agent $agent: $status\033[0m"
done
local progress=$((completed * 25)) # 25% per agent
echo -e "\033[1;36mProgress: [$completed/4] ${progress}%\033[0m"
}
# === HUMAN-IN-THE-LOOP HANDLER ===
function hil_handler {
while true; do
clear
display_status
if [ "$(get_memory 'agent1_completed')" == "true" ] && \
[ "$(get_memory 'agent2_completed')" == "true" ] && \
[ "$(get_memory 'agent3_completed')" == "true" ] && \
[ "$(get_memory 'agent4_completed')" == "true" ]; then
log_action "HIL" "All agents completed successfully"
echo -e "\033[1;32mβ All agents completed! Model generation successful.\033[0m"
break
fi
for req_file in "$REQUESTS_DIR"/*; do
if [ -f "$req_file" ]; then
local agent_id=$(basename "$req_file" .txt | sed 's/agent//')
local request=$(cat "$req_file")
echo -e "\n\033[1;33mAgent $agent_id requests your input:\033[0m $request"
echo -e "\033[1;33mEnter response (e.g., approve/reject/edit/fix):\033[0m"
read -r human_input
if [ -z "$human_input" ]; then
echo -e "\033[1;31mError: Input cannot be empty. Try again.\033[0m"
continue
fi
echo "$human_input" > "$RESPONSES_DIR/agent$agent_id.txt"
rm "$req_file"
fi
done
sleep 1
done
}
# === CLEANUP ON EXIT ===
function cleanup {
echo -e "\033[1;31mScript interrupted. Cleaning up...\033[0m"
rm -f "$REQUESTS_DIR"/* "$RESPONSES_DIR"/* 2>/dev/null
log_action "Main" "Script terminated by user"
exit 1
}
trap cleanup INT TERM
# === MAIN EXECUTION ===
echo -e "\033[1;32mStarting Bengali language model generation...\033[0m"
log_action "Main" "Script execution started"
agent1 &
agent2 &
agent3 &
agent4 &
hil_handler
echo -e "\033[1;32mProcess completed successfully!\033[0m"
echo "Model saved at: $PROJECT_DIR/model.pt"
echo "Detailed logs available at: $LOG_FILE" |