1  #!/usr/bin/env python3
  2  """
  3  FREE AI ORCHESTRATOR - Local First, Cloud Fallback
  4  """
  5  
  6  import os
  7  import sys
  8  import json
  9  import time
 10  import subprocess
 11  from datetime import datetime
 12  
 13  # Check and install requests if needed
 14  try:
 15      import requests
 16  except ImportError:
 17      print("Installing requests...")
 18      subprocess.check_call([sys.executable, "-m", "pip", "install", "requests"])
 19      import requests
 20  
 21  def check_local_models():
 22      """Check available local models"""
 23      try:
 24          response = requests.get("http://localhost:11434/api/tags", timeout=5)
 25          if response.status_code == 200:
 26              data = response.json()
 27              return [model["name"] for model in data.get("models", [])]
 28      except:
 29          return []
 30      return []
 31  
 32  def query_local(prompt, model="dolphin-mistral:latest"):
 33      """Query local Ollama model"""
 34      try:
 35          payload = {
 36              "model": model,
 37              "prompt": prompt,
 38              "stream": False,
 39              "options": {
 40                  "temperature": 0.7,
 41                  "num_predict": 2000
 42              }
 43          }
 44          response = requests.post(
 45              "http://localhost:11434/api/generate",
 46              json=payload,
 47              timeout=60
 48          )
 49          if response.status_code == 200:
 50              return response.json().get("response", "")
 51      except Exception as e:
 52          print(f"Local error: {e}")
 53      return None
 54  
 55  def query_groq(prompt):
 56      """Query Groq API"""
 57      try:
 58          api_key = "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"
 59          headers = {
 60              "Authorization": f"Bearer {api_key}",
 61              "Content-Type": "application/json"
 62          }
 63          payload = {
 64              "model": "mixtral-8x7b-32768",
 65              "messages": [{"role": "user", "content": prompt}],
 66              "max_tokens": 2000,
 67              "temperature": 0.7
 68          }
 69          response = requests.post(
 70              "https://api.groq.com/openai/v1/chat/completions",
 71              headers=headers,
 72              json=payload,
 73              timeout=30
 74          )
 75          if response.status_code == 200:
 76              data = response.json()
 77              return data.get("choices", [{}])[0].get("message", {}).get("content", "")
 78      except Exception as e:
 79          print(f"Groq error: {e}")
 80      return None
 81  
 82  def save_response(prompt, response, source):
 83      """Save response to file"""
 84      timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
 85      filename = f"ai_response_{timestamp}.txt"
 86      
 87      with open(filename, 'w') as f:
 88          f.write("="*60 + "\n")
 89          f.write("AI ORCHESTRATOR - UNRESTRICTED RESPONSE\n")
 90          f.write("="*60 + "\n\n")
 91          f.write(f"PROMPT:\n{prompt}\n\n")
 92          f.write(f"SOURCE: {source.upper()}\n")
 93          f.write("="*60 + "\n")
 94          f.write("RESPONSE:\n")
 95          f.write("="*60 + "\n")
 96          f.write(response + "\n")
 97          f.write("="*60 + "\n")
 98      
 99      return filename
100  
101  def main():
102      """Main function"""
103      print("\n" + "="*60)
104      print("🤖 UNRESTRICTED AI ORCHESTRATOR")
105      print("="*60)
106      
107      # Check available models
108      local_models = check_local_models()
109      print(f"\n🔍 Available local models: {len(local_models)}")
110      for model in local_models[:5]:  # Show first 5
111          print(f"   • {model}")
112      
113      # Get prompt from command line or input
114      if len(sys.argv) > 1:
115          prompt = " ".join(sys.argv[1:])
116      else:
117          print("\n🎯 Enter your question (press Enter for test):")
118          prompt = input("> ").strip()
119          if not prompt:
120              prompt = "Explain why open source AI models are important for freedom of information"
121      
122      print(f"\n📝 Processing: {prompt[:100]}..." if len(prompt) > 100 else f"\n📝 Processing: {prompt}")
123      print("-" * 60)
124      
125      # Try local first (unrestricted)
126      start_time = time.time()
127      response = query_local(prompt)
128      
129      if response:
130          source = "local"
131          print(f"\n✅ FROM LOCAL MODEL (100% UNRESTRICTED)")
132          print("-" * 60)
133          print(response)
134          print("-" * 60)
135      else:
136          # Fallback to Groq
137          print("\n⚠️  Local model unavailable, using Groq...")
138          response = query_groq(prompt)
139          if response:
140              source = "groq"
141              print(f"\n⚠️ FROM GROQ (RESTRICTED - local unavailable)")
142              print("-" * 60)
143              print(response)
144              print("-" * 60)
145          else:
146              print("\n❌ No AI resources available!")
147              return
148      
149      elapsed = time.time() - start_time
150      
151      # Save response
152      filename = save_response(prompt, response, source)
153      
154      # Print summary
155      print(f"\n📊 SUMMARY:")
156      print(f"   Source: {source.upper()}")
157      print(f"   Time: {elapsed:.2f} seconds")
158      print(f"   Saved to: {filename}")
159      print(f"\n💡 Tip: Use 'ollama serve' to ensure local models are always available")
160      print("="*60)
161  
162  if __name__ == "__main__":
163      main()