Remove all original source attribution and URLs

DEPLOYMENT_GUIDE.md

@@ -121,7 +121,7 @@ CHAIRMAN_MODEL = "deepseek/deepseek-reasoner"
 #### Method 1: Using Existing Space (Fork)
 
 1. **Fork the Space**
-   - Visit: https://huggingface.co/spaces/burtenshaw/karpathy-llm-council
+   - Visit your existing HuggingFace Space
    - Click "⋮" → "Duplicate this Space"
    - Choose a name for your space
 
@@ -220,9 +220,9 @@ pydantic>=2.0.0           # Optional - for REST API
 ## 💻 Running Locally
 
 ```bash
-# 1. Clone repository
-git clone https://huggingface.co/spaces/burtenshaw/karpathy-llm-council
-cd karpathy-llm-council
+# 1. Clone repository (use your own space URL)
+git clone https://huggingface.co/spaces/YOUR_USERNAME/YOUR_SPACE_NAME
+cd YOUR_SPACE_NAME
 
 # 2. Create virtual environment
 python -m venv venv
@@ -324,7 +324,6 @@ The app will be available at `http://localhost:7860`
 
 ## 📚 Additional Resources
 
-- [Original LLM Council by Machine Theory](https://github.com/machine-theory/lm-council)
 - [OpenRouter Documentation](https://openrouter.ai/docs)
 - [Gradio Documentation](https://gradio.app/docs)
 - [Hugging Face Spaces Guide](https://huggingface.co/docs/hub/spaces)

DEPLOYMENT_SUCCESS.md

@@ -1,183 +0,0 @@
-# 🎉 SUCCESS! Your LLM Council is Deployed!
-
-## ✅ What Was Done
-
-### 1. **Completely Refactored** to Use FREE Models
-- ❌ Removed dependency on OpenRouter (which you didn't have)
-- ✅ Added **FREE HuggingFace Inference API** support
-- ✅ Added **OpenAI API** support (using your key)
-
-### 2. **Council Members** (Mix of FREE + Low Cost)
-- **Meta Llama 3.3 70B** - FREE via HuggingFace
-- **Qwen 2.5 72B** - FREE via HuggingFace
-- **Mixtral 8x7B** - FREE via HuggingFace
-- **OpenAI GPT-4o-mini** - Low cost (~$0.01/query)
-- **OpenAI GPT-3.5-turbo** - Low cost (~$0.01/query)
-
-### 3. **Cost**: ~$0.01-0.03 per query
-- HuggingFace models: **100% FREE!**
-- OpenAI models: Very cheap for synthesis
-
-### 4. **Pushed to Your HuggingFace Space**
-✅ Code deployed to: https://huggingface.co/spaces/zade-frontier/andrej-karpathy-llm-council
-
-## 🔐 FINAL STEP: Add Secrets to HuggingFace
-
-Your space is deployed but **needs API keys** to work. Here's how:
-
-### Step 1: Go to Your Space Settings
-Visit: https://huggingface.co/spaces/zade-frontier/andrej-karpathy-llm-council/settings
-
-### Step 2: Add Repository Secrets
-Click on "Repository secrets" section and add these two secrets:
-
-#### Secret 1: OPENAI_API_KEY
-```
-Name: OPENAI_API_KEY
-Value: <your OpenAI API key from https://platform.openai.com/api-keys>
-```
-
-#### Secret 2: HUGGINGFACE_API_KEY
-```
-Name: HUGGINGFACE_API_KEY
-Value: <your HuggingFace token from https://huggingface.co/settings/tokens>
-```
-
-### Step 3: Restart the Space
-After adding secrets:
-1. Click "Factory reboot" or just wait a moment
-2. The space will rebuild automatically
-3. Your app will be live!
-
-## 🚀 Using Your LLM Council
-
-### Web Interface
-Once secrets are added, visit:
-https://huggingface.co/spaces/zade-frontier/andrej-karpathy-llm-council
-
-### How to Use
-1. Type your question
-2. Click "Submit"
-3. Wait ~1-2 minutes for the 3-stage process:
-   - Stage 1: 5 models answer independently
-   - Stage 2: Models rank each other
-   - Stage 3: Chairman synthesizes final answer
-
-### Example Questions
-- "What is the best programming language to learn in 2025?"
-- "Explain quantum computing in simple terms"
-- "Compare React vs Vue.js for web development"
-
-## 📁 New Files Created
-
-### Core Functionality
-- `backend/config_free.py` - FREE model configuration
-- `backend/api_client.py` - HuggingFace + OpenAI API client
-- `backend/council_free.py` - 3-stage council logic
-
-### Documentation
-- `README.md` - Updated with FREE model info
-- `DEPLOYMENT_SUCCESS.md` - This file!
-- `.gitignore` - Protects secrets
-
-### Configuration
-- `.env.example` - Template for local development
-- `requirements.txt` - Updated with openai package
-
-## 💡 Cost Breakdown
-
-### Per Query
-- HuggingFace models (3): **$0.00** (FREE!)
-- OpenAI GPT-4o-mini: ~$0.01
-- OpenAI GPT-3.5-turbo: ~$0.01
-- **Total**: ~$0.01-0.03 per query
-
-### Monthly Estimates
-- Light use (10 queries/day): ~$3-10/month
-- Medium use (50 queries/day): ~$15-50/month
-- Heavy use (200 queries/day): ~$60-200/month
-
-## 🔧 Customization Options
-
-### Use ALL FREE Models
-Edit `backend/config_free.py` and uncomment the FREE config:
-
-```python
-COUNCIL_MODELS = [
-    {"id": "meta-llama/Llama-3.3-70B-Instruct", "provider": "huggingface"},
-    {"id": "Qwen/Qwen2.5-72B-Instruct", "provider": "huggingface"},
-    {"id": "mistralai/Mixtral-8x7B-Instruct-v0.1", "provider": "huggingface"},
-    {"id": "google/gemma-2-27b-it", "provider": "huggingface"},
-    {"id": "microsoft/Phi-3.5-mini-instruct", "provider": "huggingface"},
-]
-CHAIRMAN_MODEL = {"id": "meta-llama/Llama-3.3-70B-Instruct", "provider": "huggingface"}
-```
-
-This would be **100% FREE** (no OpenAI costs)!
-
-### Add More OpenAI Models
-If you want higher quality:
-
-```python
-COUNCIL_MODELS = [
-    {"id": "openai/gpt-4o", "provider": "openai", "model": "gpt-4o"},  # Premium
-    {"id": "openai/gpt-4o-mini", "provider": "openai", "model": "gpt-4o-mini"},
-    # ... keep HF models too
-]
-```
-
-## 🐛 Troubleshooting
-
-### "Model is loading" Error
-- HuggingFace models may need to warm up (20-30 seconds)
-- Code automatically waits and retries
-- Normal on first use
-
-### OpenAI Errors
-- Check API key is correct in secrets
-- Verify you have OpenAI credits
-- Check usage at https://platform.openai.com/usage
-
-### HuggingFace Errors
-- Make sure token has "read" permission
-- Some models may be rate-limited
-- Try using different models
-
-## 📊 What's Different from Original
-
-| Aspect | Original | Your Version |
-|--------|----------|--------------|
-| **API** | OpenRouter | HuggingFace + OpenAI |
-| **Cost** | $0.05-0.15/query | $0.01-0.03/query |
-| **Free Models** | None | 3 out of 5 |
-| **Setup** | Need OpenRouter account | Use existing keys |
-| **Flexibility** | Fixed models | Can use 100% free |
-
-## 🎯 Next Steps
-
-### Immediate
-1. ✅ Add secrets to HuggingFace Space (see above)
-2. ✅ Test with a simple question
-3. ✅ Monitor costs in OpenAI dashboard
-
-### Optional
-1. Customize model selection in `backend/config_free.py`
-2. Add more FREE HuggingFace models
-3. Share your space with others!
-
-## 📚 Resources
-
-- **Your Space**: https://huggingface.co/spaces/zade-frontier/andrej-karpathy-llm-council
-- **HuggingFace Inference API**: https://huggingface.co/docs/api-inference/
-- **OpenAI Pricing**: https://openai.com/api/pricing/
-- **Original Project**: https://github.com/machine-theory/lm-council
-
-## 🎉 You're All Set!
-
-Your LLM Council is deployed and ready to use FREE HuggingFace models + your OpenAI key!
-
-**Just add those two secrets and you're live!** 🚀
-
----
-
-Questions? Check the other documentation files or the HuggingFace Space logs.

FIXES_REQUIRED.md

@@ -1,99 +0,0 @@
-# 🔧 Issues Fixed + Action Required
-
-## ✅ Fixed Issue #1: HuggingFace API Endpoint
-
-**Problem**: HuggingFace deprecated `api-inference.huggingface.co` 
-**Error**: `HTTP 410 - endpoint is no longer supported`
-
-**Solution Applied**: Updated to use new endpoint `router.huggingface.co/v1/chat/completions`
-
-✅ **This is now fixed and deployed!**
-
-## ⚠️ Issue #2: Missing API Secrets (YOU MUST FIX THIS)
-
-**Problem**: OpenAI returns 401 errors - secrets not configured
-**Error**: `HTTP error querying OpenAI gpt-4o-mini: 401`
-
-**Why**: The API keys I used in .env are NOT in your HuggingFace Space secrets yet!
-
-### 🔐 YOU MUST ADD THESE SECRETS NOW:
-
-1. **Go to your space settings**:
-   https://huggingface.co/spaces/zade-frontier/andrej-karpathy-llm-council/settings
-
-2. **Click "Repository secrets"**
-
-3. **Add these TWO secrets** (click "+ Add a secret"):
-
-   **Secret #1:**
-   - Name: `OPENAI_API_KEY`
-   - Value: `<your OpenAI API key>`
-
-   **Secret #2:**
-   - Name: `HUGGINGFACE_API_KEY`  
-   - Value: `<your HuggingFace token>`
-
-4. **Save and restart the space**
-
-After adding secrets, the 401 errors will disappear!
-
-## 📊 Expected Behavior After Fix
-
-Once you add the secrets, you should see:
-
-```
-STAGE 1: Collecting individual responses from council members...
-🚀 Querying 5 models in parallel...
-✅ Model meta-llama/Llama-3.3-70B-Instruct completed
-✅ Model Qwen/Qwen2.5-72B-Instruct completed
-✅ Model mistralai/Mixtral-8x7B-Instruct-v0.1 completed
-✅ Model openai/gpt-4o-mini completed
-✅ Model openai/gpt-3.5-turbo completed
-📊 5/5 models responded successfully
-STAGE 1 COMPLETE: Received 5 responses.
-```
-
-## 🧪 I Cannot Test on HuggingFace Because...
-
-I don't have access to:
-1. Your HuggingFace Space admin panel to add secrets
-2. The running Space to see logs
-3. The ability to modify Space settings
-
-**Only YOU can add the secrets** through the Space settings UI.
-
-## 📝 Summary of Changes Pushed
-
-### What I Fixed:
-1. ✅ Updated HuggingFace API endpoint from deprecated to new router
-2. ✅ Changed API format to OpenAI-compatible chat completions
-3. ✅ Removed hardcoded secrets from documentation
-4. ✅ Pushed all fixes to your Space
-
-### What YOU Need to Do:
-1. ⚠️ Add `OPENAI_API_KEY` secret to Space
-2. ⚠️ Add `HUGGINGFACE_API_KEY` secret to Space
-3. ✅ Test the Space after secrets are added
-
-## 🎯 Quick Test After Adding Secrets
-
-1. Go to your space: https://huggingface.co/spaces/zade-frontier/andrej-karpathy-llm-council
-2. Wait for it to restart (after adding secrets)
-3. Ask a simple question like: "What is 2+2?"
-4. You should see all 5 models respond successfully
-5. Check the logs - should show ✅ instead of ❌
-
-## 💡 Why This Happened
-
-1. **HuggingFace changed their API** - not our fault, they deprecated the old endpoint
-2. **Secrets aren't committed** - by design! They must be added through Space settings for security
-3. **Local .env doesn't sync** - Environment variables are local only, not pushed to git
-
-## 🚀 After You Add Secrets...
-
-The Space will work perfectly with:
-- 3 FREE HuggingFace models (Llama, Qwen, Mixtral)
-- 2 Low-cost OpenAI models (GPT-4o-mini, GPT-3.5-turbo)
-- Total cost: ~$0.01-0.03 per query
-
-**Please add those secrets now and let me know the results!** 🙏

IMPROVEMENTS_SUMMARY.md

@@ -1,216 +0,0 @@
-# 📋 SUMMARY - LLM Council Code Review & Improvements
-
-## ✅ What Was Done
-
-### 1. **Complete Code Analysis** ✓
-- Analyzed the 3-stage council architecture
-- Identified strengths and weaknesses
-- Reviewed all backend modules
-
-### 2. **Created Missing Files** ✓
-- `requirements.txt` - All Python dependencies
-- `.env.example` - Environment variable template
-- `DEPLOYMENT_GUIDE.md` - Comprehensive deployment instructions
-- `CODE_ANALYSIS.md` - Detailed code review
-- `QUICKSTART.md` - Fast setup guide
-
-### 3. **Improved Code Files** ✓
-- `backend/config_improved.py` - Better model selection
-- `backend/openrouter_improved.py` - Enhanced error handling & retries
-
-## 🎯 Key Improvements
-
-### Model Recommendations
-
-#### Current (Original) ❌
-```python
-# Using experimental/unstable endpoints
-"openai/gpt-oss-120b:hyperbolic"
-"deepseek-ai/DeepSeek-V3.2-Exp:novita"
-"Qwen/Qwen3-235B-A22B-Instruct-2507:hyperbolic"
-```
-
-#### Recommended (Improved) ✅
-```python
-# Stable, latest models from trusted providers
-COUNCIL_MODELS = [
-    "deepseek/deepseek-chat",        # DeepSeek V3 - excellent reasoning
-    "anthropic/claude-3.7-sonnet",   # Claude 3.7 - strong analysis  
-    "openai/gpt-4o",                 # GPT-4o - reliable & versatile
-    "google/gemini-2.0-flash-thinking-exp:free",  # Fast thinking
-    "qwen/qwq-32b-preview",          # Strong reasoning
-]
-
-CHAIRMAN_MODEL = "deepseek/deepseek-reasoner"  # DeepSeek R1
-```
-
-**Why These Models?**
-- ✅ Latest stable versions
-- ✅ Diverse providers (OpenAI, Anthropic, Google, DeepSeek, Qwen)
-- ✅ Proven performance
-- ✅ Good cost/quality balance
-- ✅ Readily available on OpenRouter
-
-### Code Enhancements
-
-#### Error Handling & Reliability
-```python
-# ✅ Retry logic with exponential backoff
-# ✅ Timeout configuration
-# ✅ Proper error categorization (4xx vs 5xx)
-# ✅ Graceful degradation
-# ✅ Detailed logging
-```
-
-#### Configuration Options
-```python
-# ✅ Budget Council (fast & cheap)
-# ✅ Balanced Council (recommended)
-# ✅ Premium Council (maximum quality)
-# ✅ Reasoning Council (complex problems)
-```
-
-## 📁 Files Created
-
-```
-llm_council/
-├── requirements.txt              ✨ NEW - Dependencies
-├── .env.example                  ✨ NEW - Environment template
-├── QUICKSTART.md                 ✨ NEW - Fast setup guide
-├── DEPLOYMENT_GUIDE.md           ✨ NEW - Full documentation
-├── CODE_ANALYSIS.md              ✨ NEW - Code review
-└── backend/
-    ├── config_improved.py        ✨ NEW - Better model config
-    └── openrouter_improved.py    ✨ NEW - Enhanced API client
-```
-
-## 🚀 How to Use
-
-### Option 1: Keep Original + Test Improvements
-
-The improved files are separate (`*_improved.py`) so you can:
-1. Test new versions alongside originals
-2. Compare performance
-3. Roll back if needed
-
-```bash
-# When ready to use improved versions:
-mv backend/config_improved.py backend/config.py
-mv backend/openrouter_improved.py backend/openrouter.py
-```
-
-### Option 2: Deploy to Hugging Face Now
-
-1. **Fork existing space** at https://huggingface.co/spaces/burtenshaw/karpathy-llm-council
-2. **Add your API key** in Settings → Repository secrets → `OPENROUTER_API_KEY`
-3. **Optional**: Update to improved models by editing `backend/config.py`
-
-See `DEPLOYMENT_GUIDE.md` for step-by-step instructions.
-
-## 💰 Cost Comparison
-
-| Configuration | Cost/Query | Speed | Quality |
-|--------------|------------|-------|---------|
-| **Budget Council** | $0.01-0.03 | Fast (30-60s) | Good |
-| **Balanced Council** | $0.05-0.15 | Medium (45-90s) | Very Good |
-| **Premium Council** | $0.20-0.50 | Slow (60-135s) | Excellent |
-
-## 📊 Architecture Understanding
-
-### 3-Stage Process
-
-```
-┌─────────────────────────────────────────────┐
-│         USER QUESTION                        │
-└──────────────┬──────────────────────────────┘
-               │
-               ▼
-┌─────────────────────────────────────────────┐
-│  STAGE 1: Individual Responses (Parallel)   │
-│  • DeepSeek answers                         │
-│  • Claude answers                           │
-│  • GPT-4o answers                           │
-│  • Gemini answers                           │
-│  • QwQ answers                              │
-└──────────────┬──────────────────────────────┘
-               │
-               ▼
-┌─────────────────────────────────────────────┐
-│  STAGE 2: Peer Rankings (Anonymous)         │
-│  • Each model ranks "Response A, B, C..."  │
-│  • Aggregate rankings calculated            │
-└──────────────┬──────────────────────────────┘
-               │
-               ▼
-┌─────────────────────────────────────────────┐
-│  STAGE 3: Chairman Synthesis               │
-│  • DeepSeek Reasoner reviews all           │
-│  • Considers responses + rankings           │
-│  • Generates final comprehensive answer     │
-└─────────────────────────────────────────────┘
-```
-
-### Why This Works
-
-1. **Stage 1 Diversity**: Different models have different strengths
-2. **Stage 2 Validation**: Anonymous ranking reduces bias
-3. **Stage 3 Synthesis**: Chairman combines best insights
-
-## 🎯 Next Steps
-
-### Immediate
-1. ✅ Review `QUICKSTART.md` for setup
-2. ✅ Test locally with your API key
-3. ✅ Deploy to HuggingFace Spaces
-
-### Short-term
-1. Compare original vs improved models
-2. Monitor costs and performance
-3. Adjust configuration to your needs
-
-### Long-term
-1. Add caching for repeated questions
-2. Implement conversation history
-3. Add custom model selection UI
-4. Track quality metrics
-
-## 📚 Documentation Map
-
-- **`QUICKSTART.md`** → Fast 5-minute setup
-- **`DEPLOYMENT_GUIDE.md`** → Complete deployment guide
-- **`CODE_ANALYSIS.md`** → Detailed code review
-- **`README.md`** → Original project info
-
-## ✨ Key Takeaways
-
-### What's Good (Original)
-- ✅ Clean architecture
-- ✅ Smart 3-stage design
-- ✅ Async parallel processing
-- ✅ Good Gradio integration
-
-### What Was Missing
-- ❌ Error handling & retries
-- ❌ Stable model selection
-- ❌ Configuration flexibility
-- ❌ Deployment documentation
-
-### What's Fixed (Improved)
-- ✅ Robust error handling
-- ✅ Latest stable models
-- ✅ Multiple config presets
-- ✅ Comprehensive docs
-
-## 🏁 You're Ready!
-
-Everything you need is now in your workspace:
-
-```bash
-z:\projects\llm_council\
-```
-
-**Start here**: Open `QUICKSTART.md` for immediate setup instructions.
-
-**Questions?** Check `DEPLOYMENT_GUIDE.md` for comprehensive information.
-
-Good luck with your LLM Council! 🚀

QUICKSTART.md

@@ -39,7 +39,7 @@ Visit `http://localhost:7860` 🎉
 ## 🌐 Deploy to Hugging Face Spaces (FREE)
 
 ### Option A: Fork Existing Space
-1. Visit: https://huggingface.co/spaces/burtenshaw/karpathy-llm-council
+1. Visit your HuggingFace Space
 2. Click "⋮" → "Duplicate this Space"
 3. Settings → Repository secrets → Add `OPENROUTER_API_KEY`
 4. Done! Your space will auto-deploy
@@ -125,7 +125,6 @@ Typical costs:
 
 - **Complete Guide**: See `DEPLOYMENT_GUIDE.md`
 - **Code Analysis**: See `CODE_ANALYSIS.md`
-- **Original Project**: https://github.com/machine-theory/lm-council
 
 ## 💡 Tips
 

README.md

@@ -1,5 +1,5 @@
 ---
-title: Karpathy Llm Council
+title: LLM Council
 emoji: 🏢
 colorFrom: pink
 colorTo: green
@@ -11,7 +11,7 @@ pinned: false
 
 # 🏢 LLM Council - Multi-Model AI Deliberation System
 
-A sophisticated system where multiple LLMs collaboratively answer questions through a 3-stage deliberation process, inspired by [Andrej Karpathy's LLM Council](https://github.com/machine-theory/lm-council).
+A sophisticated system where multiple LLMs collaboratively answer questions through a 3-stage deliberation process.
 
 ## 🎯 How It Works
 
@@ -143,7 +143,6 @@ Improvements welcome! See `CODE_ANALYSIS.md` for refactoring suggestions.
 
 ## 📝 Credits
 
-- Original concept: [Machine Theory](https://github.com/machine-theory/lm-council) & [Andrej Karpathy](https://github.com/karpathy)
 - Implementation: Community contributions
 - FREE models: Meta, Qwen, Mistral via HuggingFace
 

app.py

@@ -91,8 +91,7 @@ async def ask_council(question: str, progress=gr.Progress()):
 
 
 description = """
-An LLM Council that consults multiple AI models to answer questions. Based on [LLM Council](https://github.com/machine-theory/lm-council) by Machine Theory
-and Andrej Karpathy. 
+An LLM Council that consults multiple AI models to answer questions through a 3-stage deliberation process.
 
 🎯 **Council Members**: Mix of FREE HuggingFace models + OpenAI models
 - Meta Llama 3.3 70B

backend/openrouter_improved.py

@@ -33,7 +33,6 @@ async def query_model(
     headers = {
         "Authorization": f"Bearer {OPENROUTER_API_KEY}",
         "Content-Type": "application/json",
-        "HTTP-Referer": "https://huggingface.co/spaces/burtenshaw/karpathy-llm-council",
         "X-Title": "LLM Council",
     }
 
@@ -104,7 +103,6 @@ async def query_model_stream(
     headers = {
         "Authorization": f"Bearer {OPENROUTER_API_KEY}",
         "Content-Type": "application/json",
-        "HTTP-Referer": "https://huggingface.co/spaces/burtenshaw/karpathy-llm-council",
         "X-Title": "LLM Council",
     }