Upload folder using huggingface_hub

README.md

@@ -1,3 +1,18 @@
+---
+language:
+  - en
+license: mit
+library_name: transformers
+tags:
+  - travel
+  - itinerary
+  - assistant
+  - llama
+pipeline_tag: text-generation
+widget:
+  - text: "Plan a 3-day trip to California starting on 15/04/2024"
+---
+
 # ZenoBot Model - Hugging Face Deployment
 
 This folder contains the necessary files to deploy ZenoBot as a Hugging Face API service.

model-card.md

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+---
+language:
+  - en
+license: mit
+library_name: transformers
+tags:
+  - travel
+  - itinerary
+  - assistant
+  - llama
+pipeline_tag: text-generation
+widget:
+  - text: "Plan a 3-day trip to California starting on 15/04/2024"
+    example_title: "California Trip"
+  - text: "Create a 5-day itinerary for New York state starting next Monday"
+    example_title: "New York Trip"
+  - text: "I want to visit Florida for a weekend"
+    example_title: "Florida Weekend"
+---
+
+# ZenoBot - AI Travel Itinerary Assistant
+
+ZenoBot is an AI-powered travel assistant that specializes in creating detailed travel itineraries strictly within one state in a country. Built on the Llama 3.2 architecture, ZenoBot generates comprehensive, geographically sensible travel plans with morning, afternoon, and evening activities for each day of your trip.
+
+## Model Description
+
+ZenoBot is designed to create travel itineraries with the following characteristics:
+
+- **State-specific**: All travel plans stay within a single state
+- **Geographically sensible**: Activities are grouped to minimize unnecessary travel
+- **Comprehensive**: Each day includes morning, afternoon, evening, and an additional activity
+- **Well-structured**: Results are delivered in a consistent JSON format
+- **Realistic**: Takes into account travel times between locations
+- **Diverse**: Balances various types of experiences (nature, culture, history, etc.)
+
+## Intended Use
+
+This model is intended to help users plan trips within specific states in various countries. It's especially useful for:
+
+- Tourists planning a visit to a specific state
+- Travel agents creating custom itineraries
+- Locals looking to explore more of their own state
+- Anyone overwhelmed by the options when planning a trip
+
+## Usage Examples
+
+### API Request Format
+
+```python
+import requests
+import json
+
+query = "Plan a 3-day trip to California starting on 15/04/2024"
+
+response = requests.post(
+    "https://api-endpoint/generate",
+    json={"query": query, "temperature": 0.1}
+)
+
+result = response.json()
+print(json.dumps(result, indent=2))
+```
+
+### Sample Output
+
+```json
+{
+  "response": {
+    "tripDetails": {
+      "tripLengthHigh": false
+    },
+    "itinerary": [
+      {
+        "dayStart": "[DayStart]",
+        "date": "15/04/2024",
+        "morningStart": "[MorningStart]",
+        "morning": {
+          "name": "Golden Gate Bridge Visit",
+          "location": "San Francisco",
+          "description": "Start your California adventure with a visit to the iconic Golden Gate Bridge.",
+          "transportation": "Taxi"
+        },
+        "afternoonStart": "[AfternoonStart]",
+        "afternoon": {
+          "name": "Alcatraz Island Tour",
+          "location": "San Francisco Bay",
+          "description": "Explore the historic Alcatraz Federal Penitentiary.",
+          "transportation": "Ferry"
+        },
+        "eveningStart": "[EveningStart]",
+        "evening": {
+          "name": "Fisherman's Wharf Exploration",
+          "location": "San Francisco",
+          "description": "Enjoy the lively atmosphere of Fisherman's Wharf.",
+          "transportation": "Walking"
+        },
+        "additionalActivityStart": "[AdditionalActivityStart]",
+        "additionalActivity": {
+          "name": "Cable Car Ride",
+          "location": "San Francisco",
+          "description": "Take a ride on San Francisco's historic cable cars."
+        },
+        "dayEnd": "[DayEnd]"
+      }
+      // Additional days follow the same format
+    ]
+  }
+}
+```
+
+## Limitations
+
+- ZenoBot only plans for activities within a single state
+- It does not recommend specific hotels or accommodations
+- It does not include food or restaurant recommendations
+- The model may occasionally suggest activities that are seasonal or unavailable
+- Activities are not verified for current operating hours or availability
+
+## Training Details
+
+ZenoBot is based on the Llama 3.2 architecture and has been fine-tuned to specialize in travel itinerary generation. The model has been trained to understand geography within states and to create logical travel routes that minimize unnecessary travel time.
+
+## Ethical Considerations
+
+While ZenoBot attempts to provide useful travel suggestions, users should always:
+
+- Verify the existence and availability of suggested activities
+- Check current operating hours and admission requirements
+- Consider local travel advisories and weather conditions
+- Respect local customs and regulations
+- Make their own judgments about the suitability of suggested activities
+
+## Contact Information
+
+For questions, feedback, or issues regarding ZenoBot, please contact:
+
+- GitHub: [ZenoBot Repository](https://github.com/Zeno0007/ZenoBot)
+- Hugging Face: [@Zeno0007](https://huggingface.co/Zeno0007)

upload_to_hf.py

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+import os
+import argparse
+from huggingface_hub import HfApi, create_repo, HfFolder
+from dotenv import load_dotenv
+
+def upload_to_huggingface(repo_name = "Zeno0007/zenobot", local_dir='.', token=None):
+    """
+    Upload files to a Hugging Face repository.
+    
+    Args:
+        repo_name (str): Name of the repository (e.g., 'username/model-name')
+        local_dir (str): Local directory containing the files to upload
+        token (str, optional): Hugging Face token. If None, will look for it in env vars.
+    """
+    # Get token from different sources with priority
+    if token is None:
+        # Try to load from .env file first
+        load_dotenv()
+        
+        # If no variables found, try alternate .env filenames
+        if not (os.environ.get("HUGGINGFACE_TOKEN") or os.environ.get("HF_TOKEN")):
+            if os.path.exists(".env.sample"):
+                load_dotenv(".env.sample")
+        
+        # Check various environment variables for the token
+        token = (os.environ.get("HUGGINGFACE_TOKEN") or 
+                os.environ.get("HF_TOKEN") or 
+                os.environ.get("HF_API_TOKEN"))
+        
+        # If still no token, try the Hugging Face CLI cached token
+        if token is None:
+            token = HfFolder.get_token()
+    
+    if token is None:
+        print("Error: No Hugging Face token found.")
+        print("Please provide a token using one of these methods:")
+        print("1. Pass it as an argument: --token YOUR_TOKEN")
+        print("2. Set it as an environment variable: export HUGGINGFACE_TOKEN=YOUR_TOKEN")
+        print("3. Create a .env file with HUGGINGFACE_TOKEN=YOUR_TOKEN")
+        print("4. Login using the huggingface-cli: huggingface-cli login")
+        return
+
+    # Initialize the Hugging Face API
+    api = HfApi(token=token)
+    
+    # Create or get the repository
+    try:
+        repo_url = create_repo(repo_name, exist_ok=True, token=token)
+        print(f"Repository URL: {repo_url}")
+    except Exception as e:
+        print(f"Error creating repository: {e}")
+        print("\nPlease make sure your token is valid and has write access to this repository.")
+        print("You can create or find your token at: https://huggingface.co/settings/tokens")
+        return
+    
+    # Define files to be included/excluded
+    ignore_patterns = [
+        ".git/", 
+        "venv/", 
+        "__pycache__/", 
+        "*.pyc", 
+        ".env",
+        ".gitignore",
+        "setup_venv.sh"
+    ]
+    
+    # Upload the files
+    print(f"Uploading files to {repo_name}...")
+    try:
+        api.upload_folder(
+            folder_path=local_dir,
+            repo_id=repo_name,
+            ignore_patterns=ignore_patterns,
+            token=token
+        )
+        print("Upload complete!")
+    except Exception as e:
+        print(f"Error during upload: {e}")
+
+if __name__ == "__main__":
+    parser = argparse.ArgumentParser(description="Upload files to Hugging Face Hub")
+    parser.add_argument("repo_name", nargs="?", default="Zeno0007/zenobot", 
+                        help="Name of the repository (e.g., 'username/model-name')")
+    parser.add_argument("--dir", default=".", help="Local directory containing the files to upload")
+    parser.add_argument("--token", help="Hugging Face token (optional if set as environment variable)")
+    
+    args = parser.parse_args()
+    upload_to_huggingface(args.repo_name, args.dir, args.token)