Merge branch 'release/0.7.1'

Author: 00hello

.cursorignore

@@ -1 +1 @@
-llm.yaml
+config.yaml

.gitignore

@@ -177,7 +177,7 @@ Thumbs.db
 browser-use/browser_data/
 
 # Config files with sensitive data (use .template files instead)
-config/llm.yaml
+config/config.yaml
 # Browser data - contains private cookies and session data
 browser/browser_data/
 browser_data/

CONTRIBUTING.md

@@ -91,9 +91,9 @@ playwright install --with-deps chromium
 ### Configuration Setup
 ```bash
 # Copy the template configuration file
-cp config/llm.yaml.template config/llm.yaml
+cp config/config.yaml.template config/config.yaml
 
-# Edit config/llm.yaml to set your API key and project ID:
+# Edit config/config.yaml to set your API key and project ID:
 # Replace "YOUR_API_KEY_HERE" with your actual OpenAI API key for browser-use
 # Replace "YOUR_PROJECT_ID_HERE" with your actual OpenAI project ID
 # Daily spending limits and model settings are configurable
@@ -104,7 +104,7 @@ cp config/llm.yaml.template config/llm.yaml
 
 The system includes built-in cost tracking and spending limits to prevent unexpected charges:
 
-- **Daily Spending Limits**: Configurable via `config/llm.yaml` (default: $5.00/day)
+- **Daily Spending Limits**: Configurable via `config/config.yaml` (default: $5.00/day)
 - **Project-Specific Tracking**: Only tracks costs for your specific OpenAI project
 - **Real-Time Monitoring**: Checks spending before each browser automation run
 - **Automatic Prevention**: Stops execution if daily limit would be exceeded

Cargo.lock

@@ -8,7 +8,7 @@ resolver = "2"
 
 [package]
 name = "cliptions-core"
-version = "0.7.0"
+version = "0.7.1"
 edition = "2021"
 description = "Cliptions prediction market core functionality implemented in Rust with optional Python bindings"
 license = "MIT"

Cargo.toml

@@ -1,6 +1,36 @@
 # Cliptions
 
-Predict how an AI Agent will caption upcoming frames from live video streams. Players compete for cryptocurrency rewards based on prediction accuracy.
+Welcome to Cliptions
+
+What exactly is a "Cliption"?
+
+A Cliption is a prediction contract that pays out based on how closely a player's submitted caption matches the CLIP model's interpretation of a randomly chosen, upcoming timestamp in a livestream. It's not a tradable asset, just a commitment to your best guess in an open contest.
+
+Cliptions are like options contracts but instead of betting on a price or event, you're betting on AI's semantic interpretation of a future moment.
+
+In other words:
+
+**Cliptions = Semantic options contracts**
+
+**CLIP similarity score = Strike price**
+
+**Frame reveal timestamp = Expiry date**
+
+**Prize pool = Liquidity pool**
+
+## What is CLIP?
+
+CLIP (Contrastive Language-Image Pretraining) is a neural network created by OpenAI and trained to connect visual concepts (images, videos) with textual descriptions (English words or phrases). https://github.com/openai/CLIP
+
+It can look at an image or video frame and accurately predict which textual description best matches it—or vice versa.
+
+In Cliptions, this capability is specifically used for scoring predictions:
+
+- Players submit text predictions for upcoming video frames.
+- CLIP determines how closely each submitted caption matches the actual video frame's content, semantically.
+- Predictions ranked closest by CLIP's embeddings win payouts.
+
+This is how Cliptions leverages CLIP's unique strength in semantic interpretation—creating a novel betting product around predicting the AI's understanding of visual moments.
 
 ### Index
 - [Gameplay](#gameplay)
@@ -412,14 +442,3 @@ Groups:
 [Player3]           - Gets points for 3rd
 [Player4, Player5]   - Split points for 4th/5th
 ```
-
-## Contributing
-
-We welcome contributions! For detailed setup instructions, development guidelines, and advanced configuration options, please see [CONTRIBUTING.md](CONTRIBUTING.md).
-
-### Quick Start
-1. Clone the repository
-2. Install dependencies: `pip install -r requirements.txt`
-3. Build CLI tools: `cargo build --release --no-default-features`
-4. Run tests: `python -m unittest discover tests`
-5. Create a pull request

README.md

@@ -52,7 +52,7 @@
 - **BaseTwitterTask inheritance** - for proper cookie and cost management
 - **Saved Twitter cookies** - in `browser/browser_data/twitter_cookies.json`
 - **Environment variables**: `TWITTER_NAME`, `TWITTER_PASSWORD`, `OPENAI_API_KEY`
-- **Config file**: `config/llm.yaml` for cost limits and model settings
+- **Config file**: `config/config.yaml` for cost limits and model settings
 
 ---
 
@@ -281,7 +281,7 @@ class YourTwitterTask(BaseTwitterTask):
 ### **Environment Setup Checklist**
 - [ ] `TWITTER_NAME` and `TWITTER_PASSWORD` environment variables set
 - [ ] `OPENAI_API_KEY` configured for browser-use
-- [ ] `config/llm.yaml` exists with spending limits
+- [ ] `config/config.yaml` exists with spending limits
 - [ ] `browser/browser_data/twitter_cookies.json` exists (saved from previous login)
 - [ ] Virtual environment activated with all dependencies
 

REBRAND_COMPLETION_SUMMARY.md

@@ -43,7 +43,7 @@ def __init__(self, config: Optional[Dict[str, Any]] = None, config_file_path: Op
         
         Args:
             config: Configuration dictionary (optional)
-            config_file_path: Path to configuration file (optional, defaults to config/llm.yaml)
+            config_file_path: Path to configuration file (optional, defaults to config/config.yaml)
         """
         # Load configuration
         if config is None:
@@ -75,7 +75,7 @@ def __init__(self, config: Optional[Dict[str, Any]] = None, config_file_path: Op
 
     def load_llm_config(self, config_file_path: Optional[str] = None) -> Dict[str, Any]:
         """
-        Load LLM configuration from config/llm.yaml with environment variable substitution.
+        Load LLM configuration from config/config.yaml with environment variable substitution.
         
         Args:
             config_file_path: Optional path to config file
@@ -84,9 +84,9 @@ def load_llm_config(self, config_file_path: Optional[str] = None) -> Dict[str, A
             Configuration dictionary
         """
         if config_file_path is None:
-            # Default to config/llm.yaml in project root
+            # Default to config/config.yaml in project root
             script_dir = pathlib.Path(__file__).parent.parent.parent  # Go up from browser-use/core/ to project root
-            config_file_path = script_dir / "config" / "llm.yaml"
+            config_file_path = script_dir / "config" / "config.yaml"
         else:
             config_file_path = pathlib.Path(config_file_path)