A web-based UI for interacting with the opencode API. Enables real-time chat with AI coding agents, live streaming responses, and tool execution. Benefits developers and operations teams by streamlining AI-assisted coding workflows. Integrates with Claude Code and other supported agents.
git clone https://github.com/chris-tse/opencode-web.gitA web-based UI for interacting with the opencode API. Enables real-time chat with AI coding agents, live streaming responses, and tool execution. Benefits developers and operations teams by streamlining AI-assisted coding workflows. Integrates with Claude Code and other supported agents.
No install command available. Check the GitHub repository for manual installation instructions.
git clone https://github.com/chris-tse/opencode-webCopy the install command above and run it in your terminal.
Launch Claude Code, Cursor, or your preferred AI coding agent.
Use the prompt template or examples below to test the skill.
Adapt the skill to your specific use case and workflow.
I'm a developer at [COMPANY] working in the [INDUSTRY] sector. I need to use opencode-web to [SPECIFIC TASK, e.g., debug a Python script, generate a SQL query, or optimize a Dockerfile]. Can you guide me through the process and show me the expected output format?
# Debugging a Python Script
**Task:** Identify and fix issues in the following Python script that processes customer data.
```python
import pandas as pd
def process_data(file_path):
df = pd.read_csv(file_path)
df['total_spend'] = df['amount'] * df['quantity']
return df[df['total_spend'] > 1000]
# Example usage
processed_data = process_data('customer_data.csv')
```
**Potential Issues:**
- Missing error handling for file operations
- No input validation
- Hardcoded threshold value
**Suggested Improvements:**
1. Add try-except blocks for file operations
2. Implement input validation for file path and content
3. Make the threshold value configurable
4. Add logging for debugging purposes
**Improved Code:**
```python
import pandas as pd
import logging
logging.basicConfig(level=logging.INFO)
def process_data(file_path, threshold=1000):
try:
if not file_path.endswith('.csv'):
raise ValueError('File must be a CSV')
df = pd.read_csv(file_path)
if 'amount' not in df.columns or 'quantity' not in df.columns:
raise ValueError('Required columns missing in CSV')
df['total_spend'] = df['amount'] * df['quantity']
return df[df['total_spend'] > threshold]
except Exception as e:
logging.error(f'Error processing data: {str(e)}')
raise
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