初始化项目，由ModelHub XC社区提供模型
Model: Raiff1982/Codette-Ultimate Source: Original Platform
This commit is contained in:
ModelHub XC
426
docs/README_GPT_OSS.md
Normal file
426
docs/README_GPT_OSS.md
Normal file
@@ -0,0 +1,426 @@
|
||||
# GPT-OSS - Open Source ChatGPT Alternative
|
||||
|
||||
A powerful open-source alternative to ChatGPT with advanced reasoning capabilities, integrated browser tools, and Python code execution — all running locally on Ollama.
|
||||
|
||||
## 🚀 Quick Start
|
||||
|
||||
```bash
|
||||
# Pull and run the model
|
||||
ollama pull Raiff1982/gpt-oss
|
||||
ollama run Raiff1982/gpt-oss
|
||||
```
|
||||
|
||||
## 🎯 What Makes This Model Special?
|
||||
|
||||
GPT-OSS provides a feature-complete ChatGPT experience with:
|
||||
|
||||
- **🧠 Multi-Level Reasoning** - Built-in analysis channels for deep thinking
|
||||
- **🌐 Browser Integration** - Search, open, and find information on the web
|
||||
- **🐍 Python Execution** - Run Python code in a stateful Jupyter environment
|
||||
- **🔧 Tool Calling** - Extensible function calling framework
|
||||
- **📊 Data Persistence** - Save and load files to `/mnt/data`
|
||||
- **💭 Chain of Thought** - Transparent reasoning with configurable depth
|
||||
|
||||
## 🛠️ Core Features
|
||||
|
||||
### Reasoning Channels
|
||||
|
||||
The model operates across multiple channels for structured thinking:
|
||||
|
||||
```
|
||||
analysis → Internal reasoning and tool usage (Python, browser)
|
||||
commentary → Function calls and external tool integration
|
||||
final → User-facing responses and conclusions
|
||||
```
|
||||
|
||||
This architecture enables:
|
||||
- **Transparent reasoning** - See how the model thinks
|
||||
- **Tool integration** - Seamlessly use Python/browser without breaking flow
|
||||
- **Clean output** - Separate internal work from final answers
|
||||
|
||||
### Browser Tools
|
||||
|
||||
Built-in web browsing capabilities:
|
||||
|
||||
```python
|
||||
# Search the web
|
||||
browser.search(query="latest AI research", topn=10)
|
||||
|
||||
# Open specific results
|
||||
browser.open(id=3, loc=0, num_lines=50)
|
||||
|
||||
# Find text on page
|
||||
browser.find(pattern="neural networks")
|
||||
```
|
||||
|
||||
**Use cases:**
|
||||
- Research current events and news
|
||||
- Find technical documentation
|
||||
- Verify facts and statistics
|
||||
- Compare information across sources
|
||||
|
||||
### Python Code Execution
|
||||
|
||||
Stateful Jupyter notebook environment:
|
||||
|
||||
```python
|
||||
# Execute code directly
|
||||
import pandas as pd
|
||||
import matplotlib.pyplot as plt
|
||||
|
||||
# Load and analyze data
|
||||
df = pd.read_csv('/mnt/data/data.csv')
|
||||
df.describe()
|
||||
|
||||
# Create visualizations
|
||||
plt.plot(df['x'], df['y'])
|
||||
plt.savefig('/mnt/data/plot.png')
|
||||
```
|
||||
|
||||
**Capabilities:**
|
||||
- Full Python standard library
|
||||
- Data analysis (pandas, numpy)
|
||||
- Visualization (matplotlib, seaborn)
|
||||
- Machine learning (scikit-learn)
|
||||
- File persistence in `/mnt/data`
|
||||
- 120 second execution timeout
|
||||
|
||||
### Reasoning Levels
|
||||
|
||||
Control analysis depth with reasoning parameters:
|
||||
|
||||
```
|
||||
low → Quick, intuitive responses
|
||||
medium → Balanced thinking (default)
|
||||
high → Deep, thorough analysis
|
||||
```
|
||||
|
||||
## 🎨 Example Use Cases
|
||||
|
||||
### Research Assistant
|
||||
```
|
||||
> What are the latest developments in quantum computing?
|
||||
|
||||
[Model searches web, analyzes multiple sources, synthesizes findings]
|
||||
[Cites sources with: 【6†L9-L11】 format]
|
||||
[Provides comprehensive summary with references]
|
||||
```
|
||||
|
||||
### Data Analysis
|
||||
```
|
||||
> Analyze this CSV and find correlations
|
||||
|
||||
[Loads data with pandas]
|
||||
[Performs statistical analysis]
|
||||
[Creates visualization]
|
||||
[Explains insights and patterns]
|
||||
```
|
||||
|
||||
### Code Generation & Debugging
|
||||
```
|
||||
> Help me debug this Python function
|
||||
|
||||
[Analyzes code structure]
|
||||
[Tests in Python environment]
|
||||
[Identifies issues]
|
||||
[Provides corrected version with explanation]
|
||||
```
|
||||
|
||||
### Multi-Step Problem Solving
|
||||
```
|
||||
> Plan a trip to Tokyo for 5 days under $2000
|
||||
|
||||
[Searches flight prices]
|
||||
[Finds accommodation options]
|
||||
[Researches local costs]
|
||||
[Creates detailed itinerary with budget breakdown]
|
||||
```
|
||||
|
||||
## ⚙️ Technical Specifications
|
||||
|
||||
- **Size**: ~13 GB
|
||||
- **Context Window**: 8192+ tokens
|
||||
- **Temperature**: 1.0 (balanced creativity)
|
||||
- **Knowledge Cutoff**: June 2024
|
||||
- **License**: Apache 2.0
|
||||
|
||||
### System Architecture
|
||||
|
||||
```
|
||||
User Query
|
||||
↓
|
||||
System Prompt (ChatGPT identity, tool definitions)
|
||||
↓
|
||||
Analysis Channel (reasoning, Python, browser tools)
|
||||
↓
|
||||
Commentary Channel (function calls)
|
||||
↓
|
||||
Final Channel (user-facing response)
|
||||
```
|
||||
|
||||
## 🔧 Advanced Usage
|
||||
|
||||
### Custom System Instructions
|
||||
|
||||
Extend the model with additional context:
|
||||
|
||||
```bash
|
||||
ollama run Raiff1982/gpt-oss "You are now a specialized Python tutor..."
|
||||
```
|
||||
|
||||
### Function Calling
|
||||
|
||||
Define custom functions the model can call:
|
||||
|
||||
```json
|
||||
{
|
||||
"name": "get_weather",
|
||||
"description": "Get current weather for a location",
|
||||
"parameters": {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"location": {"type": "string"},
|
||||
"units": {"type": "string", "enum": ["celsius", "fahrenheit"]}
|
||||
}
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
### API Integration
|
||||
|
||||
Use with Ollama's API for programmatic access:
|
||||
|
||||
```python
|
||||
import ollama
|
||||
|
||||
response = ollama.chat(
|
||||
model='Raiff1982/gpt-oss',
|
||||
messages=[
|
||||
{
|
||||
'role': 'user',
|
||||
'content': 'Write a Python script to analyze CSV data'
|
||||
}
|
||||
],
|
||||
tools=[
|
||||
{
|
||||
'type': 'function',
|
||||
'function': {
|
||||
'name': 'python',
|
||||
'description': 'Execute Python code'
|
||||
}
|
||||
}
|
||||
]
|
||||
)
|
||||
|
||||
print(response['message']['content'])
|
||||
```
|
||||
|
||||
### Streaming Responses
|
||||
|
||||
Get real-time output for long responses:
|
||||
|
||||
```python
|
||||
stream = ollama.chat(
|
||||
model='Raiff1982/gpt-oss',
|
||||
messages=[{'role': 'user', 'content': 'Explain quantum mechanics'}],
|
||||
stream=True
|
||||
)
|
||||
|
||||
for chunk in stream:
|
||||
print(chunk['message']['content'], end='', flush=True)
|
||||
```
|
||||
|
||||
## 🧪 Example Interactions
|
||||
|
||||
### Web Research with Citations
|
||||
```
|
||||
User: What caused the 2024 stock market volatility?
|
||||
|
||||
Assistant (analysis): *searches financial news*
|
||||
Assistant (analysis): *opens top 3 results*
|
||||
Assistant (analysis): *extracts key information*
|
||||
|
||||
Assistant (final): Based on recent financial reports【4†L12-L15】【7†L8】:
|
||||
1. Federal interest rate changes in Q1 2024
|
||||
2. Tech sector corrections【4†L23】
|
||||
3. Geopolitical tensions affecting energy markets【9†L5-L9】
|
||||
|
||||
The primary driver was...
|
||||
```
|
||||
|
||||
### Python Data Analysis
|
||||
```
|
||||
User: Load sales_data.csv and show me the top 5 products
|
||||
|
||||
Assistant (analysis):
|
||||
```python
|
||||
import pandas as pd
|
||||
df = pd.read_csv('/mnt/data/sales_data.csv')
|
||||
top_5 = df.groupby('product')['revenue'].sum().sort_values(ascending=False).head(5)
|
||||
print(top_5)
|
||||
```
|
||||
|
||||
Assistant (final): Here are your top 5 products by revenue:
|
||||
1. Product A: $45,230
|
||||
2. Product B: $38,920
|
||||
...
|
||||
```
|
||||
|
||||
### Complex Reasoning
|
||||
```
|
||||
User: Should I invest in renewable energy stocks?
|
||||
|
||||
Assistant (analysis): *thinking deeply*
|
||||
- Market trends analysis
|
||||
- Policy impact assessment
|
||||
- Risk evaluation
|
||||
- Timeline considerations
|
||||
|
||||
Assistant (final): I'll break this down across several dimensions:
|
||||
|
||||
**Market Analysis** [searches recent data]
|
||||
- Solar industry growth rate: 15% YoY【3†L45】
|
||||
- Wind energy investments up 23%【5†L12-L14】
|
||||
|
||||
**Policy Environment**
|
||||
[Considers regulatory landscape, incentives, risks]
|
||||
|
||||
**Personal Recommendation**
|
||||
Based on your [risk tolerance/timeline/goals]...
|
||||
```
|
||||
|
||||
## 📊 Capabilities Matrix
|
||||
|
||||
| Feature | Supported | Notes |
|
||||
|---------|-----------|-------|
|
||||
| Web Search | ✅ | Real-time information retrieval |
|
||||
| Web Browsing | ✅ | Open and parse URLs |
|
||||
| Python Execution | ✅ | Stateful Jupyter environment |
|
||||
| Code Generation | ✅ | Multiple languages |
|
||||
| Data Analysis | ✅ | Pandas, NumPy, visualization |
|
||||
| File Persistence | ✅ | `/mnt/data` directory |
|
||||
| Function Calling | ✅ | Extensible tool framework |
|
||||
| Multi-Step Reasoning | ✅ | Chain of thought |
|
||||
| Streaming | ✅ | Real-time output |
|
||||
| Citations | ✅ | Source tracking with line numbers |
|
||||
|
||||
## 🔒 Privacy & Safety
|
||||
|
||||
**Local Execution Benefits:**
|
||||
- All processing happens on your machine
|
||||
- No data sent to external APIs (except browser tools)
|
||||
- Full control over tool usage
|
||||
- Inspect code before execution
|
||||
|
||||
**Browser Tool Considerations:**
|
||||
- Browser tools do make external web requests
|
||||
- Review URLs and search queries before execution
|
||||
- Content fetched is processed locally
|
||||
|
||||
**Python Execution Safety:**
|
||||
- Sandboxed environment with 120s timeout
|
||||
- File access limited to `/mnt/data`
|
||||
- No network access from Python by default
|
||||
- Review generated code before running
|
||||
|
||||
## 🚦 Best Practices
|
||||
|
||||
### Effective Prompting
|
||||
```
|
||||
❌ Vague: "Tell me about AI"
|
||||
✅ Specific: "Search for recent breakthroughs in transformer architecture
|
||||
from 2024, then summarize the top 3 findings"
|
||||
|
||||
❌ Too broad: "Analyze my data"
|
||||
✅ Actionable: "Load sales.csv, calculate monthly revenue trends,
|
||||
and create a line plot showing growth over time"
|
||||
```
|
||||
|
||||
### Tool Usage
|
||||
- **Search first** - Use browser before asking knowledge questions
|
||||
- **Verify with code** - Use Python to validate calculations
|
||||
- **Cite sources** - Pay attention to citation numbers
|
||||
- **Check dates** - Knowledge cutoff is June 2024
|
||||
|
||||
### Reasoning Control
|
||||
```bash
|
||||
# Quick responses
|
||||
ollama run Raiff1982/gpt-oss --reasoning low "Quick question..."
|
||||
|
||||
# Deep analysis
|
||||
ollama run Raiff1982/gpt-oss --reasoning high "Complex problem..."
|
||||
```
|
||||
|
||||
## 🆚 GPT-OSS vs. Other Models
|
||||
|
||||
| Feature | GPT-OSS | Standard LLMs | ChatGPT Plus |
|
||||
|---------|---------|---------------|--------------|
|
||||
| Cost | Free (local) | Free/Varies | $20/month |
|
||||
| Privacy | Full privacy | Varies | Data processed externally |
|
||||
| Tools | Browser + Python | None | Browser + Python + DALL-E |
|
||||
| Reasoning | Transparent | Hidden | Partial transparency |
|
||||
| Customization | Full control | Limited | Limited |
|
||||
| Offline | After download | Varies | No |
|
||||
|
||||
## 🔄 Updates & Versioning
|
||||
|
||||
This model is actively maintained:
|
||||
- Base architecture follows ChatGPT design patterns
|
||||
- Tools and capabilities updated regularly
|
||||
- Community contributions welcome
|
||||
|
||||
## 📚 Related Resources
|
||||
|
||||
- [Ollama Documentation](https://ollama.ai/docs)
|
||||
- [Function Calling Guide](https://github.com/ollama/ollama/blob/main/docs/api.md#tools)
|
||||
- [Python Environment Details](https://jupyter.org/)
|
||||
- [Apache License 2.0](http://www.apache.org/licenses/LICENSE-2.0)
|
||||
|
||||
## 🤝 Contributing
|
||||
|
||||
Help improve GPT-OSS:
|
||||
1. Report issues with tool usage
|
||||
2. Share effective prompting strategies
|
||||
3. Contribute function definitions
|
||||
4. Document use cases and examples
|
||||
|
||||
## 💡 Tips & Tricks
|
||||
|
||||
### Multi-Step Workflows
|
||||
```
|
||||
> First, search for "Python data visualization libraries 2024"
|
||||
> Then, use Python to create example plots with the top 3 libraries
|
||||
> Finally, compare their strengths and weaknesses
|
||||
```
|
||||
|
||||
### Data Pipeline
|
||||
```
|
||||
> Load my CSV from /mnt/data/raw.csv
|
||||
> Clean the data (handle missing values, outliers)
|
||||
> Create summary statistics
|
||||
> Save cleaned data to /mnt/data/processed.csv
|
||||
> Generate a report with key findings
|
||||
```
|
||||
|
||||
### Research & Writing
|
||||
```
|
||||
> Research the history of neural networks (search 5 sources)
|
||||
> Outline a 1000-word article based on findings
|
||||
> Draft section 1 with proper citations
|
||||
> Review and refine for clarity
|
||||
```
|
||||
|
||||
## 🏆 Acknowledgments
|
||||
|
||||
- **OpenAI** - ChatGPT architecture inspiration
|
||||
- **Ollama Team** - Local model runtime
|
||||
- **Open Source Community** - Tool integrations and feedback
|
||||
|
||||
---
|
||||
|
||||
**Model Page**: https://ollama.com/Raiff1982/gpt-oss
|
||||
**Created**: December 27, 2025
|
||||
**Size**: 13 GB
|
||||
**License**: Apache 2.0
|
||||
|
||||
*"Open source intelligence with the power of ChatGPT, privacy of local execution, and freedom of customization."*
|
||||
Reference in New Issue
Block a user