wuyang/zk-data-agent
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

add missing parts

Browse Source
This commit is contained in:
Abdelrahman Abdallah
2026-04-02 10:19:07 +02:00
parent eaf2ff63d6
commit 46778c1b5f
1 changed files with 324 additions and 324 deletions
Download Patch File Download Diff File Expand all files Collapse all files
README.md
+324 -324
View File
@@ -76,6 +76,330 @@ Built on the public porting workspace from [instructkr/claw-code](https://github
- [ ] Some deeper runtime details from the npm source - [ ] Some deeper runtime details from the npm source
- [ ] Cost tracking and budget limits - [ ] Cost tracking and budget limits
---
## 🏗️ Architecture
```text
claw-code/
├── README.md
├── pyproject.toml
├── .gitignore
├── images/
│ └── logo.png
├── src/ # Python implementation
│ ├── main.py # CLI entry point & argument parsing
│ ├── agent_runtime.py # Core agent loop (LocalCodingAgent)
│ ├── agent_tools.py # Tool definitions & execution engine
│ ├── agent_prompting.py # System prompt assembly
│ ├── agent_context.py # Context building & CLAUDE.md discovery
│ ├── agent_context_usage.py # Context usage estimation & reporting
│ ├── agent_session.py # Session state management
│ ├── agent_slash_commands.py # Local slash command processing
│ ├── agent_types.py # Shared dataclasses & type definitions
│ ├── openai_compat.py # OpenAI-compatible API client
│ ├── session_store.py # Session serialization & persistence
│ ├── permissions.py # Tool permission filtering
│ ├── tools.py # Mirrored tool inventory
│ ├── commands.py # Mirrored command inventory
│ ├── ... # 75+ modules across 30+ packages
│ ├── plugins/ # Plugin subsystem (WIP)
│ ├── hooks/ # Hook system (WIP)
│ ├── remote/ # Remote runtime modes (WIP)
│ ├── voice/ # Voice mode (WIP)
│ └── vim/ # VIM mode (WIP)
└── tests/ # Unit tests
├── test_agent_runtime.py
├── test_agent_context.py
├── test_agent_context_usage.py
├── test_agent_prompting.py
├── test_agent_slash_commands.py
└── test_porting_workspace.py
```
---
## 📦 Requirements
| Requirement | Details |
|-------------|---------|
| 🐍 Python | `3.10` or higher |
| 🖥️ Model Server | `vLLM`, `Ollama`, or `LiteLLM Proxy`, with tool calling support |
| 🧠 Model | [`Qwen/Qwen3-Coder-30B-A3B-Instruct`](https://huggingface.co/Qwen/Qwen3-Coder-30B-A3B-Instruct) (recommended) |
---
## 🚀 Quick Start
### 1. Start vLLM with Qwen3-Coder
vLLM must be started with automatic tool choice enabled. Use the `qwen3_xml` parser for Qwen3-Coder tool calling:
```bash
python -m vllm.entrypoints.openai.api_server \
--model Qwen/Qwen3-Coder-30B-A3B-Instruct \
--host 127.0.0.1 \
--port 8000 \
--enable-auto-tool-choice \
--tool-call-parser qwen3_xml
```
Verify the server is running:
```bash
curl http://127.0.0.1:8000/v1/models
```
> 📚 **References:** [vLLM Tool Calling Docs](https://docs.vllm.ai/en/v0.13.0/features/tool_calling/) · [OpenAI-Compatible Server](https://docs.vllm.ai/en/v0.13.0/serving/openai_compatible_server.html)
### Optional: Use Ollama Instead of vLLM
`claw-code-agent` can also work with Ollama because the runtime targets an OpenAI-compatible API. Use a model that supports tool calling well.
Example:
```bash
ollama serve
ollama pull qwen3
```
Then configure:
```bash
export OPENAI_BASE_URL=http://127.0.0.1:11434/v1
export OPENAI_API_KEY=ollama
export OPENAI_MODEL=qwen3
```
Notes:
- prefer tool-capable models such as `qwen3`
- plain chat-only models are not enough for full agent behavior
- Ollama does not use the `vLLM` parser flags shown above
> 📚 **References:** [Ollama OpenAI Compatibility](https://docs.ollama.com/api/openai-compatibility) · [Ollama Tool Calling](https://docs.ollama.com/capabilities/tool-calling)
### Optional: Use LiteLLM Proxy
`claw-code-agent` can also work through LiteLLM Proxy because the runtime targets an OpenAI-compatible chat completions API. The routed model still needs to support tool calling for full agent behavior.
Quick start example:
```bash
pip install 'litellm[proxy]'
litellm --model ollama/qwen3
```
LiteLLM Proxy runs on port `4000` by default. Then configure:
```bash
export OPENAI_BASE_URL=http://127.0.0.1:4000
export OPENAI_API_KEY=anything
export OPENAI_MODEL=ollama/qwen3
```
Notes:
- LiteLLM Proxy gives you an OpenAI-style gateway in front of many providers
- tool use still depends on the underlying routed model and provider behavior
- if you configure a LiteLLM master key, use that instead of `anything`
> 📚 **References:** [LiteLLM Docs](https://docs.litellm.ai/) · [LiteLLM Proxy Quick Start](https://docs.litellm.ai/)
### 2. Configure Environment
```bash
export OPENAI_BASE_URL=http://127.0.0.1:8000/v1
export OPENAI_API_KEY=local-token
export OPENAI_MODEL=Qwen/Qwen3-Coder-30B-A3B-Instruct
```
### Use Another Model With vLLM
If you want to try another model, keep the same `vLLM` server setup and change the `--model` value when you launch `vLLM`.
Example:
```bash
python -m vllm.entrypoints.openai.api_server \
--model your-model-name \
--host 127.0.0.1 \
--port 8000 \
--enable-auto-tool-choice \
--tool-call-parser your_parser
```
Then update:
```bash
export OPENAI_MODEL=your-model-name
```
Notes:
- the documented path in this repository is `vLLM`
- the model must support tool calling well enough for agent use
- some model families require a different `--tool-call-parser`
- slash commands such as `/help`, `/context`, and `/tools` are local and do not require the model server
### 3. Run the Agent
```bash
# Read-only question
python3 -m src.main agent \
"Read src/agent_runtime.py and summarize how the loop works." \
--cwd .
# Write-enabled task
python3 -m src.main agent \
"Create TEST_QWEN_AGENT.md with one line: test ok" \
--cwd . --allow-write
# Shell-enabled task
python3 -m src.main agent \
"Run pwd and ls src, then summarize the result." \
--cwd . --allow-shell
```
---
## 🛠️ Usage
### Agent Commands
| Command | Description |
|---------|-------------|
| `agent <prompt>` | Run the agent with a prompt |
| `agent-prompt` | Show the assembled system prompt |
| `agent-context` | Show estimated context usage |
| `agent-context-raw` | Show the raw context snapshot |
| `agent-resume <id> <prompt>` | Resume a saved session |
### CLI Flags
| Flag | Description |
|------|-------------|
| `--cwd <path>` | Set the workspace directory |
| `--model <name>` | Override the model name |
| `--base-url <url>` | Override the API base URL |
| `--allow-write` | Allow the agent to modify files |
| `--allow-shell` | Allow the agent to execute shell commands |
| `--unsafe` | Allow destructive shell operations |
| `--show-transcript` | Print the full message transcript |
| `--system-prompt <text>` | Set a custom system prompt |
| `--append-system-prompt <text>` | Append to the system prompt |
| `--add-dir <path>` | Add extra directories to context |
### Slash Commands
These are handled **locally** before the model loop:
| Command | Aliases | Description |
|---------|---------|-------------|
| `/help` | `/commands` | Show built-in slash commands |
| `/context` | `/usage` | Show estimated session context usage |
| `/context-raw` | `/env` | Show raw environment & context snapshot |
| `/prompt` | `/system-prompt` | Render the effective system prompt |
| `/permissions` | — | Show active tool permission mode |
| `/model` | — | Show or update the active model |
| `/tools` | — | List registered tools with permission status |
| `/memory` | — | Show loaded CLAUDE.md memory bundle |
| `/status` | `/session` | Show runtime/session status summary |
| `/clear` | — | Clear ephemeral runtime state |
```bash
python3 -m src.main agent "/help"
python3 -m src.main agent "/context" --cwd .
python3 -m src.main agent "/tools" --cwd .
python3 -m src.main agent "/status" --cwd .
```
### Utility Commands
```bash
python3 -m src.main summary # Workspace summary
python3 -m src.main manifest # Workspace manifest
python3 -m src.main commands --limit 10 # Command inventory
python3 -m src.main tools --limit 10 # Tool inventory
```
---
## 🔧 Built-in Tools
The agent has access to 7 core tools:
| Tool | Description | Permission |
|------|-------------|------------|
| `list_dir` | List files and directories | 🟢 Always |
| `read_file` | Read file contents (with line ranges) | 🟢 Always |
| `write_file` | Write or create files | 🟡 `--allow-write` |
| `edit_file` | Edit files via exact string matching | 🟡 `--allow-write` |
| `glob_search` | Find files by glob pattern | 🟢 Always |
| `grep_search` | Search file contents by regex | 🟢 Always |
| `bash` | Execute shell commands | 🔴 `--allow-shell` |
---
## 🔄 Session Persistence
Each `agent` run automatically saves a resumable session:
```text
session_id=4f2c8c6f9c0e4d7c9c7b1b2a3d4e5f67
session_path=.port_sessions/agent/4f2c8c6f...
```
Resume a previous session:
```bash
python3 -m src.main agent-resume \
4f2c8c6f9c0e4d7c9c7b1b2a3d4e5f67 \
"Continue the previous task and finish the missing parts."
```
Inspect saved sessions:
```bash
ls -lt .port_sessions/agent
```
> **Note:** Run `agent-resume` from the same `claw-code/` directory where the session was created. A resumed session continues from the saved transcript, not from scratch.
---
## 🧪 Testing
Run the full test suite:
```bash
python3 -m unittest discover -s tests -v
```
Smoke tests:
```bash
python3 -m src.main agent "/help"
python3 -m src.main agent-context --cwd .
python3 -m src.main agent \
"Read src/agent_session.py and summarize the message flow." \
--cwd .
```
---
## 🔐 Permission Model
Claw Code Agent uses a **tiered permission system** to keep the agent safe by default:
| Tier | Capability | Flag Required |
|------|-----------|---------------|
| **Read-only** | List, read, glob, grep | None (default) |
| **Write** | + file creation and editing | `--allow-write` |
| **Shell** | + shell command execution | `--allow-shell` |
| **Unsafe** | + destructive shell operations | `--unsafe` |
## 🔎 Detailed Parity Status Against npm `src` ## 🔎 Detailed Parity Status Against npm `src`
This section tracks what is already implemented in Python and what is still missing compared with the upstream npm runtime in [`/src`](/data/fs201059/aa17626/claude_code_source/src). This section tracks what is already implemented in Python and what is still missing compared with the upstream npm runtime in [`/src`](/data/fs201059/aa17626/claude_code_source/src).
@@ -429,330 +753,6 @@ Mirrored inventory / scaffold areas that still need real implementation work:
--- ---
## 🏗️ Architecture
```text
claw-code/
├── README.md
├── pyproject.toml
├── .gitignore
├── images/
│ └── logo.png
├── src/ # Python implementation
│ ├── main.py # CLI entry point & argument parsing
│ ├── agent_runtime.py # Core agent loop (LocalCodingAgent)
│ ├── agent_tools.py # Tool definitions & execution engine
│ ├── agent_prompting.py # System prompt assembly
│ ├── agent_context.py # Context building & CLAUDE.md discovery
│ ├── agent_context_usage.py # Context usage estimation & reporting
│ ├── agent_session.py # Session state management
│ ├── agent_slash_commands.py # Local slash command processing
│ ├── agent_types.py # Shared dataclasses & type definitions
│ ├── openai_compat.py # OpenAI-compatible API client
│ ├── session_store.py # Session serialization & persistence
│ ├── permissions.py # Tool permission filtering
│ ├── tools.py # Mirrored tool inventory
│ ├── commands.py # Mirrored command inventory
│ ├── ... # 75+ modules across 30+ packages
│ ├── plugins/ # Plugin subsystem (WIP)
│ ├── hooks/ # Hook system (WIP)
│ ├── remote/ # Remote runtime modes (WIP)
│ ├── voice/ # Voice mode (WIP)
│ └── vim/ # VIM mode (WIP)
└── tests/ # Unit tests
├── test_agent_runtime.py
├── test_agent_context.py
├── test_agent_context_usage.py
├── test_agent_prompting.py
├── test_agent_slash_commands.py
└── test_porting_workspace.py
```
---
## 📦 Requirements
| Requirement | Details |
|-------------|---------|
| 🐍 Python | `3.10` or higher |
| 🖥️ Model Server | `vLLM`, `Ollama`, or `LiteLLM Proxy`, with tool calling support |
| 🧠 Model | [`Qwen/Qwen3-Coder-30B-A3B-Instruct`](https://huggingface.co/Qwen/Qwen3-Coder-30B-A3B-Instruct) (recommended) |
---
## 🚀 Quick Start
### 1. Start vLLM with Qwen3-Coder
vLLM must be started with automatic tool choice enabled. Use the `qwen3_xml` parser for Qwen3-Coder tool calling:
```bash
python -m vllm.entrypoints.openai.api_server \
--model Qwen/Qwen3-Coder-30B-A3B-Instruct \
--host 127.0.0.1 \
--port 8000 \
--enable-auto-tool-choice \
--tool-call-parser qwen3_xml
```
Verify the server is running:
```bash
curl http://127.0.0.1:8000/v1/models
```
> 📚 **References:** [vLLM Tool Calling Docs](https://docs.vllm.ai/en/v0.13.0/features/tool_calling/) · [OpenAI-Compatible Server](https://docs.vllm.ai/en/v0.13.0/serving/openai_compatible_server.html)
### Optional: Use Ollama Instead of vLLM
`claw-code-agent` can also work with Ollama because the runtime targets an OpenAI-compatible API. Use a model that supports tool calling well.
Example:
```bash
ollama serve
ollama pull qwen3
```
Then configure:
```bash
export OPENAI_BASE_URL=http://127.0.0.1:11434/v1
export OPENAI_API_KEY=ollama
export OPENAI_MODEL=qwen3
```
Notes:
- prefer tool-capable models such as `qwen3`
- plain chat-only models are not enough for full agent behavior
- Ollama does not use the `vLLM` parser flags shown above
> 📚 **References:** [Ollama OpenAI Compatibility](https://docs.ollama.com/api/openai-compatibility) · [Ollama Tool Calling](https://docs.ollama.com/capabilities/tool-calling)
### Optional: Use LiteLLM Proxy
`claw-code-agent` can also work through LiteLLM Proxy because the runtime targets an OpenAI-compatible chat completions API. The routed model still needs to support tool calling for full agent behavior.
Quick start example:
```bash
pip install 'litellm[proxy]'
litellm --model ollama/qwen3
```
LiteLLM Proxy runs on port `4000` by default. Then configure:
```bash
export OPENAI_BASE_URL=http://127.0.0.1:4000
export OPENAI_API_KEY=anything
export OPENAI_MODEL=ollama/qwen3
```
Notes:
- LiteLLM Proxy gives you an OpenAI-style gateway in front of many providers
- tool use still depends on the underlying routed model and provider behavior
- if you configure a LiteLLM master key, use that instead of `anything`
> 📚 **References:** [LiteLLM Docs](https://docs.litellm.ai/) · [LiteLLM Proxy Quick Start](https://docs.litellm.ai/)
### 2. Configure Environment
```bash
export OPENAI_BASE_URL=http://127.0.0.1:8000/v1
export OPENAI_API_KEY=local-token
export OPENAI_MODEL=Qwen/Qwen3-Coder-30B-A3B-Instruct
```
### Use Another Model With vLLM
If you want to try another model, keep the same `vLLM` server setup and change the `--model` value when you launch `vLLM`.
Example:
```bash
python -m vllm.entrypoints.openai.api_server \
--model your-model-name \
--host 127.0.0.1 \
--port 8000 \
--enable-auto-tool-choice \
--tool-call-parser your_parser
```
Then update:
```bash
export OPENAI_MODEL=your-model-name
```
Notes:
- the documented path in this repository is `vLLM`
- the model must support tool calling well enough for agent use
- some model families require a different `--tool-call-parser`
- slash commands such as `/help`, `/context`, and `/tools` are local and do not require the model server
### 3. Run the Agent
```bash
# Read-only question
python3 -m src.main agent \
"Read src/agent_runtime.py and summarize how the loop works." \
--cwd .
# Write-enabled task
python3 -m src.main agent \
"Create TEST_QWEN_AGENT.md with one line: test ok" \
--cwd . --allow-write
# Shell-enabled task
python3 -m src.main agent \
"Run pwd and ls src, then summarize the result." \
--cwd . --allow-shell
```
---
## 🛠️ Usage
### Agent Commands
| Command | Description |
|---------|-------------|
| `agent <prompt>` | Run the agent with a prompt |
| `agent-prompt` | Show the assembled system prompt |
| `agent-context` | Show estimated context usage |
| `agent-context-raw` | Show the raw context snapshot |
| `agent-resume <id> <prompt>` | Resume a saved session |
### CLI Flags
| Flag | Description |
|------|-------------|
| `--cwd <path>` | Set the workspace directory |
| `--model <name>` | Override the model name |
| `--base-url <url>` | Override the API base URL |
| `--allow-write` | Allow the agent to modify files |
| `--allow-shell` | Allow the agent to execute shell commands |
| `--unsafe` | Allow destructive shell operations |
| `--show-transcript` | Print the full message transcript |
| `--system-prompt <text>` | Set a custom system prompt |
| `--append-system-prompt <text>` | Append to the system prompt |
| `--add-dir <path>` | Add extra directories to context |
### Slash Commands
These are handled **locally** before the model loop:
| Command | Aliases | Description |
|---------|---------|-------------|
| `/help` | `/commands` | Show built-in slash commands |
| `/context` | `/usage` | Show estimated session context usage |
| `/context-raw` | `/env` | Show raw environment & context snapshot |
| `/prompt` | `/system-prompt` | Render the effective system prompt |
| `/permissions` | — | Show active tool permission mode |
| `/model` | — | Show or update the active model |
| `/tools` | — | List registered tools with permission status |
| `/memory` | — | Show loaded CLAUDE.md memory bundle |
| `/status` | `/session` | Show runtime/session status summary |
| `/clear` | — | Clear ephemeral runtime state |
```bash
python3 -m src.main agent "/help"
python3 -m src.main agent "/context" --cwd .
python3 -m src.main agent "/tools" --cwd .
python3 -m src.main agent "/status" --cwd .
```
### Utility Commands
```bash
python3 -m src.main summary # Workspace summary
python3 -m src.main manifest # Workspace manifest
python3 -m src.main commands --limit 10 # Command inventory
python3 -m src.main tools --limit 10 # Tool inventory
```
---
## 🔧 Built-in Tools
The agent has access to 7 core tools:
| Tool | Description | Permission |
|------|-------------|------------|
| `list_dir` | List files and directories | 🟢 Always |
| `read_file` | Read file contents (with line ranges) | 🟢 Always |
| `write_file` | Write or create files | 🟡 `--allow-write` |
| `edit_file` | Edit files via exact string matching | 🟡 `--allow-write` |
| `glob_search` | Find files by glob pattern | 🟢 Always |
| `grep_search` | Search file contents by regex | 🟢 Always |
| `bash` | Execute shell commands | 🔴 `--allow-shell` |
---
## 🔄 Session Persistence
Each `agent` run automatically saves a resumable session:
```text
session_id=4f2c8c6f9c0e4d7c9c7b1b2a3d4e5f67
session_path=.port_sessions/agent/4f2c8c6f...
```
Resume a previous session:
```bash
python3 -m src.main agent-resume \
4f2c8c6f9c0e4d7c9c7b1b2a3d4e5f67 \
"Continue the previous task and finish the missing parts."
```
Inspect saved sessions:
```bash
ls -lt .port_sessions/agent
```
> **Note:** Run `agent-resume` from the same `claw-code/` directory where the session was created. A resumed session continues from the saved transcript, not from scratch.
---
## 🧪 Testing
Run the full test suite:
```bash
python3 -m unittest discover -s tests -v
```
Smoke tests:
```bash
python3 -m src.main agent "/help"
python3 -m src.main agent-context --cwd .
python3 -m src.main agent \
"Read src/agent_session.py and summarize the message flow." \
--cwd .
```
---
## 🔐 Permission Model
Claw Code Agent uses a **tiered permission system** to keep the agent safe by default:
| Tier | Capability | Flag Required |
|------|-----------|---------------|
| **Read-only** | List, read, glob, grep | None (default) |
| **Write** | + file creation and editing | `--allow-write` |
| **Shell** | + shell command execution | `--allow-shell` |
| **Unsafe** | + destructive shell operations | `--unsafe` |
---
## ⚠️ Disclaimer ## ⚠️ Disclaimer
- This repository is a **Python reimplementation** inspired by the Claude Code npm architecture. - This repository is a **Python reimplementation** inspired by the Claude Code npm architecture.