fix bugs for interactive of /node add

src/component/llama_node/local_llama_compute_node.py

@@ -1,9 +1,6 @@
 
-import json
 import logging
 import requests
-from typing import Optional, List
-from pydantic import BaseModel
 
 from aios import ComputeTask,Queue_ComputeNode, ComputeTaskResult, ComputeTaskResultCode, ComputeTaskState, ComputeTaskType,AIStorage,UserConfig
 

src/service/aios_shell/local_compute_node_builder/__init__.py

@@ -1,13 +1,19 @@
-from prompt_toolkit import PromptSession
+import os
+from prompt_toolkit import HTML, PromptSession, print_formatted_text
 from prompt_toolkit.styles import Style
 from service.aios_shell.local_compute_node_builder.local_llama_node_builder import LocalLlamaNodeBuilder
 from .local_compute_node_builder import BuilderState, LocalComputeNodeBuilder
+from aios_kernel.storage import AIStorage
 
 async def build(prompt_session: PromptSession, shell_style: Style) -> str or None:
     # model_type = await prompt_session.prompt_async(f"Please select the node server type (default: llama.cpp):", style = shell_style)
 
     model_type = 'llama.cpp'
 
+    download_dir = AIStorage.get_instance().get_download_dir()
+    if not os.path.exists(download_dir):
+        os.mkdir(download_dir)
+
     state = BuilderState(prompt_session, shell_style)
     
     match model_type:
@@ -19,7 +25,9 @@ async def build(prompt_session: PromptSession, shell_style: Style) -> str or Non
         if param is None:
             return None
         
-        value = await state.prompt_session.prompt_async(f"{state.last_result_prompt}{param.desc}:", style = state.shell_style)
+        if state.last_result_prompt or param.desc:
+            print_formatted_text(f"{state.last_result_prompt}{param.desc}", style = state.shell_style)
+        value = await state.prompt_session.prompt_async(f"{param.prompt}:", style = state.shell_style)
         if value:
             value = value.strip()
 

src/service/aios_shell/local_compute_node_builder/local_compute_node_builder.py

@@ -24,8 +24,9 @@ class ParameterApplier:
         pass
 
 class BuildParameter:
-    def __init__(self, name: str, applier: ParameterApplier, desc: str or None = None, default_value: str or None = None):
+    def __init__(self, name: str, applier: ParameterApplier, prompt: str or None = None, desc: str or None = None, default_value: str or None = None):
         self.name = name
+        self.prompt = prompt
         self.desc = desc
         self.default_value = default_value
         self.applier = applier

src/service/aios_shell/local_compute_node_builder/local_llama_node_builder.py

@@ -97,12 +97,13 @@ class ParameterExternParamsApplier:
     async def apply(self, state: BuilderState, name: str, value: str or None = None) -> str or None:
         extern_params = value
         docker_image = ""
-        gpu_options = None
+        gpu_options = []
+        state.next_step += 1
 
         if state.params["n_gpu_layers"] == "0":
             docker_image = "ghcr.io/abetlen/llama-cpp-python:latest"
         else:
-            gpu_options = "--gpus all"
+            gpu_options = ["--gpus", "all"]
             llama_cpp_python_repo_url = "https://github.com/abetlen/llama-cpp-python.git"
             download_path = AIStorage.get_instance().get_download_dir()
             llama_cpp_python_path = download_path + "/llama-cpp-python"
@@ -115,9 +116,10 @@ class ParameterExternParamsApplier:
                 if os.path.exists(llama_cpp_python_path):
                     result = subprocess.run(['git', 'pull'], cwd = llama_cpp_python_path, stdout = subprocess.PIPE, stderr = subprocess.PIPE, text = True)
                 else:
-                    result = subprocess.run(['git', 'clone', llama_cpp_python_repo_url, download_path], stdout = subprocess.PIPE, stderr = subprocess.PIPE, text = True)
+                    result = subprocess.run(['git', 'clone', llama_cpp_python_repo_url, llama_cpp_python_path], stdout = subprocess.PIPE, stderr = subprocess.PIPE, text = True)
 
                 if result.stderr:
+                    print_formatted_text(FormattedText([("class:warn", result.stderr)]), style = state.shell_style)
                     while True:
                         sel = await state.prompt_session.prompt_async(f"Update 'llama-cpp-python' failed, you can press 'r' to retry, or 'c' to continue with the current version.", style = state.shell_style)
                         if sel == 'r':
@@ -139,6 +141,7 @@ class ParameterExternParamsApplier:
                 result = subprocess.run(['docker', 'build', '-t', docker_image, f"{llama_cpp_python_path}/docker/cuda_simple/"], stdout = subprocess.PIPE, stderr = subprocess.PIPE, text = True)
 
                 if result.stderr:
+                    print_formatted_text(FormattedText([("class:warn", result.stderr)]), style = state.shell_style)
                     while True:
                         sel = await state.prompt_session.prompt_async(f"Build the image failed, you can press 'r' to retry, or 'c' to continue with the current version.", style = state.shell_style)
                         if sel == 'r':
@@ -151,89 +154,92 @@ class ParameterExternParamsApplier:
                 else:
                     break
             
-            retry = True
-            while True:
-                retry = False
-                run_options = ['docker', 'run', '-d']
+        retry = True
+        while retry:
+            retry = False
+            run_options = ['docker', 'run', '-d']
 
-                if gpu_options:
-                    run_options.append(gpu_options)
+            if gpu_options:
+                run_options.extend(gpu_options)
             
-                run_options.extend([
-                    '-p', f"{state.params['port']}:8000",
-                    '-v', f"{os.path.dirname(state.params['model_path'])}:/models", '-e', f"MODEL=/models/{os.path.basename(state.params['model_path'])}",
-                    'llama-cpp-python-cuda',
-                    'python3', '-m', 'llama_cpp.server',
-                    '--n_gpu_layers', state.params["n_gpu_layers"],
-                    '--n_ctx', state.params["n_ctx"],
-                    '--chat_format', state.params["chat_format"],
-                    ])
+            run_options.extend([
+                '-p', f"{state.params['port']}:8000",
+                '-v', f"{os.path.dirname(state.params['model_path'])}:/models", '-e', f"MODEL=/models/{os.path.basename(state.params['model_path'])}",
+                'llama-cpp-python-cuda',
+                'python3', '-m', 'llama_cpp.server',
+                '--n_gpu_layers', state.params["n_gpu_layers"],
+                '--n_ctx', state.params["n_ctx"],
+                '--chat_format', state.params["chat_format"],
+                ])
             
-                if extern_params:
-                    run_options.extend(extern_params.split(' '))
+            if extern_params:
+                run_options.extend(extern_params.split(' '))
 
-                result = subprocess.run(run_options, stdout = subprocess.PIPE, stderr = subprocess.PIPE, text = True)
+            print_formatted_text(FormattedText([("class:prompt", f"Will start service with: {' '.join(run_options)}")]), style = state.shell_style)
 
-                if result.stderr:
-                    while True:
-                        sel = await state.prompt_session.prompt_async(f"Start the node service failed, you can press 'r' to retry, or 'a' to abort.", style = state.shell_style)
-                        if sel == 'r':
-                            retry = True
-                            break
-                        elif sel == 'a':
-                            break
-                        else:
-                            pass # Select again
-                else:
-                    local_url = f'http://localhost:{state.params["port"]}'
-                    foreign_url = 'http://{your-host-address}:' + state.params["port"]
-                    model_name = state.params['node_name']
+            result = subprocess.run(run_options, stdout = subprocess.PIPE, stderr = subprocess.PIPE, text = True)
 
-                    ComputeNodeConfig.get_instance().add_node("llama", local_url, model_name)
-                    ComputeNodeConfig.get_instance().save()
-                    node = LocalLlama_ComputeNode(local_url, model_name)
-                    node.start()
-                    ComputeKernel.get_instance().add_compute_node(node)
+            if result.stderr:
+                print_formatted_text(FormattedText([("class:warn", result.stderr)]), style = state.shell_style)
+                while True:
+                    sel = await state.prompt_session.prompt_async(f"Start the node service failed, you can press 'r' to retry, or 'a' to abort.", style = state.shell_style)
+                    if sel == 'r':
+                        retry = True
+                        break
+                    elif sel == 'a':
+                        break
+                    else:
+                        pass # Select again
+            else:
+                local_url = f'http://localhost:{state.params["port"]}'
+                foreign_url = 'http://{your-host-address}:' + state.params["port"]
+                model_name = state.params['node_name']
 
-                    print_formatted_text(FormattedText([(
-                        "class:prompt",
-                        f"""
-                        Congratulations! The node ({model_name}) service successed.
-                        You can access it with follow url:
-                        {local_url}
-                        And 'http://{foreign_url}' in other computers.
-                        Now you can refer it in agents as `llm_model_name={model_name}`
-                        """
-                    )]), style = state.shell_style)
-                    break
+                ComputeNodeConfig.get_instance().add_node("llama", local_url, model_name)
+                ComputeNodeConfig.get_instance().save()
+                node = LocalLlama_ComputeNode(local_url, model_name)
+                node.start()
+                ComputeKernel.get_instance().add_compute_node(node)
+
+                print_formatted_text(FormattedText([(
+                    "class:prompt",
+f"""
+Congratulations! The node ({model_name}) service successed.
+You can access it with follow url:
+{local_url}
+And 'http://{foreign_url}' in other computers.
+Now you can refer it in agents as `llm_model_name={model_name}`
+"""
+                )]), style = state.shell_style)
+                break
 
 _recommend_model_urls = {
     "1": {
-        "model": "Llama-2-70B-chat",
+        "model": "Llama-2-70B-Chat-GGUF",
         "url": "https://huggingface.co/TheBloke/Llama-2-70B-chat-GGUF/resolve/main/llama-2-70b-chat.Q4_0.gguf"
     },
     "2": {
-        "model": "Llama-2-13B-chat",
+        "model": "Llama-2-13B-Chat-GGUF",
         "url": "https://huggingface.co/TheBloke/Llama-2-13B-chat-GGUF/resolve/main/llama-2-13b-chat.Q4_0.gguf"
     },
     "3": {
         "model": "Llama-2-7B-Chat-GGUF",
-        "url": "https://huggingface.co/TheBloke/Llama-2-7B-Chat-GGUF/blob/main/llama-2-7b-chat.Q4_K_M.gguf"
+        "url": "https://huggingface.co/TheBloke/Llama-2-7B-Chat-GGUF/resolve/main/llama-2-7b-chat.Q4_K_M.gguf"
     },
 }
 
-_recommend_model_url_table_str = map(lambda id, info: f"\t{id}\t{info['model']}\t{info['url']}\n", _recommend_model_urls)
+_recommend_model_url_table_str = ""
+for i in range(1, 999):
+    id = str(i)
+    info = _recommend_model_urls.get(id)
+    if info:
+        _recommend_model_url_table_str += f"\n\t{id}\t{info['model']}\t{info['url']}"
+    else:
+        break
 
 _params = [
     BuildParameter("model_path", BuildParameterModelPath(), "Please input the model file path (Press 'Enter' if you need to download it)"),
-    BuildParameter("model_url", BuildParameterModelUrl(), 
-                    f"""
-                    Please input the url to download the model, or you can input the 'ID' in the follow table to select one:
-                        ID\tmodel\turl
-                        {_recommend_model_url_table_str}
-                    Please input (default: Llama-2-70B-chat)
-                    """
-                   ),
+    BuildParameter("model_url", BuildParameterModelUrl(), "Please input (default: Llama-2-70B-chat)", f"Now you need input the url to download the model, or you can input the 'ID' in the follow table to select one:\n\tID\tmodel\t\turl{_recommend_model_url_table_str}"),
     BuildParameter("node_name", ParameterNodeNameApplier(), "Please input name for your node, and you can set it in 'llm_model_name' of 'agent.toml' (default: the name of the model file)"),
     BuildParameter("port", ParameterPortApplier(), "Please input the port which the node server will listen on (default: random)"),
     BuildParameter("n_gpu_layers", ParameterNGpuLayersApplier(), "Please input layers offload to GPU (<=83 for Llama, 0 for CPU only, default: 83)"),