feat: adapt for modularization

Author: diogoncalves

examples/01_intro_to_llmstudio copy.ipynb

@@ -222,7 +222,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from llmstudio import LLM\n",
+    "from libs.llmstudio.llmstudio import LLM\n",
     "import nest_asyncio\n",
     "nest_asyncio.apply()"
    ]

examples/01_intro_to_llmstudio_core.ipynb

@@ -23,14 +23,14 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Running LLMstudio Engine on http://0.0.0.0:8001 \n",
+      "Running LLMstudio Proxy on http://0.0.0.0:8001 \n",
       "Running LLMstudio Tracking on http://0.0.0.0:8002 \n"
      ]
     }
    ],
    "source": [
-    "from llmstudio.server import start_server\n",
-    "start_server()"
+    "from llmstudio.server import start_servers\n",
+    "start_servers()"
    ]
   },
   {
@@ -47,8 +47,8 @@
     }
    ],
    "source": [
-    "from llmstudio.engine.provider import LLMProxyProvider as LLM\n",
-    "from llmstudio.engine.provider import ProxyConfig\n",
+    "from llmstudio_proxy.provider import LLMProxyProvider as LLM\n",
+    "from llmstudio_proxy.provider import ProxyConfig\n",
     "\n",
     "# from llmstudio_core import LLMCore as LLM\n",
     "# from llmstudio import LLM\n",
@@ -61,7 +61,20 @@
    "cell_type": "code",
    "execution_count": 3,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "ename": "Exception",
+     "evalue": "{\"detail\":\"Not Found\"}",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mException\u001b[0m                                 Traceback (most recent call last)",
+      "Cell \u001b[0;32mIn[3], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m result \u001b[38;5;241m=\u001b[39m \u001b[43mllm\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mchat\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43molá\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mmodel\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mgpt-4o\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m)\u001b[49m\n",
+      "File \u001b[0;32m~/fun/LLMstudio/libs/proxy/llmstudio_proxy/provider.py:63\u001b[0m, in \u001b[0;36mLLMProxyProvider.chat\u001b[0;34m(self, chat_input, model, is_stream, retries, parameters, **kwargs)\u001b[0m\n\u001b[1;32m     61\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m response\u001b[38;5;241m.\u001b[39mok:\n\u001b[1;32m     62\u001b[0m     error_data \u001b[38;5;241m=\u001b[39m response\u001b[38;5;241m.\u001b[39mtext\n\u001b[0;32m---> 63\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mException\u001b[39;00m(error_data)\n\u001b[1;32m     65\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m is_stream:\n\u001b[1;32m     66\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mgenerate_chat(response)\n",
+      "\u001b[0;31mException\u001b[0m: {\"detail\":\"Not Found\"}"
+     ]
+    }
+   ],
    "source": [
     "result = llm.chat(\"olá\", model=\"gpt-4o\")\n"
    ]
@@ -74,15 +87,15 @@
     {
      "data": {
       "text/plain": [
-       "('Olá! Como posso ajudar você hoje?',\n",
+       "('Olá! Como posso ajudá-lo hoje?',\n",
        " {'input_tokens': 2,\n",
        "  'output_tokens': 11,\n",
        "  'total_tokens': 13,\n",
        "  'cost_usd': 0.000175,\n",
-       "  'latency_s': 0.6496210098266602,\n",
-       "  'time_to_first_token_s': 0.5341501235961914,\n",
-       "  'inter_token_latency_s': 0.01241710450914171,\n",
-       "  'tokens_per_second': 15.393590799454474})"
+       "  'latency_s': 0.9914300441741943,\n",
+       "  'time_to_first_token_s': 0.8828918933868408,\n",
+       "  'inter_token_latency_s': 0.011675781673855253,\n",
+       "  'tokens_per_second': 10.086440348223903})"
       ]
      },
      "execution_count": 4,
@@ -117,17 +130,20 @@
    "metadata": {},
    "outputs": [
     {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "host='0.0.0.0' port='8001' url=None username=None password=None\n",
-      "Connected to LLMStudio Proxy @ 0.0.0.0:8001\n"
+     "ename": "ModuleNotFoundError",
+     "evalue": "No module named 'llmstudio_proxyprovider'",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mModuleNotFoundError\u001b[0m                       Traceback (most recent call last)",
+      "Cell \u001b[0;32mIn[6], line 2\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[38;5;66;03m# You can set OPENAI_API_KEY and ANTHROPIC_API_KEY on .env file\u001b[39;00m\n\u001b[0;32m----> 2\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mllmstudio_proxyprovider\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m ProxyConfig\n\u001b[1;32m      3\u001b[0m proxy \u001b[38;5;241m=\u001b[39m ProxyConfig(host\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m0.0.0.0\u001b[39m\u001b[38;5;124m\"\u001b[39m, port\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m8001\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m      4\u001b[0m \u001b[38;5;28mprint\u001b[39m(proxy)\n",
+      "\u001b[0;31mModuleNotFoundError\u001b[0m: No module named 'llmstudio_proxyprovider'"
      ]
     }
    ],
    "source": [
     "# You can set OPENAI_API_KEY and ANTHROPIC_API_KEY on .env file\n",
-    "from llmstudio.engine.provider import ProxyConfig\n",
+    "from llmstudio_proxyprovider import ProxyConfig\n",
     "proxy = ProxyConfig(host=\"0.0.0.0\", port=\"8001\")\n",
     "print(proxy)\n",
     "\n",

examples/01_intro_to_llmstudio_with_proxy.ipynb

@@ -1,7 +1,7 @@
 from llmstudio.server import start_server
 start_server()
 
-from llmstudio.engine.provider import LLMProxyProvider
+from llmstudio_proxy.provider import LLMProxyProvider
 
 
 llm = LLMProxyProvider(provider="openai", host="0.0.0.0", port="8001")

examples/llm_proxy.py

@@ -2,9 +2,9 @@
 from typing import Optional
 from llmstudio_core.providers.provider import BaseProvider, provider_registry
 
-from llmstudio_core.providers import _load_engine_config
+from llmstudio_core.providers import _load_providers_config
 
-_engine_config = _load_engine_config()
+_engine_config = _load_providers_config()
 
 
 def LLMCore(provider: str, api_key: Optional[str] = None, **kwargs) -> BaseProvider:

libs/core/llmstudio_core/__init__.py

@@ -38,7 +38,7 @@ class EngineConfig(BaseModel):
     providers: Dict[str, ProviderConfig]
 
 
-def _load_engine_config() -> EngineConfig:
+def _load_providers_config() -> EngineConfig:
     #TODO read from github
     default_config_path = Path(os.path.join(os.path.dirname(__file__), "config.yaml"))
     local_config_path = Path(os.getcwd(), "config.yaml")