backend api

.gitignore

@@ -1,6 +1,7 @@
 build/bin
 node_modules
 frontend/dist
+__pycache__
 .idea
 .vs
 package.json.md5

backend-python/global_var.py

@@ -0,0 +1,27 @@
+from enum import Enum, auto
+
+Model = 'model'
+Model_Status = 'model_status'
+
+
+class ModelStatus(Enum):
+    Offline = auto()
+    Loading = auto()
+    Working = auto()
+
+
+def init():
+    global GLOBALS
+    GLOBALS = {}
+    set(Model_Status, ModelStatus.Offline)
+
+
+def set(key, value):
+    GLOBALS[key] = value
+
+
+def get(key):
+    if key in GLOBALS:
+        return GLOBALS[key]
+    else:
+        return None

backend-python/main.py

@@ -1,42 +1,15 @@
-import json
-import pathlib
-import sys
-from typing import List
 import os
-import sysconfig
+import psutil
 
-from fastapi import FastAPI, Request, status, HTTPException
-from langchain.llms import RWKV
-from pydantic import BaseModel
-from sse_starlette.sse import EventSourceResponse
+from fastapi import FastAPI
 from fastapi.middleware.cors import CORSMiddleware
 import uvicorn
 
-from rwkv_helper import rwkv_generate
-
-
-def set_torch():
-    torch_path = os.path.join(sysconfig.get_paths()["purelib"], "torch\\lib")
-    paths = os.environ.get("PATH", "")
-    if os.path.exists(torch_path):
-        print(f"torch found: {torch_path}")
-        if torch_path in paths:
-            print("torch already set")
-        else:
-            print("run:")
-            os.environ['PATH'] = paths + os.pathsep + torch_path + os.pathsep
-            print(f'set Path={paths + os.pathsep + torch_path + os.pathsep}')
-    else:
-        print("torch not found")
-
-
-def torch_gc():
-    import torch
-
-    if torch.cuda.is_available():
-        with torch.cuda.device(0):
-            torch.cuda.empty_cache()
-            torch.cuda.ipc_collect()
+from utils.rwkv import *
+from utils.torch import *
+from utils.ngrok import *
+from routes import completion, config
+import global_var
 
 
 app = FastAPI()
@@ -49,87 +22,33 @@ app.add_middleware(
     allow_headers=["*"],
 )
 
+app.include_router(completion.router)
+app.include_router(config.router)
+
 
 @app.on_event('startup')
 def init():
-    global model
+    global_var.init()
 
     set_torch()
 
-    model = RWKV(
-        model=sys.argv[2],
-        strategy=sys.argv[1],
-        tokens_path=f"{pathlib.Path(__file__).parent.resolve()}/20B_tokenizer.json"
-    )
-
     if os.environ.get("ngrok_token") is not None:
         ngrok_connect()
 
 
-def ngrok_connect():
-    from pyngrok import ngrok, conf
-    conf.set_default(conf.PyngrokConfig(ngrok_path="./ngrok"))
-    ngrok.set_auth_token(os.environ["ngrok_token"])
-    http_tunnel = ngrok.connect(8000)
-    print(http_tunnel.public_url)
-
-
-class Message(BaseModel):
-    role: str
-    content: str
-
-
-class Body(BaseModel):
-    messages: List[Message]
-    model: str
-    stream: bool
-    max_tokens: int
-
-
 @app.get("/")
 def read_root():
     return {"Hello": "World!"}
 
-@app.post("update-config")
-def updateConfig(body: Body):
-    pass
 
-
-@app.post("/v1/chat/completions")
-@app.post("/chat/completions")
-async def completions(body: Body, request: Request):
-    global model
-
-    question = body.messages[-1]
-    if question.role == 'user':
-        question = question.content
-    else:
-        raise HTTPException(status.HTTP_400_BAD_REQUEST, "No Question Found")
-
-    completion_text = ""
-    for message in body.messages:
-        if message.role == 'user':
-            completion_text += "Bob: " + message.content + "\n\n"
-        elif message.role == 'assistant':
-            completion_text += "Alice: " + message.content + "\n\n"
-    completion_text += "Alice:"
-
-    async def eval_rwkv():
-        if body.stream:
-            for response, delta in rwkv_generate(model, completion_text):
-                if await request.is_disconnected():
-                    break
-                yield json.dumps({"response": response, "choices": [{"delta": {"content": delta}}], "model": "rwkv"})
-            yield "[DONE]"
-        else:
-            response = None
-            for response, delta in rwkv_generate(model, completion_text):
-                pass
-            yield json.dumps({"response": response, "model": "rwkv"})
-        # torch_gc()
-
-    return EventSourceResponse(eval_rwkv())
+@app.post("/exit")
+def read_root():
+    parent_pid = os.getpid()
+    parent = psutil.Process(parent_pid)
+    for child in parent.children(recursive=True):
+        child.kill()
+    parent.kill()
 
 
 if __name__ == "__main__":
-    uvicorn.run("main:app", reload=False, app_dir="backend-python")
+    uvicorn.run("main:app", port=8000)

backend-python/routes/completion.py

@@ -0,0 +1,58 @@
+import json
+from typing import List
+
+from fastapi import APIRouter, Request, status, HTTPException
+from sse_starlette.sse import EventSourceResponse
+from pydantic import BaseModel
+from utils.rwkv import *
+import global_var
+
+router = APIRouter()
+
+
+class Message(BaseModel):
+    role: str
+    content: str
+
+
+class CompletionBody(BaseModel):
+    messages: List[Message]
+    model: str
+    stream: bool
+    max_tokens: int
+
+
+@router.post("/v1/chat/completions")
+@router.post("/chat/completions")
+async def completions(body: CompletionBody, request: Request):
+    model = global_var.get(global_var.Model)
+
+    question = body.messages[-1]
+    if question.role == 'user':
+        question = question.content
+    else:
+        raise HTTPException(status.HTTP_400_BAD_REQUEST, "no question found")
+
+    completion_text = ""
+    for message in body.messages:
+        if message.role == 'user':
+            completion_text += "Bob: " + message.content + "\n\n"
+        elif message.role == 'assistant':
+            completion_text += "Alice: " + message.content + "\n\n"
+    completion_text += "Alice:"
+
+    async def eval_rwkv():
+        if body.stream:
+            for response, delta in rwkv_generate(model, completion_text):
+                if await request.is_disconnected():
+                    break
+                yield json.dumps({"response": response, "choices": [{"delta": {"content": delta}}], "model": "rwkv"})
+            yield "[DONE]"
+        else:
+            response = None
+            for response, delta in rwkv_generate(model, completion_text):
+                pass
+            yield json.dumps({"response": response, "model": "rwkv"})
+        # torch_gc()
+
+    return EventSourceResponse(eval_rwkv())

backend-python/routes/config.py

@@ -0,0 +1,46 @@
+import pathlib
+import sys
+
+from fastapi import APIRouter, HTTPException, status
+from pydantic import BaseModel
+from langchain.llms import RWKV
+from utils.rwkv import *
+from utils.torch import *
+import global_var
+
+router = APIRouter()
+
+
+class UpdateConfigBody(BaseModel):
+    model: str = None
+    strategy: str = None
+    max_response_token: int = None
+    temperature: float = None
+    top_p: float = None
+    presence_penalty: float = None
+    count_penalty: float = None
+
+
+@router.post("/update-config")
+def update_config(body: UpdateConfigBody):
+    if (global_var.get(global_var.Model_Status) is global_var.ModelStatus.Loading):
+        return "loading"
+
+    global_var.set(global_var.Model_Status, global_var.ModelStatus.Offline)
+    global_var.set(global_var.Model, None)
+    torch_gc()
+
+    global_var.set(global_var.Model_Status, global_var.ModelStatus.Loading)
+    try:
+        global_var.set(global_var.Model, RWKV(
+            model=sys.argv[2],
+            strategy=sys.argv[1],
+            tokens_path=f"{pathlib.Path(__file__).parent.parent.resolve()}/20B_tokenizer.json"
+        ))
+    except Exception:
+        global_var.set(global_var.Model_Status, global_var.ModelStatus.Offline)
+        raise HTTPException(status.HTTP_500_INTERNAL_SERVER_ERROR, "failed to load")
+
+    global_var.set(global_var.Model_Status, global_var.ModelStatus.Working)
+
+    return "success"

backend-python/utils/ngrok.py

@@ -0,0 +1,9 @@
+import os
+
+
+def ngrok_connect():
+    from pyngrok import ngrok, conf
+    conf.set_default(conf.PyngrokConfig(ngrok_path="./ngrok"))
+    ngrok.set_auth_token(os.environ["ngrok_token"])
+    http_tunnel = ngrok.connect(8000)
+    print(http_tunnel.public_url)

backend-python/utils/rwkv.py

@@ -15,8 +15,8 @@ def rwkv_generate(model: RWKV, prompt: str):
     for i in range(model.max_tokens_per_generation):
         for n in occurrence:
             logits[n] -= (
-                    model.penalty_alpha_presence
-                    + occurrence[n] * model.penalty_alpha_frequency
+                model.penalty_alpha_presence
+                + occurrence[n] * model.penalty_alpha_frequency
             )
         token = model.pipeline.sample_logits(
             logits, temperature=model.temperature, top_p=model.top_p

backend-python/utils/torch.py

@@ -0,0 +1,26 @@
+import os
+import sysconfig
+
+
+def set_torch():
+    torch_path = os.path.join(sysconfig.get_paths()["purelib"], "torch\\lib")
+    paths = os.environ.get("PATH", "")
+    if os.path.exists(torch_path):
+        print(f"torch found: {torch_path}")
+        if torch_path in paths:
+            print("torch already set")
+        else:
+            print("run:")
+            os.environ['PATH'] = paths + os.pathsep + torch_path + os.pathsep
+            print(f'set Path={paths + os.pathsep + torch_path + os.pathsep}')
+    else:
+        print("torch not found")
+
+
+def torch_gc():
+    import torch
+
+    if torch.cuda.is_available():
+        with torch.cuda.device(0):
+            torch.cuda.empty_cache()
+            torch.cuda.ipc_collect()