add stream output

pilot/configs/model_config.py

@@ -7,6 +7,7 @@ import os
 root_path = os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
 model_path = os.path.join(root_path, "models")
 vector_storepath = os.path.join(root_path, "vector_store")
+LOGDIR = os.path.join(root_path, "logs")
 
 
 DEVICE = "cuda" if torch.cuda.is_available() else "cpu"
@@ -16,8 +17,8 @@ llm_model_config = {
 }
 
 LLM_MODEL = "vicuna-13b"
-
+LIMIT_MODEL_CONCURRENCY = 5
-
+MAX_POSITION_EMBEDDINGS = 2048
 vicuna_model_server = "http://192.168.31.114:8000/"
 
 

pilot/server/embdserver.py

@@ -0,0 +1,3 @@
+#!/usr/bin/env python3
+# -*- coding:utf-8 -*-
+

pilot/server/vicuna_server.py

@@ -2,8 +2,12 @@
 # -*- coding: utf-8 -*-
 
 import uvicorn
+import asyncio
+import json
 from typing import Optional, List
-from fastapi import FastAPI
+from fastapi import FastAPI, Request, BackgroundTasks
+from fastapi.responses import StreamingResponse
+from fastchat.serve.inference import generate_stream
 from pydantic import BaseModel
 from pilot.model.inference import generate_output, get_embeddings
 from fastchat.serve.inference import load_model
@@ -11,6 +15,11 @@ from pilot.model.loader import ModerLoader
 from pilot.configs.model_config import *
 
 model_path = llm_model_config[LLM_MODEL] 
+
+
+global_counter = 0
+model_semaphore = None
+
 # ml = ModerLoader(model_path=model_path)
 # model, tokenizer = ml.loader(load_8bit=isload_8bit, debug=isdebug)
 
@@ -27,6 +36,47 @@ class PromptRequest(BaseModel):
 class EmbeddingRequest(BaseModel):
     prompt: str
 
+def release_model_semaphore():
+    model_semaphore.release()
+
+
+def generate_stream_gate(params):
+    try:
+        for output in generate_stream(
+            model, 
+            tokenizer,
+            params,
+            DEVICE,
+            MAX_POSITION_EMBEDDINGS,
+            2,
+        ):
+            ret = {
+                "text": output,
+                "error_code": 0,
+            }
+            yield json.dumps(ret).encode() + b"\0"
+    except torch.cuda.CudaError:
+        ret = {
+            "text": "**GPU OutOfMemory, Please Refresh.**",
+            "error_code": 0
+        }
+        yield json.dumps(ret).encode() + b"\0"
+
+
+@app.post("/generate_stream")
+async def api_generate_stream(request: Request):
+    global model_semaphore, global_counter
+    global_counter += 1
+    params = await request.json()
+    
+    if model_semaphore is None:
+        model_semaphore = asyncio.Semaphore(LIMIT_MODEL_CONCURRENCY)
+    await model_semaphore.acquire()
+    
+    generator = generate_stream_gate(params)
+    background_tasks = BackgroundTasks()
+    background_tasks.add_task(release_model_semaphore)
+    return StreamingResponse(generator, background=background_tasks)
 
 @app.post("/generate")
 def generate(prompt_request: PromptRequest):

pilot/server/webserver.py

@@ -0,0 +1,117 @@
+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+
+import os
+import uuid
+import time
+import gradio as gr
+import datetime
+
+from pilot.configs.model_config import LOGDIR
+
+from pilot.conversation import (
+    get_default_conv_template,
+    compute_skip_echo_len,
+    SeparatorStyle
+)
+
+from fastchat.utils import (
+    build_logger,
+    server_error_msg,
+    violates_moderation,
+    moderation_msg
+)
+
+from fastchat.serve.gradio_patch import Chatbot as grChatbot
+from fastchat.serve.gradio_css import code_highlight_css
+
+logger = build_logger("webserver", "webserver.log")
+headers = {"User-Agent": "dbgpt Client"}
+
+no_change_btn = gr.Button.update()
+enable_btn = gr.Button.update(interactive=True)
+disable_btn = gr.Button.update(interactive=True)
+
+enable_moderation = False
+models = []
+
+priority = {
+    "vicuna-13b": "aaa"
+}
+
+def set_global_vars(enable_moderation_, models_):
+    global enable_moderation, models
+    enable_moderation = enable_moderation_
+    models = models_
+
+def get_conv_log_filename():
+    t = datetime.datetime.now()
+    name = os.path.join(LOGDIR, f"{t.year}-{t.month:02d}-{t.day:02d}-conv.json")
+    return name
+
+
+def regenerate(state, request: gr.Request):
+    logger.info(f"regenerate. ip: {request.client.host}")
+    state.messages[-1][-1] = None
+    state.skip_next = False
+    return (state, state.to_gradio_chatbot(), "") + (disable_btn,) * 5
+
+def clear_history(request: gr.Request):
+    logger.info(f"clear_history. ip: {request.client.host}")
+    state = None
+    return (state, [], "") + (disable_btn,) * 5
+
+def add_text(state, text, request: gr.Request):
+    logger.info(f"add_text. ip: {request.client.host}. len:{len(text)}")
+
+    if state is None:
+        state = get_default_conv_template("vicuna").copy()
+    
+    if len(text) <= 0:
+        state.skip_next = True
+        return (state, state.to_gradio_chatbot(), "") + (no_change_btn,) * 5
+    
+    if enable_moderation:
+        flagged = violates_moderation(text)
+        if flagged:
+            logger.info(f"violate moderation. ip: {request.client.host}. text: {text}")
+            state.skip_next = True
+            return (state, state.to_gradio_chatbot(), moderation_msg) + (no_change_btn,) * 5
+    text = text[:1536]  # ? 
+    state.append_message(state.roles[0], text)      
+    state.append_message(state.roles[1], None)
+    state.skip_next = False
+
+    return (state, state.to_gradio_chatbot(), "") + (disable_btn,) * 5
+
+def post_process_code(code):
+    sep = "\n```"
+    if sep in code:
+        blocks = code.split(sep)
+        if len(blocks) % 2 == 1:
+            for i in range(1, len(blocks), 2):
+                blocks[i] = blocks[i].replace("\\_", "_")
+        code = sep.join(blocks)
+    return code
+
+def http_bot(state, model_selector, temperature, max_new_tokens, request: gr.Request):
+    logger.info(f"http_bot. ip: {request.client.host}")
+    start_tstamp = time.time()
+
+    model_name = model_selector
+    temperature = float(temperature)
+    max_new_tokens = int(max_new_tokens)
+
+    if state.skip_next:
+        yield (state, state.to_gradio_chatbot()) + (no_change_btn,) * 5
+        return
+
+    if len(state.message) == state.offset + 2:
+        new_state = get_default_conv_template(model_name).copy()
+        new_state.conv_id = uuid.uuid4().hex
+        new_state.append_message(new_state.roles[0], state.messages[-2][1])
+        new_state.append_message(new_state.roles[1], None)
+        state = new_state
+
+
+    # TODO