fda

mysite/asgi copy 2.py

@@ -0,0 +1,59 @@
+import os
+from django.core.asgi import get_asgi_application
+from fastapi import FastAPI,Request
+from fastapi.staticfiles import StaticFiles
+from fastapi.templating import Jinja2Templates
+
+from starlette.middleware.cors import CORSMiddleware
+import logging
+import gradio as gr
+from mysite.gradio_config import setup_gradio_interfaces
+from mysite.webhook import setup_webhook_routes
+from mysite.database import setup_database_routes
+from mysite.asgi_config import init_django_app
+
+# ロガーの設定
+logging.basicConfig(level=logging.INFO)
+logger = logging.getLogger(__name__)
+file_handler = logging.FileHandler("app.log")
+file_handler.setLevel(logging.INFO)
+formatter = logging.Formatter("%(asctime)s - %(name)s - %(levelname)s - %(message)s")
+file_handler.setFormatter(formatter)
+logger.addHandler(file_handler)
+
+os.environ.setdefault("DJANGO_SETTINGS_MODULE", "mysite.settings")
+application = get_asgi_application()
+
+app = FastAPI()
+
+# Djangoアプリケーションの初期化
+init_django_app(app, application)
+
+# ミドルウェアの設定
+app.add_middleware(
+    CORSMiddleware,
+    allow_origins=["*"],
+    allow_credentials=True,
+    allow_methods=["*"],
+    allow_headers=["*"],
+)
+
+# Gradioインターフェースの設定
+gradio_interfaces = setup_gradio_interfaces()
+
+# Webhookルートの設定
+setup_webhook_routes(app)
+
+# データベースルートの設定
+setup_database_routes(app)
+
+# Gradioアプリのマウント
+app.mount("/static", StaticFiles(directory="static", html=True), name="static")
+app = gr.mount_gradio_app(app, gradio_interfaces, "/")
+
+# テンプレートファイルが格納されているディレクトリを指定
+templates = Jinja2Templates(directory="static")
+
+@app.get("/test")
+def get_some_page(request: Request):
+    return templates.TemplateResponse("index.html", {"request": request})

mysite/asgi.py

@@ -11,7 +11,8 @@ from mysite.gradio_config import setup_gradio_interfaces
 from mysite.webhook import setup_webhook_routes
 from mysite.database import setup_database_routes
 from mysite.asgi_config import init_django_app
-
+from interpreter import interpreter
+import mysite.interpreter_config  # インポートするだけで設定が適用されます
 # ロガーの設定
 logging.basicConfig(level=logging.INFO)
 logger = logging.getLogger(__name__)

mysite/gradio_config.py

@@ -1,5 +1,43 @@
 import gradio as gr
 from mysite.utilities import chat_with_interpreter, completion, process_file
+from interpreter import interpreter
+import mysite.interpreter_config  # インポートするだけで設定が適用されます
+import importlib
+import os
+import pkgutil
+from routers.chat.chat import demo44 as demo4
+
+def include_gradio_interfaces():
+    package_dir = "/home/user/app/routers"
+    gradio_interfaces = []
+    gradio_names = set()
+
+    for module_info in pkgutil.walk_packages([package_dir], "routers."):
+        sub_module_name = module_info.name
+        try:
+            print(f"Trying to import {sub_module_name}")
+            module = importlib.import_module(sub_module_name)
+            if hasattr(module, "gradio_interface"):
+                print(f"Found gradio_interface in {sub_module_name}")
+                interface_name = module_info.name.split(".")[-1]
+                if interface_name not in gradio_names:
+                    gradio_interfaces.append(module.gradio_interface)
+                    gradio_names.add(interface_name)
+                else:
+                    unique_name = f"{interface_name}_{len(gradio_names)}"
+                    gradio_interfaces.append(module.gradio_interface)
+                    gradio_names.add(unique_name)
+        except ModuleNotFoundError:
+            print(f"ModuleNotFoundError: {sub_module_name}")
+            pass
+        except Exception as e:
+            print(f"Failed to import {sub_module_name}: {e}")
+
+    print(f"Collected Gradio Interfaces: {gradio_names}")
+    return gradio_interfaces, list(gradio_names)
+
+
+
 
 def setup_gradio_interfaces():
     chat_interface = gr.ChatInterface(
@@ -16,15 +54,7 @@ def setup_gradio_interfaces():
     )
     chat_interface2.queue()
 
-    demo4 = gr.ChatInterface(
-        chat_with_interpreter,
-        additional_inputs=[
-            gr.Textbox(value="You are a friendly Chatbot.", label="System message"),
-            gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
-            gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
-            gr.Slider(minimum=0.1, maximum=1.0, value=0.95, step=0.05, label="Top-p (nucleus sampling)"),
-        ],
-    )
+
 
     democs = gr.Interface(
         fn=process_file,
@@ -40,6 +70,11 @@ def setup_gradio_interfaces():
     default_interfaces = [demo4,democs]
     default_names = ["demo4","仕様書から作成"]
 
-    tabs = gr.TabbedInterface(default_interfaces, default_names)
+    gradio_interfaces, gradio_names = include_gradio_interfaces()
+
+    all_interfaces = default_interfaces + gradio_interfaces
+    all_names = default_names + gradio_names
+
+    tabs = gr.TabbedInterface(all_interfaces, all_names)
     tabs.queue()
     return tabs

mysite/interpreter_config.py

@@ -0,0 +1,28 @@
+# interpreter_config.py
+
+import os
+from interpreter import interpreter
+
+# 環境変数でOpenAI APIキーを保存および使用
+interpreter.auto_run = True
+interpreter.llm.model = "huggingface/meta-llama/Meta-Llama-3-8B-Instruct"
+interpreter.llm.api_key = os.getenv("hf_token")
+interpreter.llm.api_base = "https://api.groq.com/openai/v1"
+interpreter.llm.api_key = os.getenv("api_key")
+interpreter.llm.model = "Llama3-70b-8192"
+
+# interpreter.llm.fp16 = False  # 明示的にFP32を使用するように設定
+# interpreter --conversations
+# LLM設定の適用
+interpreter.llm.context_window = 4096  # 一般的なLLMのコンテキストウィンドウサイズ
+interpreter.context_window = 4096  # 一般的なLLMのコンテキストウィンドウサイズ
+
+interpreter.llm.max_tokens = 3000  # 1回のリクエストで処理するトークンの最大数
+interpreter.max_tokens = 3000  # 1回のリクエストで処理するトークンの最大数
+
+interpreter.llm.max_output = 10000  # 出力の最大トークン数
+interpreter.max_output = 10000  # 出力の最大トークン数
+
+interpreter.conversation_history = True
+interpreter.debug_mode = False
+# interpreter.temperature = 0.7

mysite/utilities.py

@@ -5,6 +5,7 @@ import base64
 import subprocess
 import time
 
+
 def validate_signature(body: str, signature: str, secret: str) -> bool:
     hash = hmac.new(secret.encode("utf-8"), body.encode("utf-8"), hashlib.sha256).digest()
     expected_signature = base64.b64encode(hash).decode("utf-8")

routers/chat/chat.py

@@ -0,0 +1,180 @@
+import gradio as gr
+from mysite.utilities import chat_with_interpreter, completion, process_file
+from interpreter import interpreter
+import mysite.interpreter_config  # インポートするだけで設定が適用されます
+import duckdb
+
+def format_response(chunk, full_response):
+    # Message
+    if chunk["type"] == "message":
+        full_response += chunk.get("content", "")
+        if chunk.get("end", False):
+            full_response += "\n"
+
+    # Code
+    if chunk["type"] == "code":
+        if chunk.get("start", False):
+            full_response += "```python\n"
+        full_response += chunk.get("content", "").replace("`", "")
+        if chunk.get("end", False):
+            full_response += "\n```\n"
+
+    # Output
+    if chunk["type"] == "confirmation":
+        if chunk.get("start", False):
+            full_response += "```python\n"
+        full_response += chunk.get("content", {}).get("code", "")
+        if chunk.get("end", False):
+            full_response += "```\n"
+
+    # Console
+    if chunk["type"] == "console":
+        if chunk.get("start", False):
+            full_response += "```python\n"
+        if chunk.get("format", "") == "active_line":
+            console_content = chunk.get("content", "")
+            if console_content is None:
+                full_response += "No output available on console."
+        if chunk.get("format", "") == "output":
+            console_content = chunk.get("content", "")
+            full_response += console_content
+        if chunk.get("end", False):
+            full_response += "\n```\n"
+
+    # Image
+    if chunk["type"] == "image":
+        if chunk.get("start", False) or chunk.get("end", False):
+            full_response += "\n"
+        else:
+            image_format = chunk.get("format", "")
+            if image_format == "base64.png":
+                image_content = chunk.get("content", "")
+                if image_content:
+                    image = Image.open(BytesIO(base64.b64decode(image_content)))
+                    new_image = Image.new("RGB", image.size, "white")
+                    new_image.paste(image, mask=image.split()[3])
+                    buffered = BytesIO()
+                    new_image.save(buffered, format="PNG")
+                    img_str = base64.b64encode(buffered.getvalue()).decode()
+                    full_response += f"![Image](data:image/png;base64,{img_str})\n"
+
+    return full_response
+
+
+# Set the environment variable.
+def chat_with_interpreter(
+    message, history, a=None, b=None, c=None, d=None
+):  # , openai_api_key):
+    # Set the API key for the interpreter
+    # interpreter.llm.api_key = openai_api_key
+    if message == "reset":
+        interpreter.reset()
+        return "Interpreter reset", history
+    full_response = ""
+    # add_conversation(history,20)
+    user_entry = {"role": "user", "type": "message", "content": message}
+    #messages.append(user_entry)
+    # Call interpreter.chat and capture the result
+    # message = message + "\nシンタックスを確認してください。"
+    # result = interpreter.chat(message)
+    for chunk in interpreter.chat(message, display=False, stream=True):
+        # print(chunk)
+        # output = '\n'.join(item['content'] for item in result if 'content' in item)
+        full_response = format_response(chunk, full_response)
+        yield full_response  # chunk.get("content", "")
+
+    # Extract the 'content' field from all elements in the result
+    """
+    if isinstance(result, list):
+        for item in result:
+            if 'content' in item:
+                #yield item['content']#, history
+                output = '\n'.join(item['content'] for item in result if 'content' in item)
+    else:
+        #yield str(result)#, history
+        output = str(result)
+     """
+
+    age = 28
+    con = duckdb.connect(database="./workspace/sample.duckdb")
+    con.execute(
+        """
+    CREATE SEQUENCE IF NOT EXISTS sample_id_seq START 1;
+    CREATE TABLE IF NOT EXISTS samples (
+        id INTEGER DEFAULT nextval('sample_id_seq'),
+        name VARCHAR,
+        age INTEGER,
+        PRIMARY KEY(id)
+    );
+    """
+    )
+    cur = con.cursor()
+    con.execute("INSERT INTO samples (name, age) VALUES (?, ?)", (full_response, age))
+    con.execute("INSERT INTO samples (name, age) VALUES (?, ?)", (message, age))
+    # データをCSVファイルにエクスポート
+    con.execute("COPY samples TO 'sample.csv' (FORMAT CSV, HEADER)")
+    # データをコミット
+    con.commit()
+
+    # データを選択
+    cur = con.execute("SELECT * FROM samples")
+
+    # 結果をフェッチ
+    res = cur.fetchall()
+    rows = ""
+    # 結果を表示
+    # 結果を文字列に整形
+    rows = "\n".join([f"name: {row[0]}, age: {row[1]}" for row in res])
+
+    # コネクションを閉じる
+    con.close()
+    # print(cur.fetchall())
+    yield full_response + rows  # , history
+    return full_response, history
+
+PLACEHOLDER = """
+<div style="padding: 30px; text-align: center; display: flex; flex-direction: column; align-items: center;">
+   <img src="https://ysharma-dummy-chat-app.hf.space/file=/tmp/gradio/8e75e61cc9bab22b7ce3dec85ab0e6db1da5d107/Meta_lockup_positive%20primary_RGB.jpg" style="width: 80%; max-width: 550px; height: auto; opacity: 0.55;  ">
+   <h1 style="font-size: 28px; margin-bottom: 2px; opacity: 0.55;">Meta llama3</h1>
+   <p style="font-size: 18px; margin-bottom: 2px; opacity: 0.65;">Ask me anything...</p>
+</div>
+"""
+
+chatbot = gr.Chatbot(height=650, placeholder=PLACEHOLDER, label="Gradio ChatInterface")
+
+
+
+demo44 = gr.ChatInterface(
+    fn=chat_with_interpreter,
+    chatbot=chatbot,
+    fill_height=True,
+    additional_inputs_accordion=gr.Accordion(
+        label="⚙️ Parameters", open=False, render=False
+    ),
+    additional_inputs=[
+        gr.Slider(
+            minimum=0,
+            maximum=1,
+            step=0.1,
+            value=0.95,
+            label="Temperature",
+            render=False,
+        ),
+        gr.Slider(
+            minimum=128,
+            maximum=4096,
+            step=1,
+            value=512,
+            label="Max new tokens",
+            render=False,
+        ),
+    ],
+    # democs,
+    examples=[
+        ["HTMLのサンプルを作成して"],
+        [
+            "CUDA_VISIBLE_DEVICES=0 llamafactory-cli train examples/lora_single_gpu/llama3_lora_sft.yaml"
+        ],
+    ],
+    cache_examples=False,
+)

routers/chat/demo3.py

@@ -0,0 +1,18 @@
+
+import gradio as gr
+from mysite.utilities import chat_with_interpreter, completion, process_file
+from interpreter import interpreter
+import mysite.interpreter_config  # インポートするだけで設定が適用されます
+import mysite.interpreter_config
+
+
+
+demo4 = gr.ChatInterface(
+    chat_with_interpreter,
+    additional_inputs=[
+        gr.Textbox(value="You are a friendly Chatbot.", label="System message"),
+        gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
+        gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
+        gr.Slider(minimum=0.1, maximum=1.0, value=0.95, step=0.05, label="Top-p (nucleus sampling)"),
+    ],
+)