d

mysite/database/database.py

@@ -6,6 +6,45 @@ import gradio as gr
 con = duckdb.connect(database="./workspace/mydatabase.duckdb")
 con.execute("CREATE TABLE IF NOT EXISTS items (id INTEGER, name VARCHAR);")
 
+# Extract the 'content' field from all elements in the result
+def insert(full_response,message):
+    age = 28
+    # データベースファイルのパス
+    db_path = "./workspace/sample.duckdb"
+
+    # DuckDBに接続（データベースファイルが存在しない場合は新規作成）
+    con = duckdb.connect(database=db_path)
+    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())
+    insert(full_response,message)
+
 def setup_database_routes(app: FastAPI):
     def create_item(name):
         con.execute("INSERT INTO items (name) VALUES (?);", (name,))

mysite/interpreter/interpreter.py

@@ -0,0 +1,96 @@
+import os
+import shutil
+import hmac
+import hashlib
+import base64
+import subprocess
+import time
+from mysite.libs.logger import logger
+import async_timeout
+import asyncio
+import mysite.interpreter.interpreter_config 
+
+GENERATION_TIMEOUT_SEC=60
+
+def set_environment_variables():
+    os.environ["OPENAI_API_BASE"] = "https://api.groq.com/openai/v1"
+    os.environ["OPENAI_API_KEY"] = "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"
+    os.environ["MODEL_NAME"] = "llama3-8b-8192"
+    os.environ["LOCAL_MODEL"] = "true"
+
+# 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
+    messages = []
+    recent_messages = history[-20:]
+    for conversation in recent_messages:
+        user_message = conversation[0]
+        user_entry = {"role": "user", "content": user_message}
+        messages.append(user_entry)
+        assistant_message = conversation[1]
+        assistant_entry = {"role": "assistant", "content": assistant_message}
+        messages.append(assistant_entry)
+
+    user_entry = {"role": "user", "content": message}
+    messages.append(user_entry)
+    #system_prompt = {"role": "system", "content": "あなたは日本語の優秀なアシスタントです。"}
+    #messages.insert(0, system_prompt)
+
+    for chunk in interpreter.chat(messages, 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", "")
+
+    yield full_response + rows  # , history
+    return full_response, history
+
+async def completion(message: str, history, c=None, d=None):
+    from groq import Groq
+    client = Groq(api_key=os.getenv("api_key"))
+    messages = []
+    recent_messages = history[-20:]
+    for conversation in recent_messages:
+        user_message = conversation[0]
+        user_entry = {"role": "user", "content": user_message}
+        messages.append(user_entry)
+        assistant_message = conversation[1]
+        assistant_entry = {"role": "assistant", "content": assistant_message}
+        messages.append(assistant_entry)
+
+    user_entry = {"role": "user", "content": message}
+    messages.append(user_entry)
+    system_prompt = {"role": "system", "content": "あなたは日本語の優秀なアシスタントです。"}
+    messages.insert(0, system_prompt)
+    async with async_timeout.timeout(GENERATION_TIMEOUT_SEC):
+        try:
+            stream = client.chat.completions.create(
+                model="llama3-8b-8192",
+                messages=messages,
+                temperature=1,
+                max_tokens=1024,
+                top_p=1,
+                stream=True,
+                stop=None,
+            )
+            all_result = ""
+            for chunk in stream:
+                current_content = chunk.choices[0].delta.content or ""
+                all_result += current_content
+                yield current_content
+            yield all_result
+            #return all_result
+        except asyncio.TimeoutError:
+            raise HTTPException(status_code=504, detail="Stream timed out")
+

mysite/interpreter/process.py

@@ -0,0 +1,99 @@
+import os
+import shutil
+import hmac
+import hashlib
+import base64
+import subprocess
+import time
+from mysite.libs.logger import logger
+import async_timeout
+import asyncio
+import mysite.interpreter.interpreter_config 
+
+GENERATION_TIMEOUT_SEC=60
+
+def set_environment_variables():
+    os.environ["OPENAI_API_BASE"] = "https://api.groq.com/openai/v1"
+    os.environ["OPENAI_API_KEY"] = "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"
+    os.environ["MODEL_NAME"] = "llama3-8b-8192"
+    os.environ["LOCAL_MODEL"] = "true"
+
+def validate_signature(body: str, signature: str, secret: str) -> bool:
+    if secret is None:
+        logger.error("Secret is None")
+        return False
+
+    hash = hmac.new(
+        secret.encode("utf-8"), body.encode("utf-8"), hashlib.sha256
+    ).digest()
+    expected_signature = base64.b64encode(hash).decode("utf-8")
+    return hmac.compare_digest(expected_signature, signature)
+
+def no_process_file(prompt, foldername):
+    set_environment_variables()
+    try:
+        proc = subprocess.Popen(["mkdir", f"/home/user/app/routers/{foldername}"])
+    except subprocess.CalledProcessError as e:
+        return f"Processed Content:\n{e.stdout}\n\nMake Command Error:\n{e.stderr}"
+
+    no_extension_path = f"/home/user/app/routers/{foldername}/prompt"
+    time.sleep(1)
+    with open(no_extension_path, "a") as f:
+        f.write(prompt)
+    time.sleep(1)
+    try:
+        prompt_file_path = no_extension_path
+        with open(prompt_file_path, "w") as prompt_file:
+            prompt_file.write(prompt)
+    except Exception as e:
+        return f"Error writing prompt to file: {str(e)}"
+    time.sleep(1)
+    try:
+        proc = subprocess.Popen(
+            ["make", "run", foldername],
+            stdin=subprocess.PIPE,
+            stdout=subprocess.PIPE,
+            stderr=subprocess.PIPE,
+            text=True,
+        )
+        stdout, stderr = proc.communicate(input="n\ny\ny\n")
+        return f"Processed Content:\n{stdout}\n\nMake Command Output:\n{stdout}\n\nMake Command Error:\n{stderr}"
+    except subprocess.CalledProcessError as e:
+        return f"Processed Content:\n{e.stdout}\n\nMake Command Error:\n{e.stderr}"
+
+
+
+def process_file(fileobj, prompt, foldername):
+    set_environment_variables()
+    try:
+        proc = subprocess.Popen(["mkdir", f"/home/user/app/routers/{foldername}"])
+    except subprocess.CalledProcessError as e:
+        return f"Processed Content:\n{e.stdout}\n\nMake Command Error:\n{e.stderr}"
+    time.sleep(2)
+    path = f"/home/user/app/routers/{foldername}/" + os.path.basename(fileobj)
+    shutil.copyfile(fileobj.name, path)
+    base_name = os.path.splitext(os.path.basename(fileobj))[0]
+    no_extension_path = f"/home/user/app/routers/{foldername}/{base_name}"
+    shutil.copyfile(fileobj, no_extension_path)
+    with open(no_extension_path, "a") as f:
+        f.write(prompt)
+    try:
+        prompt_file_path = no_extension_path
+        with open(prompt_file_path, "w") as prompt_file:
+            prompt_file.write(prompt)
+    except Exception as e:
+        return f"Error writing prompt to file: {str(e)}"
+    time.sleep(1)
+    try:
+        proc = subprocess.Popen(
+            ["make", "run", foldername],
+            stdin=subprocess.PIPE,
+            stdout=subprocess.PIPE,
+            stderr=subprocess.PIPE,
+            text=True,
+        )
+        stdout, stderr = proc.communicate(input="n\ny\ny\n")
+        return f"Processed Content:\n{stdout}\n\nMake Command Output:\n{stdout}\n\nMake Command Error:\n{stderr}"
+    except subprocess.CalledProcessError as e:
+        return f"Processed Content:\n{stdout}\n\nMake Command Error:\n{e.stderr}"
+

mysite/libs/utilities.py

@@ -8,6 +8,7 @@ import time
 from mysite.libs.logger import logger
 import async_timeout
 import asyncio
+import mysite.interpreter.interpreter_config 
 
 
 

routers/ai/prompt

@@ -1,10 +1 @@
-googleappsscript
-ラインの画像検索システム
-
-1,lineからデータがくる
-2,doPostで取得
-3.typeがイメージの場合はドライブに保存
-4,保存したデータをS3にアップロード
-5.データはシークレットから取得
-6,plantumlでフローの作成
-7,システムドキュメントの作成
+HTMLのサンプルを作成して

workspace/script.py

@@ -0,0 +1 @@
+print('Hello, World!')