FROM promptengineers-ai:ryaneggz/6-update-local TO development

.example.env

@@ -0,0 +1 @@
+JUPYTER_TOKEN=

.gitignore

@@ -2,4 +2,7 @@ uploads
 downloads
 toolkilt/.venv/
 toolkilt/__pycache__/
-toolkilt/tools/__pycache__/
+toolkilt/tools/__pycache__/
+**/notebooks/
+**/.env*
+**/__pycache__/

Dockerfile

@@ -6,9 +6,10 @@ RUN pip install fastapi uvicorn python-multipart
 
 # Copy the API script to the root directory
 COPY api.py /home/jovyan/api.py
+COPY README.md /home/jovyan/README.md
 
 # Expose port 8888 for the Jupyter Notebook
 EXPOSE 8888
 
 # Expose an additional port for the FastAPI server
-EXPOSE 8000
+EXPOSE 8100

Makefile

@@ -0,0 +1,10 @@
+.PHONY: build run test
+
+build:
+	docker build --push -t ghcr.io/enso-labs/interpreter:latest .
+
+docker_run:
+	docker run -d --name interpreter ghcr.io/enso-labs/interpreter:latest
+
+test:
+	python -m unittest discover

README.md

@@ -12,17 +12,20 @@ Unlock the potential of executing Python code safely and efficiently with the Pr
 Our sandbox is designed with security as a top priority. By isolating execution environments, we mitigate risks associated with running untrusted code. This makes it an ideal solution for developers and organizations who need a safe and controlled way to execute scripts, test code snippets, or provide coding functionalities within their applications.
 
 Key Features:
-- 🛡️ **Secure Execution:** Run Python code in a sandboxed environment to ensure the applications remains secure and unaffected.
-- 📁 **File Management:** Upload and manage files within isolated sessions to maintain data integrity and security.
-- 📦 **Package Installation:** Install required Python packages per session without affecting the global environment.
-- 🕹️ **Session Management:** Efficiently create, manage, and terminate sessions to maintain clean and organized execution spaces.
+
+-   🛡️ **Secure Execution:** Run Python code in a sandboxed environment to ensure the applications remains secure and unaffected.
+-   📁 **File Management:** Upload and manage files within isolated sessions to maintain data integrity and security.
+-   📦 **Package Installation:** Install required Python packages per session without affecting the global environment.
+-   🕹️ **Session Management:** Efficiently create, manage, and terminate sessions to maintain clean and organized execution spaces.
 
 ### Start Interpreter
+
 ```bash
 docker-compose up --build
 ```
 
 ### Test the Langchain Toolkit
+
 ```bash
 ## Change Directory
 cd toolkit
@@ -43,7 +46,7 @@ python interpreter.py
 Simple Example
 
 ```bash
-curl -X POST http://localhost:8001/execute -H "Content-Type: application/json" -d '{
+curl -X POST http://localhost:8100/execute -H "Content-Type: application/json" -d '{
   "session_id": "your_session_id",
   "code": "print(\"Hello from Interpreter!\")"
 }'
@@ -55,7 +58,7 @@ curl -X POST http://localhost:8001/execute -H "Content-Type: application/json" -
 Example curl Request (Verify will error when numpy is not installed):
 
 ```bash
-curl -X POST http://localhost:8001/execute -H "Content-Type: application/json" -d '{
+curl -X POST http://localhost:8100/execute -H "Content-Type: application/json" -d '{
   "session_id": "your_session_id",
   "code": "import os\nimport numpy as np\na = int(os.getenv(\"VAR_A\"))\nb = int(os.getenv(\"VAR_B\"))\nc = int(os.getenv(\"VAR_C\"))\narray = np.array([a, b, c])\nresult = np.sum(array)\nprint(f\"Result of summing [{a}, {b}, {c}] is: {result}\")",
   "env": {
@@ -72,7 +75,7 @@ curl -X POST http://localhost:8001/execute -H "Content-Type: application/json" -
 Example curl Request (Install numpy and execute the code):
 
 ```bash
-curl -X POST http://localhost:8001/install -H "Content-Type: application/json" -d '{
+curl -X POST http://localhost:8100/install -H "Content-Type: application/json" -d '{
   "session_id": "your_session_id",
   "packages": ["numpy"]
 }'
@@ -84,7 +87,7 @@ curl -X POST http://localhost:8001/install -H "Content-Type: application/json" -
 Execute numpy with Env vars
 
 ```bash
-curl -X POST http://localhost:8001/execute -H "Content-Type: application/json" -d '{
+curl -X POST http://localhost:8100/execute -H "Content-Type: application/json" -d '{
   "session_id": "your_session_id",
   "code": "import os\nimport numpy as np\na = int(os.getenv(\"VAR_A\"))\nb = int(os.getenv(\"VAR_B\"))\nc = int(os.getenv(\"VAR_C\"))\narray = np.array([a, b, c])\nresult = np.sum(array)\nprint(f\"Result of summing [{a}, {b}, {c}] is: {result}\")",
   "env": {
@@ -101,14 +104,14 @@ curl -X POST http://localhost:8001/execute -H "Content-Type: application/json" -
 Example curl Request (Verify numpy has been uninstalled):
 
 ```bash
-curl -X POST http://localhost:8001/terminate -H "Content-Type: application/json" -d '{
+curl -X POST http://localhost:8100/terminate -H "Content-Type: application/json" -d '{
   "session_id": "your_session_id"
 }'
 
 ## Result
 # {"status":"success","message":"Session your_session_id terminated successfully."}
 
-curl -X POST http://localhost:8001/execute -H "Content-Type: application/json" -d '{
+curl -X POST http://localhost:8100/execute -H "Content-Type: application/json" -d '{
   "session_id": "your_session_id",
   "code": "import os\nimport numpy as np\na = int(os.getenv(\"VAR_A\"))\nb = int(os.getenv(\"VAR_B\"))\nc = int(os.getenv(\"VAR_C\"))\narray = np.array([a, b, c])\nresult = np.sum(array)\nprint(f\"Result of summing [{a}, {b}, {c}] is: {result}\")",
   "env": {
@@ -127,7 +130,7 @@ curl -X POST http://localhost:8001/execute -H "Content-Type: application/json" -
 Upload a file for a specific session.
 
 ```bash
-curl -X POST "http://localhost:8001/upload" \
+curl -X POST "http://localhost:8100/upload" \
   -H "accept: application/json" \
   -F "session_id=your_session_id" \
   -F "file=@data/AAPL.csv"
@@ -139,7 +142,7 @@ curl -X POST "http://localhost:8001/upload" \
 Install pandas pacakage for created session to interact with csv.
 
 ```bash
-curl -X POST http://localhost:8001/install -H "Content-Type: application/json" -d '{
+curl -X POST http://localhost:8100/install -H "Content-Type: application/json" -d '{
   "session_id": "your_session_id",
   "packages": ["pandas"]
 }'
@@ -151,7 +154,7 @@ curl -X POST http://localhost:8001/install -H "Content-Type: application/json" -
 Execute to interact with csv
 
 ```bash
-curl -X POST http://localhost:8001/execute -H "Content-Type: application/json" -d '{
+curl -X POST http://localhost:8100/execute -H "Content-Type: application/json" -d '{
   "session_id": "your_session_id",
   "code": "import pandas as pd\nfile_path = \"/tmp/your_session_id/AAPL.csv\"\ndf = pd.read_csv(file_path)\nfirst_row = df.iloc[0]\nprint(first_row.to_json())"
 }'
@@ -163,7 +166,7 @@ curl -X POST http://localhost:8001/execute -H "Content-Type: application/json" -
 Download file from session
 
 ```bash
-curl -X GET "http://localhost:8001/download?session_id=your_session_id&filename=AAPL.csv" -o AAPL_downloaded.csv
+curl -X GET "http://localhost:8100/download?session_id=your_session_id&filename=AAPL.csv" -o AAPL_downloaded.csv
 
 ## Result
 # File downloaded to workspace
@@ -172,10 +175,21 @@ curl -X GET "http://localhost:8001/download?session_id=your_session_id&filename=
 Terminate session to uninstall pacakges and remove files.
 
 ```bash
-curl -X POST http://localhost:8001/terminate -H "Content-Type: application/json" -d '{
+curl -X POST http://localhost:8100/terminate -H "Content-Type: application/json" -d '{
   "session_id": "your_session_id"
 }'
 
 ## Result
 # {"status":"success","message":"Session your_session_id terminated successfully."}
-```
+```
+
+```bash
+docker run -d \
+  --name jupyter \
+  --restart always \
+  --env-file .env.jupyter \
+  -p 8888:8888 \
+  -v "$PWD/notebooks:/home/jovyan/work" \
+  -v jupyter_data:/home/jovyan/.jupyter \
+  jupyter/base-notebook:latest
+```

api.py

@@ -6,7 +6,7 @@
 import shutil
 from typing import List, Dict
 
-app = FastAPI()
+app = FastAPI(name="Enso Labs Interpreter", docs_url="/")
 
 class CodeExecutionRequest(BaseModel):
     session_id: str
@@ -141,4 +141,4 @@ def download_file(session_id: str, filename: str):
 
 if __name__ == '__main__':
     import uvicorn
-    uvicorn.run(app, host="0.0.0.0", port=8000)
+    uvicorn.run(app, host=os.getenv("HOST", "0.0.0.0"), port=int(os.getenv("PORT", 8100)))

docker-compose.yml

@@ -1,17 +1,17 @@
-version: '3'
-
 services:
   interpreter:
     container_name: interpreter
-    image: promptengineers/interpreter:latest
+    # image: ghcr.io/enso-labs/interpreter:latest
     build: .
     restart: always
     ports:
       - "8888:8888"
-      - "8001:8000"
+      - "8100:8100"
     environment:
       - JUPYTER_ENABLE_LAB=yes
+      - JUPYTER_TOKEN=${JUPYTER_TOKEN}
       - PYTHONPATH=/home/jovyan
-    entrypoint: ["sh", "-c", "start-notebook.sh --NotebookApp.token='' & uvicorn api:app --host 0.0.0.0 --port 8000"]
+    entrypoint: ["sh", "-c", "start-notebook.sh --NotebookApp.token=${JUPYTER_TOKEN} & uvicorn api:app --host 0.0.0.0 --port 8100"]
     volumes:
       - ./uploads:/tmp
+      - ./notebooks:/home/jovyan/.ipynb_checkpoints

toolkit/interpreter.py

@@ -1,28 +1,30 @@
+import os
 from typing import List
+from pydantic import Field
 
 from langchain_core.tools import BaseToolkit
-from langchain_core.pydantic_v1 import Field
-from langchain_community.tools import BaseTool
+from langchain_community.tools import StructuredTool
 
 from tools import Interpreter
 
 class InterpreterToolkit(BaseToolkit):
-    """Toolkit for the interpreter."""
+	"""Toolkit for the interpreter."""
 
-    api_url: str = Field(default="http://localhost:8001")
+	api_url: str = Field(default=os.getenv("INTERPRETER_URL", "http://localhost:8100"))
 
-    class Config:
-        """Pydantic config."""
-        arbitrary_types_allowed = True
+	class Config:
+		"""Pydantic config."""
+		arbitrary_types_allowed = True
 
-    def get_tools(self) -> List[BaseTool]:
-        """Get the tools in the toolkit."""
-        toolkit = Interpreter(api_url=self.api_url).toolkit()
-        return toolkit
+	def get_tools(self) -> List[StructuredTool]:
+		"""Get the tools in the toolkit."""
+		toolkit = Interpreter(api_url=self.api_url).toolkit()
+		return toolkit
 
 if __name__ == "__main__":
-	toolkit = InterpreterToolkit(api_url="http://localhost:8001")
+	toolkit = InterpreterToolkit(api_url=os.getenv("INTERPRETER_URL", "http://localhost:8100"))
 	tools = toolkit.get_tools()
 	result = tools[0].run({"session_id": "test", "code": "print('Hello, World!')"})
 	print(">>> Tools: ", tools)
+	print("\n\n")
 	print(">>> Result: ", result)

toolkit/tools/__init__.py

@@ -1,8 +1,10 @@
+import os
 import httpx
 import logging
 from typing import List
+from pydantic import BaseModel, Field
+
 from langchain.tools import StructuredTool
-from langchain_core.pydantic_v1 import BaseModel, Field
 from langchain_core.tools import ToolException
 
 ########################################################
@@ -32,7 +34,7 @@ class DownloadSchema(BaseModel):
 ## Class
 ########################################################
 class Interpreter:
-    def __init__(self, api_url: str = "http://localhost:8000"):
+    def __init__(self, api_url: str = os.getenv("INTERPRETER_URL", "http://localhost:8100")):
         self.api_url = api_url
 
     def install(self, session_id: str, packages: List[str]):
@@ -256,8 +258,5 @@ def toolkit(self) -> List[StructuredTool]:
 ## Test
 ########################################################
 if __name__ == "__main__":
-    result = Interpreter(api_url="http://localhost:8001").execute().run({
-        "session_id": "test",
-        "code": "print('Hello, World!')"
-    })
+    result = Interpreter().execute(session_id="test", code="print('Hello, World!')")
     print(result)