Remove LangChain

.env.azure.example

@@ -0,0 +1,31 @@
+# Azure OpenAI Configuration for Jupyter AI Agents
+# 
+# Copy this file to .env and fill in your values:
+#   cp .env.azure.example .env
+#
+# Then load it:
+#   source .env
+#
+# Or use direnv:
+#   direnv allow
+
+# Azure OpenAI API Key (required)
+export AZURE_OPENAI_API_KEY="your-api-key-here"
+
+# Azure OpenAI Endpoint - Base URL only (required)
+# Format: https://your-resource-name.openai.azure.com
+# Do NOT include /openai/deployments/... or query parameters
+export AZURE_OPENAI_ENDPOINT="https://your-resource-name.openai.azure.com"
+
+# Azure OpenAI API Version (optional, defaults to latest)
+# Use the version that matches your deployment
+export AZURE_OPENAI_API_VERSION="2024-08-01-preview"
+
+# Example deployment names you might use with --model-name:
+# - gpt-4o-mini
+# - gpt-4o
+# - gpt-35-turbo
+# - Your custom deployment names
+
+# Test your configuration:
+#   python -c "import os; print('API Key:', 'SET' if os.getenv('AZURE_OPENAI_API_KEY') else 'NOT SET'); print('Endpoint:', os.getenv('AZURE_OPENAI_ENDPOINT')); print('Version:', os.getenv('AZURE_OPENAI_API_VERSION', 'default'))"

.yarnrc.yml

@@ -1,4 +1,4 @@
-# Copyright (c) Datalayer, Inc. https://datalayer.io
+# Copyright (c) Datalayer, Inc. https://datalayer.ai
 # Distributed under the terms of the Datalayer License.
 
 enableImmutableInstalls: false

Makefile

@@ -42,22 +42,35 @@ example-fastapi: ## example-fastapi server
 	@exec echo
 	python -m uvicorn jupyter_ai_agents.examples.fastapi.main:main --reload --port 4400
 
-jupyter-ai-agents-prompt:
-	jupyter-ai-agents prompt \
+repl:
+	jupyter-ai-agents repl \
 		--url http://localhost:8888 \
 		--token MY_TOKEN \
-		--model-provider azure-openai \
-		--model-name gpt-4o-mini \
+		--model azure-openai:gpt-4o-mini
+
+# Note: For Azure OpenAI, ensure these environment variables are set:
+# - AZURE_OPENAI_API_KEY
+# - AZURE_OPENAI_ENDPOINT (base URL, e.g., https://your-resource.openai.azure.com)
+# - AZURE_OPENAI_API_VERSION (optional, defaults to latest)
+# Adjust --max-requests based on your Azure tier (CLI default: 4; lower if you hit rate limits)
+prompt:
+	jupyter-ai-agents prompt \
+		--verbose \
+		--mcp-servers http://localhost:8888/mcp \
+		--model anthropic:claude-sonnet-4-20250514 \
 		--path notebook.ipynb \
+		--max-requests 20 \
+		--max-tool-calls 10 \
 		--input "Create a matplotlib example"
 
-jupyter-ai-agents-explain-error:
+explain-error:
 	jupyter-ai-agents explain-error \
-		--url http://localhost:8888 \
-		--token MY_TOKEN \
-		--model-provider azure-openai \
-		--model-name gpt-4o-mini \
-		--path notebook.ipynb
+		--verbose \
+		--mcp-servers http://localhost:8888/mcp \
+		--model anthropic:claude-sonnet-4-20250514 \
+		--path notebook.ipynb \
+		--max-requests 20 \
+		--max-tool-calls 10
 
 publish-pypi: # publish the pypi package
 	git clean -fdx && \

README.md

@@ -4,7 +4,7 @@
   ~ BSD 3-Clause License
 -->
 
-[![Datalayer](https://assets.datalayer.tech/datalayer-25.svg)](https://datalayer.io)
+[![Datalayer](https://assets.datalayer.tech/datalayer-25.svg)](https://datalayer.ai)
 
 [![Become a Sponsor](https://img.shields.io/static/v1?label=Become%20a%20Sponsor&message=%E2%9D%A4&logo=GitHub&style=flat&color=1ABC9C)](https://github.com/sponsors/datalayer)
 
@@ -75,7 +75,6 @@ You can also use Jupyter AI Agents through the command line interface for automa
 
 ![Jupyter AI Agents CLI](https://assets.datalayer.tech/jupyter-ai-agent/ai-agent-prompt-demo-terminal.gif)
 
-
 ### Basic Installation
 
 To install Jupyter AI Agents, run the following command:
@@ -110,7 +109,7 @@ pip install datalayer_pycrdt==0.12.17
 ```
 ### Examples
 
-We put here a quick example for a Out-Kernel Stateless Agent via CLI helping your JupyterLab session.
+Jupyter AI Agents provides CLI commands to help your JupyterLab session using **Pydantic AI agents** with **Model Context Protocol (MCP)** for tool integration.
 
 Start JupyterLab, setting a `port` and a `token` to be reused by the agent, and create a notebook `notebook.ipynb`.
 
@@ -121,49 +120,186 @@ jupyter lab --port 8888 --IdentityProvider.token MY_TOKEN
 
 Jupyter AI Agents supports multiple AI model providers (more information can be found on [this documentation page](https://jupyter-ai-agents.datalayer.tech/docs/models)).
 
-The following takes you through an example with the Azure OpenAI provider. Read the [Azure Documentation](https://learn.microsoft.com/en-us/azure/ai-services/openai) to get the needed credentials and make sure you define them in the following `.env` file.
+### API Keys Configuration
+
+Set the appropriate API key for your chosen provider:
+
+**OpenAI:**
+```bash
+export OPENAI_API_KEY='your-api-key-here'
+```
+
+**Anthropic:**
+```bash
+export ANTHROPIC_API_KEY='your-api-key-here'
+```
+
+**Azure OpenAI:**
+```bash
+export AZURE_OPENAI_API_KEY='your-api-key-here'
+export AZURE_OPENAI_ENDPOINT='https://your-resource.openai.azure.com'
+export AZURE_OPENAI_API_VERSION='2024-08-01-preview'  # optional
+```
+
+**Important for Azure OpenAI:** 
+- The `AZURE_OPENAI_ENDPOINT` should be just the base URL (e.g., `https://your-resource.openai.azure.com`)
+- Do NOT include `/openai/deployments/...` or query parameters in the endpoint
+- The deployment name is specified via the `--model-name` parameter
+- See `.env.azure.example` for a complete configuration template
 
+**Other providers:**
 ```bash
-cat << EOF >>.env
-OPENAI_API_VERSION="..."
-AZURE_OPENAI_ENDPOINT="..."
-AZURE_OPENAI_API_KEY="..."
-EOF
+export GOOGLE_API_KEY='your-api-key-here'        # For Google/Gemini
+export COHERE_API_KEY='your-api-key-here'        # For Cohere
+export GROQ_API_KEY='your-api-key-here'          # For Groq
+export MISTRAL_API_KEY='your-api-key-here'       # For Mistral
+# AWS credentials for Bedrock
+export AWS_ACCESS_KEY_ID='your-key'
+export AWS_SECRET_ACCESS_KEY='your-secret'
+export AWS_REGION='us-east-1'
 ```
 
-**Prompt Agent**
+### Model Specification
+
+You can specify the model in two ways:
+
+1. **Using `--model` with full string** (recommended):
+   ```bash
+   --model "openai:gpt-4o"
+   --model "anthropic:claude-sonnet-4-0"
+   --model "azure-openai:deployment-name"
+   ```
+
+2. **Using `--model-provider` and `--model-name`**:
+   ```bash
+   --model-provider openai --model-name gpt-4o
+   --model-provider anthropic --model-name claude-sonnet-4-0
+   ```
+
+Supported providers: `openai`, `anthropic`, `azure-openai`, `github-copilot`, `google`, `bedrock`, `groq`, `mistral`, `cohere`
+
+### Prompt Agent
 
-To use the Jupyter AI Agents, an easy way is to launch a CLI (update the Azure deployment name based on your setup).
+Create and execute code based on user instructions:
 
 ```bash
-# Prompt agent example.
-# make jupyter-ai-agents-prompt
+# Using full model string (recommended)
 jupyter-ai-agents prompt \
   --url http://localhost:8888 \
   --token MY_TOKEN \
-  --model-provider azure-openai \
-  --model-name gpt-4o-mini \
+  --model "anthropic:claude-sonnet-4-0" \
   --path notebook.ipynb \
   --input "Create a matplotlib example"
+
+# Using provider and model name
+jupyter-ai-agents prompt \
+  --url http://localhost:8888 \
+  --token MY_TOKEN \
+  --model-provider anthropic \
+  --model-name claude-sonnet-4-0 \
+  --path notebook.ipynb \
+  --input "Create a pandas dataframe with sample data and plot it"
 ```
 
-![Jupyter AI Agents](https://assets.datalayer.tech/jupyter-ai-agent/ai-agent-prompt-demo-terminal.gif)
+![Jupyter AI Agents - Prompt](https://assets.datalayer.tech/jupyter-ai-agent/ai-agent-prompt-demo-terminal.gif)
+
+### Explain Error Agent
 
-**Explain Error Agent**
+Analyze and fix notebook errors:
 
 ```bash
-# Explain Error agent example.
-# make jupyter-ai-agents-explain-error
 jupyter-ai-agents explain-error \
   --url http://localhost:8888 \
   --token MY_TOKEN \
-  --model-provider azure-openai \
-  --model-name gpt-4o-mini \
-  --path notebook.ipynb
+  --model "anthropic:claude-sonnet-4-0" \
+  --path notebook.ipynb \
+  --current-cell-index 5
+```
+
+![Jupyter AI Agents - Explain Error](https://assets.datalayer.tech/jupyter-ai-agent/ai-agent-explainerror-demo-terminal.gif)
+
+### REPL Mode (Interactive)
+
+For an interactive experience with direct access to all Jupyter MCP tools, use the REPL mode:
+
+```bash
+jupyter-ai-agents repl \
+  --url http://localhost:8888 \
+  --token MY_TOKEN \
+  --model "anthropic:claude-sonnet-4-0"
 ```
 
-![Jupyter AI Agents](https://assets.datalayer.tech/jupyter-ai-agent/ai-agent-explainerror-demo-terminal.gif)
+In REPL mode, you can directly ask the AI to:
+- List notebooks in directories
+- Read and analyze notebook contents
+- Execute code in cells
+- Insert new cells
+- Modify existing cells
+- Install Python packages
+
+Example REPL interactions:
+
+```
+> List all notebooks in the current directory
+> Create a new notebook called analysis.ipynb
+> In analysis.ipynb, create a cell that imports pandas and loads data.csv
+> Execute the cell and show me the first 5 rows
+> Add a matplotlib plot showing the distribution of the 'age' column
+```
+
+The REPL provides special commands:
+- `/exit`: Exit the session
+- `/markdown`: Show last response in markdown format
+- `/multiline`: Toggle multiline input mode (use Ctrl+D to submit)
+- `/cp`: Copy last response to clipboard
+
+You can also use a custom system prompt:
+
+```bash
+jupyter-ai-agents repl \
+  --url http://localhost:8888 \
+  --token MY_TOKEN \
+  --model "anthropic:claude-sonnet-4-0" \
+  --system-prompt "You are a data science expert specializing in pandas and matplotlib."
+```
+
+### Prompt Agent
+
+Create and execute code based on user instructions:
+
+```bash
+# Using full model string (recommended)
+jupyter-ai-agents prompt \
+  --url http://localhost:8888 \
+  --token MY_TOKEN \
+  --model "anthropic:claude-sonnet-4-0" \
+  --path notebook.ipynb \
+  --input "Create a matplotlib example"
+
+# Using provider and model name
+jupyter-ai-agents prompt \
+  --url http://localhost:8888 \
+  --token MY_TOKEN \
+  --model-provider anthropic \
+  --model-name claude-sonnet-4-0 \
+  --path notebook.ipynb \
+  --input "Create a pandas dataframe with sample data and plot it"
+```
+
+### Explain Error Agent
+
+Analyze and fix notebook errors:
+
+```bash
+jupyter-ai-agents explain-error \
+  --url http://localhost:8888 \
+  --token MY_TOKEN \
+  --model "anthropic:claude-sonnet-4-0" \
+  --path notebook.ipynb \
+  --current-cell-index 5
+```
 
+## Uninstall
 
 ### About the Technology
 

dev/README.md

@@ -4,6 +4,6 @@
   ~ BSD 3-Clause License
 -->
 
-[![Datalayer](https://assets.datalayer.tech/datalayer-25.svg)](https://datalayer.io)
+[![Datalayer](https://assets.datalayer.tech/datalayer-25.svg)](https://datalayer.ai)
 
 [![Become a Sponsor](https://img.shields.io/static/v1?label=Become%20a%20Sponsor&message=%E2%9D%A4&logo=GitHub&style=flat&color=1ABC9C)](https://github.com/sponsors/datalayer)

dev/content/README.md

@@ -4,6 +4,6 @@
   ~ BSD 3-Clause License
 -->
 
-[![Datalayer](https://assets.datalayer.tech/datalayer-25.svg)](https://datalayer.io)
+[![Datalayer](https://assets.datalayer.tech/datalayer-25.svg)](https://datalayer.ai)
 
 [![Become a Sponsor](https://img.shields.io/static/v1?label=Become%20a%20Sponsor&message=%E2%9D%A4&logo=GitHub&style=flat&color=1ABC9C)](https://github.com/sponsors/datalayer)

dev/content/notebook.ipynb

@@ -3,15 +3,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "a582b625-e712-4581-b611-3def5f40bd59",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "84ca6269-06aa-42c3-815c-292980f031c0",
+   "id": "6e785ae0-34d9-462e-aa9a-22d7b40e15d8",
    "metadata": {},
    "outputs": [],
    "source": []

docs/.yarnrc.yml

@@ -1,4 +1,4 @@
-# Copyright (c) Datalayer, Inc. https://datalayer.io
+# Copyright (c) Datalayer, Inc. https://datalayer.ai
 # Distributed under the terms of the MIT License.
 
 enableImmutableInstalls: false

docs/Makefile

@@ -1,4 +1,4 @@
-# Copyright (c) Datalayer, Inc. https://datalayer.io
+# Copyright (c) Datalayer, Inc. https://datalayer.ai
 # Distributed under the terms of the MIT License.
 
 SHELL=/bin/bash