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.env

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+#.env
+
+# 🔐 Secure your model provider tokens here
+HUGGINGFACEHUB_API_TOKEN=your_huggingface_token_here
+OPENAI_API_KEY=your_openai_token_here
+ANTHROPIC_API_KEY=your_anthropic_token_here
+OLLAMA_API_KEY=your_ollama_token_here
+TOGETHER_API_KEY=your_together_token_here
+OPENROUTER_API_KEY=your_openrouter_token_here
+
+
+💡 You can use the python-dotenv package to auto-load these in Python via os.getenv().

.gitignore

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+text
+# Python
+__pycache__/
+*.py[cod]
+*.env
+env/
+venv/
+
+# Gradio Cache
+gradio_cached_examples/
+
+# VS Code
+.vscode/
+
+# Docker
+*.container

app.py

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+import gradio as gr
+import os
+import json
+import yaml
+from pathlib import Path
+from smolagents import (
+    CodeAgent, ToolCallingAgent, ManagedAgent,
+    InferenceClientModel, TransformersModel, LiteLLMModel,
+    OllamaModel, OpenAIModel, AnthropicModel,
+    TogetherModel, OpenRouterModel,
+    WebSearchTool, PythonTool, FileTool, ImageTool,
+    TerminalTool, FinalAnswerTool, UserInputTool,
+    LangChainTool, HFModelDownloadsTool
+)
+
+# 🎯 Tool and Model Mappings
+TOOL_MAP = {
+    "WebSearchTool": (WebSearchTool, "🔍 Search the internet"),
+    "PythonTool": (PythonTool, "🐍 Execute Python code"),
+    "FileTool": (FileTool, "📂 Read/write local files"),
+    "ImageTool": (ImageTool, "🖼️ Handle image input/output"),
+    "TerminalTool": (TerminalTool, "💻 Run shell commands"),
+    "FinalAnswerTool": (FinalAnswerTool, "✅ Finalize agent response"),
+    "UserInputTool": (UserInputTool, "👤 Interactive user input"),
+    "LangChainTool": (LangChainTool, "🔗 Wrap LangChain tools"),
+    "HFModelDownloadsTool": (HFModelDownloadsTool, "📊 Hugging Face stats")
+}
+
+MODEL_MAP = {
+    "Hugging Face API": (InferenceClientModel, "Use hosted HF models"),
+    "Transformers (local)": (TransformersModel, "Run local models"),
+    "LiteLLM": (LiteLLMModel, "Connect to LiteLLM"),
+    "OpenAI": (OpenAIModel, "Use OpenAI GPT models"),
+    "Anthropic": (AnthropicModel, "Access Claude via Anthropic"),
+    "Ollama": (OllamaModel, "Use local Ollama models"),
+    "Together.ai": (TogetherModel, "Use Together-hosted models"),
+    "OpenRouter": (OpenRouterModel, "Universal model router")
+}
+
+AGENT_TYPES = {
+    "CodeAgent": "Generates and runs Python code",
+    "ToolCallingAgent": "Uses structured tool calls",
+    "ManagedAgent": "Manages tool routing and sub-agents"
+}
+
+# ✏️ Helper: Generate Agent Code Preview
+def generate_code_preview(model_choice, tools_selected, agent_type, prompt):
+    model_cls_name = model_choice.replace(" ", "")
+    imports = f"from smolagents import {agent_type}, {model_cls_name}, {', '.join(tools_selected)}\nimport os"
+    setup = f'os.environ["HUGGINGFACEHUB_API_TOKEN"] = "your_token_here"'
+    model = f'model = {model_cls_name}(provider="{model_choice}", token=os.getenv("HUGGINGFACEHUB_API_TOKEN"))'
+    tools = f'tools = [{", ".join(tool + "()" for tool in tools_selected)}]'
+    agent = f'agent = {agent_type}(tools=tools, model=model, stream_outputs=True)'
+    run = f'result = agent.run("{prompt}")\nprint(result)'
+    return "\n".join([imports, setup, model, tools, agent, run])
+
+# 🚀 Main Execution Logic
+def run_agent(model_choice, token, tools_selected, agent_type, prompt):
+    os.environ["HUGGINGFACEHUB_API_TOKEN"] = token
+    model_cls = MODEL_MAP[model_choice][0]
+    model = model_cls(provider=model_choice, token=token)
+    tools = [TOOL_MAP[t][0]() for t in tools_selected]
+
+    if agent_type == "CodeAgent":
+        agent = CodeAgent(tools=tools, model=model, stream_outputs=True)
+    elif agent_type == "ToolCallingAgent":
+        agent = ToolCallingAgent(tools=tools, model=model)
+    else:
+        agent = ManagedAgent(tools=tools, model=model)
+
+    try:
+        result = agent.run(prompt)
+    except Exception as e:
+        result = f"⚠️ Agent Error: {e}"
+
+    code = generate_code_preview(model_choice, tools_selected, agent_type, prompt)
+    return result, code
+
+# 💾 Export Agent Setup
+def export_agent_config(model_choice, tools_selected, agent_type, prompt, format):
+    config = {
+        "model": model_choice,
+        "tools": tools_selected,
+        "agent_type": agent_type,
+        "prompt": prompt
+    }
+    path = Path(f"agent_config.{format}")
+    if format == "yaml":
+        path.write_text(yaml.dump(config, sort_keys=False))
+    elif format == "py":
+        code = generate_code_preview(model_choice, tools_selected, agent_type, prompt)
+        path.write_text(code)
+    else:
+        path.write_text(json.dumps(config, indent=2))
+    return f"✅ Exported to {path}"
+
+# 🧪 Gradio Interface
+with gr.Blocks(title="SmolAgent Studio IDE") as demo:
+    gr.Markdown("# 🛠️ SmolAgent Studio")
+    gr.Markdown("Build and deploy smart agents visually. Select tools, models, and prompts — with live code preview and export.")
+
+    with gr.Row():
+        model_dropdown = gr.Dropdown(list(MODEL_MAP.keys()), label="Model Provider", info="Choose LLM backend")
+        token_input = gr.Textbox(label="API Token", type="password", placeholder="Paste your token securely")
+
+    with gr.Row():
+        tool_selector = gr.CheckboxGroup(list(TOOL_MAP.keys()), label="Tools", info="Select tools for your agent")
+        agent_dropdown = gr.Dropdown(list(AGENT_TYPES.keys()), label="Agent Type", info="Select agent logic")
+
+    prompt_box = gr.Textbox(label="Prompt", lines=4, placeholder="Ask your agent something...")
+
+    code_view = gr.Code(label="Generated Python Code", language="python")
+    output_box = gr.Textbox(label="Agent Output")
+
+    with gr.Row():
+        run_button = gr.Button("🚀 Run Agent")
+        format_dropdown = gr.Dropdown(["json", "yaml", "py"], label="Export Format", value="json")
+        export_button = gr.Button("💾 Export Config")
+
+    run_button.click(
+        fn=run_agent,
+        inputs=[model_dropdown, token_input, tool_selector, agent_dropdown, prompt_box],
+        outputs=[output_box, code_view]
+    )
+
+    export_button.click(
+        fn=export_agent_config,
+        inputs=[model_dropdown, tool_selector, agent_dropdown, prompt_box, format_dropdown],
+        outputs=gr.Textbox(label="Export Status")
+    )
+
+demo.launch()

requirements.txt

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+#requirements.txt
+
+# 🧩 SmolAgent Studio dependencies
+smolagents>=0.1.21
+gradio>=4.0.0
+python-dotenv>=1.0.0
+
+#🧪 You can install with pip install -r requirements.txt

smolagent_studio_ide.py

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+import gradio as gr
+import os
+import json
+import yaml
+from pathlib import Path
+from smolagents import (
+    CodeAgent, ToolCallingAgent, ManagedAgent,
+    InferenceClientModel, TransformersModel, LiteLLMModel,
+    OllamaModel, OpenAIModel, AnthropicModel,
+    TogetherModel, OpenRouterModel,
+    WebSearchTool, PythonTool, FileTool, ImageTool,
+    TerminalTool, FinalAnswerTool, UserInputTool,
+    LangChainTool, HFModelDownloadsTool
+)
+
+# 🎯 Tool and Model Mappings
+TOOL_MAP = {
+    "WebSearchTool": (WebSearchTool, "🔍 Search the internet"),
+    "PythonTool": (PythonTool, "🐍 Execute Python code"),
+    "FileTool": (FileTool, "📂 Read/write local files"),
+    "ImageTool": (ImageTool, "🖼️ Handle image input/output"),
+    "TerminalTool": (TerminalTool, "💻 Run shell commands"),
+    "FinalAnswerTool": (FinalAnswerTool, "✅ Finalize agent response"),
+    "UserInputTool": (UserInputTool, "👤 Interactive user input"),
+    "LangChainTool": (LangChainTool, "🔗 Wrap LangChain tools"),
+    "HFModelDownloadsTool": (HFModelDownloadsTool, "📊 Hugging Face stats")
+}
+
+MODEL_MAP = {
+    "Hugging Face API": (InferenceClientModel, "Use hosted HF models"),
+    "Transformers (local)": (TransformersModel, "Run local models"),
+    "LiteLLM": (LiteLLMModel, "Connect to LiteLLM"),
+    "OpenAI": (OpenAIModel, "Use OpenAI GPT models"),
+    "Anthropic": (AnthropicModel, "Access Claude via Anthropic"),
+    "Ollama": (OllamaModel, "Use local Ollama models"),
+    "Together.ai": (TogetherModel, "Use Together-hosted models"),
+    "OpenRouter": (OpenRouterModel, "Universal model router")
+}
+
+AGENT_TYPES = {
+    "CodeAgent": "Generates and runs Python code",
+    "ToolCallingAgent": "Uses structured tool calls",
+    "ManagedAgent": "Manages tool routing and sub-agents"
+}
+
+# ✏️ Helper: Generate Agent Code Preview
+def generate_code_preview(model_choice, tools_selected, agent_type, prompt):
+    model_cls_name = model_choice.replace(" ", "")
+    imports = f"from smolagents import {agent_type}, {model_cls_name}, {', '.join(tools_selected)}\nimport os"
+    setup = f'os.environ["HUGGINGFACEHUB_API_TOKEN"] = "your_token_here"'
+    model = f'model = {model_cls_name}(provider="{model_choice}", token=os.getenv("HUGGINGFACEHUB_API_TOKEN"))'
+    tools = f'tools = [{", ".join(tool + "()" for tool in tools_selected)}]'
+    agent = f'agent = {agent_type}(tools=tools, model=model, stream_outputs=True)'
+    run = f'result = agent.run("{prompt}")\nprint(result)'
+    return "\n".join([imports, setup, model, tools, agent, run])
+
+# 🚀 Main Execution Logic
+def run_agent(model_choice, token, tools_selected, agent_type, prompt):
+    os.environ["HUGGINGFACEHUB_API_TOKEN"] = token
+    model_cls = MODEL_MAP[model_choice][0]
+    model = model_cls(provider=model_choice, token=token)
+    tools = [TOOL_MAP[t][0]() for t in tools_selected]
+
+    if agent_type == "CodeAgent":
+        agent = CodeAgent(tools=tools, model=model, stream_outputs=True)
+    elif agent_type == "ToolCallingAgent":
+        agent = ToolCallingAgent(tools=tools, model=model)
+    else:
+        agent = ManagedAgent(tools=tools, model=model)
+
+    try:
+        result = agent.run(prompt)
+    except Exception as e:
+        result = f"⚠️ Agent Error: {e}"
+
+    code = generate_code_preview(model_choice, tools_selected, agent_type, prompt)
+    return result, code
+
+# 💾 Export Agent Setup
+def export_agent_config(model_choice, tools_selected, agent_type, prompt, format):
+    config = {
+        "model": model_choice,
+        "tools": tools_selected,
+        "agent_type": agent_type,
+        "prompt": prompt
+    }
+    path = Path(f"agent_config.{format}")
+    if format == "yaml":
+        path.write_text(yaml.dump(config, sort_keys=False))
+    elif format == "py":
+        code = generate_code_preview(model_choice, tools_selected, agent_type, prompt)
+        path.write_text(code)
+    else:
+        path.write_text(json.dumps(config, indent=2))
+    return f"✅ Exported to {path}"
+
+# 🧪 Gradio Interface
+with gr.Blocks(title="SmolAgent Studio IDE") as demo:
+    gr.Markdown("# 🛠️ SmolAgent Studio")
+    gr.Markdown("Build and deploy smart agents visually. Select tools, models, and prompts — with live code preview and export.")
+
+    with gr.Row():
+        model_dropdown = gr.Dropdown(list(MODEL_MAP.keys()), label="Model Provider", info="Choose LLM backend")
+        token_input = gr.Textbox(label="API Token", type="password", placeholder="Paste your token securely")
+
+    with gr.Row():
+        tool_selector = gr.CheckboxGroup(list(TOOL_MAP.keys()), label="Tools", info="Select tools for your agent")
+        agent_dropdown = gr.Dropdown(list(AGENT_TYPES.keys()), label="Agent Type", info="Select agent logic")
+
+    prompt_box = gr.Textbox(label="Prompt", lines=4, placeholder="Ask your agent something...")
+
+    code_view = gr.Code(label="Generated Python Code", language="python")
+    output_box = gr.Textbox(label="Agent Output")
+
+    with gr.Row():
+        run_button = gr.Button("🚀 Run Agent")
+        format_dropdown = gr.Dropdown(["json", "yaml", "py"], label="Export Format", value="json")
+        export_button = gr.Button("💾 Export Config")
+
+    run_button.click(
+        fn=run_agent,
+        inputs=[model_dropdown, token_input, tool_selector, agent_dropdown, prompt_box],
+        outputs=[output_box, code_view]
+    )
+
+    export_button.click(
+        fn=export_agent_config,
+        inputs=[model_dropdown, tool_selector, agent_dropdown, prompt_box, format_dropdown],
+        outputs=gr.Textbox(label="Export Status")
+    )
+
+demo.launch()