Feat/integration examples

examples/README.md

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+# Gradient Python SDK Examples
+
+This directory contains examples demonstrating how to use the Gradient Python SDK with various frameworks and for different use cases.
+
+## Available Examples
+
+### Framework Integrations
+
+These examples show how to integrate the Gradient Python SDK with popular web frameworks:
+
+- **[Django Integration](django_integration.py)** - Simple Django views for chat completions, image generation, and agent listing
+- **[Flask Integration](flask_integration.py)** - Flask routes demonstrating SDK usage with proper error handling
+- **[FastAPI Integration](fastapi_integration.py)** - FastAPI endpoints with Pydantic models and async support
+
+## Running Examples
+
+Each example is a standalone Python script that can be run directly:
+
+```bash
+# Make sure you have the required environment variables set
+export DIGITALOCEAN_ACCESS_TOKEN="your_token_here"
+export GRADIENT_MODEL_ACCESS_KEY="your_model_key_here"
+export GRADIENT_AGENT_ACCESS_KEY="your_agent_key_here"
+export GRADIENT_AGENT_ENDPOINT="https://your-agent.agents.do-ai.run"
+
+# Run an example
+python examples/django_integration.py
+```
+
+## Framework-Specific Setup
+
+### Django
+The Django example shows how to create a Django view that uses the Gradient SDK for AI-powered responses.
+
+### Flask
+The Flask example demonstrates integrating Gradient SDK with Flask routes for web applications.
+
+### FastAPI
+The FastAPI example shows how to create async endpoints that leverage the Gradient SDK's async capabilities.
+
+## Environment Variables
+
+All examples require proper authentication setup:
+
+- `DIGITALOCEAN_ACCESS_TOKEN` - For DigitalOcean API operations
+- `GRADIENT_MODEL_ACCESS_KEY` - For serverless inference
+- `GRADIENT_AGENT_ACCESS_KEY` - For agent-specific operations
+- `GRADIENT_AGENT_ENDPOINT` - Your deployed agent endpoint
+
+## Contributing
+
+When adding new examples:
+
+1. Follow the existing naming convention
+2. Include comprehensive comments
+3. Handle errors appropriately
+4. Use environment variables for configuration
+5. Add the example to this README

examples/django_integration.py

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+#!/usr/bin/env python3
+"""
+Django Integration Example for Gradient Python SDK
+
+This example demonstrates how to integrate the Gradient Python SDK
+with a Django application to create AI-powered endpoints.
+
+Requirements:
+- Django
+- gradient (this SDK)
+
+Setup:
+1. Install dependencies: pip install django gradient
+2. Set environment variables (see below)
+3. Run: python manage.py runserver
+
+Environment Variables Required:
+- DIGITALOCEAN_ACCESS_TOKEN
+- GRADIENT_MODEL_ACCESS_KEY
+"""
+
+import os
+import json
+from typing import Dict, Any
+
+# Django imports
+from django.http import JsonResponse
+from django.views.decorators.csrf import csrf_exempt
+from django.views.decorators.http import require_http_methods
+
+# Gradient SDK imports
+from gradient import Gradient
+
+# Initialize Gradient client
+gradient_client = Gradient(
+    access_token=os.getenv("DIGITALOCEAN_ACCESS_TOKEN"),
+    model_access_key=os.getenv("GRADIENT_MODEL_ACCESS_KEY"),
+)
+
+
+@csrf_exempt
+@require_http_methods(["POST"])
+def chat_completion(request) -> JsonResponse:
+    """
+    Django view for chat completions using Gradient SDK.
+
+    Expects JSON payload:
+    {
+        "messages": [{"role": "user", "content": "Hello!"}],
+        "model": "llama3.3-70b-instruct"
+    }
+    """
+    try:
+        data: Dict[str, Any] = json.loads(request.body)
+        messages = data.get("messages", [])
+        model = data.get("model", "llama3.3-70b-instruct")
+
+        if not messages:
+            return JsonResponse({"error": "Messages are required"}, status=400)
+
+        response = gradient_client.chat.completions.create(
+            messages=messages,
+            model=model,
+        )
+
+        return JsonResponse({
+            "response": response.choices[0].message.content,
+            "model": response.model,
+        })
+
+    except json.JSONDecodeError:
+        return JsonResponse({"error": "Invalid JSON payload"}, status=400)
+    except Exception as e:
+        return JsonResponse({"error": str(e)}, status=500)
+
+
+@csrf_exempt
+@require_http_methods(["POST"])
+def image_generation(request) -> JsonResponse:
+    """
+    Django view for image generation using Gradient SDK.
+
+    Expects JSON payload:
+    {
+        "prompt": "A beautiful sunset over mountains"
+    }
+    """
+    try:
+        data: Dict[str, Any] = json.loads(request.body)
+        prompt = data.get("prompt")
+
+        if not prompt:
+            return JsonResponse({"error": "Prompt is required"}, status=400)
+
+        response = gradient_client.images.generate(prompt=prompt)
+
+        return JsonResponse({
+            "image_url": response.data[0].url,
+        })
+
+    except json.JSONDecodeError:
+        return JsonResponse({"error": "Invalid JSON payload"}, status=400)
+    except Exception as e:
+        return JsonResponse({"error": str(e)}, status=500)
+
+
+@require_http_methods(["GET"])
+def list_agents(request) -> JsonResponse:
+    """
+    Django view to list available agents.
+
+    Query parameters:
+    - limit: Maximum number of agents to return (default: 10)
+    """
+    try:
+        limit = int(request.GET.get("limit", 10))
+
+        response = gradient_client.agents.list(limit=limit)
+
+        return JsonResponse({
+            "agents": [
+                {
+                    "uuid": agent.uuid,
+                    "name": agent.name,
+                }
+                for agent in response.agents
+            ]
+        })
+
+    except Exception as e:
+        return JsonResponse({"error": str(e)}, status=500)
+
+
+# URL patterns for Django
+"""
+# In your Django urls.py:
+
+from django.urls import path
+from . import views
+
+urlpatterns = [
+    path('api/chat/', views.chat_completion, name='chat_completion'),
+    path('api/images/generate/', views.image_generation, name='image_generation'),
+    path('api/agents/', views.list_agents, name='list_agents'),
+]
+
+# Example usage:
+# POST /api/chat/ with {"messages": [{"role": "user", "content": "Hello!"}]}
+# POST /api/images/generate/ with {"prompt": "A sunset"}
+# GET /api/agents/
+"""

examples/fastapi_integration.py

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+#!/usr/bin/env python3
+"""
+FastAPI Integration Example for Gradient Python SDK
+
+This example demonstrates how to integrate the Gradient Python SDK
+with a FastAPI application to create AI-powered endpoints.
+
+Requirements:
+- fastapi
+- uvicorn
+- gradient (this SDK)
+
+Setup:
+1. Install dependencies: pip install fastapi uvicorn gradient
+2. Set environment variables (see below)
+3. Run: python fastapi_integration.py
+
+Environment Variables Required:
+- DIGITALOCEAN_ACCESS_TOKEN
+- GRADIENT_MODEL_ACCESS_KEY
+"""
+
+import os
+from typing import List, Dict, Any
+from fastapi import FastAPI, HTTPException
+from pydantic import BaseModel
+
+# Gradient SDK imports
+from gradient import Gradient
+
+app = FastAPI(title="Gradient AI API", version="1.0.0")
+
+# Initialize Gradient client
+gradient_client = Gradient(
+    access_token=os.getenv("DIGITALOCEAN_ACCESS_TOKEN"),
+    model_access_key=os.getenv("GRADIENT_MODEL_ACCESS_KEY"),
+)
+
+
+class ChatMessage(BaseModel):
+    role: str
+    content: str
+
+
+class ChatRequest(BaseModel):
+    messages: List[ChatMessage]
+    model: str = "llama3.3-70b-instruct"
+
+
+class ImageRequest(BaseModel):
+    prompt: str
+
+
+@app.post("/api/chat")
+async def chat_completion(request: ChatRequest):
+    """
+    FastAPI endpoint for chat completions using Gradient SDK.
+    """
+    try:
+        messages = [{"role": msg.role, "content": msg.content} for msg in request.messages]
+
+        response = gradient_client.chat.completions.create(
+            messages=messages,
+            model=request.model,
+        )
+
+        return {
+            "response": response.choices[0].message.content,
+            "model": response.model,
+        }
+
+    except Exception as e:
+        raise HTTPException(status_code=500, detail=str(e))
+
+
+@app.post("/api/images/generate")
+async def image_generation(request: ImageRequest):
+    """
+    FastAPI endpoint for image generation using Gradient SDK.
+    """
+    try:
+        response = gradient_client.images.generate(prompt=request.prompt)
+
+        return {
+            "image_url": response.data[0].url,
+        }
+
+    except Exception as e:
+        raise HTTPException(status_code=500, detail=str(e))
+
+
+@app.get("/api/agents")
+async def list_agents(limit: int = 10):
+    """
+    FastAPI endpoint to list available agents.
+    """
+    try:
+        response = gradient_client.agents.list(limit=limit)
+
+        return {
+            "agents": [
+                {
+                    "uuid": agent.uuid,
+                    "name": agent.name,
+                }
+                for agent in response.agents
+            ]
+        }
+
+    except Exception as e:
+        raise HTTPException(status_code=500, detail=str(e))
+
+
+if __name__ == "__main__":
+    import uvicorn
+    uvicorn.run(app, host="0.0.0.0", port=8000)