Structured Outputs

from tinfoil import TinfoilAI
import os
import json

# Load environment variables
try:
    from dotenv import load_dotenv
    load_dotenv()
except ImportError:
    pass

# Initialize client (works with any chat model)
client = TinfoilAI(
    enclave="qwen2-5-72b.model.tinfoil.sh",
    repo="tinfoilsh/confidential-qwen2-5-72b",
    api_key=os.getenv("TINFOIL_API_KEY")
)

# Create a JSON schema prompt
schema_prompt = """
Extract contact information and return it as JSON with this exact structure:
{
    "name": "string (required)",
    "email": "string or null",
    "phone": "string or null",
    "company": "string or null"
}

Text to extract from: John Smith works at Acme Corp, his email is [email protected] and phone is +1-555-0123

Return only the JSON object:
"""

# Extract structured data
response = client.chat.completions.create(
    model="qwen2-5-72b",
    messages=[
        {"role": "user", "content": schema_prompt}
    ],
    temperature=0.1  # Lower temperature for more consistent formatting
)

# Parse the JSON response
contact_json = json.loads(response.choices[0].message.content)
print(f"Name: {contact_json['name']}")
print(f"Email: {contact_json.get('email')}")
print(f"Company: {contact_json.get('company')}")
print(f"Phone: {contact_json.get('phone')}")

# Create a detailed JSON schema prompt
company_prompt = """
Create a company profile and return it as JSON with this exact structure:
{
    "name": "string",
    "founded_year": integer,
    "employees": [
        {
            "name": "string",
            "age": integer,
            "email": "string or null",
            "addresses": [
                {
                    "street": "string",
                    "city": "string", 
                    "state": "string",
                    "zip_code": "string"
                }
            ],
            "is_employed": boolean
        }
    ],
    "headquarters": {
        "street": "string",
        "city": "string",
        "state": "string", 
        "zip_code": "string"
    }
}

Company details:
- Name: TechCorp
- Founded in 2020
- Headquarters: 123 Tech St, San Francisco, CA 94105
- Employees: Alice Johnson (age 30, [email protected], employed) and Bob Smith (age 25, no email, employed)
- Alice lives at 456 Oak Ave, Palo Alto, CA 94301

Return only the JSON object:
"""

# Initialize client for complex example
client = TinfoilAI(
    enclave="mistral-small-3-1-24b-p.model.tinfoil.sh",
    repo="tinfoilsh/confidential-mistral-small-3-1-24b-prod",
    api_key=os.getenv("TINFOIL_API_KEY")
)

# Extract complex structured data
response = client.chat.completions.create(
    model="mistral-small-3-1-24b",
    messages=[{"role": "user", "content": company_prompt}],
    temperature=0.1
)

company = json.loads(response.choices[0].message.content)
print(f"Company: {company['name']}")
print(f"Founded: {company['founded_year']}")
print(f"HQ: {company['headquarters']['city']}, {company['headquarters']['state']}")
print(f"Employees: {len(company['employees'])}")

# Create analysis prompt with schema
analysis_prompt = """
Analyze these product reviews and return a JSON analysis with this exact structure:
{
    "product_name": "string",
    "overall_rating": number,
    "reviews": [
        {
            "rating": integer (1-5),
            "sentiment": "positive" | "negative" | "neutral",
            "key_points": ["string", "string"],
            "would_recommend": boolean
        }
    ],
    "summary": "string"
}

Reviews for the "SuperPhone X":

Review 1: "Amazing phone! Great camera quality and fast performance. Battery lasts all day. Definitely recommend! 5 stars."

Review 2: "Phone is okay but overpriced. Camera is good but not revolutionary. Battery life is average. 3 stars."

Review 3: "Worst phone ever! Crashes constantly, terrible battery life, customer service is awful. Save your money! 1 star."

Return only the JSON object:
"""

# Initialize client for analysis example
client = TinfoilAI(
    enclave="llama3-3-70b-p.model.tinfoil.sh",
    repo="tinfoilsh/confidential-llama3-3-70b-prod",
    api_key=os.getenv("TINFOIL_API_KEY")
)

# Analyze product reviews
response = client.chat.completions.create(
    model="llama3-3-70b",
    messages=[{"role": "user", "content": analysis_prompt}],
    temperature=0.1
)

analysis = json.loads(response.choices[0].message.content)
print(f"Product: {analysis['product_name']}")
print(f"Overall Rating: {analysis['overall_rating']}/5")
print(f"Number of Reviews: {len(analysis['reviews'])}")
for i, review in enumerate(analysis['reviews'], 1):
    print(f"Review {i}: {review['rating']} stars, {review['sentiment']}")

import os
import json
from tinfoil import TinfoilAI

# Load environment variables
try:
    from dotenv import load_dotenv
    load_dotenv()
except ImportError:
    pass

try:
    client = TinfoilAI(
        enclave="qwen2-5-72b.model.tinfoil.sh",
        repo="tinfoilsh/confidential-qwen2-5-72b",
        api_key=os.getenv("TINFOIL_API_KEY")
    )
    
    schema_prompt = """
    Extract contact information and return it as JSON with this exact structure:
    {
        "name": "string (required)",
        "email": "string or null",
        "phone": "string or null",
        "company": "string or null"
    }
    
    Text: Extract data...
    
    Return only the JSON object:
    """
    
    response = client.chat.completions.create(
        model="qwen2-5-72b",
        messages=[{"role": "user", "content": schema_prompt}],
        temperature=0.1
    )
    
    # Try to parse JSON response
    try:
        contact = json.loads(response.choices[0].message.content)
        print(f"Successfully parsed: {contact['name']}")
        print(f"Email: {contact.get('email')}")
        print(f"Company: {contact.get('company')}")
    except json.JSONDecodeError:
        print("JSON parsing failed, raw response:")
        print(response.choices[0].message.content)
        
except Exception as e:
    print(f"Error: {e}")