Quickstart

Get started with the Bizora API in under 5 minutes.

Prerequisites

• API key from https://webapp-dev.bizora.ai
• Python 3.7+ or Node.js 14+ (for SDK usage)

Step 1: Get Your API Key

1. Log in to https://webapp-dev.bizora.ai
2. Navigate to API Keys section
3. Click Create API Key
4. Copy and save your key securely

Step 2: Install SDK (Optional)

Python

pip install openai

JavaScript/TypeScript

npm install openai
# or
yarn add openai

Step 3: Make Your First Request

Ask a tax question and get streaming responses in real-time:

PythonJavaScriptcURL

import openai

# Initialize client with your API key
client = openai.OpenAI(
  api_key="sk_live_YOUR_API_KEY",
  base_url="https://integration-api-cf.damp-bar-d133.workers.dev/v2"
)

# Ask a tax question with streaming
stream = client.chat.completions.create(
  model="bizora-1.0",
  messages=[{"role": "human", "content": "What is section 179?"}],
  stream=True
)

# Print the answer as it arrives
for chunk in stream:
  if chunk.choices and chunk.choices[0].delta.content:
      print(chunk.choices[0].delta.content, end="", flush=True)

Step 4: Enable Streaming

Get responses in real-time as they're generated:

PythonJavaScriptcURL

# Add stream=True to get responses in real-time
stream = client.chat.completions.create(
  model="bizora-1.0",
  messages=[{"role": "human", "content": "What is section 179?"}],
  stream=True
)

# Print each chunk as it arrives
for chunk in stream:
  if chunk.choices and chunk.choices[0].delta.content:
      print(chunk.choices[0].delta.content, end="", flush=True)

Step 5: Handle Custom Messages

When streaming, the API sends additional information like research steps, sources, and suggestions:

PythonJavaScript

# Stream responses and get custom messages
stream = client.chat.completions.create(
  model="bizora-1.0",
  messages=[{"role": "human", "content": "What is section 179?"}],
  stream=True
)

for chunk in stream:
  # AI content - the actual answer
  if chunk.choices and chunk.choices[0].delta.content:
      print(chunk.choices[0].delta.content, end="", flush=True)
  
  # Custom messages - steps, sources, suggestions
  elif hasattr(chunk, 'custom_data'):
      msg_type = chunk.custom_data.get('type')
      
      if msg_type == 'step_message':
          # Shows what the AI is doing
          print(f"\n🔄 {chunk.custom_data.get('title')}")
      
      elif msg_type == 'source_message':
          # Shows which documents were referenced
          sources = chunk.custom_data.get('content', [])
          print(f"\n📚 {len(sources)} sources found")
      
      elif msg_type == 'suggestions':
          # Follow-up question suggestions
          suggestions = chunk.custom_data.get('suggestions', [])
          print(f"\n💡 {len(suggestions)} suggested questions")

Common Parameters

Parameter	Type	Required	Description
model	string	Yes	Must be "bizora-1.0"
messages	array	Yes	Array of message objects
stream	boolean	No	Enable streaming (default: false)
webSearch	boolean	No	Enable web search mode (default: false)

Multi-Turn Conversations

Build context by including previous messages. Use "human" for user messages and "ai" for AI responses:

PythonJavaScript

# Include conversation history for context
messages = [
  {"role": "human", "content": "What is section 179?"},
  {"role": "ai", "content": "Section 179 allows businesses to deduct the full purchase price of qualifying equipment..."},
  {"role": "human", "content": "What are the dollar limits?"}
]

response = client.chat.completions.create(
  model="bizora-1.0",
  messages=messages
)

print(response.choices[0].message.content)

Next Steps

• MCP Server - Use Bizora with MCP-compatible clients
• Chat Completions API - Complete API documentation with streaming examples
• Error Handling - Handle errors properly
• Rate Limits - Understand rate limits

Need Help?

• Security Bugs: admin@bizora.ai
• Dashboard: https://webapp-dev.bizora.ai