import OpenAI from 'openai';

const client = new OpenAI({
  apiKey: process.env.OUTCRY_API_KEY,
  baseURL: 'https://api.outcryai.com/v1'
});

const session = await client.get('/chat/completions/chat_abc123');
console.log(session);

from openai import OpenAI
import os

client = OpenAI(
    api_key=os.environ.get("OUTCRY_API_KEY"),
    base_url="https://api.outcryai.com/v1"
)

session = client.get("/chat/completions/chat_abc123")
print(session)

curl https://api.outcryai.com/v1/chat/completions/chat_abc123 \
  -H "Authorization: Bearer oc_live_..."

async function continueConversation(sessionId: string, newMessage: string) {
  // Get existing session
  const session = await client.get(`/chat/completions/${sessionId}`);

  // Build messages array from history
  const messages = session.messages.map(m => ({
    role: m.role,
    content: m.content
  }));

  // Add new message
  messages.push({
    role: 'user',
    content: newMessage
  });

  // Create completion with full history
  const completion = await client.chat.completions.create({
    model: 'grok-2',
    messages
  });

  return completion.choices[0].message.content;
}

const response = await continueConversation(
  'chat_abc123',
  'Can you give me more examples?'
);

async def continue_conversation(session_id: str, new_message: str):
    # Get existing session
    session = client.get(f"/chat/completions/{session_id}")

    # Build messages array from history
    messages = [
        {"role": m["role"], "content": m["content"]}
        for m in session["messages"]
    ]

    # Add new message
    messages.append({
        "role": "user",
        "content": new_message
    })

    # Create completion with full history
    completion = client.chat.completions.create(
        model="grok-2",
        messages=messages
    )

    return completion.choices[0].message.content

response = await continue_conversation(
    "chat_abc123",
    "Can you give me more examples?"
)

async function exportConversationAsMarkdown(sessionId: string) {
  const session = await client.get(`/chat/completions/${sessionId}`);

  let markdown = `# Conversation ${sessionId}\n\n`;
  markdown += `**Created:** ${new Date(session.created_at * 1000).toISOString()}\n\n---\n\n`;

  for (const message of session.messages) {
    const role = message.role === 'user' ? '**You:**' : '**Assistant:**';
    markdown += `${role}\n\n${message.content}\n\n---\n\n`;
  }

  return markdown;
}

const markdown = await exportConversationAsMarkdown('chat_abc123');
console.log(markdown);

async def export_conversation_as_markdown(session_id: str):
    session = client.get(f"/chat/completions/{session_id}")

    markdown = f"# Conversation {session_id}\n\n"
    markdown += f"**Created:** {session['created_at']}\n\n---\n\n"

    for message in session["messages"]:
        role = "**You:**" if message["role"] == "user" else "**Assistant:**"
        markdown += f"{role}\n\n{message['content']}\n\n---\n\n"

    return markdown

markdown = await export_conversation_as_markdown("chat_abc123")
print(markdown)

async function analyzeConversation(sessionId: string) {
  const session = await client.get(`/chat/completions/${sessionId}`);

  const userMessages = session.messages.filter(m => m.role === 'user');
  const assistantMessages = session.messages.filter(m => m.role === 'assistant');

  const stats = {
    totalMessages: session.messages.length,
    userMessages: userMessages.length,
    assistantMessages: assistantMessages.length,
    avgMessageLength: session.messages.reduce(
      (sum, m) => sum + m.content.length, 0
    ) / session.messages.length,
    duration: session.messages[session.messages.length - 1].created_at - session.created_at
  };

  return stats;
}

const analysis = await analyzeConversation('chat_abc123');
console.log(analysis);

async def analyze_conversation(session_id: str):
    session = client.get(f"/chat/completions/{session_id}")

    user_messages = [m for m in session["messages"] if m["role"] == "user"]
    assistant_messages = [m for m in session["messages"] if m["role"] == "assistant"]

    stats = {
        "total_messages": len(session["messages"]),
        "user_messages": len(user_messages),
        "assistant_messages": len(assistant_messages),
        "avg_message_length": sum(len(m["content"]) for m in session["messages"]) / len(session["messages"]),
        "duration": session["messages"][-1]["created_at"] - session["created_at"]
    }

    return stats

analysis = await analyze_conversation("chat_abc123")
print(analysis)