AI-Powered Reply Generation¶

import asyncio
from xeepy.ai import ContentGenerator

async def generate_reply():
    ai = ContentGenerator(
        provider="openai",
        api_key="your-openai-api-key",
        model="gpt-4"
    )

    # Generate a reply to a tweet
    reply = await ai.generate_reply(
        tweet_text="Just launched my first Python package! 🎉",
        style="supportive"
    )

    print(f"Generated reply: {reply}")

asyncio.run(generate_reply())

from xeepy.ai import ContentGenerator

# OpenAI Configuration
openai_ai = ContentGenerator(
    provider="openai",
    api_key="sk-...",
    model="gpt-4-turbo"  # or gpt-3.5-turbo
)

# Anthropic (Claude) Configuration
anthropic_ai = ContentGenerator(
    provider="anthropic",
    api_key="sk-ant-...",
    model="claude-3-opus-20240229"  # or claude-3-sonnet
)

# Ollama (Local) Configuration
ollama_ai = ContentGenerator(
    provider="ollama",
    base_url="http://localhost:11434",
    model="llama2"  # or mistral, codellama
)

async def styled_replies():
    ai = ContentGenerator(provider="openai", api_key="...", model="gpt-4")

    tweet = "Struggling to learn machine learning. Any tips?"

    # Different style options
    styles = ["supportive", "professional", "witty", "educational", "casual"]

    for style in styles:
        reply = await ai.generate_reply(
            tweet_text=tweet,
            style=style,
            max_length=280
        )
        print(f"\n[{style.upper()}]: {reply}")

asyncio.run(styled_replies())

async def contextual_reply():
    ai = ContentGenerator(provider="openai", api_key="...", model="gpt-4")

    # Provide additional context for better replies
    reply = await ai.generate_reply(
        tweet_text="What's the best programming language for beginners?",
        style="educational",
        context={
            "your_expertise": "Python developer with 10 years experience",
            "brand_voice": "helpful, encouraging, practical",
            "target_audience": "coding beginners",
            "avoid_topics": ["language wars", "negative comparisons"]
        },
        max_length=280
    )

    print(f"Reply: {reply}")

asyncio.run(contextual_reply())

async def batch_replies():
    from xeepy import Xeepy
    from xeepy.ai import ContentGenerator

    async with Xeepy() as x:
        ai = ContentGenerator(provider="openai", api_key="...", model="gpt-4")

        # Get tweets to reply to
        mentions = await x.scrape.search("@yourusername", limit=20)

        replies = []
        for tweet in mentions:
            reply = await ai.generate_reply(
                tweet_text=tweet.text,
                style="professional",
                max_length=280
            )
            replies.append({
                "original_tweet": tweet.text,
                "author": tweet.author.username,
                "generated_reply": reply
            })
            print(f"@{tweet.author.username}: {reply[:50]}...")

        # Export for review before posting
        x.export.to_json(replies, "draft_replies.json")

asyncio.run(batch_replies())

async def generate_thread_reply():
    ai = ContentGenerator(provider="openai", api_key="...", model="gpt-4")

    # Generate reply with thread context
    reply = await ai.generate_reply(
        tweet_text="This is the 5th tweet in the thread",
        thread_context=[
            "First tweet introducing the topic",
            "Second tweet with more details",
            "Third tweet with examples",
            "Fourth tweet addressing concerns"
        ],
        style="educational",
        max_length=280
    )

    print(f"Thread-aware reply: {reply}")

asyncio.run(generate_thread_reply())

async def custom_prompt_reply():
    ai = ContentGenerator(provider="openai", api_key="...", model="gpt-4")

    # Use a completely custom prompt
    reply = await ai.generate_reply(
        tweet_text="What's your favorite productivity tool?",
        custom_prompt="""
        You are a tech productivity expert. Generate a reply that:
        1. Recommends one specific tool
        2. Gives a brief reason why
        3. Keeps it under 200 characters
        4. Ends with an engaging question

        Tweet to reply to: {tweet_text}
        """,
        max_length=280
    )

    print(f"Custom reply: {reply}")

asyncio.run(custom_prompt_reply())

async def quality_filtered_replies():
    ai = ContentGenerator(provider="openai", api_key="...", model="gpt-4")

    tweet = "Just shipped my first feature!"

    # Generate multiple options and score them
    options = []
    for _ in range(3):
        reply = await ai.generate_reply(
            tweet_text=tweet,
            style="supportive",
            temperature=0.8  # Higher variance
        )

        # Score the reply
        score = await ai.score_reply(
            original_tweet=tweet,
            reply=reply,
            criteria=["relevance", "engagement_potential", "brand_alignment"]
        )

        options.append({"reply": reply, "score": score})

    # Pick the best one
    best = max(options, key=lambda x: x["score"])
    print(f"Best reply (score {best['score']:.2f}): {best['reply']}")

asyncio.run(quality_filtered_replies())