Simple Gemini LLM

pip install cycls

import cycls

@cycls.app(pip=["google-genai"], copy=[".env"])
async def app(context):
    import os
    from google import genai

    # Convert messages to Gemini format
    contents = [
        {
            'role': 'model' if m['role'] == 'assistant' else 'user',
            'parts': [{'text': m['content']}]
        }
        for m in context.messages if m['role'] != 'system'
    ]

    # Initialize Gemini client
    client = genai.Client(api_key=os.getenv("GEMINI_API_KEY"))

    # Stream the response
    async for chunk in await client.aio.models.generate_content_stream(
        model="gemini-2.5-flash",
        contents=contents,
        config={'system_instruction': "You are a helpful AI assistant."}
    ):
        if chunk.text:
            yield chunk.text

app.local()

GEMINI_API_KEY=your_api_key_here

python app.py

import cycls

@cycls.app(pip=["google-genai"], copy=[".env"])
async def app(context):
    import os
    from google import genai

    # Convert messages to Gemini format
    contents = [
        {
            'role': 'model' if m['role'] == 'assistant' else 'user',
            'parts': [{'text': m['content']}]
        }
        for m in context.messages if m['role'] != 'system'
    ]

    # Initialize Gemini client
    client = genai.Client(api_key=os.getenv("GEMINI_API_KEY"))

    # Stream the response
    async for chunk in await client.aio.models.generate_content_stream(
        model="gemini-2.5-flash",
        contents=contents,
        config={'system_instruction': "You are a helpful AI assistant."}
    ):
        if chunk.text:
            yield chunk.text

app.local()

import cycls
import os

cycls.api_key = os.getenv("CYCLS_API_KEY")

@cycls.app(pip=["google-genai"], copy=[".env"])
async def app(context):
    from google import genai

    contents = [
        {
            'role': 'model' if m['role'] == 'assistant' else 'user',
            'parts': [{'text': m['content']}]
        }
        for m in context.messages if m['role'] != 'system'
    ]

    client = genai.Client(api_key=os.getenv("GEMINI_API_KEY"))

    async for chunk in await client.aio.models.generate_content_stream(
        model="gemini-2.5-flash",
        contents=contents,
        config={'system_instruction': "You are a helpful AI assistant."}
    ):
        if chunk.text:
            yield chunk.text

app.deploy()