mirror of
https://github.com/VinciGit00/Scrapegraph-ai.git
synced 2026-06-28 21:01:55 +08:00
128 lines
3.8 KiB
Python
128 lines
3.8 KiB
Python
"""
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GenerateAnswerFromImageNode Module
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"""
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import asyncio
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import base64
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from typing import List, Optional
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import aiohttp
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from .base_node import BaseNode
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class GenerateAnswerFromImageNode(BaseNode):
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"""
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GenerateAnswerFromImageNode analyzes images from the state dictionary using the OpenAI API
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and updates the state with the consolidated answers.
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"""
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def __init__(
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self,
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input: str,
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output: List[str],
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node_config: Optional[dict] = None,
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node_name: str = "GenerateAnswerFromImageNode",
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):
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super().__init__(node_name, "node", input, output, 2, node_config)
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async def process_image(self, session, api_key, image_data, user_prompt):
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"""
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async process image
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"""
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base64_image = base64.b64encode(image_data).decode("utf-8")
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headers = {
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"Content-Type": "application/json",
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"Authorization": f"Bearer {api_key}",
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}
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payload = {
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"model": self.node_config["config"]["llm"]["model"],
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"messages": [
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{
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"role": "user",
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"content": [
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{"type": "text", "text": user_prompt},
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{
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"type": "image_url",
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"image_url": {
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"url": f"data:image/jpeg;base64,{base64_image}"
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},
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},
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],
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}
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],
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"max_tokens": 300,
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}
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async with session.post(
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"https://api.openai.com/v1/chat/completions", headers=headers, json=payload
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) as response:
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result = await response.json()
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return (
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result.get("choices", [{}])[0]
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.get("message", {})
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.get("content", "No response")
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)
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async def execute_async(self, state: dict) -> dict:
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"""
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Processes images from the state, generates answers,
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consolidates the results, and updates the state asynchronously.
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"""
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self.logger.info(f"--- Executing {self.node_name} Node ---")
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images = state.get("screenshots", [])
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analyses = []
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supported_models = ("gpt-4o", "gpt-4o-mini", "gpt-4-turbo", "gpt-4")
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if (
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self.node_config["config"]["llm"]["model"].split("/")[-1]
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not in supported_models
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):
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raise ValueError(
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f"""The model provided
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is not supported. Supported models are:
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{", ".join(supported_models)}."""
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)
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api_key = self.node_config.get("config", {}).get("llm", {}).get("api_key", "")
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async with aiohttp.ClientSession() as session:
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tasks = [
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self.process_image(
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session,
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api_key,
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image_data,
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state.get("user_prompt", "Extract information from the image"),
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)
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for image_data in images
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]
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analyses = await asyncio.gather(*tasks)
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consolidated_analysis = " ".join(analyses)
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state["answer"] = {"consolidated_analysis": consolidated_analysis}
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return state
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def execute(self, state: dict) -> dict:
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"""
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Wrapper to run the asynchronous execute_async function in a synchronous context.
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"""
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try:
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eventloop = asyncio.get_event_loop()
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except RuntimeError:
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eventloop = None
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if eventloop and eventloop.is_running():
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task = eventloop.create_task(self.execute_async(state))
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state = eventloop.run_until_complete(asyncio.gather(task))[0]
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else:
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state = asyncio.run(self.execute_async(state))
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return state
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