parent
399099ef67
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9c3a292938
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from swarms.structs import Flow
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from swarms.models.gpt4_vision_api import GPT4VisionAPI
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llm = GPT4VisionAPI()
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task = "What is the color of the object?"
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img = "images/swarms.jpeg"
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## Initialize the workflow
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flow = Flow(
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llm=llm,
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max_loops='auto',
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dashboard=True,
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)
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flow.run(task=task, img=img)
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@ -1,33 +0,0 @@
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from swarms.structs import Flow
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from swarms.models import Idefics
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# Multi Modality Auto Agent
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llm = Idefics(max_length=2000)
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task = (
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"User: What is in this image?"
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" https://upload.wikimedia.org/wikipedia/commons/8/86/Id%C3%A9fix.JPG"
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)
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## Initialize the workflow
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flow = Flow(
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llm=llm,
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max_loops=2,
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dashboard=True,
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# stopping_condition=None, # You can define a stopping condition as needed.
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# loop_interval=1,
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# retry_attempts=3,
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# retry_interval=1,
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# interactive=False, # Set to 'True' for interactive mode.
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# dynamic_temperature=False, # Set to 'True' for dynamic temperature handling.
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)
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# out = flow.load_state("flow_state.json")
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# temp = flow.dynamic_temperature()
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# filter = flow.add_response_filter("Trump")
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out = flow.run(task)
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# out = flow.validate_response(out)
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# out = flow.analyze_feedback(out)
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# out = flow.print_history_and_memory()
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# # out = flow.save_state("flow_state.json")
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# print(out)
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@ -0,0 +1,127 @@
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import base64
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import os
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import requests
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from dotenv import load_dotenv
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# Load environment variables
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load_dotenv()
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openai_api_key = os.getenv("OPENAI_API_KEY")
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class GPT4VisionAPI:
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"""
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GPT-4 Vision API
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This class is a wrapper for the OpenAI API. It is used to run the GPT-4 Vision model.
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Parameters
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----------
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openai_api_key : str
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The OpenAI API key. Defaults to the OPENAI_API_KEY environment variable.
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Methods
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-------
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encode_image(img: str)
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Encode image to base64.
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run(task: str, img: str)
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Run the model.
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__call__(task: str, img: str)
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Run the model.
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Examples:
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---------
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>>> from swarms.models import GPT4VisionAPI
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>>> llm = GPT4VisionAPI()
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>>> task = "What is the color of the object?"
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>>> img = "https://i.imgur.com/2M2ZGwC.jpeg"
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>>> llm.run(task, img)
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"""
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def __init__(
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self,
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openai_api_key: str = openai_api_key
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):
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super().__init__()
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self.openai_api_key = openai_api_key
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def encode_image(self, img: str):
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"""Encode image to base64."""
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with open(img, "rb") as image_file:
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return base64.b64encode(image_file.read()).decode("utf-8")
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# Function to handle vision tasks
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def run(self, task: str, img: str):
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"""Run the model."""
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try:
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base64_image = self.encode_image(img)
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headers = {
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"Content-Type": "application/json",
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"Authorization": f"Bearer {openai_api_key}",
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}
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payload = {
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"model": "gpt-4-vision-preview",
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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": task},
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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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response = requests.post(
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"https://api.openai.com/v1/chat/completions",
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headers=headers,
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json=payload,
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)
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out = response.json()
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out = out["choices"][0]["text"]
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except Exception as error:
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print(f"Error with the request: {error}")
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raise error
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# Function to handle vision tasks
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def __call__(self, task: str, img: str):
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"""Run the model."""
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try:
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base64_image = self.encode_image(img)
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headers = {
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"Content-Type": "application/json",
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"Authorization": f"Bearer {openai_api_key}",
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}
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payload = {
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"model": "gpt-4-vision-preview",
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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": task},
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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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response = requests.post(
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"https://api.openai.com/v1/chat/completions",
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headers=headers,
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json=payload,
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)
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return response.json()
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except Exception as error:
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print(f"Error with the request: {error}")
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raise error
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