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44 lines
1.3 KiB
44 lines
1.3 KiB
from swarms.models import OpenAI
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from swarms.structs import Flow
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from langchain.schema.messages import ChatMessage, BaseMessage
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import os
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from dotenv import load_dotenv
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load_dotenv()
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message: BaseMessage = [ ChatMessage(role="user", content='Translate the following English text to French: Hello World"') ]
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api_key = os.environ.get("OPENAI_API_KEY")
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# Initialize the language model, this model can be swapped out with Anthropic, ETC, Huggingface Models like Mistral, ETC
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llm = OpenAI(
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# model_name="gpt-4"
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openai_api_key=api_key,
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temperature=0.5,
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# max_tokens=100,
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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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# tools = [search_api, slack, ]
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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(message)
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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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