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import gradio as gr |
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import requests |
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from g4f import Provider, models |
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from langchain.llms.base import LLM |
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from langchain_g4f import G4FLLM |
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url = "https://app.embedchain.ai/api/v1/pipelines/f14b3df8-db63-456c-8a7f-4323b4467271/context/" |
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def greet(name): |
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payload = { |
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"query": f"{name}", |
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"count": 5 |
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} |
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headers = { |
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'Authorization': 'Token ec-pbVFWamfNAciPwb18ZwaQkKKUCCBnafko9ydl3Y5', |
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} |
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response = requests.request("POST", url, headers=headers, json=payload) |
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print(name) |
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c = response.text |
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llm = LLM = G4FLLM( |
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model=models.gpt_35_turbo, |
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provider=Provider.Aichat, |
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) |
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res = llm(f"contexte:{c}. {name}") |
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print(res) |
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return res |
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iface = gr.Interface(fn=greet, inputs="text", outputs="text") |
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iface.launch() |