更新

.gitignore

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+.venv/

README.md

@@ -1,10 +1,10 @@
 ---
-title: Summarize
-emoji: 🏢
-colorFrom: purple
-colorTo: purple
+title: Summarize Your Webpage Api
+emoji: 🐨
+colorFrom: green
+colorTo: indigo
 sdk: gradio
-sdk_version: 3.40.1
+sdk_version: 3.35.2
 app_file: app.py
 pinned: false
 ---

app.py

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+import gradio
+import os
+
+from langchain.chains.question_answering import load_qa_chain
+from langchain.document_loaders import UnstructuredURLLoader
+from langchain import HuggingFaceHub
+
+os.environ["HUGGINGFACEHUB_API_TOKEN"] = "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"
+
+llm = HuggingFaceHub(repo_id="declare-lab/flan-alpaca-large", model_kwargs={"temperature":0.1, "max_length":512})
+
+os.environ["LANGCHAIN_TRACING_V2"] = "true"
+os.environ["LANGCHAIN_ENDPOINT"] = "https://api.smith.langchain.com"
+os.environ["LANGCHAIN_API_KEY"] = "ls__ae9b316f4ee9475b84f66c616344d713"
+os.environ["LANGCHAIN_PROJECT"] = "Sequential-Chain"
+
+def main():
+
+    gradio_interface = gradio.Interface(
+    fn = my_inference_function,
+    inputs = "text",
+    outputs = "text")
+
+    gradio_interface.launch()
+
+
+def my_inference_function(url):
+  loader = UnstructuredURLLoader(urls=[url])
+  data = loader.load()
+  chain = load_qa_chain(llm=llm, chain_type="stuff")
+  response = chain.run(input_documents=data, question="Summarize this article in a paragraph and provide a name and link")
+  return response
+
+if __name__ == '__main__':
+    main()

requirements.txt

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+langchain
+huggingface_hub
+unstructured
+gradio