First commit

app.py

@@ -0,0 +1,95 @@
+from typing import Callable, Optional
+
+import gradio as gr
+from langchain.embeddings.openai import OpenAIEmbeddings
+from langchain.vectorstores import Zilliz
+from langchain.document_loaders import WebBaseLoader
+from langchain.text_splitter import CharacterTextSplitter
+from langchain.chains import RetrievalQAWithSourcesChain
+from langchain.llms import OpenAI
+
+chain: Optional[Callable] = None
+
+
+def web_loader(url_list, openai_key, zilliz_uri, user, password):
+    if not url_list:
+        return "please enter url list"
+    loader = WebBaseLoader(url_list.split())
+    docs = loader.load()
+
+    text_splitter = CharacterTextSplitter(chunk_size=1024, chunk_overlap=0)
+    docs = text_splitter.split_documents(docs)
+    embeddings = OpenAIEmbeddings(model="ada", openai_api_key=openai_key)
+
+    docsearch = Zilliz.from_documents(
+        docs,
+        embedding=embeddings,
+        connection_args={
+            "uri": zilliz_uri,
+            "user": user,
+            "password": password,
+            "secure": True,
+        },
+    )
+
+    global chain
+    chain = RetrievalQAWithSourcesChain.from_chain_type(
+        OpenAI(temperature=0, openai_api_key=openai_key),
+        chain_type="map_reduce",
+        retriever=docsearch.as_retriever(),
+    )
+    return "success to load data"
+
+
+def query(question):
+    global chain
+    # "What is milvus?"
+    if not chain:
+        return "please load the data first"
+    return chain(inputs={"question": question}, return_only_outputs=True).get(
+        "answer", "fail to get answer"
+    )
+
+
+if __name__ == "__main__":
+    block = gr.Blocks()
+    with block as demo:
+        gr.Markdown("<h1><center>Langchain And Zilliz Cloud Demo</center></h1>")
+        url_list_text = gr.Textbox(
+            label="Url list",
+            lines=3,
+        )
+        openai_key_text = gr.Textbox(label="openai api key")
+        with gr.Row():
+            zilliz_uri_text = gr.Textbox(label="zilliz cloud uri")
+            user_text = gr.Textbox(label="user")
+            password_text = gr.Textbox(label="password", type="password")
+        loader_output = gr.Textbox(label="Load Status")
+        loader_btn = gr.Button("WebLoader")
+        loader_btn.click(
+            fn=web_loader,
+            inputs=[
+                url_list_text,
+                openai_key_text,
+                zilliz_uri_text,
+                user_text,
+                password_text,
+            ],
+            outputs=loader_output,
+            api_name="web_load",
+        )
+
+        question_text = gr.Textbox(
+            label="question",
+            lines=3,
+        )
+        query_output = gr.Textbox(label="question answer", lines=3)
+        query_btn = gr.Button("Generate")
+        query_btn.click(
+            fn=query,
+            inputs=[question_text],
+            outputs=query_output,
+            api_name="generate_answer",
+        )
+
+        demo.queue().launch(server_name="0.0.0.0", share=False)

requirements.txt

@@ -0,0 +1,6 @@
+pymilvus
+langchain
+openai
+tiktoken
+gradio
+bs4