【Hackathon + No.224】 + 提交作品

.gitignore

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+*egg-info
+**/*/__pycache__
+**/.vscode
+**/.pdm.toml
+**/.venv
+**/pdm.lock

README.md

@@ -1 +1,12 @@
 # 极纳 x 百度飞桨黑客马拉松
+
+## 实现
+
+1. [src/uie](./src/uie/) Jina 的 UIE Executor & Flow 实现、功能测试、可视化页面
+
+![](https://user-images.githubusercontent.com/53158137/221882155-05a23b18-2007-4321-a0bb-961eebe7439b.png)
+![](https://user-images.githubusercontent.com/53158137/221882528-14070e16-4829-4552-ad7e-88fe78ea1e23.png)
+
+2. [src/plato-mini](./src/plato-mini/) Jina 的 Plato-Mini Executor & Flow 实现、功能测试
+
+![](https://user-images.githubusercontent.com/53158137/221911101-f6f053a9-6c78-40da-ba36-3be1c49cce3c.png)

rfcs/plato-mini.md

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+# Jina X Plato
+
+实现一个 requests 以 schema 为参数，对输入的 DocArray 进行提取 history 对话信息
+
+flows 中定义服务如下：
+
+| 协议名称  | 端口号 |
+| --------- | ------ |
+| grpc      | 12344  |
+| http      | 12345  |
+| websocket | 12346  |
+
+## 测试
+
+1. 运行服务端
+
+```
+pdm start
+```
+
+2. 运行客户端
+
+```
+pdm test
+```
+
+即可进行对话

src/plato-mini/README.md

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+## Jina X plato-mini
+
+## GetStart
+
+please install pdm first: `pip install pdm` (Pdm is a modern Python package and
+dependency manager supporting the latest PEP standards. )
+
+after that:
+
+```
+pdm prepare
+```
+
+this commond can auto install dependencies in virtual env
+
+then:
+
+```
+pdm start
+```
+
+this commond starts a jina flow server
+
+then:
+
+```
+pdm test
+```
+
+this commond starts a chat with plato-mini:
+
+```
+=====================Test calling=====================
+Test http: 你好,你是做什么的?
+Test grpc: 你好,你是做什么工作的?
+Test websocket: 你好,你是哪里人啊?
+======================Plato chat======================
+我: hi
+Plato:  你好,你是做什么的?
+我:
+```

src/plato-mini/pyproject.toml

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+[tool.pdm]
+
+[project]
+name = "jina-paddle-hackathon-PlatoXL"
+version = "0.1.0"
+description = ""
+authors = [
+    {name = "", email = "gonorth@qq.com"},
+]
+dependencies = [
+    "jina>=3.14.1",
+    "paddlepaddle>=2.4.2",
+    "paddlenlp>=2.5.1",
+    "autopep8>=2.0.1",
+    "pip>=23.0.1",
+]
+requires-python = ">=3.10"
+readme = "README.md"
+license = {text = "MIT"}
+
+[tool.pdm.scripts]
+dev = ""
+start = "python src/flow.py"
+test = "python src/main.py"
+create_venv = "pdm venv create 3.10"
+activate_venv = "pdm venv activate in-project"
+prepare = {composite = ["create_venv", "activate_venv", "pdm install"]}

src/plato-mini/src/flow.py

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+from jina import Flow
+from plato_executor.executor import PlatoXLExecutor
+
+f = Flow(port=[12345, 12344, 12346], protocol=["http", "grpc", "websocket"], cors=True).add(
+    name='uie', uses=PlatoXLExecutor)
+
+with f:
+    f.block()

src/plato-mini/src/main.py

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+from jina import Client, Document, DocumentArray
+
+ppmap = {
+    "http": 12345,
+    "grpc": 12344,
+    "websocket": 12346
+}
+
+print("=====================Test calling=====================")
+
+for protocol in ppmap:
+    c = Client(port=ppmap[protocol], protocol=protocol)
+    response_docs = c.post(on='/', inputs=DocumentArray(
+        [Document(text='你好！')]))
+    print(f"Test {protocol}:", response_docs[0].text)
+
+print("======================Plato chat======================")
+
+docs = DocumentArray([])
+while True:
+    docs.append(Document(text=input("我: ")))
+    response_docs = c.post(on='/', inputs=docs)
+    docs.append(response_docs[0])
+    print("Plato: ", response_docs[0].text)

src/plato-mini/src/plato_executor/config.yml

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+jtype: PlatoXLExecutor
+py_modules:
+  - executor.py
+metas:
+  name: PlatoXLExecutor
+  description: Paddle Plato-Mini Executor
+  url: https://github.com/jina-ai/jina-paddle-hackathon
+  keywords: ['nlp', 'plato-mini', 'chatbot']

src/plato-mini/src/plato_executor/executor.py

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+from paddlenlp.transformers import (UnifiedTransformerLMHeadModel,
+                                    UnifiedTransformerTokenizer)
+from typing import List, Dict, Any
+from jina import Executor, requests, DocumentArray, Document, Deployment
+from typing import List, Dict
+
+import paddle
+
+paddle.set_default_dtype("float32")
+if paddle.device.cuda.device_count() > 0:
+    paddle.device.set_device("cuda:0")
+
+
+class PlatoXLExecutor(Executor):
+    def __init__(self,  **kwargs):
+        super().__init__(**kwargs)
+        self.tokenizer = UnifiedTransformerTokenizer.from_pretrained(
+            'plato-mini')
+        self.model = UnifiedTransformerLMHeadModel.from_pretrained(
+            'plato-mini')
+
+    @requests
+    async def dialog_predict(
+        self,
+        docs: List[Document],
+        parameters: Dict[str, Any], **kwargs
+    ) -> str:
+        history = [doc.text for doc in docs]
+        output_ids, score = self.model.generate(
+            **self.tokenizer.dialogue_encode(
+                history,
+                add_start_token_as_response=True,
+                return_tensors=True,
+                is_split_into_words=False
+            ),
+            **parameters,
+        )
+
+        token_ids = output_ids.numpy()[0]
+
+        eos_pos = len(token_ids)
+        for i, tok_id in enumerate(token_ids):
+            if tok_id == self.tokenizer.sep_token_id:
+                eos_pos = i
+                break
+        token_ids = token_ids[:eos_pos]
+        tokens = self.tokenizer.convert_ids_to_tokens(token_ids)
+        tokens = self.tokenizer.merge_subword(tokens)
+
+        return DocumentArray([Document(text=''.join(tokens))])
+
+
+if __name__ == "__main__":
+    with Deployment(uses=PlatoXLExecutor) as dep:
+        response_docs = dep.post(
+            on='/', inputs=DocumentArray([Document(text='你好！')]))
+        print(f'Text: {response_docs[0].text}')