search

parthsarthi03 / raptor

The official implementation of RAPTOR: Recursive Abstractive Processing for Tree-Organized Retrieval
https://arxiv.org/abs/2401.18059
MIT License
687 stars 98 forks source link

Is it not possible to use in AZURE? #25

Open sonnydfa opened 3 months ago

sonnydfa commented 3 months ago

I tried with the following configuration, but it doesn't work.

os.environ["OPENAI_API_TYPE"] = "azure" os.environ["OPENAI_API_BASE"] = "https://proxy url" os.environ["OPENAI_API_KEY"] = "key" os.environ["OPENAI_API_VERSION"] = "version"

Traceback (most recent call last): File "c:\GPT\raptor\raptor-39\lib\site-packages\httpx_transports\default.py", line 69, in map_httpcore_exceptions yield File "c:\GPT\raptor\raptor-39\lib\site-packages\httpx_transports\default.py", line 233, in handle_request resp = self._pool.handle_request(req) File "c:\GPT\raptor\raptor-39\lib\site-packages\httpcore_sync\connection_pool.py", line 216, in handle_request raise exc from None File "c:\GPT\raptor\raptor-39\lib\site-packages\httpcore_sync\connection_pool.py", line 196, in handle_request response = connection.handle_request( File "c:\GPT\raptor\raptor-39\lib\site-packages\httpcore_sync\connection.py", line 99, in handle_request raise exc File "c:\GPT\raptor\raptor-39\lib\site-packages\httpcore_sync\connection.py", line 76, in handle_request stream = self._connect(request) File "c:\GPT\raptor\raptor-39\lib\site-packages\httpcore_sync\connection.py", line 154, in _connect stream = stream.start_tls(**kwargs) File "c:\GPT\raptor\raptor-39\lib\site-packages\httpcore_backends\sync.py", line 168, in start_tls raise exc File "C:\Users\10021782\AppData\Local\Programs\Python\Python39\lib\contextlib.py", line 135, in exit self.gen.throw(type, value, traceback) File "c:\GPT\raptor\raptor-39\lib\site-packages\httpcore_exceptions.py", line 14, in map_exceptions raise to_exc(exc) from exc httpcore.ConnectError: [SSL: CERTIFICATE_VERIFY_FAILED] certificate verify failed: self signed certificate in certificate chain (_ssl.c:1123)

The above exception was the direct cause of the following exception:

Traceback (most recent call last): File "c:\GPT\raptor\raptor-39\lib\site-packages\openai_base_client.py", line 858, in _request response = self._client.send(request, auth=self.custom_auth, stream=stream) File "c:\GPT\raptor\raptor-39\lib\site-packages\httpx_client.py", line 914, in send response = self._send_handling_auth( File "c:\GPT\raptor\raptor-39\lib\site-packages\httpx_client.py", line 942, in _send_handling_auth response = self._send_handling_redirects( File "c:\GPT\raptor\raptor-39\lib\site-packages\httpx_client.py", line 979, in _send_handling_redirects response = self._send_single_request(request) File "c:\GPT\raptor\raptor-39\lib\site-packages\httpx_client.py", line 1015, in _send_single_request response = transport.handle_request(request) File "c:\GPT\raptor\raptor-39\lib\site-packages\httpx_transports\default.py", line 233, in handle_request resp = self._pool.handle_request(req) File "C:\Users\10021782\AppData\Local\Programs\Python\Python39\lib\contextlib.py", line 135, in exit self.gen.throw(type, value, traceback) File "c:\GPT\raptor\raptor-39\lib\site-packages\httpx_transports\default.py", line 86, in map_httpcore_exceptions raise mapped_exc(message) from exc httpx.ConnectError: [SSL: CERTIFICATE_VERIFY_FAILED] certificate verify failed: self signed certificate in certificate chain (_ssl.c:1123)

The above exception was the direct cause of the following exception:

Traceback (most recent call last): File "c:\GPT\raptor\raptor-39\lib\site-packages\tenacity__init.py", line 382, in call__ result = fn(*args, **kwargs) File "c:\GPT\raptor\raptor-39\raptor\EmbeddingModels.py", line 26, in create_embedding self.client.embeddings.create(input=[text], model=self.model) File "c:\GPT\raptor\raptor-39\lib\site-packages\openai\resources\embeddings.py", line 105, in create return self._post( File "c:\GPT\raptor\raptor-39\lib\site-packages\openai_base_client.py", line 1055, in post return cast(ResponseT, self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)) File "c:\GPT\raptor\raptor-39\lib\site-packages\openai_base_client.py", line 834, in request return self._request( File "c:\GPT\raptor\raptor-39\lib\site-packages\openai_base_client.py", line 890, in _request return self._retry_request( File "c:\GPT\raptor\raptor-39\lib\site-packages\openai_base_client.py", line 925, in _retry_request return self._request( File "c:\GPT\raptor\raptor-39\lib\site-packages\openai_base_client.py", line 890, in _request return self._retry_request( File "c:\GPT\raptor\raptor-39\lib\site-packages\openai_base_client.py", line 925, in _retry_request return self._request( File "c:\GPT\raptor\raptor-39\lib\site-packages\openai_base_client.py", line 897, in _request raise APIConnectionError(request=request) from err openai.APIConnectionError: Connection error.

The above exception was the direct cause of the following exception:

Traceback (most recent call last): File "c:\GPT\raptor\raptor-39\rag.py", line 28, in RA.add_documents(text) File "c:\GPT\raptor\raptor-39\raptor\RetrievalAugmentation.py", line 220, in add_documents self.tree = self.tree_builder.build_from_text(text=docs, use_multithreading=False) File "c:\GPT\raptor\raptor-39\raptor\tree_builder.py", line 280, in build_from_text , node = self.create_node(index, text) File "c:\GPT\raptor\raptor-39\raptor\tree_builder.py", line 175, in create_node embeddings = { File "c:\GPT\raptor\raptor-39\raptor\tree_builder.py", line 176, in model_name: model.create_embedding(text) File "c:\GPT\raptor\raptor-39\lib\site-packages\tenacity__init__.py", line 289, in wrapped_f return self(f, *args, **kw) File "c:\GPT\raptor\raptor-39\lib\site-packages\tenacity\init.py", line 379, in call do = self.iter(retry_state=retry_state) File "c:\GPT\raptor\raptor-39\lib\site-packages\tenacity\init__.py", line 326, in iter raise retry_exc from fut.exception() tenacity.RetryError: RetryError[<Future at 0x1c7ff8743d0 state=finished raised APIConnectionError>]

parthsarthi03 commented 3 months ago

Hi, I'm not very familiar with the Azure setup, but it should be easy to set up RAPTOR with any inference setup. You can define your own inference code to use Azure by defining your custom SummarizationModel, QAModel, and/or Embedding model. We have a tutorial for how to extend to custon models here and you can do something similar for Azure.