AzureOpenai access from behind company proxies. (#1459)

embedchain/embedchain/config/embedder/base.py

@@ -1,4 +1,6 @@
-from typing import Any, Dict, Optional
+from typing import Any, Dict, Optional, Union
+
+import httpx
 
 from embedchain.helpers.json_serializable import register_deserializable
 
@@ -14,6 +16,8 @@ class BaseEmbedderConfig:
         api_key: Optional[str] = None,
         api_base: Optional[str] = None,
         model_kwargs: Optional[Dict[str, Any]] = None,
+        http_client_proxies: Optional[Union[Dict, str]] = None,
+        http_async_client_proxies: Optional[Union[Dict, str]] = None,
     ):
         """
         Initialize a new instance of an embedder config class.
@@ -32,6 +36,11 @@ class BaseEmbedderConfig:
         :type api_base: Optional[str], optional
         :param model_kwargs: key-value arguments for the embedding model, defaults a dict inside init.
         :type model_kwargs: Optional[Dict[str, Any]], defaults a dict inside init.
+        :param http_client_proxies: The proxy server settings used to create self.http_client, defaults to None
+        :type http_client_proxies: Optional[Dict | str], optional
+        :param http_async_client_proxies: The proxy server settings for async calls used to create
+        self.http_async_client, defaults to None
+        :type http_async_client_proxies: Optional[Dict | str], optional
         """
         self.model = model
         self.deployment_name = deployment_name
@@ -40,3 +49,7 @@ class BaseEmbedderConfig:
         self.api_key = api_key
         self.api_base = api_base
         self.model_kwargs = model_kwargs or {}
+        self.http_client = httpx.Client(proxies=http_client_proxies) if http_client_proxies else None
+        self.http_async_client = (
+            httpx.AsyncClient(proxies=http_async_client_proxies) if http_async_client_proxies else None
+        )

embedchain/embedchain/embedder/azure_openai.py

@@ -1,6 +1,6 @@
 from typing import Optional
 
-from langchain_community.embeddings import AzureOpenAIEmbeddings
+from langchain_openai import AzureOpenAIEmbeddings
 
 from embedchain.config import BaseEmbedderConfig
 from embedchain.embedder.base import BaseEmbedder
@@ -14,7 +14,11 @@ class AzureOpenAIEmbedder(BaseEmbedder):
         if self.config.model is None:
             self.config.model = "text-embedding-ada-002"
 
-        embeddings = AzureOpenAIEmbeddings(deployment=self.config.deployment_name)
+        embeddings = AzureOpenAIEmbeddings(
+            deployment=self.config.deployment_name,
+            http_client=self.config.http_client,
+            http_async_client=self.config.http_async_client,
+        )
         embedding_fn = BaseEmbedder._langchain_default_concept(embeddings)
 
         self.set_embedding_fn(embedding_fn=embedding_fn)

embedchain/embedchain/llm/azure_openai.py

@@ -30,6 +30,8 @@ class AzureOpenAILlm(BaseLlm):
             temperature=config.temperature,
             max_tokens=config.max_tokens,
             streaming=config.stream,
+            http_client=config.http_client,
+            http_async_client=config.http_async_client,
         )
 
         if config.top_p and config.top_p != 1:

embedchain/embedchain/utils/misc.py

@@ -479,6 +479,8 @@ def validate_config(config_data):
                     Optional("base_url"): str,
                     Optional("endpoint"): str,
                     Optional("model_kwargs"): dict,
+                    Optional("http_client_proxies"): Or(str, dict),
+                    Optional("http_async_client_proxies"): Or(str, dict),
                 },
             },
             Optional("embedding_model"): {