Release/promptflow/1.1.0

examples/flows/chat/chat-with-pdf/chat_with_pdf/utils/oai.py

@@ -1,5 +1,6 @@
 from typing import List
 import openai
+from openai.version import VERSION as OPENAI_VERSION
 import os
 import tiktoken
 from jinja2 import Template
@@ -25,106 +26,105 @@ def extract_delay_from_rate_limit_error_msg(text):
 
 class OAI:
     def __init__(self):
-        if os.getenv("OPENAI_API_TYPE") is not None:
-            openai.api_type = os.getenv("OPENAI_API_TYPE")
-        if os.getenv("OPENAI_API_BASE") is not None:
-            openai.api_base = os.environ.get("OPENAI_API_BASE")
+        if OPENAI_VERSION.startswith("0."):
+            raise Exception(
+                "Please upgrade your OpenAI package to version >= 1.0.0 or "
+                "using the command: pip install --upgrade openai."
+            )
+        init_params = {}
+        api_type = os.environ.get("OPENAI_API_TYPE")
         if os.getenv("OPENAI_API_VERSION") is not None:
-            openai.api_version = os.environ.get("OPENAI_API_VERSION")
+            init_params["api_version"] = os.environ.get("OPENAI_API_VERSION")
         if os.getenv("OPENAI_ORG_ID") is not None:
-            openai.organization = os.environ.get("OPENAI_ORG_ID")
+            init_params["organization"] = os.environ.get("OPENAI_ORG_ID")
         if os.getenv("OPENAI_API_KEY") is None:
             raise ValueError("OPENAI_API_KEY is not set in environment variables")
+        if os.getenv("OPENAI_API_BASE") is not None:
+            if api_type == "azure":
+                init_params["azure_endpoint"] = os.environ.get("OPENAI_API_BASE")
+            else:
+                init_params["base_url"] = os.environ.get("OPENAI_API_BASE")
 
-        openai.api_key = os.environ.get("OPENAI_API_KEY")
+        init_params["api_key"] = os.environ.get("OPENAI_API_KEY")
 
         # A few sanity checks
-        if openai.api_type == "azure" and openai.api_base is None:
-            raise ValueError(
-                "OPENAI_API_BASE is not set in environment variables, this is required when api_type==azure"
-            )
-        if openai.api_type == "azure" and openai.api_version is None:
-            raise ValueError(
-                "OPENAI_API_VERSION is not set in environment variables, this is required when api_type==azure"
-            )
-        if openai.api_type == "azure" and openai.api_key.startswith("sk-"):
-            raise ValueError(
-                "OPENAI_API_KEY should not start with sk- when api_type==azure, are you using openai key by mistake?"
-            )
+        if api_type == "azure":
+            if init_params.get("azure_endpoint") is None:
+                raise ValueError(
+                    "OPENAI_API_BASE is not set in environment variables, this is required when api_type==azure"
+                )
+            if init_params.get("api_version") is None:
+                raise ValueError(
+                    "OPENAI_API_VERSION is not set in environment variables, this is required when api_type==azure"
+                )
+            if init_params["api_key"].startswith("sk-"):
+                raise ValueError(
+                    "OPENAI_API_KEY should not start with sk- when api_type==azure, "
+                    "are you using openai key by mistake?"
+                )
+            from openai import AzureOpenAI as Client
+        else:
+            from openai import OpenAI as Client
+        self.client = Client(**init_params)
 
 
 class OAIChat(OAI):
     @retry_and_handle_exceptions(
         exception_to_check=(
-            openai.error.RateLimitError,
-            openai.error.APIError,
+            openai.RateLimitError,
+            openai.APIStatusError,
+            openai.APIConnectionError,
             KeyError,
         ),
         max_retries=5,
         extract_delay_from_error_message=extract_delay_from_rate_limit_error_msg,
     )
     def generate(self, messages: list, **kwargs) -> List[float]:
-        if openai.api_type == "azure":
-            return openai.ChatCompletion.create(
-                engine=os.environ.get("CHAT_MODEL_DEPLOYMENT_NAME"),
-                messages=messages,
-                **kwargs,
-            )["choices"][0]["message"]["content"]
-        else:
-            return openai.ChatCompletion.create(
-                model=os.environ.get("CHAT_MODEL_DEPLOYMENT_NAME"),
-                messages=messages,
-                **kwargs,
-            )["choices"][0]["message"]["content"]
+        # chat api may return message with no content.
+        message = self.client.chat.completions.create(
+            model=os.environ.get("CHAT_MODEL_DEPLOYMENT_NAME"),
+            messages=messages,
+            **kwargs,
+        ).choices[0].message
+        return getattr(message, "content", "")
 
     @retry_and_handle_exceptions_for_generator(
         exception_to_check=(
-            openai.error.RateLimitError,
-            openai.error.APIError,
+            openai.RateLimitError,
+            openai.APIStatusError,
+            openai.APIConnectionError,
             KeyError,
         ),
         max_retries=5,
         extract_delay_from_error_message=extract_delay_from_rate_limit_error_msg,
     )
     def stream(self, messages: list, **kwargs):
-        if openai.api_type == "azure":
-            response = openai.ChatCompletion.create(
-                engine=os.environ.get("CHAT_MODEL_DEPLOYMENT_NAME"),
-                messages=messages,
-                stream=True,
-                **kwargs,
-            )
-        else:
-            response = openai.ChatCompletion.create(
-                model=os.environ.get("CHAT_MODEL_DEPLOYMENT_NAME"),
-                messages=messages,
-                stream=True,
-                **kwargs,
-            )
+        response = self.client.chat.completions.create(
+            model=os.environ.get("CHAT_MODEL_DEPLOYMENT_NAME"),
+            messages=messages,
+            stream=True,
+            **kwargs,
+        )
 
         for chunk in response:
-            if "choices" not in chunk or len(chunk["choices"]) == 0:
+            if not chunk.choices:
                 continue
-            delta = chunk["choices"][0]["delta"]
-            if "content" in delta:
-                yield delta["content"]
+            if chunk.choices[0].delta.content:
+                yield chunk.choices[0].delta.content
+            else:
+                yield ""
 
 
 class OAIEmbedding(OAI):
     @retry_and_handle_exceptions(
-        exception_to_check=openai.error.RateLimitError,
+        exception_to_check=openai.RateLimitError,
         max_retries=5,
         extract_delay_from_error_message=extract_delay_from_rate_limit_error_msg,
     )
     def generate(self, text: str) -> List[float]:
-        if openai.api_type == "azure":
-            return openai.Embedding.create(
-                input=text, engine=os.environ.get("EMBEDDING_MODEL_DEPLOYMENT_NAME")
-            )["data"][0]["embedding"]
-        else:
-            return openai.Embedding.create(
-                input=text, model=os.environ.get("EMBEDDING_MODEL_DEPLOYMENT_NAME")
-            )["data"][0]["embedding"]
+        return self.client.embeddings.create(
+            input=text, model=os.environ.get("EMBEDDING_MODEL_DEPLOYMENT_NAME")
+        ).data[0].embedding
 
 
 def count_token(text: str) -> int:

examples/flows/chat/chat-with-pdf/chat_with_pdf/utils/retry.py

@@ -1,11 +1,11 @@
-from typing import Tuple, Union, Optional
+from typing import Tuple, Union, Optional, Type
 import functools
 import time
 import random
 
 
 def retry_and_handle_exceptions(
-    exception_to_check: Union[Exception, Tuple[Exception]],
+    exception_to_check: Union[Type[Exception], Tuple[Type[Exception], ...]],
     max_retries: int = 3,
     initial_delay: float = 1,
     exponential_base: float = 2,
@@ -48,7 +48,7 @@ def wrapper(*args, **kwargs):
 
 
 def retry_and_handle_exceptions_for_generator(
-    exception_to_check: Union[Exception, Tuple[Exception]],
+    exception_to_check: Union[Type[Exception], Tuple[Type[Exception], ...]],
     max_retries: int = 3,
     initial_delay: float = 1,
     exponential_base: float = 2,

examples/flows/standard/basic-with-connection/hello.py

@@ -1,5 +1,5 @@
 from typing import Union
-import openai
+from openai.version import VERSION as OPENAI_VERSION
 
 from promptflow import tool
 from promptflow.connections import CustomConnection, AzureOpenAIConnection
@@ -13,6 +13,28 @@ def to_bool(value) -> bool:
     return str(value).lower() == "true"
 
 
+def get_client(connection: Union[CustomConnection, AzureOpenAIConnection]):
+    if OPENAI_VERSION.startswith("0."):
+        raise Exception(
+            "Please upgrade your OpenAI package to version >= 1.0.0 or using the command: pip install --upgrade openai."
+        )
+    # connection can be extract as a dict object contains the configs and secrets
+    connection_dict = dict(connection)
+    api_key = connection_dict.get("api_key")
+    conn = dict(
+        api_key=api_key,
+    )
+    if api_key.startswith("sk-"):
+        from openai import OpenAI as Client
+    else:
+        from openai import AzureOpenAI as Client
+        conn.update(
+            azure_endpoint=connection_dict.get("api_base"),
+            api_version=connection_dict.get("api_version", "2023-07-01-preview"),
+        )
+    return Client(**conn)
+
+
 @tool
 def my_python_tool(
     prompt: str,
@@ -37,12 +59,10 @@ def my_python_tool(
 
     # TODO: remove below type conversion after client can pass json rather than string.
     echo = to_bool(echo)
-    # connection can be extract as a dict object contains the configs and secrets
-    connection_dict = dict(connection)
 
-    response = openai.Completion.create(
+    response = get_client(connection).completions.create(
         prompt=prompt,
-        engine=deployment_name,
+        model=deployment_name,
         # empty string suffix should be treated as None.
         suffix=suffix if suffix else None,
         max_tokens=int(max_tokens),
@@ -59,8 +79,6 @@ def my_python_tool(
         # Logit bias must be a dict if we passed it to openai api.
         logit_bias=logit_bias if logit_bias else {},
         user=user,
-        request_timeout=30,
-        **connection_dict,
     )
 
     # get first element because prompt is single.

examples/flows/standard/basic/hello.py

@@ -1,5 +1,5 @@
 import os
-import openai
+from openai.version import VERSION as OPENAI_VERSION
 
 from dotenv import load_dotenv
 from promptflow import tool
@@ -13,6 +13,26 @@ def to_bool(value) -> bool:
     return str(value).lower() == "true"
 
 
+def get_client():
+    if OPENAI_VERSION.startswith("0."):
+        raise Exception(
+            "Please upgrade your OpenAI package to version >= 1.0.0 or using the command: pip install --upgrade openai."
+        )
+    api_key = os.environ["AZURE_OPENAI_API_KEY"]
+    conn = dict(
+        api_key=os.environ["AZURE_OPENAI_API_KEY"],
+    )
+    if api_key.startswith("sk-"):
+        from openai import OpenAI as Client
+    else:
+        from openai import AzureOpenAI as Client
+        conn.update(
+            azure_endpoint=os.environ["AZURE_OPENAI_API_BASE"],
+            api_version=os.environ.get("AZURE_OPENAI_API_VERSION", "2023-07-01-preview"),
+        )
+    return Client(**conn)
+
+
 @tool
 def my_python_tool(
     prompt: str,
@@ -40,19 +60,12 @@ def my_python_tool(
     if "AZURE_OPENAI_API_KEY" not in os.environ:
         raise Exception("Please specify environment variables: AZURE_OPENAI_API_KEY")
 
-    conn = dict(
-        api_key=os.environ["AZURE_OPENAI_API_KEY"],
-        api_base=os.environ["AZURE_OPENAI_API_BASE"],
-        api_type=os.environ.get("AZURE_OPENAI_API_TYPE", "azure"),
-        api_version=os.environ.get("AZURE_OPENAI_API_VERSION", "2023-07-01-preview"),
-    )
-
     # TODO: remove below type conversion after client can pass json rather than string.
     echo = to_bool(echo)
 
-    response = openai.Completion.create(
+    response = get_client().completions.create(
         prompt=prompt,
-        engine=deployment_name,
+        model=deployment_name,
         # empty string suffix should be treated as None.
         suffix=suffix if suffix else None,
         max_tokens=int(max_tokens),
@@ -69,8 +82,6 @@ def my_python_tool(
         # Logit bias must be a dict if we passed it to openai api.
         logit_bias=logit_bias if logit_bias else {},
         user=user,
-        request_timeout=30,
-        **conn,
     )
 
     # get first element because prompt is single.