feat: optimize langchain llm credential pass in

api/core/llm/streamable_azure_chat_open_ai.py

@@ -1,12 +1,50 @@
-import requests
 from langchain.schema import BaseMessage, ChatResult, LLMResult
 from langchain.chat_models import AzureChatOpenAI
-from typing import Optional, List
+from typing import Optional, List, Dict, Any
+
+from pydantic import root_validator
 
 from core.llm.error_handle_wraps import handle_llm_exceptions, handle_llm_exceptions_async
 
 
 class StreamableAzureChatOpenAI(AzureChatOpenAI):
+    @root_validator()
+    def validate_environment(cls, values: Dict) -> Dict:
+        """Validate that api key and python package exists in environment."""
+        try:
+            import openai
+        except ImportError:
+            raise ValueError(
+                "Could not import openai python package. "
+                "Please install it with `pip install openai`."
+            )
+        try:
+            values["client"] = openai.ChatCompletion
+        except AttributeError:
+            raise ValueError(
+                "`openai` has no `ChatCompletion` attribute, this is likely "
+                "due to an old version of the openai package. Try upgrading it "
+                "with `pip install --upgrade openai`."
+            )
+        if values["n"] < 1:
+            raise ValueError("n must be at least 1.")
+        if values["n"] > 1 and values["streaming"]:
+            raise ValueError("n must be 1 when streaming.")
+        return values
+
+    @property
+    def _default_params(self) -> Dict[str, Any]:
+        """Get the default parameters for calling OpenAI API."""
+        return {
+            **super()._default_params,
+            "engine": self.deployment_name,
+            "api_type": self.openai_api_type,
+            "api_base": self.openai_api_base,
+            "api_version": self.openai_api_version,
+            "api_key": self.openai_api_key,
+            "organization": self.openai_organization if self.openai_organization else None,
+        }
+
     def get_messages_tokens(self, messages: List[BaseMessage]) -> int:
         """Get the number of tokens in a list of messages.
 

api/core/llm/streamable_azure_open_ai.py

@@ -1,11 +1,55 @@
+import os
+
 from langchain.llms import AzureOpenAI
 from langchain.schema import LLMResult
-from typing import Optional, List
+from typing import Optional, List, Dict, Mapping, Any
+
+from pydantic import root_validator
 
 from core.llm.error_handle_wraps import handle_llm_exceptions, handle_llm_exceptions_async
 
 
 class StreamableAzureOpenAI(AzureOpenAI):
+    openai_api_type: str = "azure"
+    openai_api_version: str = ""
+
+    @root_validator()
+    def validate_environment(cls, values: Dict) -> Dict:
+        """Validate that api key and python package exists in environment."""
+        try:
+            import openai
+
+            values["client"] = openai.Completion
+        except ImportError:
+            raise ValueError(
+                "Could not import openai python package. "
+                "Please install it with `pip install openai`."
+            )
+        if values["streaming"] and values["n"] > 1:
+            raise ValueError("Cannot stream results when n > 1.")
+        if values["streaming"] and values["best_of"] > 1:
+            raise ValueError("Cannot stream results when best_of > 1.")
+        return values
+
+    @property
+    def _invocation_params(self) -> Dict[str, Any]:
+        return {**super()._invocation_params, **{
+            "api_type": self.openai_api_type,
+            "api_base": self.openai_api_base,
+            "api_version": self.openai_api_version,
+            "api_key": self.openai_api_key,
+            "organization": self.openai_organization if self.openai_organization else None,
+        }}
+
+    @property
+    def _identifying_params(self) -> Mapping[str, Any]:
+        return {**super()._identifying_params, **{
+            "api_type": self.openai_api_type,
+            "api_base": self.openai_api_base,
+            "api_version": self.openai_api_version,
+            "api_key": self.openai_api_key,
+            "organization": self.openai_organization if self.openai_organization else None,
+        }}
 
     @handle_llm_exceptions
     def generate(

api/core/llm/streamable_chat_open_ai.py

@@ -1,12 +1,52 @@
+import os
+
 from langchain.schema import BaseMessage, ChatResult, LLMResult
 from langchain.chat_models import ChatOpenAI
-from typing import Optional, List
+from typing import Optional, List, Dict, Any
+
+from pydantic import root_validator
 
 from core.llm.error_handle_wraps import handle_llm_exceptions, handle_llm_exceptions_async
 
 
 class StreamableChatOpenAI(ChatOpenAI):
 
+    @root_validator()
+    def validate_environment(cls, values: Dict) -> Dict:
+        """Validate that api key and python package exists in environment."""
+        try:
+            import openai
+        except ImportError:
+            raise ValueError(
+                "Could not import openai python package. "
+                "Please install it with `pip install openai`."
+            )
+        try:
+            values["client"] = openai.ChatCompletion
+        except AttributeError:
+            raise ValueError(
+                "`openai` has no `ChatCompletion` attribute, this is likely "
+                "due to an old version of the openai package. Try upgrading it "
+                "with `pip install --upgrade openai`."
+            )
+        if values["n"] < 1:
+            raise ValueError("n must be at least 1.")
+        if values["n"] > 1 and values["streaming"]:
+            raise ValueError("n must be 1 when streaming.")
+        return values
+
+    @property
+    def _default_params(self) -> Dict[str, Any]:
+        """Get the default parameters for calling OpenAI API."""
+        return {
+            **super()._default_params,
+            "api_type": 'openai',
+            "api_base": os.environ.get("OPENAI_API_BASE", "https://api.openai.com/v1"),
+            "api_version": None,
+            "api_key": self.openai_api_key,
+            "organization": self.openai_organization if self.openai_organization else None,
+        }
+
     def get_messages_tokens(self, messages: List[BaseMessage]) -> int:
         """Get the number of tokens in a list of messages.
 

api/core/llm/streamable_open_ai.py

@@ -1,12 +1,54 @@
+import os
+
 from langchain.schema import LLMResult
-from typing import Optional, List
+from typing import Optional, List, Dict, Any, Mapping
 from langchain import OpenAI
+from pydantic import root_validator
 
 from core.llm.error_handle_wraps import handle_llm_exceptions, handle_llm_exceptions_async
 
 
 class StreamableOpenAI(OpenAI):
 
+    @root_validator()
+    def validate_environment(cls, values: Dict) -> Dict:
+        """Validate that api key and python package exists in environment."""
+        try:
+            import openai
+
+            values["client"] = openai.Completion
+        except ImportError:
+            raise ValueError(
+                "Could not import openai python package. "
+                "Please install it with `pip install openai`."
+            )
+        if values["streaming"] and values["n"] > 1:
+            raise ValueError("Cannot stream results when n > 1.")
+        if values["streaming"] and values["best_of"] > 1:
+            raise ValueError("Cannot stream results when best_of > 1.")
+        return values
+
+    @property
+    def _invocation_params(self) -> Dict[str, Any]:
+        return {**super()._invocation_params, **{
+            "api_type": 'openai',
+            "api_base": os.environ.get("OPENAI_API_BASE", "https://api.openai.com/v1"),
+            "api_version": None,
+            "api_key": self.openai_api_key,
+            "organization": self.openai_organization if self.openai_organization else None,
+        }}
+
+    @property
+    def _identifying_params(self) -> Mapping[str, Any]:
+        return {**super()._identifying_params, **{
+            "api_type": 'openai',
+            "api_base": os.environ.get("OPENAI_API_BASE", "https://api.openai.com/v1"),
+            "api_version": None,
+            "api_key": self.openai_api_key,
+            "organization": self.openai_organization if self.openai_organization else None,
+        }}
+
+
     @handle_llm_exceptions
     def generate(
             self, prompts: List[str], stop: Optional[List[str]] = None