Merge branch 'fix/azure-completion-choices-empty' into deploy/dev

api/core/llm/streamable_azure_open_ai.py

-from langchain.callbacks.manager import Callbacks
+from langchain.callbacks.manager import Callbacks, CallbackManagerForLLMRun
 from langchain.llms import AzureOpenAI
+from langchain.llms.openai import _streaming_response_template, completion_with_retry, _update_response, \
+    update_token_usage
 from langchain.schema import LLMResult
 from typing import Optional, List, Dict, Mapping, Any, Union, Tuple
 
@@ -67,3 +69,58 @@ class StreamableAzureOpenAI(AzureOpenAI):
     @classmethod
     def get_kwargs_from_model_params(cls, params: dict):
         return params
+
+    def _generate(
+        self,
+        prompts: List[str],
+        stop: Optional[List[str]] = None,
+        run_manager: Optional[CallbackManagerForLLMRun] = None,
+        **kwargs: Any,
+    ) -> LLMResult:
+        """Call out to OpenAI's endpoint with k unique prompts.
+
+        Args:
+            prompts: The prompts to pass into the model.
+            stop: Optional list of stop words to use when generating.
+
+        Returns:
+            The full LLM output.
+
+        Example:
+            .. code-block:: python
+
+                response = openai.generate(["Tell me a joke."])
+        """
+        params = self._invocation_params
+        params = {**params, **kwargs}
+        sub_prompts = self.get_sub_prompts(params, prompts, stop)
+        choices = []
+        token_usage: Dict[str, int] = {}
+        # Get the token usage from the response.
+        # Includes prompt, completion, and total tokens used.
+        _keys = {"completion_tokens", "prompt_tokens", "total_tokens"}
+        for _prompts in sub_prompts:
+            if self.streaming:
+                if len(_prompts) > 1:
+                    raise ValueError("Cannot stream results with multiple prompts.")
+                params["stream"] = True
+                response = _streaming_response_template()
+                for stream_resp in completion_with_retry(
+                    self, prompt=_prompts, **params
+                ):
+                    if len(stream_resp["choices"]) > 0:
+                        if run_manager:
+                            run_manager.on_llm_new_token(
+                                stream_resp["choices"][0]["text"],
+                                verbose=self.verbose,
+                                logprobs=stream_resp["choices"][0]["logprobs"],
+                            )
+                        _update_response(response, stream_resp)
+                choices.extend(response["choices"])
+            else:
+                response = completion_with_retry(self, prompt=_prompts, **params)
+                choices.extend(response["choices"])
+            if not self.streaming:
+                # Can't update token usage if streaming
+                update_token_usage(_keys, response, token_usage)
+        return self.create_llm_result(choices, prompts, token_usage)
\ No newline at end of file

web/app/components/app-sidebar/basic.tsx

@@ -4,7 +4,6 @@ import {
 } from '@heroicons/react/24/outline'
 import Tooltip from '../base/tooltip'
 import AppIcon from '../base/app-icon'
-
 const chars = '0123456789abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ-_'
 
 export function randomString(length: number) {
@@ -21,6 +20,7 @@ export type IAppBasicProps = {
   type: string | React.ReactNode
   hoverTip?: string
   textStyle?: { main?: string; extra?: string }
+  isExtraInLine?: boolean
 }
 
 const ApiSvg = <svg width="18" height="18" viewBox="0 0 18 18" fill="none" xmlns="http://www.w3.org/2000/svg">
@@ -61,7 +61,7 @@ const ICON_MAP = {
   notion: <AppIcon innerIcon={NotionSvg} className='!border-[0.5px] !border-indigo-100 !bg-white' />,
 }
 
-export default function AppBasic({ icon, icon_background, name, type, hoverTip, textStyle, iconType = 'app' }: IAppBasicProps) {
+export default function AppBasic({ icon, icon_background, name, type, hoverTip, textStyle, iconType = 'app', isExtraInLine }: IAppBasicProps) {
   return (
     <div className="flex items-start">
       {icon && icon_background && iconType === 'app' && (