feat(llms): support more tasks in HuggingFaceHub LLM and remove deprecated dep (#14406)

- **Description:** this PR upgrades the `HuggingFaceHub` LLM:
   * support more tasks (`translation` and `conversational`)
   * replaced the deprecated `InferenceApi` with `InferenceClient`
* adjusted the overall logic to use the "recommended" model for each
task when no model is provided, and vice-versa.
- **Tag mainter(s)**: @baskaryan @hwchase17

libs/community/langchain_community/llms/huggingface_hub.py

@@ -1,3 +1,4 @@
+import json
 from typing import Any, Dict, List, Mapping, Optional
 
 from langchain_core.callbacks import CallbackManagerForLLMRun
@@ -7,8 +8,15 @@ from langchain_core.utils import get_from_dict_or_env
 
 from langchain_community.llms.utils import enforce_stop_tokens
 
-DEFAULT_REPO_ID = "gpt2"
-VALID_TASKS = ("text2text-generation", "text-generation", "summarization")
+# key: task
+# value: key in the output dictionary
+VALID_TASKS_DICT = {
+    "translation": "translation_text",
+    "summarization": "summary_text",
+    "conversational": "generated_text",
+    "text-generation": "generated_text",
+    "text2text-generation": "generated_text",
+}
 
 
 class HuggingFaceHub(LLM):
@@ -18,7 +26,8 @@ class HuggingFaceHub(LLM):
     environment variable ``HUGGINGFACEHUB_API_TOKEN`` set with your API token, or pass
     it as a named parameter to the constructor.
 
-    Only supports `text-generation`, `text2text-generation` and `summarization` for now.
+    Supports `text-generation`, `text2text-generation`, `conversational`, `translation`,
+     and `summarization`.
 
     Example:
         .. code-block:: python
@@ -28,11 +37,13 @@ class HuggingFaceHub(LLM):
     """
 
     client: Any  #: :meta private:
-    repo_id: str = DEFAULT_REPO_ID
-    """Model name to use."""
+    repo_id: Optional[str] = None
+    """Model name to use. 
+    If not provided, the default model for the chosen task will be used."""
     task: Optional[str] = None
     """Task to call the model with.
-    Should be a task that returns `generated_text` or `summary_text`."""
+    Should be a task that returns `generated_text`, `summary_text`, 
+    or `translation_text`."""
     model_kwargs: Optional[dict] = None
     """Keyword arguments to pass to the model."""
 
@@ -50,18 +61,27 @@ class HuggingFaceHub(LLM):
             values, "huggingfacehub_api_token", "HUGGINGFACEHUB_API_TOKEN"
         )
         try:
-            from huggingface_hub.inference_api import InferenceApi
+            from huggingface_hub import HfApi, InferenceClient
 
             repo_id = values["repo_id"]
-            client = InferenceApi(
-                repo_id=repo_id,
+            client = InferenceClient(
+                model=repo_id,
                 token=huggingfacehub_api_token,
-                task=values.get("task"),
             )
-            if client.task not in VALID_TASKS:
+            if not values["task"]:
+                if not repo_id:
+                    raise ValueError(
+                        "Must specify either `repo_id` or `task`, or both."
+                    )
+                # Use the recommended task for the chosen model
+                model_info = HfApi(token=huggingfacehub_api_token).model_info(
+                    repo_id=repo_id
+                )
+                values["task"] = model_info.pipeline_tag
+            if values["task"] not in VALID_TASKS_DICT:
                 raise ValueError(
-                    f"Got invalid task {client.task}, "
-                    f"currently only {VALID_TASKS} are supported"
+                    f"Got invalid task {values['task']}, "
+                    f"currently only {VALID_TASKS_DICT.keys()} are supported"
                 )
             values["client"] = client
         except ImportError:
@@ -108,23 +128,20 @@ class HuggingFaceHub(LLM):
         """
         _model_kwargs = self.model_kwargs or {}
         params = {**_model_kwargs, **kwargs}
-        response = self.client(inputs=prompt, params=params)
+
+        response = self.client.post(
+            json={"inputs": prompt, "params": params}, task=self.task
+        )
+        response = json.loads(response.decode())
         if "error" in response:
             raise ValueError(f"Error raised by inference API: {response['error']}")
-        if self.client.task == "text-generation":
-            # Text generation sometimes return includes the starter text.
-            text = response[0]["generated_text"]
-            if text.startswith(prompt):
-                text = response[0]["generated_text"][len(prompt) :]
-        elif self.client.task == "text2text-generation":
-            text = response[0]["generated_text"]
-        elif self.client.task == "summarization":
-            text = response[0]["summary_text"]
+
+        response_key = VALID_TASKS_DICT[self.task]  # type: ignore
+        if isinstance(response, list):
+            text = response[0][response_key]
         else:
-            raise ValueError(
-                f"Got invalid task {self.client.task}, "
-                f"currently only {VALID_TASKS} are supported"
-            )
+            text = response[response_key]
+
         if stop is not None:
             # This is a bit hacky, but I can't figure out a better way to enforce
             # stop tokens when making calls to huggingface_hub.