HuggingFaceTextGenInference bug fix: Multiple values for keyword argument (#8044)

Fixed the bug causing: `TypeError: generate() got multiple values for
keyword argument 'stop_sequences'`

```python
res = await self.async_client.generate(
                prompt,
                **self._default_params,
                stop_sequences=stop,
                **kwargs,
            )
```
The above throws an error because stop_sequences is in also in the
self._default_params.
---------

Co-authored-by: Bagatur <baskaryan@gmail.com>

langchain/llms/huggingface_text_gen_inference.py

@@ -140,6 +140,13 @@ class HuggingFaceTextGenInference(LLM):
             "seed": self.seed,
         }
 
+    def _invocation_params(
+        self, runtime_stop: Optional[List[str]], **kwargs: Any
+    ) -> Dict[str, Any]:
+        params = {**self._default_params, **kwargs}
+        params["stop_sequences"] = params["stop_sequences"] + (runtime_stop or [])
+        return params
+
     def _call(
         self,
         prompt: str,
@@ -147,20 +154,11 @@ class HuggingFaceTextGenInference(LLM):
         run_manager: Optional[CallbackManagerForLLMRun] = None,
         **kwargs: Any,
     ) -> str:
-        if stop is None:
-            stop = self.stop_sequences
-        else:
-            stop += self.stop_sequences
-
+        invocation_params = self._invocation_params(stop, **kwargs)
         if not self.stream:
-            res = self.client.generate(
-                prompt,
-                **self._default_params,
-                stop_sequences=stop,
-                **kwargs,
-            )
+            res = self.client.generate(prompt, **invocation_params)
             # remove stop sequences from the end of the generated text
-            for stop_seq in stop:
+            for stop_seq in invocation_params["stop_sequences"]:
                 if stop_seq in res.generated_text:
                     res.generated_text = res.generated_text[
                         : res.generated_text.index(stop_seq)
@@ -172,16 +170,11 @@ class HuggingFaceTextGenInference(LLM):
                 text_callback = partial(
                     run_manager.on_llm_new_token, verbose=self.verbose
                 )
-            params = {
-                **self._default_params,
-                "stop_sequences": stop,
-                **kwargs,
-            }
             text = ""
-            for res in self.client.generate_stream(prompt, **params):
+            for res in self.client.generate_stream(prompt, **invocation_params):
                 token = res.token
                 is_stop = False
-                for stop_seq in stop:
+                for stop_seq in invocation_params["stop_sequences"]:
                     if stop_seq in token.text:
                         is_stop = True
                         break
@@ -200,20 +193,14 @@ class HuggingFaceTextGenInference(LLM):
         run_manager: Optional[AsyncCallbackManagerForLLMRun] = None,
         **kwargs: Any,
     ) -> str:
-        if stop is None:
-            stop = self.stop_sequences
-        else:
-            stop += self.stop_sequences
-
+        invocation_params = self._invocation_params(stop, **kwargs)
         if not self.stream:
             res = await self.async_client.generate(
                 prompt,
-                **self._default_params,
-                stop_sequences=stop,
-                **kwargs,
+                **invocation_params,
             )
             # remove stop sequences from the end of the generated text
-            for stop_seq in stop:
+            for stop_seq in invocation_params["stop_sequences"]:
                 if stop_seq in res.generated_text:
                     res.generated_text = res.generated_text[
                         : res.generated_text.index(stop_seq)
@@ -225,16 +212,13 @@ class HuggingFaceTextGenInference(LLM):
                 text_callback = partial(
                     run_manager.on_llm_new_token, verbose=self.verbose
                 )
-            params = {
-                **self._default_params,
-                "stop_sequences": stop,
-                **kwargs,
-            }
             text = ""
-            async for res in self.async_client.generate_stream(prompt, **params):
+            async for res in self.async_client.generate_stream(
+                prompt, **invocation_params
+            ):
                 token = res.token
                 is_stop = False
-                for stop_seq in stop:
+                for stop_seq in invocation_params["stop_sequences"]:
                     if stop_seq in token.text:
                         is_stop = True
                         break

tests/integration_tests/llms/test_huggingface_text_gen_inference.py

@@ -0,0 +1,19 @@
+from langchain import HuggingFaceTextGenInference
+
+
+def test_invocation_params_stop_sequences() -> None:
+    llm = HuggingFaceTextGenInference()
+    assert llm._default_params["stop_sequences"] == []
+
+    runtime_stop = None
+    assert llm._invocation_params(runtime_stop)["stop_sequences"] == []
+    assert llm._default_params["stop_sequences"] == []
+
+    runtime_stop = ["stop"]
+    assert llm._invocation_params(runtime_stop)["stop_sequences"] == ["stop"]
+    assert llm._default_params["stop_sequences"] == []
+
+    llm = HuggingFaceTextGenInference(stop_sequences=["."])
+    runtime_stop = ["stop"]
+    assert llm._invocation_params(runtime_stop)["stop_sequences"] == [".", "stop"]
+    assert llm._default_params["stop_sequences"] == ["."]