community: Add Baichuan LLM to community (#16724)

Replace this entire comment with:
- **Description:** Add Baichuan LLM to integration/llm, also updated
related docs.

Co-authored-by: BaiChuanHelper <wintergyc@WinterGYCs-MacBook-Pro.local>

libs/community/langchain_community/llms/baichuan.py

@@ -0,0 +1,95 @@
+from __future__ import annotations
+
+import json
+import logging
+from typing import Any, Dict, List, Optional
+
+import requests
+from langchain_core.callbacks import CallbackManagerForLLMRun
+from langchain_core.language_models.llms import LLM
+from langchain_core.pydantic_v1 import Field, SecretStr, root_validator
+from langchain_core.utils import convert_to_secret_str, get_from_dict_or_env
+
+from langchain_community.llms.utils import enforce_stop_tokens
+
+logger = logging.getLogger(__name__)
+
+
+class BaichuanLLM(LLM):
+    # TODO: Adding streaming support.
+    """Wrapper around Baichuan large language models."""
+
+    model: str = "Baichuan2-Turbo-192k"
+    """
+    Other models are available at https://platform.baichuan-ai.com/docs/api.
+    """
+    temperature: float = 0.3
+    top_p: float = 0.95
+    timeout: int = 60
+    model_kwargs: Dict[str, Any] = Field(default_factory=dict)
+
+    baichuan_api_host: Optional[str] = None
+    baichuan_api_key: Optional[SecretStr] = None
+
+    @root_validator()
+    def validate_environment(cls, values: Dict) -> Dict:
+        values["baichuan_api_key"] = convert_to_secret_str(
+            get_from_dict_or_env(values, "baichuan_api_key", "BAICHUAN_API_KEY")
+        )
+        values["baichuan_api_host"] = get_from_dict_or_env(
+            values,
+            "baichuan_api_host",
+            "BAICHUAN_API_HOST",
+            default="https://api.baichuan-ai.com/v1/chat/completions",
+        )
+        return values
+
+    @property
+    def _default_params(self) -> Dict[str, Any]:
+        return {
+            "model": self.model,
+            "temperature": self.temperature,
+            "top_p": self.top_p,
+            **self.model_kwargs,
+        }
+
+    def _post(self, request: Any) -> Any:
+        headers = {
+            "Content-Type": "application/json",
+            "Authorization": f"Bearer {self.baichuan_api_key.get_secret_value()}",
+        }
+        try:
+            response = requests.post(
+                self.baichuan_api_host,
+                headers=headers,
+                json=request,
+                timeout=self.timeout,
+            )
+
+            if response.status_code == 200:
+                parsed_json = json.loads(response.text)
+                return parsed_json["choices"][0]["message"]["content"]
+            else:
+                response.raise_for_status()
+        except Exception as e:
+            raise ValueError(f"An error has occurred: {e}")
+
+    def _call(
+        self,
+        prompt: str,
+        stop: Optional[List[str]] = None,
+        run_manager: Optional[CallbackManagerForLLMRun] = None,
+        **kwargs: Any,
+    ) -> str:
+        request = self._default_params
+        request["messages"] = [{"role": "user", "content": prompt}]
+        request.update(kwargs)
+        text = self._post(request)
+        if stop is not None:
+            text = enforce_stop_tokens(text, stop)
+        return text
+
+    @property
+    def _llm_type(self) -> str:
+        """Return type of chat_model."""
+        return "baichuan-llm"