Allow replicate prompt key to be manually specified (#10516)

Since inference logic doesn't work for all models

Co-authored-by: Taqi Jaffri <tjaffri@gmail.com>
Co-authored-by: Taqi Jaffri <tjaffri@docugami.com>

libs/langchain/langchain/llms/replicate.py

@@ -1,5 +1,5 @@
 import logging
-from typing import Any, Dict, List, Mapping, Optional
+from typing import Any, Dict, List, Optional
 
 from langchain.callbacks.manager import CallbackManagerForLLMRun
 from langchain.llms.base import LLM
@@ -33,6 +33,7 @@ class Replicate(LLM):
     input: Dict[str, Any] = Field(default_factory=dict)
     model_kwargs: Dict[str, Any] = Field(default_factory=dict)
     replicate_api_token: Optional[str] = None
+    prompt_key: Optional[str] = None
 
     streaming: bool = Field(default=False)
     """Whether to stream the results."""
@@ -81,7 +82,7 @@ class Replicate(LLM):
         return values
 
     @property
-    def _identifying_params(self) -> Mapping[str, Any]:
+    def _identifying_params(self) -> Dict[str, Any]:
         """Get the identifying parameters."""
         return {
             "model": self.model,
@@ -114,6 +115,7 @@ class Replicate(LLM):
         model = replicate_python.models.get(model_str)
         version = model.versions.get(version_str)
 
+        if not self.prompt_key:
             # sort through the openapi schema to get the name of the first input
             input_properties = sorted(
                 version.openapi_schema["components"]["schemas"]["Input"][
@@ -121,8 +123,10 @@ class Replicate(LLM):
                 ].items(),
                 key=lambda item: item[1].get("x-order", 0),
             )
-        first_input_name = input_properties[0][0]
+
-        inputs = {first_input_name: prompt, **self.input}
+            self.prompt_key = input_properties[0][0]
+
+        inputs: Dict = {self.prompt_key: prompt, **self.input}
 
         prediction = replicate_python.predictions.create(
             version=version, input={**inputs, **kwargs}