diff --git a/libs/community/langchain_community/chat_models/bedrock.py b/libs/community/langchain_community/chat_models/bedrock.py
index f9d87b6274..933343d6a9 100644
--- a/libs/community/langchain_community/chat_models/bedrock.py
+++ b/libs/community/langchain_community/chat_models/bedrock.py
@@ -5,7 +5,14 @@ from langchain_core.callbacks import (
     CallbackManagerForLLMRun,
 )
 from langchain_core.language_models.chat_models import BaseChatModel
-from langchain_core.messages import AIMessage, AIMessageChunk, BaseMessage
+from langchain_core.messages import (
+    AIMessage,
+    AIMessageChunk,
+    BaseMessage,
+    ChatMessage,
+    HumanMessage,
+    SystemMessage,
+)
 from langchain_core.outputs import ChatGeneration, ChatGenerationChunk, ChatResult
 from langchain_core.pydantic_v1 import Extra
 
@@ -20,6 +27,27 @@ from langchain_community.utilities.anthropic import (
 )
 
 
+def _convert_one_message_to_text_mistral(message: BaseMessage) -> str:
+    if isinstance(message, ChatMessage):
+        message_text = f"\n\n{message.role.capitalize()}: {message.content}"
+    elif isinstance(message, HumanMessage):
+        message_text = f"[INST] {message.content} [/INST]"
+    elif isinstance(message, AIMessage):
+        message_text = f"{message.content}"
+    elif isinstance(message, SystemMessage):
+        message_text = f"<<SYS>> {message.content} <</SYS>>"
+    else:
+        raise ValueError(f"Got unknown type {message}")
+    return message_text
+
+
+def convert_messages_to_prompt_mistral(messages: List[BaseMessage]) -> str:
+    """Convert a list of messages to a prompt for mistral."""
+    return "\n".join(
+        [_convert_one_message_to_text_mistral(message) for message in messages]
+    )
+
+
 def _format_image(image_url: str) -> Dict:
     """
     Formats an image of format data:image/jpeg;base64,{b64_string}
@@ -137,6 +165,8 @@ class ChatPromptAdapter:
             prompt = convert_messages_to_prompt_anthropic(messages=messages)
         elif provider == "meta":
             prompt = convert_messages_to_prompt_llama(messages=messages)
+        elif provider == "mistral":
+            prompt = convert_messages_to_prompt_mistral(messages=messages)
         elif provider == "amazon":
             prompt = convert_messages_to_prompt_anthropic(
                 messages=messages,
diff --git a/libs/community/langchain_community/llms/bedrock.py b/libs/community/langchain_community/llms/bedrock.py
index d126995b93..9b7515a5f4 100644
--- a/libs/community/langchain_community/llms/bedrock.py
+++ b/libs/community/langchain_community/llms/bedrock.py
@@ -103,6 +103,7 @@ class LLMInputOutputAdapter:
         "amazon": "outputText",
         "cohere": "text",
         "meta": "generation",
+        "mistral": "outputs",
     }
 
     @classmethod
@@ -127,7 +128,7 @@ class LLMInputOutputAdapter:
                 input_body["prompt"] = _human_assistant_format(prompt)
                 if "max_tokens_to_sample" not in input_body:
                     input_body["max_tokens_to_sample"] = 1024
-        elif provider in ("ai21", "cohere", "meta"):
+        elif provider in ("ai21", "cohere", "meta", "mistral"):
             input_body["prompt"] = prompt
         elif provider == "amazon":
             input_body = dict()
@@ -156,6 +157,8 @@ class LLMInputOutputAdapter:
                 text = response_body.get("generations")[0].get("text")
             elif provider == "meta":
                 text = response_body.get("generation")
+            elif provider == "mistral":
+                text = response_body.get("outputs")[0].get("text")
             else:
                 text = response_body.get("results")[0].get("outputText")
 
@@ -198,6 +201,13 @@ class LLMInputOutputAdapter:
                 chunk_obj["is_finished"] or chunk_obj[output_key] == "<EOS_TOKEN>"
             ):
                 return
+
+            elif (
+                provider == "mistral"
+                and chunk_obj.get(output_key, [{}])[0].get("stop_reason", "") == "stop"
+            ):
+                return
+
             elif messages_api and (chunk_obj.get("type") == "content_block_stop"):
                 return
 
@@ -214,11 +224,17 @@ class LLMInputOutputAdapter:
             else:
                 # chunk obj format varies with provider
                 yield GenerationChunk(
-                    text=chunk_obj[output_key],
+                    text=(
+                        chunk_obj[output_key]
+                        if provider != "mistral"
+                        else chunk_obj[output_key][0]["text"]
+                    ),
                     generation_info={
-                        GUARDRAILS_BODY_KEY: chunk_obj.get(GUARDRAILS_BODY_KEY)
-                        if GUARDRAILS_BODY_KEY in chunk_obj
-                        else None,
+                        GUARDRAILS_BODY_KEY: (
+                            chunk_obj.get(GUARDRAILS_BODY_KEY)
+                            if GUARDRAILS_BODY_KEY in chunk_obj
+                            else None
+                        ),
                     },
                 )
 
@@ -250,7 +266,19 @@ class LLMInputOutputAdapter:
             ):
                 return
 
-            yield GenerationChunk(text=chunk_obj[output_key])
+            if (
+                provider == "mistral"
+                and chunk_obj.get(output_key, [{}])[0].get("stop_reason", "") == "stop"
+            ):
+                return
+
+            yield GenerationChunk(
+                text=(
+                    chunk_obj[output_key]
+                    if provider != "mistral"
+                    else chunk_obj[output_key][0]["text"]
+                )
+            )
 
 
 class BedrockBase(BaseModel, ABC):
@@ -300,6 +328,7 @@ class BedrockBase(BaseModel, ABC):
         "amazon": "stopSequences",
         "ai21": "stop_sequences",
         "cohere": "stop_sequences",
+        "mistral": "stop_sequences",
     }
 
     guardrails: Optional[Mapping[str, Any]] = {