Bedrock integration (#85)

* Llama-index-upgrade

* Upgrade SDK version

* pdm lock file update

* Token counter fixes

* Bedrock integration

* Update mistalai version to resolve backward comaptibility issues of latest release my mistralai

---------

Signed-off-by: Gayathri <[email protected]>

Author: gaya3-zipstack

pdm.lock

@@ -36,12 +36,19 @@ dependencies = [
     "llama-index-llms-openai==0.1.27",
     "llama-index-llms-palm==0.1.5",
     "llama-index-llms-mistralai==0.1.19",
+    #Todo: Remove the version locking for mistralai below
+    #once the the following error is resolved from mistralai side
+    #Unable to import llm adapters : No module named 'mistralai.models.chat_completion'
+    #Looks like mistralai>0.4.2 is not backward compatible
+    "mistralai==0.4.2",
+
     "llama-index-llms-anyscale==0.1.4",
     "llama-index-llms-anthropic==0.1.16",
     "llama-index-llms-azure-openai==0.1.10",
     "llama-index-llms-vertex==0.2.2",
     "llama-index-llms-replicate==0.1.3",
     "llama-index-llms-ollama==0.2.2",
+    "llama-index-llms-bedrock==0.1.12",
     # For Llama Parse X2Text
     "llama-parse==0.4.9",
     # OCR

pyproject.toml

@@ -0,0 +1 @@
+# Unstract Bedrock LLM Adapter

src/unstract/sdk/adapters/llm/bedrock/README.md

@@ -0,0 +1,25 @@
+[build-system]
+requires = ["pdm-backend"]
+build-backend = "pdm.backend"
+
+
+[project]
+name = "unstract-bedrock-llm"
+version = "0.0.1"
+description = "Bedrock LLM"
+authors = [
+    {name = "Zipstack Inc.", email = "[email protected]"},
+]
+dependencies = [
+]
+requires-python = ">=3.9"
+readme = "README.md"
+classifiers = [
+  "Programming Language :: Python"
+]
+license = {text = "MIT"}
+
+[tool.pdm.build]
+includes = ["src"]
+package-dir = "src"
+# source-includes = ["tests"]

src/unstract/sdk/adapters/llm/bedrock/pyproject.toml

@@ -0,0 +1,9 @@
+from .bedrock import BedrockLLM
+
+metadata = {
+    "name": BedrockLLM.__name__,
+    "version": "1.0.0",
+    "adapter": BedrockLLM,
+    "description": "Bedrock LLM adapter",
+    "is_active": True,
+}

src/unstract/sdk/adapters/llm/bedrock/src/__init__.py

@@ -0,0 +1,84 @@
+import os
+from typing import Any, Optional
+
+from llama_index.core.llms import LLM
+from llama_index.llms.bedrock import Bedrock
+
+from unstract.sdk.adapters.exceptions import AdapterError
+from unstract.sdk.adapters.llm.constants import LLMKeys
+from unstract.sdk.adapters.llm.helper import LLMHelper
+from unstract.sdk.adapters.llm.llm_adapter import LLMAdapter
+
+
+class Constants:
+    MODEL = "model"
+    API_KEY = "api_key"
+    TIMEOUT = "timeout"
+    MAX_RETIRES = "max_retries"
+    SECRET_ACCESS_KEY = "aws_secret_access_key"
+    ACCESS_KEY_ID = "aws_access_key_id"
+    REGION_NAME = "region_name"
+    CONTEXT_SIZE = "context_size"
+
+
+class BedrockLLM(LLMAdapter):
+    def __init__(self, settings: dict[str, Any]):
+        super().__init__("Bedrock")
+        self.config = settings
+
+    @staticmethod
+    def get_id() -> str:
+        return "bedrock|8d18571f-5e96-4505-bd28-ad0379c64064"
+
+    @staticmethod
+    def get_name() -> str:
+        return "Bedrock"
+
+    @staticmethod
+    def get_description() -> str:
+        return "Bedrock LLM"
+
+    @staticmethod
+    def get_provider() -> str:
+        return "bedrock"
+
+    @staticmethod
+    def get_icon() -> str:
+        return "/icons/adapter-icons/Bedrock.png"
+
+    @staticmethod
+    def get_json_schema() -> str:
+        f = open(f"{os.path.dirname(__file__)}/static/json_schema.json")
+        schema = f.read()
+        f.close()
+        return schema
+
+    def get_llm_instance(self) -> LLM:
+        try:
+            context_size: Optional[int] = (
+                int(self.config.get(Constants.CONTEXT_SIZE, 0))
+                if self.config.get(Constants.CONTEXT_SIZE)
+                else None
+            )
+            llm: LLM = Bedrock(
+                model=self.config.get(Constants.MODEL),
+                aws_access_key_id=self.config.get(Constants.ACCESS_KEY_ID),
+                aws_secret_access_key=self.config.get(Constants.SECRET_ACCESS_KEY),
+                region_name=self.config.get(Constants.REGION_NAME),
+                timeout=float(
+                    self.config.get(Constants.TIMEOUT, LLMKeys.DEFAULT_TIMEOUT)
+                ),
+                max_retries=int(
+                    self.config.get(Constants.MAX_RETIRES, LLMKeys.DEFAULT_MAX_RETRIES)
+                ),
+                temperature=0,
+                context_size=context_size,
+            )
+            return llm
+        except Exception as e:
+            raise AdapterError(str(e))
+
+    def test_connection(self) -> bool:
+        llm = self.get_llm_instance()
+        test_result: bool = LLMHelper.test_llm_instance(llm=llm)
+        return test_result

src/unstract/sdk/adapters/llm/bedrock/src/bedrock.py

@@ -0,0 +1,65 @@
+{
+  "title": "Bedrock LLM",
+  "type": "object",
+  "required": [
+    "aws_secret_access_key",
+    "region_name",
+    "aws_access_key_id",
+    "model",
+    "adapter_name"
+  ],
+  "properties": {
+    "adapter_name": {
+      "type": "string",
+      "title": "Name",
+      "default": "",
+      "description": "Provide a unique name for this adapter instance. Example: Bedrock-1"
+    },
+    "model": {
+      "type": "string",
+      "title": "Model",
+      "default": "amazon.titan-text-express-v1",
+      "description": "Model name. Refer to Bedrock's documentation for the list of available models."
+    },
+    "context_size": {
+      "type": "number",
+      "minimum": 0,
+      "multipleOf": 1,
+      "title": "Context Size",
+      "description": "The maximum number of context tokens for the model. For setting default in supportied models, leave this empty."
+    },
+    "aws_access_key_id": {
+      "type": "string",
+      "title": "AWS Access Key ID",
+      "description": "Provide your AWS Access Key ID",
+      "format": "password"
+    },
+    "aws_secret_access_key": {
+      "type": "string",
+      "title": "AWS Secret Access Key",
+      "description": "Provide your AWS Secret Access Key",
+      "format": "password"
+    },
+    "region_name": {
+      "type": "string",
+      "title": "AWS Region name",
+      "description": "Provide the AWS Region name where the service is running. Eg. us-east-1"
+    },
+    "timeout": {
+      "type": "number",
+      "minimum": 0,
+      "multipleOf": 1,
+      "title": "Timeout",
+      "default": 900,
+      "description": "Timeout in seconds"
+    },
+    "max_retries": {
+      "type": "number",
+      "minimum": 0,
+      "multipleOf": 1,
+      "title": "Max Retries",
+      "default": 5,
+      "description": "Maximum number of retries to attempt when a request fails."
+    }
+  }
+}