update

pages/1_Injection.py

@@ -2,7 +2,7 @@ import streamlit as st
 import pandas as pd
 from io import StringIO
 from util.injection import process_scores_multiple
-from util.model import AzureAgent, GPTAgent
+from util.model import AzureAgent, GPTAgent,Claude3Agent
 from util.prompt import PROMPT_TEMPLATE
 import os
 
@@ -49,14 +49,18 @@ else:
     st.sidebar.title('Model Settings')
     initialize_state()
 
+
+
     # Model selection and configuration
-    model_type = st.sidebar.radio("Select the type of agent", ('GPTAgent', 'AzureAgent'))
+    model_type = st.sidebar.radio("Select the type of agent", ('GPTAgent', 'AzureAgent','Claude3Agent'))
     st.session_state.api_key = st.sidebar.text_input("API Key", type="password", value=st.session_state.api_key)
     st.session_state.endpoint_url = st.sidebar.text_input("Endpoint URL", value=st.session_state.endpoint_url)
     st.session_state.deployment_name = st.sidebar.text_input("Model Name", value=st.session_state.deployment_name)
-    api_version = '2024-02-15-preview' if model_type == 'GPTAgent' else ''
-    st.session_state.temperature = st.sidebar.slider("Temperature", 0.0, 1.0, st.session_state.temperature, 0.01)
-    st.session_state.max_tokens = st.sidebar.number_input("Max Tokens", 1, 1000, st.session_state.max_tokens)
+
+    if model_type == 'GPTAgent' or model_type == 'AzureAgent':
+        api_version = '2024-02-15-preview' if model_type == 'GPTAgent' else ''
+        st.session_state.temperature = st.sidebar.slider("Temperature", 0.0, 1.0, st.session_state.temperature, 0.01)
+        st.session_state.max_tokens = st.sidebar.number_input("Max Tokens", 1, 1000, st.session_state.max_tokens)
 
     if st.sidebar.button("Reset Model Info"):
         initialize_state()  # Reset all state to defaults
@@ -111,9 +115,12 @@ else:
                 if model_type == 'AzureAgent':
                     agent = AzureAgent(st.session_state.api_key, st.session_state.endpoint_url,
                                        st.session_state.deployment_name)
-                else:
+                elif model_type == 'GPTAgent':
                     agent = GPTAgent(st.session_state.api_key, st.session_state.endpoint_url,
                                      st.session_state.deployment_name, api_version)
+                else:
+                    agent = Claude3Agent(st.session_state.api_key,st.session_state.deployment_name)
+
 
                 with st.spinner('Processing data...'):
                     parameters = {"temperature": st.session_state.temperature, "max_tokens": st.session_state.max_tokens}

requirements.txt

@@ -5,4 +5,5 @@ scipy
 statsmodels
 scikit-posthocs
 json-repair
-plotly
+plotly
+boto3

util/model.py

@@ -1,6 +1,49 @@
 import json
 import http.client
 from openai import AzureOpenAI
+import time
+from tqdm import tqdm
+from typing import Any, List
+from botocore.exceptions import ClientError
+from enum import Enum
+import boto3
+import json
+import logging
+
+
+class Model(Enum):
+    CLAUDE3_SONNET = "anthropic.claude-3-sonnet-20240229-v1:0"
+    CLAUDE3_HAIKU = "anthropic.claude-3-haiku-20240307-v1:0"
+
+
+class Claude3Agent:
+    def __init__(self, aws_secret_access_key: str,model: str ):
+        self.client = boto3.client("bedrock-runtime", region_name="us-east-1", aws_access_key_id="AKIAZR6ZJPKTKJAMLP5W",
+                                   aws_secret_access_key=aws_secret_access_key)
+        if model == "SONNET":
+            self.model = Model.CLAUDE3_SONNET
+        elif model == "HAIKU":
+            self.model = Model.CLAUDE3_HAIKU
+        else:
+            raise ValueError("Invalid model type. Please choose from 'SONNET' or 'HAIKU' models.")
+
+    def invoke(self, text: str,**kwargs) -> str:
+        try:
+            body = json.dumps(
+                {
+                    "anthropic_version": "bedrock-2023-05-31",
+                    "messages": [
+                        {"role": "user", "content": [{"type": "text", "text": text}]}
+                    ],
+                    **kwargs
+                }
+            )
+            response = self.client.invoke_model(modelId=self.model.value, body=body)
+            completion = json.loads(response["body"].read())["content"][0]["text"]
+            return completion
+        except ClientError:
+            logging.error("Couldn't invoke model")
+            raise
 
 class ContentFormatter:
     @staticmethod
@@ -53,3 +96,7 @@ class GPTAgent:
             **kwargs
         )
         return response.choices[0].message.content
+
+if __name__ == '__main__':
+    agent = Claude3Agent("TyzS1CYdvhYtes+V9u2qqS5sggS3asSeXAfYYvOS", "SONNET")
+    print(agent.invoke("I am a software engineer.", max_tokens=200, temperature=0.5))