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yash bhaskar
commited on
Commit
·
b54f15f
1
Parent(s):
7f02691
Modifying Config Files
Browse files
Agents/rankerAgent.py
CHANGED
@@ -1,14 +1,14 @@
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import json
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from together import Together
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def rerank_best_answer(json_files, config_file='config.json', model="meta-llama/Llama-3-8b-chat-hf"):
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# Load API key from configuration file
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with open(config_file, 'r') as file:
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config = json.load(file)
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if not together_ai_key:
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raise ValueError("TOGETHER_AI
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# Initialize Together client
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client = Together(api_key=together_ai_key)
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@@ -81,12 +81,10 @@ Just Output the best_answer from above JSON and nothing else.
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def rankerAgent(prompt, config_file='config.json', model="meta-llama/Meta-Llama-3.1-8B-Instruct-Turbo"):
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# Load API key from configuration file
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config = json.load(file)
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together_ai_key = config.get("TOGETHER_AI")
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if not together_ai_key:
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raise ValueError("TOGETHER_AI
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# Initialize Together client
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client = Together(api_key=together_ai_key)
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@@ -131,28 +129,3 @@ Just Output the best_answer from above JSON and nothing else.
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return response_bestModel.choices[0].message.content, response_bestAnswer.choices[0].message.content
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# # Usage example
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# json_files = ["../QnA_Eval/Responses/BOW_1_2_top_100_response.json",
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# "../QnA_Eval/Responses/BOW_1_2_top_100_modified_response.json",
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# "../QnA_Eval/Responses/tf-idf_1_2_top_100_response.json",
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# "../QnA_Eval/Responses/tf-idf_1_2_top_100_modified_response.json",
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# "../QnA_Eval/Responses/bm25_1_2_top_100_response.json",
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# "../QnA_Eval/Responses/bm25_1_2_top_100_modified_response.json",
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# "../QnA_Eval/Responses/open_source_1_2_top_100_response.json",
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# "../QnA_Eval/Responses/open_source_1_2_top_100_modified_response.json",
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# "../QnA_Eval/Responses/vision_1_2_top_100_response.json",
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# "../QnA_Eval/Responses/vision_1_2_top_100_modified_response.json",
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# "../QnA_Eval/Responses/ZeroShot_response.json",
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# "../QnA_Eval/Responses/WikiAgent_response.json",
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# "../QnA_Eval/Responses/WikiAgent_response_modified.json",
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# "../QnA_Eval/Responses/LlamaAgent_response.json",
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# "../QnA_Eval/Responses/LlamaAgent_response_modified.json",
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# "../QnA_Eval/Responses/tf_idf_bm25_open_1_2_top_100_combined_response.json", "../QnA_Eval/Responses/tf_idf_bm25_open_1_2_top_100_combined_modified_response.json", "../QnA_Eval/Responses/tf_idf_bm25_open_1_2_top_100_combined_both_response.json"]
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# config_file = "../config.json"
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# result = rerank_best_answer(json_files, config_file)
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# with open("reranked_best_answers_1_2.json", 'w') as file:
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# json.dump(result, file, indent=4, ensure_ascii=False)
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import json
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import os
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from together import Together
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def rerank_best_answer(json_files, config_file='config.json', model="meta-llama/Llama-3-8b-chat-hf"):
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# Load API key from configuration file
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together_ai_key = os.getenv("TOGETHER_AI")
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if not together_ai_key:
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raise ValueError("TOGETHER_AI environment variable not found. Please set it before running the script.")
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# Initialize Together client
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client = Together(api_key=together_ai_key)
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def rankerAgent(prompt, config_file='config.json', model="meta-llama/Meta-Llama-3.1-8B-Instruct-Turbo"):
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# Load API key from configuration file
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together_ai_key = os.getenv("TOGETHER_AI")
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if not together_ai_key:
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raise ValueError("TOGETHER_AI environment variable not found. Please set it before running the script.")
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# Initialize Together client
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client = Together(api_key=together_ai_key)
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return response_bestModel.choices[0].message.content, response_bestAnswer.choices[0].message.content
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Agents/togetherAIAgent.py
CHANGED
@@ -1,4 +1,4 @@
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import json
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from together import Together
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def generate_article_from_query(query, config_file='config.json', model="meta-llama/Llama-3-8b-chat-hf"):
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Returns:
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- str: The generated article content.
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"""
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# Load API key from configuration file
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with open(config_file, 'r') as file:
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config = json.load(file)
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together_ai_key =
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if not together_ai_key:
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raise ValueError("TOGETHER_AI
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# Initialize Together client
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client = Together(api_key=together_ai_key)
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import json, os
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from together import Together
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def generate_article_from_query(query, config_file='config.json', model="meta-llama/Llama-3-8b-chat-hf"):
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Returns:
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- str: The generated article content.
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"""
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together_ai_key = os.getenv("TOGETHER_AI")
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if not together_ai_key:
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raise ValueError("TOGETHER_AI environment variable not found. Please set it before running the script.")
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# Initialize Together client
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client = Together(api_key=together_ai_key)
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AnswerGeneration/getAnswer.py
CHANGED
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from together import Together
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def generate_answer_withContext(question, context):
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together_ai_key = config.get("TOGETHER_AI")
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client = Together(api_key=together_ai_key)
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@@ -26,10 +26,10 @@ Question: {question}
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def generate_answer_zeroShot(question):
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together_ai_key = config.get("TOGETHER_AI")
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client = Together(api_key=together_ai_key)
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from together import Together
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def generate_answer_withContext(question, context):
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together_ai_key = os.getenv("TOGETHER_AI")
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if not together_ai_key:
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raise ValueError("TOGETHER_AI environment variable not found. Please set it before running the script.")
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client = Together(api_key=together_ai_key)
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def generate_answer_zeroShot(question):
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together_ai_key = os.getenv("TOGETHER_AI")
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if not together_ai_key:
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raise ValueError("TOGETHER_AI environment variable not found. Please set it before running the script.")
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client = Together(api_key=together_ai_key)
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Query_Modification/QueryModification.py
CHANGED
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import json
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import pandas as pd
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import google.generativeai as genai
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# Function to process text input with Gemini model
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def query_Modifier(input_text):
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gemini_key = config.get("GEMINI")
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# Initialize the API key
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genai.configure(api_key=gemini_key)
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def getKeywords(input_text):
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# Extract keywords from the input text
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gemini_key = config.get("GEMINI")
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# Initialize the API key
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genai.configure(api_key=gemini_key)
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import json, os
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import pandas as pd
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import google.generativeai as genai
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# Function to process text input with Gemini model
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def query_Modifier(input_text):
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gemini_key = os.getenv("GEMINI")
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if not gemini_key:
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raise ValueError("GEMINI environment variable not found. Please set it before running the script.")
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# Initialize the API key
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genai.configure(api_key=gemini_key)
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def getKeywords(input_text):
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# Extract keywords from the input text
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gemini_key = os.getenv("GEMINI")
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if not gemini_key:
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raise ValueError("GEMINI environment variable not found. Please set it before running the script.")
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# Initialize the API key
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genai.configure(api_key=gemini_key)
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