Duplicate from iamplus/Conversational_Data

.gitattributes

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+*.arrow filter=lfs diff=lfs merge=lfs -text
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+*.pcm filter=lfs diff=lfs merge=lfs -text
+*.sam filter=lfs diff=lfs merge=lfs -text
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+openassistant_oasst1_conversation_deep_clean_lang_en_split.json filter=lfs diff=lfs merge=lfs -text
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+baize_medical.json filter=lfs diff=lfs merge=lfs -text
+baize_quora.json filter=lfs diff=lfs merge=lfs -text
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+baize_stackoverflow.json filter=lfs diff=lfs merge=lfs -text
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README.md

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+---
+license: apache-2.0
+---
+
+Respective Repos are in **manojpreveen/ConversationalRepo**
+
+Post-Process Code Info : 
+
+* data_process_conv.py
+* data_process_conv_split.py
+
+Datasets Info : 
+
+1. sharegpt_deep_clean_lang_en.json - ***https://huggingface.co/datasets/manojpreveen/ConversationalRepo/tree/main/sharegpt-raw***
+
+2. openassistant_oasst1_conversation_deep_clean_lang_en.json - ***https://huggingface.co/datasets/manojpreveen/ConversationalRepo/tree/main/OpenAssistant***
+
+3. ultrachat.json - ***https://huggingface.co/datasets/manojpreveen/ConversationalRepo/tree/main/ultrachat***
+
+4. baize_medical.json - ***https://huggingface.co/datasets/manojpreveen/ConversationalRepo/tree/main/baize***
+
+5. baize_quora.json - ***https://huggingface.co/datasets/manojpreveen/ConversationalRepo/tree/main/baize***
+
+6. baize_stackoverflow.json - ***https://huggingface.co/datasets/manojpreveen/ConversationalRepo/tree/main/baize***
+
+7. camel_ai_society.json - ***https://huggingface.co/datasets/manojpreveen/ConversationalRepo/tree/main/camel***
+
+8. camel_code.json - ***https://huggingface.co/datasets/manojpreveen/ConversationalRepo/tree/main/camel***
+
+9. iamai_roleplay.json - ***https://huggingface.co/datasets/manojpreveen/ConversationalRepo/tree/main/roleplay***
+

baize_medical.json

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baize_quora.json

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data_process_conv.py

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+import json
+from tqdm import tqdm
+import pandas as pd 
+
+in_file_1 = "openassistant_oasst1_conversation_deep_clean_lang_en.json"
+in_file_2 = "sharegpt_deep_clean_lang_en.json"
+in_file_3 = "ultrachat.json"
+in_file_4 = "camel_code.json"
+in_file_5 = "camel_ai_society.json"
+in_file_6 = "baize_stackoverflow.json"
+in_file_7 = "baize_quora.json"
+in_file_8 = "baize_medical.json"
+in_file_9 = "iamai_roleplay.json"
+
+content_1 = json.load(open(in_file_1, "r"))
+content_2 = json.load(open(in_file_2, "r"))
+content_3 = json.load(open(in_file_3, "r"))
+content_4 = json.load(open(in_file_4, "r"))
+content_5 = json.load(open(in_file_5, "r"))
+content_6 = json.load(open(in_file_6, "r"))
+content_7 = json.load(open(in_file_7, "r"))
+content_8 = json.load(open(in_file_8, "r"))
+content_9 = json.load(open(in_file_9, "r"))
+
+data = {"text":[]}
+
+def preprocess(text):
+    text = text.replace("AI language model", "Artificial intelligence Language Model")
+    text = text.replace("AI assistant", "Artificial intelligence Assistant")
+    text = text.replace("AI model", "Artificial intelligence Language Model")
+    text = text.replace("openai", "iam+").replace("OpenAI", "iam+").replace("OPENAI", "iam+").replace("Openai", "iam+")
+    return text
+
+content_list = [content_1, content_2, content_3, content_4, content_5, content_6, content_7, content_8, content_9]
+for content in content_list:
+    for conv in tqdm(content):
+        final_text = ""
+        final_list = conv["conversations"]
+        for val in final_list:
+            if val["from"] in ["human", "user"]:
+                text = "<human>: " + val["value"].strip("\n")
+            else:
+                text = "<bot>: " + val["value"].strip("\n")
+            if final_text == "":
+                final_text = text
+            else:
+                if text.startswith("<human>"):
+                    final_text += " ###\n" + text
+                else:
+                    final_text += "\n" + text
+        final_text += " ###\n"
+        final_text = preprocess(final_text)
+        data["text"].append(final_text)
+
+final_df = pd.DataFrame(data)
+final_df = final_df.sample(frac = 1)
+print(len(final_df))
+final_df.to_csv("iamai_conversation_data.csv", header=True, index=False)

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