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https://github.com/arc53/DocsGPT.git
synced 2025-11-29 08:33:20 +00:00
fix: linting issue
This commit is contained in:
@@ -4,7 +4,6 @@ import shutil
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import uuid
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from urllib.parse import urlparse
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import requests
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from bson.binary import Binary, UuidRepresentation
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from bson.dbref import DBRef
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from bson.objectid import ObjectId
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@@ -30,7 +29,9 @@ user_logs_collection = db["user_logs"]
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user = Blueprint("user", __name__)
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current_dir = os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
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current_dir = os.path.dirname(
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os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
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)
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def generate_minute_range(start_date, end_date):
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@@ -81,7 +82,9 @@ def get_conversations():
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conversations = conversations_collection.find().sort("date", -1).limit(30)
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list_conversations = []
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for conversation in conversations:
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list_conversations.append({"id": str(conversation["_id"]), "name": conversation["name"]})
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list_conversations.append(
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{"id": str(conversation["_id"]), "name": conversation["name"]}
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)
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# list_conversations = [{"id": "default", "name": "default"}, {"id": "jeff", "name": "jeff"}]
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@@ -112,7 +115,12 @@ def api_feedback():
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question = data["question"]
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answer = data["answer"]
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feedback = data["feedback"]
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new_doc = {"question": question, "answer": answer, "feedback": feedback, "timestamp": datetime.datetime.now(datetime.timezone.utc)}
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new_doc = {
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"question": question,
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"answer": answer,
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"feedback": feedback,
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"timestamp": datetime.datetime.now(datetime.timezone.utc),
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}
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if "api_key" in data:
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new_doc["api_key"] = data["api_key"]
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feedback_collection.insert_one(new_doc)
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@@ -138,24 +146,31 @@ def delete_by_ids():
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def delete_old():
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"""Delete old indexes."""
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import shutil
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source_id = request.args.get("source_id")
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doc = sources_collection.find_one({
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"_id": ObjectId(source_id),
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"user": "local",
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})
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if(doc is None):
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return {"status":"not found"},404
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doc = sources_collection.find_one(
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{
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"_id": ObjectId(source_id),
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"user": "local",
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}
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)
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if doc is None:
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return {"status": "not found"}, 404
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if settings.VECTOR_STORE == "faiss":
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try:
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shutil.rmtree(os.path.join(current_dir, str(doc["_id"])))
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except FileNotFoundError:
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pass
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else:
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vetorstore = VectorCreator.create_vectorstore(settings.VECTOR_STORE, source_id=str(doc["_id"]))
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vetorstore = VectorCreator.create_vectorstore(
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settings.VECTOR_STORE, source_id=str(doc["_id"])
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)
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vetorstore.delete_index()
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sources_collection.delete_one({
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"_id": ObjectId(source_id),
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})
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sources_collection.delete_one(
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{
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"_id": ObjectId(source_id),
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}
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)
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return {"status": "ok"}
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@@ -189,7 +204,9 @@ def upload_file():
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file.save(os.path.join(temp_dir, filename))
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# Use shutil.make_archive to zip the temp directory
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zip_path = shutil.make_archive(base_name=os.path.join(save_dir, job_name), format="zip", root_dir=temp_dir)
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zip_path = shutil.make_archive(
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base_name=os.path.join(save_dir, job_name), format="zip", root_dir=temp_dir
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)
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final_filename = os.path.basename(zip_path)
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# Clean up the temporary directory after zipping
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@@ -231,7 +248,9 @@ def upload_remote():
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source_data = request.form["data"]
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if source_data:
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task = ingest_remote.delay(source_data=source_data, job_name=job_name, user=user, loader=source)
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task = ingest_remote.delay(
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source_data=source_data, job_name=job_name, user=user, loader=source
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)
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task_id = task.id
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return {"status": "ok", "task_id": task_id}
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else:
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@@ -276,7 +295,9 @@ def combined_json():
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"model": settings.EMBEDDINGS_NAME,
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"location": "local",
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"tokens": index["tokens"] if ("tokens" in index.keys()) else "",
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"retriever": index["retriever"] if ("retriever" in index.keys()) else "classic",
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"retriever": (
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index["retriever"] if ("retriever" in index.keys()) else "classic"
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),
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}
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)
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if "duckduck_search" in settings.RETRIEVERS_ENABLED:
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@@ -345,7 +366,9 @@ def get_prompts():
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list_prompts.append({"id": "creative", "name": "creative", "type": "public"})
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list_prompts.append({"id": "strict", "name": "strict", "type": "public"})
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for prompt in prompts:
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list_prompts.append({"id": str(prompt["_id"]), "name": prompt["name"], "type": "private"})
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list_prompts.append(
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{"id": str(prompt["_id"]), "name": prompt["name"], "type": "private"}
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)
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return jsonify(list_prompts)
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@@ -354,15 +377,21 @@ def get_prompts():
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def get_single_prompt():
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prompt_id = request.args.get("id")
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if prompt_id == "default":
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with open(os.path.join(current_dir, "prompts", "chat_combine_default.txt"), "r") as f:
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with open(
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os.path.join(current_dir, "prompts", "chat_combine_default.txt"), "r"
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) as f:
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chat_combine_template = f.read()
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return jsonify({"content": chat_combine_template})
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elif prompt_id == "creative":
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with open(os.path.join(current_dir, "prompts", "chat_combine_creative.txt"), "r") as f:
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with open(
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os.path.join(current_dir, "prompts", "chat_combine_creative.txt"), "r"
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) as f:
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chat_reduce_creative = f.read()
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return jsonify({"content": chat_reduce_creative})
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elif prompt_id == "strict":
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with open(os.path.join(current_dir, "prompts", "chat_combine_strict.txt"), "r") as f:
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with open(
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os.path.join(current_dir, "prompts", "chat_combine_strict.txt"), "r"
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) as f:
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chat_reduce_strict = f.read()
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return jsonify({"content": chat_reduce_strict})
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@@ -391,7 +420,9 @@ def update_prompt_name():
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# check if name is null
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if name == "":
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return {"status": "error"}
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prompts_collection.update_one({"_id": ObjectId(id)}, {"$set": {"name": name, "content": content}})
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prompts_collection.update_one(
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{"_id": ObjectId(id)}, {"$set": {"name": name, "content": content}}
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)
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return {"status": "ok"}
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@@ -401,7 +432,7 @@ def get_api_keys():
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keys = api_key_collection.find({"user": user})
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list_keys = []
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for key in keys:
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if "source" in key and isinstance(key["source"],DBRef):
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if "source" in key and isinstance(key["source"], DBRef):
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source = db.dereference(key["source"])
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if source is None:
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continue
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@@ -411,7 +442,7 @@ def get_api_keys():
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source_name = key["retriever"]
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else:
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continue
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list_keys.append(
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{
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"id": str(key["_id"]),
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@@ -471,8 +502,10 @@ def share_conversation():
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conversation_id = data["conversation_id"]
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isPromptable = request.args.get("isPromptable").lower() == "true"
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conversation = conversations_collection.find_one({"_id": ObjectId(conversation_id)})
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if(conversation is None):
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conversation = conversations_collection.find_one(
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{"_id": ObjectId(conversation_id)}
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)
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if conversation is None:
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raise Exception("Conversation does not exist")
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current_n_queries = len(conversation["queries"])
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@@ -484,24 +517,24 @@ def share_conversation():
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chunks = "2" if "chunks" not in data else data["chunks"]
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name = conversation["name"] + "(shared)"
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new_api_key_data = {
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"prompt_id": prompt_id,
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"chunks": chunks,
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"user": user,
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}
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new_api_key_data = {
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"prompt_id": prompt_id,
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"chunks": chunks,
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"user": user,
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}
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if "source" in data and ObjectId.is_valid(data["source"]):
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new_api_key_data["source"] = DBRef("sources",ObjectId(data["source"]))
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new_api_key_data["source"] = DBRef("sources", ObjectId(data["source"]))
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elif "retriever" in data:
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new_api_key_data["retriever"] = data["retriever"]
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pre_existing_api_document = api_key_collection.find_one(
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new_api_key_data
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)
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pre_existing_api_document = api_key_collection.find_one(new_api_key_data)
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if pre_existing_api_document:
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api_uuid = pre_existing_api_document["key"]
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pre_existing = shared_conversations_collections.find_one(
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{
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"conversation_id": DBRef("conversations", ObjectId(conversation_id)),
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"conversation_id": DBRef(
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"conversations", ObjectId(conversation_id)
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),
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"isPromptable": isPromptable,
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"first_n_queries": current_n_queries,
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"user": user,
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@@ -532,33 +565,39 @@ def share_conversation():
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"api_key": api_uuid,
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}
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)
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return jsonify({"success": True, "identifier": str(explicit_binary.as_uuid())})
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return jsonify(
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{"success": True, "identifier": str(explicit_binary.as_uuid())}
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)
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else:
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api_uuid = str(uuid.uuid4())
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new_api_key_data["key"] = api_uuid
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new_api_key_data["name"] = name
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if "source" in data and ObjectId.is_valid(data["source"]):
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new_api_key_data["source"] = DBRef("sources", ObjectId(data["source"]))
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new_api_key_data["source"] = DBRef(
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"sources", ObjectId(data["source"])
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)
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if "retriever" in data:
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new_api_key_data["retriever"] = data["retriever"]
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api_key_collection.insert_one(new_api_key_data)
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shared_conversations_collections.insert_one(
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{
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"uuid": explicit_binary,
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"conversation_id": {
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"$ref": "conversations",
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"$id": ObjectId(conversation_id),
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},
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"isPromptable": isPromptable,
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"first_n_queries": current_n_queries,
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"user": user,
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"api_key": api_uuid,
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}
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)
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{
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"uuid": explicit_binary,
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"conversation_id": {
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"$ref": "conversations",
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"$id": ObjectId(conversation_id),
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},
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"isPromptable": isPromptable,
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"first_n_queries": current_n_queries,
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"user": user,
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"api_key": api_uuid,
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}
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)
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## Identifier as route parameter in frontend
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return (
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jsonify({"success": True, "identifier": str(explicit_binary.as_uuid())}),
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jsonify(
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{"success": True, "identifier": str(explicit_binary.as_uuid())}
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),
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201,
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)
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@@ -573,7 +612,9 @@ def share_conversation():
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)
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if pre_existing is not None:
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return (
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jsonify({"success": True, "identifier": str(pre_existing["uuid"].as_uuid())}),
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jsonify(
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{"success": True, "identifier": str(pre_existing["uuid"].as_uuid())}
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),
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200,
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)
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else:
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@@ -591,7 +632,9 @@ def share_conversation():
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)
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## Identifier as route parameter in frontend
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return (
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jsonify({"success": True, "identifier": str(explicit_binary.as_uuid())}),
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jsonify(
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{"success": True, "identifier": str(explicit_binary.as_uuid())}
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),
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201,
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)
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except Exception as err:
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@@ -603,10 +646,16 @@ def share_conversation():
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@user.route("/api/shared_conversation/<string:identifier>", methods=["GET"])
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def get_publicly_shared_conversations(identifier: str):
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try:
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query_uuid = Binary.from_uuid(uuid.UUID(identifier), UuidRepresentation.STANDARD)
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query_uuid = Binary.from_uuid(
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uuid.UUID(identifier), UuidRepresentation.STANDARD
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)
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shared = shared_conversations_collections.find_one({"uuid": query_uuid})
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conversation_queries = []
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if shared and "conversation_id" in shared and isinstance(shared["conversation_id"], DBRef):
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if (
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shared
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and "conversation_id" in shared
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and isinstance(shared["conversation_id"], DBRef)
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):
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# Resolve the DBRef
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conversation_ref = shared["conversation_id"]
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conversation = db.dereference(conversation_ref)
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@@ -620,7 +669,9 @@ def get_publicly_shared_conversations(identifier: str):
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),
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404,
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)
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conversation_queries = conversation["queries"][: (shared["first_n_queries"])]
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conversation_queries = conversation["queries"][
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: (shared["first_n_queries"])
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]
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for query in conversation_queries:
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query.pop("sources") ## avoid exposing sources
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else:
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