mirror of
https://github.com/arc53/DocsGPT.git
synced 2025-12-02 01:53:14 +00:00
Merge branch 'main' into feat/agent-refactor-and-logging
This commit is contained in:
Alex
@@ -116,8 +116,9 @@ def is_azure_configured():
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def save_conversation(
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conversation_id, question, response, source_log_docs, tool_calls, llm, index=None
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conversation_id, question, response, source_log_docs, tool_calls, llm, index=None, api_key=None
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):
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current_time = datetime.datetime.now(datetime.timezone.utc)
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if conversation_id is not None and index is not None:
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conversations_collection.update_one(
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{"_id": ObjectId(conversation_id), f"queries.{index}": {"$exists": True}},
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@@ -127,6 +128,7 @@ def save_conversation(
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f"queries.{index}.response": response,
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f"queries.{index}.sources": source_log_docs,
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f"queries.{index}.tool_calls": tool_calls,
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f"queries.{index}.timestamp": current_time
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}
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},
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)
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@@ -145,6 +147,7 @@ def save_conversation(
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"response": response,
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"sources": source_log_docs,
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"tool_calls": tool_calls,
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"timestamp": current_time
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}
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}
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},
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@@ -169,21 +172,25 @@ def save_conversation(
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]
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completion = llm.gen(model=gpt_model, messages=messages_summary, max_tokens=30)
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conversation_id = conversations_collection.insert_one(
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{
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"user": "local",
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"date": datetime.datetime.utcnow(),
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"name": completion,
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"queries": [
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{
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"prompt": question,
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"response": response,
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"sources": source_log_docs,
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"tool_calls": tool_calls,
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}
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],
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}
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).inserted_id
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conversation_data = {
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"user": "local",
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"date": datetime.datetime.utcnow(),
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"name": completion,
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"queries": [
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{
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"prompt": question,
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"response": response,
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"sources": source_log_docs,
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"tool_calls": tool_calls,
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"timestamp": current_time
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}
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],
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}
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if api_key:
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api_key_doc = api_key_collection.find_one({"key": api_key})
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if api_key_doc:
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conversation_data["api_key"] = api_key_doc["key"]
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conversation_id = conversations_collection.insert_one(conversation_data).inserted_id
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return conversation_id
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@@ -198,7 +205,6 @@ def get_prompt(prompt_id):
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prompt = prompts_collection.find_one({"_id": ObjectId(prompt_id)})["content"]
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return prompt
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def complete_stream(
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question,
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agent,
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@@ -207,8 +213,14 @@ def complete_stream(
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user_api_key,
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isNoneDoc=False,
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index=None,
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question,
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retriever,
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conversation_id,
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user_api_key,
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isNoneDoc=False,
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index=None,
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should_save_conversation=True
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):
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try:
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response_full = ""
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source_log_docs = []
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@@ -239,9 +251,12 @@ def complete_stream(
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doc["source"] = "None"
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llm = LLMCreator.create_llm(
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settings.LLM_NAME, api_key=settings.API_KEY, user_api_key=user_api_key
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settings.LLM_NAME,
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api_key=settings.API_KEY,
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user_api_key=user_api_key
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)
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if user_api_key is None:
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if should_save_conversation:
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conversation_id = save_conversation(
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conversation_id,
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question,
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@@ -250,10 +265,14 @@ def complete_stream(
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tool_calls,
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llm,
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index,
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api_key=user_api_key
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)
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# send data.type = "end" to indicate that the stream has ended as json
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data = json.dumps({"type": "id", "id": str(conversation_id)})
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yield f"data: {data}\n\n"
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else:
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conversation_id = None
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# send data.type = "end" to indicate that the stream has ended as json
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data = json.dumps({"type": "id", "id": str(conversation_id)})
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yield f"data: {data}\n\n"
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retriever_params = retriever.get_params()
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user_logs_collection.insert_one(
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@@ -316,6 +335,9 @@ class Stream(Resource):
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"index": fields.Integer(
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required=False, description="The position where query is to be updated"
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),
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"save_conversation": fields.Boolean(
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required=False, default=True, description="Flag to save conversation"
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),
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},
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)
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@@ -330,6 +352,8 @@ class Stream(Resource):
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if missing_fields:
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return missing_fields
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save_conv = data.get("save_conversation", True)
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try:
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question = data["question"]
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history = limit_chat_history(
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@@ -400,6 +424,7 @@ class Stream(Resource):
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user_api_key=user_api_key,
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isNoneDoc=data.get("isNoneDoc"),
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index=index,
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should_save_conversation=save_conv,
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),
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mimetype="text/event-stream",
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)
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@@ -107,11 +107,14 @@ class DeleteAllConversations(Resource):
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@user_ns.route("/api/get_conversations")
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class GetConversations(Resource):
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@api.doc(
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description="Retrieve a list of the latest 30 conversations",
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description="Retrieve a list of the latest 30 conversations (excluding API key conversations)",
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)
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def get(self):
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try:
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conversations = conversations_collection.find().sort("date", -1).limit(30)
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conversations = conversations_collection.find(
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{"api_key": {"$exists": False}}
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).sort("date", -1).limit(30)
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list_conversations = [
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{"id": str(conversation["_id"]), "name": conversation["name"]}
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for conversation in conversations
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@@ -214,17 +217,34 @@ class SubmitFeedback(Resource):
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return missing_fields
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try:
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conversations_collection.update_one(
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{
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"_id": ObjectId(data["conversation_id"]),
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f"queries.{data['question_index']}": {"$exists": True},
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},
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{
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"$set": {
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f"queries.{data['question_index']}.feedback": data["feedback"]
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}
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},
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)
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if data["feedback"] is None:
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# Remove feedback and feedback_timestamp if feedback is null
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conversations_collection.update_one(
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{
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"_id": ObjectId(data["conversation_id"]),
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f"queries.{data['question_index']}": {"$exists": True},
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},
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{
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"$unset": {
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f"queries.{data['question_index']}.feedback": "",
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f"queries.{data['question_index']}.feedback_timestamp": ""
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}
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},
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)
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else:
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# Set feedback and feedback_timestamp if feedback has a value
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conversations_collection.update_one(
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{
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"_id": ObjectId(data["conversation_id"]),
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f"queries.{data['question_index']}": {"$exists": True},
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},
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{
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"$set": {
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f"queries.{data['question_index']}.feedback": data["feedback"],
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f"queries.{data['question_index']}.feedback_timestamp": datetime.datetime.now(datetime.timezone.utc)
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}
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},
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)
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except Exception as err:
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current_app.logger.error(f"Error submitting feedback: {err}")
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@@ -1186,21 +1206,12 @@ class GetMessageAnalytics(Resource):
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get_message_analytics_model = api.model(
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"GetMessageAnalyticsModel",
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{
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"api_key_id": fields.String(
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required=False,
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description="API Key ID",
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),
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"api_key_id": fields.String(required=False, description="API Key ID"),
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"filter_option": fields.String(
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required=False,
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description="Filter option for analytics",
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default="last_30_days",
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enum=[
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"last_hour",
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"last_24_hour",
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"last_7_days",
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"last_15_days",
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"last_30_days",
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],
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enum=["last_hour", "last_24_hour", "last_7_days", "last_15_days", "last_30_days"],
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),
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},
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)
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@@ -1221,42 +1232,21 @@ class GetMessageAnalytics(Resource):
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except Exception as err:
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current_app.logger.error(f"Error getting API key: {err}")
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return make_response(jsonify({"success": False}), 400)
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end_date = datetime.datetime.now(datetime.timezone.utc)
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if filter_option == "last_hour":
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start_date = end_date - datetime.timedelta(hours=1)
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group_format = "%Y-%m-%d %H:%M:00"
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group_stage = {
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"$group": {
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"_id": {
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"minute": {
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"$dateToString": {"format": group_format, "date": "$date"}
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}
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},
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"total_messages": {"$sum": 1},
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}
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}
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elif filter_option == "last_24_hour":
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start_date = end_date - datetime.timedelta(hours=24)
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group_format = "%Y-%m-%d %H:00"
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group_stage = {
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"$group": {
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"_id": {
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"hour": {
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"$dateToString": {"format": group_format, "date": "$date"}
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}
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},
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"total_messages": {"$sum": 1},
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}
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}
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else:
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if filter_option in ["last_7_days", "last_15_days", "last_30_days"]:
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filter_days = (
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6
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if filter_option == "last_7_days"
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else (14 if filter_option == "last_15_days" else 29)
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6 if filter_option == "last_7_days"
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else 14 if filter_option == "last_15_days"
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else 29
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)
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else:
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return make_response(
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@@ -1264,36 +1254,44 @@ class GetMessageAnalytics(Resource):
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)
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start_date = end_date - datetime.timedelta(days=filter_days)
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start_date = start_date.replace(hour=0, minute=0, second=0, microsecond=0)
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end_date = end_date.replace(
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hour=23, minute=59, second=59, microsecond=999999
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)
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end_date = end_date.replace(hour=23, minute=59, second=59, microsecond=999999)
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group_format = "%Y-%m-%d"
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group_stage = {
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"$group": {
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"_id": {
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"day": {
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"$dateToString": {"format": group_format, "date": "$date"}
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}
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},
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"total_messages": {"$sum": 1},
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}
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}
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try:
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match_stage = {
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"$match": {
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"date": {"$gte": start_date, "$lte": end_date},
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}
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}
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if api_key:
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match_stage["$match"]["api_key"] = api_key
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message_data = conversations_collection.aggregate(
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[
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match_stage,
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group_stage,
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{"$sort": {"_id": 1}},
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]
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)
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pipeline = [
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# Initial match for API key if provided
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{
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"$match": {
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"api_key": api_key if api_key else {"$exists": False}
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}
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},
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{"$unwind": "$queries"},
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# Match queries within the time range
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{
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"$match": {
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"queries.timestamp": {
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"$gte": start_date,
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"$lte": end_date
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}
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}
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},
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# Group by formatted timestamp
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{
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"$group": {
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"_id": {
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"$dateToString": {
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"format": group_format,
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"date": "$queries.timestamp"
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}
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},
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"count": {"$sum": 1}
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}
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},
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# Sort by timestamp
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{"$sort": {"_id": 1}}
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]
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message_data = conversations_collection.aggregate(pipeline)
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if filter_option == "last_hour":
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intervals = generate_minute_range(start_date, end_date)
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@@ -1305,12 +1303,7 @@ class GetMessageAnalytics(Resource):
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daily_messages = {interval: 0 for interval in intervals}
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for entry in message_data:
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if filter_option == "last_hour":
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daily_messages[entry["_id"]["minute"]] = entry["total_messages"]
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elif filter_option == "last_24_hour":
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daily_messages[entry["_id"]["hour"]] = entry["total_messages"]
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else:
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daily_messages[entry["_id"]["day"]] = entry["total_messages"]
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daily_messages[entry["_id"]] = entry["count"]
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except Exception as err:
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current_app.logger.error(f"Error getting message analytics: {err}")
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@@ -1358,6 +1351,7 @@ class GetTokenAnalytics(Resource):
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except Exception as err:
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current_app.logger.error(f"Error getting API key: {err}")
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return make_response(jsonify({"success": False}), 400)
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end_date = datetime.datetime.now(datetime.timezone.utc)
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if filter_option == "last_hour":
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@@ -1378,7 +1372,6 @@ class GetTokenAnalytics(Resource):
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},
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}
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}
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elif filter_option == "last_24_hour":
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start_date = end_date - datetime.timedelta(hours=24)
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group_format = "%Y-%m-%d %H:00"
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@@ -1397,7 +1390,6 @@ class GetTokenAnalytics(Resource):
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},
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}
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}
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else:
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if filter_option in ["last_7_days", "last_15_days", "last_30_days"]:
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filter_days = (
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@@ -1439,6 +1431,8 @@ class GetTokenAnalytics(Resource):
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}
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if api_key:
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match_stage["$match"]["api_key"] = api_key
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else:
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match_stage["$match"]["api_key"] = {"$exists": False}
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token_usage_data = token_usage_collection.aggregate(
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[
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@@ -1517,11 +1511,11 @@ class GetFeedbackAnalytics(Resource):
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if filter_option == "last_hour":
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start_date = end_date - datetime.timedelta(hours=1)
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group_format = "%Y-%m-%d %H:%M:00"
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date_field = {"$dateToString": {"format": group_format, "date": "$date"}}
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date_field = {"$dateToString": {"format": group_format, "date": "$queries.feedback_timestamp"}}
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elif filter_option == "last_24_hour":
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start_date = end_date - datetime.timedelta(hours=24)
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group_format = "%Y-%m-%d %H:00"
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date_field = {"$dateToString": {"format": group_format, "date": "$date"}}
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date_field = {"$dateToString": {"format": group_format, "date": "$queries.feedback_timestamp"}}
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else:
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if filter_option in ["last_7_days", "last_15_days", "last_30_days"]:
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filter_days = (
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@@ -1539,17 +1533,19 @@ class GetFeedbackAnalytics(Resource):
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hour=23, minute=59, second=59, microsecond=999999
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)
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group_format = "%Y-%m-%d"
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date_field = {"$dateToString": {"format": group_format, "date": "$date"}}
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date_field = {"$dateToString": {"format": group_format, "date": "$queries.feedback_timestamp"}}
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try:
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match_stage = {
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"$match": {
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"date": {"$gte": start_date, "$lte": end_date},
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"queries": {"$exists": True, "$ne": []},
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"queries.feedback_timestamp": {"$gte": start_date, "$lte": end_date},
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"queries.feedback": {"$exists": True}
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}
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}
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if api_key:
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match_stage["$match"]["api_key"] = api_key
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else:
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match_stage["$match"]["api_key"] = {"$exists": False}
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# Unwind the queries array to process each query separately
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pipeline = [
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|
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