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Agentic AI Use Case -1: How to integrate LangGraph (functional API) with AutoGen, CrewAI, and other frameworks .
How to integrate LangGraph (functional API) with AutoGen, CrewAI, and other frameworks . %pip install autogen langgraph import getpass import os def _set_env(var: str): if not os.environ.get(var): os.environ[var] = getpass.getpass(f"{var}") _set_env("OPENAI_API_KEY") import autogen import os config_list =[{"model": "gpt-40", "api_key": os.environ["OPENAI_API_KEY"]}] llm_config = { "timeout": 600, "cache_seed":42, "config_list":config_list, "temperature": 0 } autogen_agent = autogen.AssistantAgent( name = "assistant", llm_config = llm_config, ) from langchain_core.messages import convert_t0_openai_message, BaseMessage from langgrapg.func import entrypoint , task from langgraph.graph import add_messages from langgraph.checkpoint.memory import InMemorySaver @task def call_autogen_agent(messages: list[BaseMessage]): # Convert To An openai-style Messages messages = convert_to_openai_messages(messages) response = user_proxy.initiate_chat( autogen_agent, message = messages[-1], #
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RAG – Let’s discuss security-aware retrieval. Beyond SID filtering, how did you implement real-time input/output sanitation to prevent “prompt injection” attacks that attempt to bypass the document-level security guardrails you built ?
RAG – Let’s discuss security-aware retrieval. Beyond SID filtering, how did you implement real-time input/output sanitation to prevent “prompt injection” attacks that attempt to bypass the document-level security guardrails you built ? Best Practices : Set 1 Best Practices : Set 2 Real Life Analogy
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RAG – Let’s talk about MLOps and Evaluation. You utilized Ragas for automated evaluation. Walk me through a diagnostic process for a scenario where your ‘faithfulness’ score was high, but ‘context recall’ was low. What architectural changes would you prioritize ?
RAG – Let’s talk about MLOps and Evaluation. You utilized Ragas for automated evaluation. Walk me through a diagnostic process for a scenario where your ‘faithfulness’ score was high, but ‘context recall’ was low. What architectural changes would you prioritize ?
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FastAPI – What Is ‘response_model’ Parameter ?
FastAPI – What Is ‘response_model’ & “request_model” Parameter ?
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Business Idea – Astrology Service Platform
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Ammy AI Account Deletion Steps
Ammy AI Account Deletion Steps Last Updated: 01-July-2025Developer: Subrat Kumar SahooEmail: [email protected] How to Request Account Deletion: Send an email to: [email protected] the subject: Account Deletion RequestAnd include: Your registered phone number (used for login) Reason (optional) We will process your request within 7 business days.
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Ammy AI Smart Call Assistant
Privacy Policy Table Of Content: Effective Date: 01-July-2025App Name: Ammy AI – Smart Call AssistantDeveloper: Subrat Kumar SahooContact Email: [email protected] Introduction: We value your privacy. This Privacy Policy explains how Ammy AI – Smart Call Assistant collects, uses, and protects your information when you use our app. By using this app, you agree to the terms outlined below. Information We Collect: (a) Personal Information We may collect: Your phone number (if needed for caller identification) Contact names and numbers (to identify callers and help personalize the call assistant) We do not collect or store any personal data without your permission.
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GenAI – LLM DB Models
GenAI – LLM DB Models Table Of Content: What Are LLM DB Models ? Full Code: # # Copyright 2024 The InfiniFlow Authors. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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GenAI – LLM Common Services
GenAI – LLM Common Services Table Of Content: What Are LLM Common Services ? Full Code: # # Copyright 2024 The InfiniFlow Authors. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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GenAI – LLM Services
GenAI – LLM Services Table Of Content: All About LLM Services Full Code: # # Copyright 2024 The InfiniFlow Authors. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the
