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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,24 @@ | ||
| from dataclasses import dataclass | ||
| from enum import Enum, auto | ||
| from typing import Optional | ||
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| class DocumentType(Enum): | ||
| """ | ||
| Enum for supporting document type. | ||
| """ | ||
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| TEXT = auto() | ||
| HTML = auto() | ||
| PDF = auto() | ||
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| @dataclass | ||
| class Document: | ||
| """ | ||
| A wrapper of graph store query results. | ||
| """ | ||
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| doctype: DocumentType | ||
| data: Optional[object] = None | ||
| path_or_url: Optional[str] = "" |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,51 @@ | ||
| from dataclasses import dataclass, field | ||
| from typing import List, Optional, Protocol | ||
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| from .document import Document | ||
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| @dataclass | ||
| class GraphStoreQueryResult: | ||
| """ | ||
| A wrapper of graph store query results. | ||
| answer: human readable answer to question/query. | ||
| results: intermediate results to question/query, e.g. node entities. | ||
| """ | ||
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| answer: Optional[str] = None | ||
| results: list = field(default_factory=list) | ||
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| class GraphQueryEngine(Protocol): | ||
| """An abstract base class that represents a graph query engine on top of a underlying graph database. | ||
| This interface defines the basic methods for graph rag. | ||
| """ | ||
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| def init_db(self, input_doc: List[Document] | None = None): | ||
| """ | ||
| This method initializes graph database with the input documents or records. | ||
| Usually, it takes the following steps, | ||
| 1. connecting to a graph database. | ||
| 2. extract graph nodes, edges based on input data, graph schema and etc. | ||
| 3. build indexes etc. | ||
| Args: | ||
| input_doc: a list of input documents that are used to build the graph in database. | ||
| Returns: GraphStore | ||
| """ | ||
| pass | ||
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| def add_records(self, new_records: List) -> bool: | ||
| """ | ||
| Add new records to the underlying database and add to the graph if required. | ||
| """ | ||
| pass | ||
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| def query(self, question: str, n_results: int = 1, **kwargs) -> GraphStoreQueryResult: | ||
| """ | ||
| This method transform a string format question into database query and return the result. | ||
| """ | ||
| pass |
56 changes: 56 additions & 0 deletions
56
autogen/agentchat/contrib/graph_rag/graph_rag_capability.py
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,56 @@ | ||
| from autogen.agentchat.contrib.capabilities.agent_capability import AgentCapability | ||
| from autogen.agentchat.conversable_agent import ConversableAgent | ||
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| from .graph_query_engine import GraphQueryEngine | ||
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| class GraphRagCapability(AgentCapability): | ||
| """ | ||
| A graph rag capability uses a graph query engine to give a conversable agent the graph rag ability. | ||
| An agent class with graph rag capability could | ||
| 1. create a graph in the underlying database with input documents. | ||
| 2. retrieved relevant information based on messages received by the agent. | ||
| 3. generate answers from retrieved information and send messages back. | ||
| For example, | ||
| graph_query_engine = GraphQueryEngine(...) | ||
| graph_query_engine.init_db([Document(doc1), Document(doc2), ...]) | ||
| graph_rag_agent = ConversableAgent( | ||
| name="graph_rag_agent", | ||
| max_consecutive_auto_reply=3, | ||
| ... | ||
| ) | ||
| graph_rag_capability = GraphRagCapbility(graph_query_engine) | ||
| graph_rag_capability.add_to_agent(graph_rag_agent) | ||
| user_proxy = UserProxyAgent( | ||
| name="user_proxy", | ||
| code_execution_config=False, | ||
| is_termination_msg=lambda msg: "TERMINATE" in msg["content"], | ||
| human_input_mode="ALWAYS", | ||
| ) | ||
| user_proxy.initiate_chat(graph_rag_agent, message="Name a few actors who've played in 'The Matrix'") | ||
| # ChatResult( | ||
| # chat_id=None, | ||
| # chat_history=[ | ||
| # {'content': 'Name a few actors who've played in \'The Matrix\'', 'role': 'graph_rag_agent'}, | ||
| # {'content': 'A few actors who have played in The Matrix are: | ||
| # - Keanu Reeves | ||
| # - Laurence Fishburne | ||
| # - Carrie-Anne Moss | ||
| # - Hugo Weaving', | ||
| # 'role': 'user_proxy'}, | ||
| # ...) | ||
| """ | ||
|
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| def __init__(self, query_engine: GraphQueryEngine): | ||
| """ | ||
| initialize graph rag capability with a graph query engine | ||
| """ | ||
| ... | ||
|
|
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| def add_to_agent(self, agent: ConversableAgent): ... |
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37 changes: 37 additions & 0 deletions
37
dotnet/sample/AutoGen.OpenAI.Sample/Connect_To_OpenAI_o1_preview.cs
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| Original file line number | Diff line number | Diff line change |
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| @@ -0,0 +1,37 @@ | ||
| // Copyright (c) Microsoft Corporation. All rights reserved. | ||
| // Connect_To_OpenAI_o1_preview.cs | ||
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| using AutoGen.Core; | ||
| using OpenAI; | ||
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| namespace AutoGen.OpenAI.Sample; | ||
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| public class Connect_To_OpenAI_o1_preview | ||
| { | ||
| public static async Task RunAsync() | ||
| { | ||
| #region create_agent | ||
| var apiKey = Environment.GetEnvironmentVariable("OPENAI_API_KEY") ?? throw new InvalidOperationException("Please set environment variable OPENAI_API_KEY"); | ||
| var openAIClient = new OpenAIClient(apiKey); | ||
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| // until 2024/09/12 | ||
| // openai o1-preview doesn't support systemMessage, temperature, maxTokens, streaming output | ||
| // so in order to use OpenAIChatAgent with o1-preview, you need to set those parameters to null | ||
| var agent = new OpenAIChatAgent( | ||
| chatClient: openAIClient.GetChatClient("o1-preview"), | ||
| name: "assistant", | ||
| systemMessage: null, | ||
| temperature: null, | ||
| maxTokens: null, | ||
| seed: 0) | ||
| // by using RegisterMiddleware instead of RegisterStreamingMiddleware | ||
| // it turns an IStreamingAgent into an IAgent and disables streaming | ||
| .RegisterMiddleware(new OpenAIChatRequestMessageConnector()) | ||
| .RegisterPrintMessage(); | ||
| #endregion create_agent | ||
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| #region send_message | ||
| await agent.SendAsync("Can you write a piece of C# code to calculate 100th of fibonacci?"); | ||
| #endregion send_message | ||
| } | ||
| } |
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