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Merge pull request HamaWhiteGG#15 from HamaWhiteGG/dev
Support Agents of Chat models
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136 changes: 136 additions & 0 deletions
136
langchain-core/src/main/java/com/hw/langchain/agents/chat/base/ChatAgent.java
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,136 @@ | ||
| /* | ||
| * Licensed to the Apache Software Foundation (ASF) under one | ||
| * or more contributor license agreements. See the NOTICE file | ||
| * distributed with this work for additional information | ||
| * regarding copyright ownership. The ASF licenses this file | ||
| * to you 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 License for the specific language governing permissions and | ||
| * limitations under the License. | ||
| */ | ||
|
|
||
| package com.hw.langchain.agents.chat.base; | ||
|
|
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| import com.hw.langchain.agents.agent.Agent; | ||
| import com.hw.langchain.agents.agent.AgentOutputParser; | ||
| import com.hw.langchain.agents.chat.output.parser.ChatOutputParser; | ||
| import com.hw.langchain.base.language.BaseLanguageModel; | ||
| import com.hw.langchain.chains.llm.LLMChain; | ||
| import com.hw.langchain.prompts.base.BasePromptTemplate; | ||
| import com.hw.langchain.prompts.chat.BaseMessagePromptTemplate; | ||
| import com.hw.langchain.prompts.chat.ChatPromptTemplate; | ||
| import com.hw.langchain.prompts.chat.HumanMessagePromptTemplate; | ||
| import com.hw.langchain.prompts.chat.SystemMessagePromptTemplate; | ||
| import com.hw.langchain.schema.AgentAction; | ||
| import com.hw.langchain.tools.base.BaseTool; | ||
|
|
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| import org.apache.commons.lang3.tuple.Pair; | ||
|
|
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| import java.util.List; | ||
| import java.util.Map; | ||
|
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| import static com.hw.langchain.agents.chat.prompt.Prompt.*; | ||
| import static com.hw.langchain.agents.utils.Utils.validateToolsSingleInput; | ||
|
|
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| /** | ||
| * @author HamaWhite | ||
| */ | ||
| public class ChatAgent extends Agent { | ||
|
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| public ChatAgent(LLMChain llmChain, List<String> allowedTools, AgentOutputParser outputParser) { | ||
| super(llmChain, allowedTools, outputParser); | ||
| } | ||
|
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| @Override | ||
| public String observationPrefix() { | ||
| return "Observation: "; | ||
| } | ||
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| @Override | ||
| public String llmPrefix() { | ||
| return "Thought:"; | ||
| } | ||
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| @Override | ||
| public String constructScratchpad(List<Pair<AgentAction, String>> intermediateSteps) { | ||
| var agentScratchpad = super.constructScratchpad(intermediateSteps); | ||
| if (!(agentScratchpad instanceof String)) { | ||
| throw new IllegalArgumentException("agent_scratchpad should be of type String."); | ||
| } | ||
| String scratchpad = agentScratchpad.toString(); | ||
| if (!scratchpad.isEmpty()) { | ||
| return "This was your previous work (but I haven't seen any of it! I only see what " | ||
| + "you return as the final answer):\n" + scratchpad; | ||
| } else { | ||
| return scratchpad; | ||
| } | ||
| } | ||
|
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| private static AgentOutputParser getDefaultOutputParser(Map<String, Object> kwargs) { | ||
| return new ChatOutputParser(); | ||
| } | ||
|
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| public static void validateTools(List<BaseTool> tools) { | ||
| validateToolsSingleInput(ChatAgent.class.getSimpleName(), tools); | ||
| } | ||
|
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| @Override | ||
| public List<String> stop() { | ||
| return List.of("Observation:"); | ||
| } | ||
|
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| public static BasePromptTemplate createPrompt(List<BaseTool> tools, String systemMessagePrefix, | ||
| String systemMessageSuffix, String humanMessage, String formatInstructions, List<String> inputVariables) { | ||
| String toolNames = String.join(", ", tools.stream().map(BaseTool::getName).toList()); | ||
| String toolStrings = | ||
| String.join("\n", tools.stream().map(tool -> tool.getName() + ": " + tool.getDescription()).toList()); | ||
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| formatInstructions = formatInstructions.replace("{tool_names}", toolNames); | ||
| // In Python format() method, the curly braces '{{}}' are used to represent the output '{}'. | ||
| formatInstructions = formatInstructions.replace("{{{{", "{{").replace("}}}}", "}}"); | ||
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| String template = | ||
| String.join("\n\n", systemMessagePrefix, toolStrings, formatInstructions, systemMessageSuffix); | ||
|
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| List<BaseMessagePromptTemplate> messages = List.of( | ||
| SystemMessagePromptTemplate.fromTemplate(template), | ||
| HumanMessagePromptTemplate.fromTemplate(humanMessage)); | ||
| if (inputVariables == null) { | ||
| inputVariables = List.of("input", "agent_scratchpad"); | ||
| } | ||
| return new ChatPromptTemplate(inputVariables, messages); | ||
| } | ||
|
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| /** | ||
| * Construct an agent from an LLM and tools. | ||
| */ | ||
| public static Agent fromLLMAndTools(BaseLanguageModel llm, List<BaseTool> tools, Map<String, Object> kwargs) { | ||
| return fromLLMAndTools(llm, tools, null, SYSTEM_MESSAGE_PREFIX, SYSTEM_MESSAGE_SUFFIX, HUMAN_MESSAGE, | ||
| FORMAT_INSTRUCTIONS, null, kwargs); | ||
| } | ||
|
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| /** | ||
| * Construct an agent from an LLM and tools. | ||
| */ | ||
| public static Agent fromLLMAndTools(BaseLanguageModel llm, List<BaseTool> tools, AgentOutputParser outputParser, | ||
| String systemMessagePrefix, String systemMessageSuffix, String humanMessage, String formatInstructions, | ||
| List<String> inputVariables, Map<String, Object> kwargs) { | ||
| validateTools(tools); | ||
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| var prompt = createPrompt(tools, systemMessagePrefix, systemMessageSuffix, humanMessage, formatInstructions, | ||
| inputVariables); | ||
| var llmChain = new LLMChain(llm, prompt); | ||
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| var toolNames = tools.stream().map(BaseTool::getName).toList(); | ||
| outputParser = (outputParser != null) ? outputParser : getDefaultOutputParser(kwargs); | ||
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| return new ChatAgent(llmChain, toolNames, outputParser); | ||
| } | ||
| } |
70 changes: 70 additions & 0 deletions
70
...chain-core/src/main/java/com/hw/langchain/agents/chat/output/parser/ChatOutputParser.java
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,70 @@ | ||
| /* | ||
| * Licensed to the Apache Software Foundation (ASF) under one | ||
| * or more contributor license agreements. See the NOTICE file | ||
| * distributed with this work for additional information | ||
| * regarding copyright ownership. The ASF licenses this file | ||
| * to you 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 License for the specific language governing permissions and | ||
| * limitations under the License. | ||
| */ | ||
|
|
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| package com.hw.langchain.agents.chat.output.parser; | ||
|
|
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| import com.google.gson.Gson; | ||
| import com.google.gson.reflect.TypeToken; | ||
| import com.hw.langchain.agents.agent.AgentOutputParser; | ||
| import com.hw.langchain.schema.AgentAction; | ||
| import com.hw.langchain.schema.AgentFinish; | ||
| import com.hw.langchain.schema.AgentResult; | ||
| import com.hw.langchain.schema.OutputParserException; | ||
|
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| import java.lang.reflect.Type; | ||
| import java.util.Map; | ||
|
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| import static com.hw.langchain.agents.chat.prompt.Prompt.FORMAT_INSTRUCTIONS; | ||
|
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| /** | ||
| * @author HamaWhite | ||
| */ | ||
| public class ChatOutputParser extends AgentOutputParser { | ||
|
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| private static final String FINAL_ANSWER_ACTION = "Final Answer:"; | ||
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| @Override | ||
| public AgentResult parse(String text) { | ||
| boolean includesAnswer = text.contains(FINAL_ANSWER_ACTION); | ||
| try { | ||
| String action = text.split("```")[1]; | ||
| Type mapType = new TypeToken<Map<String, Object>>() { | ||
| }.getType(); | ||
| Map<String, Object> response = new Gson().fromJson(action.strip(), mapType); | ||
|
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| boolean includesAction = response.containsKey("action") && response.containsKey("action_input"); | ||
| if (includesAnswer && includesAction) { | ||
| throw new OutputParserException( | ||
| "Parsing LLM output produced a final answer and a parse-able action: " + text); | ||
| } | ||
| return new AgentAction(response.get("action").toString(), response.get("action_input"), text); | ||
| } catch (Exception e) { | ||
| if (!includesAnswer) { | ||
| throw new OutputParserException("Could not parse LLM output: " + text); | ||
| } | ||
| String[] splitText = text.split(FINAL_ANSWER_ACTION); | ||
| String output = splitText[splitText.length - 1].strip(); | ||
| return new AgentFinish(Map.ofEntries(Map.entry("output", output)), text); | ||
| } | ||
| } | ||
|
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| @Override | ||
| public String getFormatInstructions() { | ||
| return FORMAT_INSTRUCTIONS; | ||
| } | ||
| } |
62 changes: 62 additions & 0 deletions
62
langchain-core/src/main/java/com/hw/langchain/agents/chat/prompt/Prompt.java
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,62 @@ | ||
| /* | ||
| * Licensed to the Apache Software Foundation (ASF) under one | ||
| * or more contributor license agreements. See the NOTICE file | ||
| * distributed with this work for additional information | ||
| * regarding copyright ownership. The ASF licenses this file | ||
| * to you 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 License for the specific language governing permissions and | ||
| * limitations under the License. | ||
| */ | ||
|
|
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| package com.hw.langchain.agents.chat.prompt; | ||
|
|
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| /** | ||
| * @author HamaWhite | ||
| */ | ||
| public class Prompt { | ||
|
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| public static String SYSTEM_MESSAGE_PREFIX = """ | ||
| Answer the following questions as best you can. You have access to the following tools:"""; | ||
|
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| public static String FORMAT_INSTRUCTIONS = | ||
| """ | ||
| The way you use the tools is by specifying a json blob. | ||
| Specifically, this json should have a `action` key (with the name of the tool to use) and a `action_input` key (with the input to the tool going here). | ||
| The only values that should be in the "action" field are: {tool_names} | ||
| The $JSON_BLOB should only contain a SINGLE action, do NOT return a list of multiple actions. Here is an example of a valid $JSON_BLOB: | ||
| ``` | ||
| {{{{ | ||
| "action": $TOOL_NAME, | ||
| "action_input": $INPUT | ||
| }}}} | ||
| ``` | ||
| ALWAYS use the following format: | ||
| Question: the input question you must answer | ||
| Thought: you should always think about what to do | ||
| Action: | ||
| ``` | ||
| $JSON_BLOB | ||
| ``` | ||
| Observation: the result of the action | ||
| ... (this Thought/Action/Observation can repeat N times) | ||
| Thought: I now know the final answer | ||
| Final Answer: the final answer to the original input question"""; | ||
|
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| public static String SYSTEM_MESSAGE_SUFFIX = """ | ||
| Begin! Reminder to always use the exact characters `Final Answer` when responding."""; | ||
|
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| public static String HUMAN_MESSAGE = "{input}\n\n{agent_scratchpad}"; | ||
| } |
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