support auto-planning

src/bisheng-langchain/experimental/autoplanning/README.md

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+# Bisheng—Autoplanning

src/bisheng-langchain/experimental/autoplanning/autoplanning_agent.py

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+import os
+import sys
+import json
+from time import sleep
+from tqdm import trange
+from planning_chain import Chains
+from graph.graph import GraphGenerator
+
+
+class AutoPlanning:
+
+    def __init__(
+        self,
+        openai_api_key=os.getenv("OPENAI_API_KEY", ""),
+        model_name="gpt-3.5-turbo-16k-0613",
+        max_steps=10,
+        openai_api_base="",
+    ):
+        assert len(
+            openai_api_key.strip()
+        ), "Either give openai_api_key as an argument or put it in the environment variable"
+        self.model_name = model_name
+        self.openai_api_key = openai_api_key
+        self.max_steps = max_steps  # max iteration for refining the model purpose
+        self.openai_api_base = openai_api_base
+        Chains.setLlm(
+            self.model_name, self.openai_api_key, openai_api_base=self.openai_api_base
+        )
+
+    def setModel(self, model_name):
+        self.model_name = model_name
+        Chains.setLlm(
+            self.model_name, self.openai_api_key, openai_api_base=self.openai_api_base
+        )
+
+    def __repr__(self) -> str:
+        return f"AutoPlanning(model_name='{self.model_name}',max_steps={self.max_steps})"
+
+    def __call__(
+        self,
+        skill,
+        description,
+        save_file=''
+    ):
+        # phase1: skill -> plan
+        instruction = f'{skill}: {description}'
+        plan = Chains.plan(instruction)
+        print('plan:', plan)
+
+        yield {
+            "stage": "plan",
+            "completed": True,
+            "percentage": 20,
+            "done": False,
+            "message": "Plan has been generated.",
+        }
+
+        # phase2: plan -> tasks
+        task_list = Chains.tasks(instruction=instruction, plan=plan)
+        print('task_list:', task_list)
+
+        yield {
+            "stage": "task",
+            "completed": True,
+            "percentage": 50,
+            "done": False,
+            "message": "Tasks have been generated.",
+            "tasks": task_list,
+        }
+
+        # phase3: tasks -> chain graph
+        graph_generator = GraphGenerator(task_list, skill=skill, description=description)
+        agent_graph = graph_generator.build_graph()
+        with open(save_file, 'w') as f:
+            json.dump(agent_graph, f, ensure_ascii=False, indent=2)
+
+