Merge pull request #21 from rusiaaman/2.7.1

2.7.1

Author: rusiaaman

gpt_action_json_schema.json

@@ -290,16 +290,16 @@
         }
       }
     },
-    "/v1/knowledge_transfer": {
+    "/v1/context_save": {
       "post": {
         "x-openai-isConsequential": false,
-        "summary": "Knowledge Transfer",
-        "operationId": "knowledge_transfer_v1_knowledge_transfer_post",
+        "summary": "Context Save",
+        "operationId": "context_save_v1_context_save_post",
         "requestBody": {
           "content": {
             "application/json": {
               "schema": {
-                "$ref": "#/components/schemas/KTWithUUID"
+                "$ref": "#/components/schemas/ContextSaveWithUUID"
               }
             }
           },
@@ -312,7 +312,7 @@
               "application/json": {
                 "schema": {
                   "type": "string",
-                  "title": "Response Knowledge Transfer V1 Knowledge Transfer Post"
+                  "title": "Response Context Save V1 Context Save Post"
                 }
               }
             }
@@ -427,6 +427,44 @@
         ],
         "title": "CommandWithUUID"
       },
+      "ContextSaveWithUUID": {
+        "properties": {
+          "id": {
+            "type": "string",
+            "title": "Id"
+          },
+          "project_root_path": {
+            "type": "string",
+            "title": "Project Root Path"
+          },
+          "description": {
+            "type": "string",
+            "title": "Description"
+          },
+          "relevant_file_globs": {
+            "items": {
+              "type": "string"
+            },
+            "type": "array",
+            "title": "Relevant File Globs"
+          },
+          "user_id": {
+            "type": "string",
+            "format": "uuid",
+            "title": "User Id"
+          }
+        },
+        "additionalProperties": false,
+        "type": "object",
+        "required": [
+          "id",
+          "project_root_path",
+          "description",
+          "relevant_file_globs",
+          "user_id"
+        ],
+        "title": "ContextSaveWithUUID"
+      },
       "FileEditWithUUID": {
         "properties": {
           "file_path": {
@@ -498,64 +536,6 @@
         ],
         "title": "InitializeWithUUID"
       },
-      "KTWithUUID": {
-        "properties": {
-          "id": {
-            "type": "string",
-            "title": "Id"
-          },
-          "project_root_path": {
-            "type": "string",
-            "title": "Project Root Path"
-          },
-          "objective": {
-            "type": "string",
-            "title": "Objective"
-          },
-          "all_user_instructions": {
-            "type": "string",
-            "title": "All User Instructions"
-          },
-          "current_status_of_the_task": {
-            "type": "string",
-            "title": "Current Status Of The Task"
-          },
-          "all_issues_snippets": {
-            "type": "string",
-            "title": "All Issues Snippets"
-          },
-          "relevant_file_paths": {
-            "items": {
-              "type": "string"
-            },
-            "type": "array",
-            "title": "Relevant File Paths"
-          },
-          "build_and_development_instructions": {
-            "type": "string",
-            "title": "Build And Development Instructions"
-          },
-          "user_id": {
-            "type": "string",
-            "format": "uuid",
-            "title": "User Id"
-          }
-        },
-        "additionalProperties": false,
-        "type": "object",
-        "required": [
-          "id",
-          "project_root_path",
-          "objective",
-          "all_user_instructions",
-          "current_status_of_the_task",
-          "all_issues_snippets",
-          "relevant_file_paths",
-          "build_and_development_instructions",
-          "user_id"
-        ],
-        "title": "KTWithUUID"
-      },
       "ReadFileWithUUID": {
         "properties": {
           "file_paths": {

gpt_instructions.txt

@@ -44,6 +44,11 @@ Instructions for `BashInteraction`
 Instructions for `ResetShell`
 - Resets the shell. Use only if all interrupts and prompt reset attempts have failed repeatedly.
 
+Instructions for `ContextSave`
+- Saves provided description and file contents of all the relevant file paths or globs in a single text file.
+  - Provide random unqiue id or whatever user provided.
+  - Leave project path as empty string if no project path
+
 Instructions for `FileEdit`:
     - Use absolute file path only.
     - Use SEARCH/REPLACE blocks to edit the file.

pyproject.toml

@@ -1,7 +1,7 @@
 [project]
 authors = [{ name = "Aman Rusia", email = "[email protected]" }]
 name = "wcgw"
-version = "2.7.0"
+version = "2.7.1"
 description = "Shell and coding agent on claude and chatgpt"
 readme = "README.md"
 requires-python = ">=3.11, <3.13"

src/wcgw/client/anthropic_client.py

@@ -25,10 +25,10 @@
 from ..types_ import (
     BashCommand,
     BashInteraction,
+    ContextSave,
     FileEdit,
     GetScreenInfo,
     Keyboard,
-    KnowledgeTransfer,
     Mouse,
     ReadFiles,
     ReadImage,
@@ -130,7 +130,12 @@ def loop(
     memory = None
     if resume:
         try:
-            memory = load_memory(resume)
+            _, memory = load_memory(
+                resume,
+                8000,
+                lambda x: default_enc.encode(x).ids,
+                lambda x: default_enc.decode(x),
+            )
         except OSError:
             if resume == "latest":
                 resume_path = sorted(Path(".wcgw").iterdir(), key=os.path.getmtime)[-1]
@@ -215,22 +220,12 @@ def loop(
 """,
         ),
         ToolParam(
-            input_schema=KnowledgeTransfer.model_json_schema(),
-            name="KnowledgeTransfer",
+            input_schema=ContextSave.model_json_schema(),
+            name="ContextSave",
             description="""
-Write detailed description in order to do a KT, if the user asks for it.
-Save all information necessary for a person to understand the task and the problems.
-
-- `all_user_instructions` should contain all instructions user shared in the conversation.
-- `current_status_of_the_task` should contain only what is already achieved, not what's remaining.
-- `all_issues_snippets` should only contain snippets of error, traceback, file snippets, commands, etc., no comments or solutions (important!).
-- Be very verbose in `all_issues_snippets` providing as much error context as possible.
-- Provide an id if the user hasn't provided one. 
-- This tool will return a text file path where the information is saved.
-- After the tool completes succesfully, tell the user the task id and the generate file path. (important!)
-- Leave arguments as empty string if they aren't relevant.
-- This tool marks end of your conversation, do not run any further tools after calling this.
-- Provide absolute file paths only in `relevant_file_paths` containing all relevant files.
+Saves provided description and file contents of all the relevant file paths or globs in a single text file.
+- Provide random unqiue id or whatever user provided.
+- Leave project path as empty string if no project path
 """,
         ),
     ]

src/wcgw/client/mcp_server/server.py

@@ -14,6 +14,7 @@
 from ...types_ import (
     BashCommand,
     BashInteraction,
+    ContextSave,
     FileEdit,
     GetScreenInfo,
     Initialize,
@@ -46,14 +47,47 @@ async def handle_read_resource(uri: AnyUrl) -> str:
 
 @server.list_prompts()  # type: ignore
 async def handle_list_prompts() -> list[types.Prompt]:
-    return []
+    return [
+        types.Prompt(
+            name="KnowledgeTransfer",
+            description="Prompt for invoking ContextSave tool in order to do a comprehensive knowledge transfer of a coding task. Prompts to save detailed error log and instructions.",
+        )
+    ]
 
 
 @server.get_prompt()  # type: ignore
 async def handle_get_prompt(
     name: str, arguments: dict[str, str] | None
 ) -> types.GetPromptResult:
-    return types.GetPromptResult(messages=[])
+    messages = []
+    if name == "KnowledgeTransfer":
+        messages = [
+            types.PromptMessage(
+                role="user",
+                content=types.TextContent(
+                    type="text",
+                    text="""Use `ContextSave` tool to do a knowledge transfer of the task in hand.
+Write detailed description in order to do a KT.
+Save all information necessary for a person to understand the task and the problems.
+
+Format the `description` field using Markdown with the following sections.
+- "# Objective" section containing project and task objective.
+- "# All user instructions" section should be provided containing all instructions user shared in the conversation.
+- "# Current status of the task" should be provided containing only what is already achieved, not what's remaining.
+- "# All issues with snippets" section containing snippets of error, traceback, file snippets, commands, etc. But no comments or solutions.
+- Be very verbose in the all issues with snippets section providing as much error context as possible.
+- "# Build and development instructions" section containing instructions to build or run project or run tests, or envrionment related information. Only include what's known. Leave empty if unknown.
+- After the tool completes succesfully, tell me the task id and the file path the tool generated (important!)
+- This tool marks end of your conversation, do not run any further tools after calling this.
+
+Provide all relevant file paths in order to understand and solve the the task. Err towards providing more file paths than fewer.
+
+(Note to self: this conversation can then be resumed later asking "Resume `<generated id>`" which should call Initialize tool)
+""",
+                ),
+            )
+        ]
+    return types.GetPromptResult(messages=messages)
 
 
 @server.list_tools()  # type: ignore
@@ -153,24 +187,14 @@ async def handle_list_tools() -> list[types.Tool]:
 """
             + diffinstructions,
         ),
-        #         ToolParam(
-        #             inputSchema=KnowledgeTransfer.model_json_schema(),
-        #             name="KnowledgeTransfer",
-        #             description="""
-        # Write detailed description in order to do a KT, if the user asks for it.
-        # Save all information necessary for a person to understand the task and the problems.
-        # - `all_user_instructions` should contain all instructions user shared in the conversation.
-        # - `current_status_of_the_task` should contain only what is already achieved, not what's remaining.
-        # - `all_issues_snippets` should only contain snippets of error, traceback, file snippets, commands, etc., no comments or solutions (important!).
-        # - Be very verbose in `all_issues_snippets` providing as much error context as possible.
-        # - Provide an id if the user hasn't provided one.
-        # - This tool will return a text file path where the information is saved.
-        # - After the tool completes succesfully, tell the user the task id and the generate file path. (important!)
-        # - Leave arguments as empty string if they aren't relevant.
-        # - This tool marks end of your conversation, do not run any further tools after calling this.
-        # - Provide absolute file paths only in `relevant_file_paths` containing all relevant files.
-        # """,
-        #         ),
+        ToolParam(
+            inputSchema=ContextSave.model_json_schema(),
+            name="ContextSave",
+            description="""
+Saves provided description and file contents of all the relevant file paths or globs in a single text file.
+- Provide random unqiue id or whatever user provided.
+- Leave project path as empty string if no project path""",
+        ),
     ]
     if COMPUTER_USE_ON_DOCKER_ENABLED:
         tools += [

src/wcgw/client/memory.py

@@ -1,26 +1,36 @@
 import os
+import re
+import shlex
+from typing import Callable, Optional
 
-from ..types_ import KnowledgeTransfer
+from ..types_ import ContextSave
 
 
 def get_app_dir_xdg() -> str:
     xdg_data_dir = os.environ.get("XDG_DATA_HOME", os.path.expanduser("~/.local/share"))
     return os.path.join(xdg_data_dir, "wcgw")
 
 
-def format_memory(task_memory: KnowledgeTransfer, relevant_files: str) -> str:
-    memory_data = f"""# Goal: {task_memory.objective}\n\n
-# Instructions:\n{task_memory.all_user_instructions}\n\n
-# Current Status:\n{task_memory.current_status_of_the_task}\n\n
-# Pending Issues:\n{task_memory.all_issues_snippets}\n\n
-# Build Instructions:\n{task_memory.build_and_development_instructions}\n"""
+def format_memory(task_memory: ContextSave, relevant_files: str) -> str:
+    memory_data = ""
+    if task_memory.project_root_path:
+        memory_data += (
+            f"# PROJECT ROOT = {shlex.quote(task_memory.project_root_path)}\n"
+        )
+    memory_data += task_memory.description
 
-    memory_data += "\n# Relevant Files:\n" + relevant_files
+    memory_data += (
+        "\n\n"
+        + "# Relevant file paths\n"
+        + ", ".join(map(shlex.quote, task_memory.relevant_file_globs))
+    )
+
+    memory_data += "\n\n# Relevant Files:\n" + relevant_files
 
     return memory_data
 
 
-def save_memory(task_memory: KnowledgeTransfer, relevant_files: str) -> str:
+def save_memory(task_memory: ContextSave, relevant_files: str) -> str:
     app_dir = get_app_dir_xdg()
     memory_dir = os.path.join(app_dir, "memory")
     os.makedirs(memory_dir, exist_ok=True)
@@ -30,23 +40,39 @@ def save_memory(task_memory: KnowledgeTransfer, relevant_files: str) -> str:
         raise Exception("Task id can not be empty")
     memory_data = format_memory(task_memory, relevant_files)
 
-    memory_file = os.path.join(memory_dir, f"{task_id}.json")
     memory_file_full = os.path.join(memory_dir, f"{task_id}.txt")
 
     with open(memory_file_full, "w") as f:
         f.write(memory_data)
 
-    with open(memory_file, "w") as f:
-        f.write(task_memory.model_dump_json())
-
     return memory_file_full
 
 
-def load_memory(task_id: str) -> KnowledgeTransfer:
+def load_memory[T](
+    task_id: str,
+    max_tokens: Optional[int],
+    encoder: Callable[[str], list[T]],
+    decoder: Callable[[list[T]], str],
+) -> tuple[str, str]:
     app_dir = get_app_dir_xdg()
     memory_dir = os.path.join(app_dir, "memory")
-    memory_file = os.path.join(memory_dir, f"{task_id}.json")
+    memory_file = os.path.join(memory_dir, f"{task_id}.txt")
 
     with open(memory_file, "r") as f:
-        task_save = KnowledgeTransfer.model_validate_json(f.read())
-    return task_save
+        data = f.read()
+
+    if max_tokens:
+        toks = encoder(data)
+        if len(toks) > max_tokens:
+            toks = toks[: max(0, max_tokens - 10)]
+            data = decoder(toks)
+            data += "\n(... truncated)"
+
+    project_root_match = re.search(r"# PROJECT ROOT = \s*(.*?)\s*$", data, re.MULTILINE)
+    project_root_path = ""
+    if project_root_match:
+        matched_path = project_root_match.group(1)
+        parsed_ = shlex.split(matched_path)
+        if parsed_ and len(parsed_) == 1:
+            project_root_path = parsed_[0]
+    return project_root_path, data