Add Patch File Generation to AI Bot

main.py

@@ -11,7 +11,13 @@
     increment_usage_limit,
     is_rate_limit_reached,
     reset_usage_limits,
-    run_query,
+    from utils.github_utils import (
+        USAGE_LIMIT,
+        increment_usage_limit,
+        is_rate_limit_reached,
+        reset_usage_limits,
+        run_query,
+    )
 )
 
 app = Flask(__name__)
@@ -184,17 +190,22 @@ def solve_problem(mention, issue_number, issue_description):
 
     prompt = generate_gpt_prompt(issue_data)
 
-    out = run_query(
+    ai_response, patch_file = run_query(
         prompt,
         mention["repository"]["owner"]["login"],
         mention["repository"]["name"],
     )
 
-    # response = generate_response(issue_description)
-    # print(response)
     post_comment_to_issue(
         issue_number,
-        out,
+        ai_response,
+        mention["repository"]["owner"]["login"],
+        mention["repository"]["name"],
+    )
+
+    post_comment_to_issue(
+        issue_number,
+        patch_file,
         mention["repository"]["owner"]["login"],
         mention["repository"]["name"],
     )
@@ -242,16 +253,16 @@ def respond_to_unread_issues():
             post_comment_to_issue(
                 issue_number=issue_number,
                 comment_text=f"""#### 🛑 **Rate Limit Exceeded!**
-
-⌛ **Limit:** {USAGE_LIMIT} requests / day / repository
-🔒 **Refreshes In:** {int(hours)} hours, {int(minutes)} minutes
-
-<!-- To continue using the service, please consider upgrading to our **Pro Plan**.
-
-##### 🚀 **Upgrade to Pro**
-Upgrade to the Pro Plan to enjoy enhanced access, faster response times, and priority support. Click [here](Upgrade_Link) to upgrade now! -->
-
-📬 For any inquiries for support or rate limit extension, please contact <a href="https://discord.gg/T6Hz6zpK7D" target="_blank">Support</a>.""",
+            
+            ⌛ **Limit:** {USAGE_LIMIT} requests / day / repository
+            🔒 **Refreshes In:** {int(hours)} hours, {int(minutes)} minutes
+            
+            <!-- To continue using the service, please consider upgrading to our **Pro Plan**.
+            
+            ##### 🚀 **Upgrade to Pro**
+            Upgrade to the Pro Plan to enjoy enhanced access, faster response times, and priority support. Click [here](Upgrade_Link) to upgrade now! -->
+            
+            📬 For any inquiries for support or rate limit extension, please contact <a href="https://discord.gg/T6Hz6zpK7D" target="_blank">Support</a>.""",
                 OWNER=mention["repository"]["owner"]["login"],
                 REPO=mention["repository"]["name"],
             )
@@ -287,7 +298,6 @@ def respond_to_unread_issues():
 #         response = generate_response(problem_description)
 
 #         # Post the response as a comment on the issue
-#         post_comment_to_issue(issue_number, response)
 
 #     return jsonify({"message": "Webhook processed successfully"})
 

utils/github_utils.py

@@ -273,6 +273,8 @@ def setup_repo(owner, repo_name):
         print("Repo already exists")
 
 
+import difflib
+
 def run_query(query: str, owner: str, repo_name: str):
     setup_repo(owner, repo_name)
     matched_docs = vector_store.similarity_search(
@@ -284,6 +286,69 @@ def run_query(query: str, owner: str, repo_name: str):
 
     current_tokens = 0
 
+    for doc in matched_docs:
+        doc_content = doc.page_content + "\n\n"
+        doc_tokens = num_tokens_from_string(doc_content)
+        print(matched_docs.index(doc), doc_tokens)
+        if current_tokens + doc_tokens < MAX_TOKENS:
+            code_str += doc_content
+            current_tokens += doc_tokens
+        else:
+            break  # stop adding more content if it exceeds the max token limit
+
+    template = """
+    You are Codebase AI. You are a super intelligent AI that answers questions about code bases.
+
+    You are:
+    - helpful & friendly
+    - good at answering complex questions in simple language
+    - an expert in all programming languages
+    - able to infer the intent of the user's question
+
+    The user will ask a question about their codebase, and you will answer it.
+
+    When the user asks their question, you will answer it by searching the codebase for the answer.
+
+    Here is the user's question and code file(s) you found to answer the question:
+
+    Question:
+    {query}
+
+    Code file(s):
+    {code}
+
+    [END OF CODE FILE(S)]w
+
+    Now answer the question using the code file(s) above.
+    """
+
+    chat = ChatOpenAI(
+        streaming=True,
+        callback_manager=CallbackManager([StreamingStdOutCallbackHandler()]),
+        verbose=True,
+        temperature=0.5,
+    )
+    system_message_prompt = SystemMessagePromptTemplate.from_template(template)
+    chat_prompt = ChatPromptTemplate.from_messages([system_message_prompt])
+    chain = LLMChain(llm=chat, prompt=chat_prompt)
+
+    print("running chain...")
+    ai_said = chain.run(code=code_str, query=query)
+    print("chain output...")
+
+    # Generate patch file
+    original_code = code_str.splitlines()
+    modified_code = code_str.replace(query, ai_said).splitlines()
+    diff = difflib.unified_diff(original_code, modified_code)
+    patch_file = '\n'.join(diff)
+
+    return ai_said, patch_file
+
+    code_str = ""
+    MAX_TOKENS = 3500
+
+    current_tokens = 0
+
     for doc in matched_docs:
         doc_content = doc.page_content + "\n\n"
         doc_tokens = num_tokens_from_string(doc_content)