Update app.py

app.py

@@ -4,10 +4,6 @@ import os
 import requests
 from transformers import pipeline
 from sentence_transformers import SentenceTransformer, util
-import gradio as gr
-from huggingface_hub import InferenceClient
-from sentence_transformers import SentenceTransformer, util
-from transformers import pipeline
 
 # Hugging Face Inference Client
 client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
@@ -19,13 +15,11 @@ similarity_model = SentenceTransformer('all-mpnet-base-v2')
 def analyze_issues(issue_text: str, model_name: str, severity: str = None, programming_language: str = None) -> str:
     """
     Analyze issues and provide solutions.
-
     Args:
     issue_text (str): The issue text.
     model_name (str): The model name.
     severity (str, optional): The severity of the issue. Defaults to None.
     programming_language (str, optional): The programming language. Defaults to None.
-
     Returns:
     str: The analyzed issue and solution.
     """
@@ -65,11 +59,9 @@ Please provide a comprehensive resolution in the following format:
 def find_related_issues(issue_text: str, issues: list) -> list:
     """
     Find related issues.
-
     Args:
     issue_text (str): The issue text.
     issues (list): The list of issues.
-
     Returns:
     list: The list of related issues.
     """
@@ -86,104 +78,10 @@ def find_related_issues(issue_text: str, issues: list) -> list:
 def fetch_github_issues(github_api_token: str, github_username: str, github_repository: str) -> list:
     """
     Fetch GitHub issues.
-
     Args:
     github_api_token (str): The GitHub API token.
     github_username (str): The GitHub username.
     github_repository (str): The GitHub repository.
-
-    Returns:
-    list: The list of GitHub issues.
-    """
-    url = f"https://api.github.com/repos/{github_username}/{github_repository}/issues"
-    headers = {
-        "Authorization": f"Bearer {github_api_token}",
-        "Accept": "application/vnd.github.v3+json"
-    }
-    response = requests.get(url, headers=headers)
-if __name__ == "__main__":
-    client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")  # Correctly indented
-
-# Load a pre-trained model for sentence similarity
-similarity_model = SentenceTransformer('all-mpnet-base-v2')
-
-### Function to analyze issues and provide solutions
-def analyze_issues(issue_text: str, model_name: str, severity: str = None, programming_language: str = None) -> str:
-    """
-    Analyze issues and provide solutions.
-
-    Args:
-    issue_text (str): The issue text.
-    model_name (str): The model name.
-    severity (str, optional): The severity of the issue. Defaults to None.
-    programming_language (str, optional): The programming language. Defaults to None.
-
-    Returns:
-    str: The analyzed issue and solution.
-    """
-    prompt = f"""Issue: {issue_text}
-Severity: {severity}
-Programming Language: {programming_language}
-Please provide a comprehensive resolution in the following format:
-## Problem Summary:
-(Concise summary of the issue)
-## Root Cause Analysis:
-(Possible reasons for the issue)
-## Solution Options:
-1. **Option 1:** (Description)
-   - Pros: (Advantages)
-   - Cons: (Disadvantages)
-2. **Option 2:** (Description)
-   - Pros: (Advantages)
-   - Cons: (Disadvantages)
-## Recommended Solution:
-(The best solution with justification)
-## Implementation Steps:
-1. (Step 1)
-2. (Step 2)
-3. (Step 3)
-## Verification Steps:
-1. (Step 1)
-2. (Step 2)
-"""
-    try:
-        nlp = pipeline("text-generation", model=model_name, max_length=1000)  # Increase max_length
-        result = nlp(prompt)
-        return result[0]['generated_text']
-    except Exception as e:
-        return f"Error analyzing issue with model {model_name}: {e}"
-
-### Function to find related issues
-def find_related_issues(issue_text: str, issues: list) -> list:
-    """
-    Find related issues.
-
-    Args:
-    issue_text (str): The issue text.
-    issues (list): The list of issues.
-
-    Returns:
-    list: The list of related issues.
-    """
-    issue_embedding = similarity_model.encode(issue_text)
-    related_issues = []
-    for issue in issues:
-        title_embedding = similarity_model.encode(issue['title'])
-        similarity = util.cos_sim(issue_embedding, title_embedding)[0][0]
-        related_issues.append((issue, similarity))
-    related_issues = sorted(related_issues, key=lambda x: x[1], reverse=True)
-    return related_issues[:3]  # Return top 3 most similar issues
-
-### Function to fetch GitHub issues
-def fetch_github_issues(github_api_token: str, github_username: str, github_repository: str) -> list:
-    """
-    Fetch GitHub issues.
-
-    Args:
-    github_api_token (str): The GitHub API token.
-    github_username (str): The GitHub username.
-    github_repository (str): The GitHub repository.
-
     Returns:
     list: The list of GitHub issues.
     """
@@ -212,10 +110,9 @@ def respond(
     selected_model: str,
     severity: str,
     programming_language: str
-) -> gr.Interface:
+) -> str: 
     """
     Handle chat responses.
-
     Args:
     command (str): The command.
     history (list[tuple[str, str]]): The chat history.
@@ -229,11 +126,6 @@ def respond(
     selected_model (str): The selected model.
     severity (str): The severity.
     programming_language (str): The programming language.
-
-    Returns:
-    gr.Interface: The chat response.
-    programming_language (str): The programming language.
-
     Returns:
     str: The chat response.
     """
@@ -264,7 +156,11 @@ def respond(
     elif command == "/help":
         yield "Available commands:\n" \
               "- `/github`: Analyze a GitHub issue\n" \
-              "- `/help`: Show this help message"
+              "- `/help`: Show this help message\n" \
+              "- `/generate_code [code description]`: Generate code based on the description\n" \
+              "- `/explain_concept [concept]`: Explain a concept\n" \
+              "- `/write_documentation [topic]`: Write documentation for a given topic\n" \
+              "- `/translate_code [code] to [target language]`: Translate code to another language"
 
     elif command.isdigit() and issues:
         try:
@@ -282,6 +178,57 @@ def respond(
             yield f"Resolution for Issue '{issue['title']}':\n{resolution}\n\nRelated Issues:\n{related_issue_text}"
         except Exception as e:
             yield f"Error analyzing issue: {e}"
+
+    elif command.startswith("/generate_code"):
+        # Extract the code description from the command
+        code_description = command.replace("/generate_code", "").strip()
+        if not code_description:
+            yield "Please provide a description of the code you want to generate."
+        else:
+            prompt = f"Generate code for the following: {code_description}\nProgramming Language: {programming_language}"
+            try:
+                generated_code = analyze_issues(prompt, selected_model)  # Reuse analyze_issues for code generation
+                yield f"```{programming_language}\n{generated_code}\n```"
+            except Exception as e:
+                yield f"Error generating code: {e}"
+
+    elif command.startswith("/explain_concept"):
+        concept = command.replace("/explain_concept", "").strip()
+        if not concept:
+            yield "Please provide a concept to explain."
+        else:
+            prompt = f"Explain the concept of {concept} in detail."
+            try:
+                explanation = analyze_issues(prompt, selected_model)  # Reuse analyze_issues for explanation
+                yield explanation
+            except Exception as e:
+                yield f"Error explaining concept: {e}"
+
+    elif command.startswith("/write_documentation"):
+        topic = command.replace("/write_documentation", "").strip()
+        if not topic:
+            yield "Please provide a topic for documentation."
+        else:
+            prompt = f"Write comprehensive documentation for the following topic: {topic}"
+            try:
+                documentation = analyze_issues(prompt, selected_model)
+                yield documentation
+            except Exception as e:
+                yield f"Error writing documentation: {e}"
+
+    elif command.startswith("/translate_code"):
+        parts = command.replace("/translate_code", "").strip().split(" to ")
+        if len(parts) != 2:
+            yield "Invalid command format. Use: /translate_code [code] to [target language]"
+        else:
+            code, target_language = parts
+            prompt = f"Translate the following code to {target_language}:\n```\n{code}\n```"
+            try:
+                translated_code = analyze_issues(prompt, selected_model)
+                yield f"```{target_language}\n{translated_code}\n```"
+            except Exception as e:
+                yield f"Error translating code: {e}"
+
     else:
         messages.append({"role": "user", "content": command})
 
@@ -305,7 +252,7 @@ with gr.Blocks() as demo:
 
     # Define system_message here, after github_username and github_repository are defined
     system_message = gr.Textbox(
-        value="You are GitBot, the Github project guardian angel. You resolve issues and propose implementation of feature requests",
+        value="You are GitBot, the Github project guardian angel. You resolve issues and propose implementation of feature requests", 
         label="System message",
     )
 
@@ -314,36 +261,17 @@ with gr.Blocks() as demo:
         choices=[
             "Xenova/gpt-4o",
             "acecalisto3/InstructiPhi",
-            "DevShubham/Codellama-70B-AWQ",
             "DevShubham/Codellama-13B-Instruct-GGUF",
-            "DevShubham/Codellama-7B-Instruct-GGUF",
             "ricardo-larosa/SWE_Lite_dev-CodeLlama-34b",
             "DevsDoCode/Gemma-2b-Code-Instruct-Finetune-v0.1",
-            "devcodes8/textClassifier",
-            "mole-code/dev.langchain4j-starcoderbase-1b-fft",
-            "mole-code/dev.langchain4j-codegen-2B-mono-fft",
-            "mole-code/dev.langchain4j-starcoderbase-1b-prefix",
-            "mole-code/org.springframework.ai-dev.langchain4j-com.theokanning.openai-codegen-2B-mono-fft-fft-fft",
-            "mole-code/dev.langchain4j-codegen-2B-mono-prefix",
-            "mole-code/dev.langchain4j-com.theokanning.openai-starcoderbase-1b-fft-fft",
-            "mole-code/org.springframework.ai-dev.langchain4j-com.theokanning.openai-starcoderbase-1b-fft-fft-fft",
-            "ahmedgongi/code_llama_instruct_devops_expert",
-            "Dev2410/gemma-Code-Instruct-Finetune-test",
-            "Dev2410/code_llama_main",
-            "Dev2410/Code_llama",
-            "codefuse-ai/CodeFuse-DevOps-Model-14B-Chat",
-            "codefuse-ai/CodeFuse-DevOps-Model-7B-Base",
-            "codefuse-ai/CodeFuse-DevOps-Model-7B-Chat",
-            "codefuse-ai/CodeFuse-DevOps-Model-14B-Base",
-            "keonju/devocean-code-llama2",
-            "keonju/devocean-code-llama",
-            "keonju/Devocean_code_llama_lora",
-            "KuaFuAI-DevOpsGPT/codellama-7b-instruct-v1",
-            "dev011brasil/code",
-            "CodeJunior/devjunior"
+            "google/flan-t5-xxl",
+            "facebook/bart-large-cnn",
+            "microsoft/CodeBERT-base",
+            "Salesforce/codegen-350M-mono",
+            "bigcode/starcoder" 
         ],
         label="Select Model for Issue Resolution",
-        value="DevShubham/Codellama-70B-AWQ"
+        value="microsoft/CodeBERT-base"
     )
 
     # Severity Dropdown
@@ -358,7 +286,14 @@ with gr.Blocks() as demo:
 
     # Command Dropdown
     command_dropdown = gr.Dropdown(
-        choices=["/github", "/help"],  # Add your commands here
+        choices=[
+            "/github", 
+            "/help", 
+            "/generate_code", 
+            "/explain_concept",
+            "/write_documentation",
+            "/translate_code"
+        ],
         label="Select Command",
     )